Polymeric micelles are one of the most promising nanovehicles for drug delivery. In addition to amphiphilicity, various individual or synergistic noncovalent interplays including strong hydrophobic, electrostatic, host-guest, hydrogen bonding, stereocomplex and coordination interactions have been recently employed to improve the physical stability of micelles, and even provide them with certain intelligences or bioactivities. Through the ingenious designs and precise preparations, many noncovalent-mediated micelles display great prospects in the realm of controlled drug delivery, and certain species have been promoted to clinical trials. The current review presents the diverse noncovalent interactions that are applied to enhance polymeric micelles as drug nanocarriers, and preliminarily discusses the future directions and perspectives of this field.

This paper describes the Voice Conversion Challenge 2016 devised by the authors to better understand different voice conversion (VC) techniques by comparing their performance on a common dataset. The task of the challenge was speaker conversion, i.e., to transform the voice identity of a source speaker into that of a target speaker while preserving the linguistic content. Using a common dataset consisting of 162 utterances for training and 54 utterances for evaluation from each of 5 source and 5 target speakers, 17 groups working in VC around the world developed their own VC systems for every combination of the source and target speakers, i.e., 25 systems in total, and generated voice samples converted by the developed systems. These samples were evaluated in terms of target speaker similarity and naturalness by 200 listeners in a controlled environment. This paper summarizes the design of the challenge, its result, and a future plan to share views about unsolved problems and challenges faced by the current VC techniques.

This paper presents a new spectral envelope conversion method using deep neural networks (DNNs). The conventional joint density Gaussian mixture model (JDGMM) based spectral conversion methods perform stably and effectively. However, the speech generated by these methods suffer severe quality degradation due to the following two factors: 1) inadequacy of JDGMM in modeling the distribution of spectral features as well as the non-linear mapping relationship between the source and target speakers, 2) spectral detail loss caused by the use of high-level spectral features such as mel-cepstra. Previously, we have proposed to use the mixture of restricted Boltzmann machines (MoRBM) and the mixture of Gaussian bidirectional associative memories (MoGBAM) to cope with these problems. In this paper, we propose to use a DNN to construct a global non-linear mapping relationship between the spectral envelopes of two speakers. The proposed DNN is generatively trained by cascading two RBMs, which model the distributions of spectral envelopes of source and target speakers respectively, using a Bernoulli BAM (BBAM). Therefore, the proposed training method takes the advantage of the strong modeling ability of RBMs in modeling the distribution of spectral envelopes and the superiority of BAMs in deriving the conditional distributions for conversion. Careful comparisons and analysis among the proposed method and some conventional methods are presented in this paper. The subjective results show that the proposed method can significantly improve the performance in terms of both similarity and naturalness compared to conventional methods.Index Terms-Bidirectional associative memory, deep neural network, Gaussian mixture model, restricted Boltzmann machine, spectral envelope conversion, voice conversion.

BackgroundAberrant expression of the RON receptor tyrosine kinase is a pathogenic feature and a validated drug target in various types of cancers. Currently, therapeutic antibodies targeting RON for cancer therapy are under intensive evaluation. Here we report the development and validation of a novel humanized anti-RON antibody-drug conjugate for cancer therapy.MethodsAntibody humanization was achieved by grafting sequences of complementarity-determining regions from mouse monoclonal antibody Zt/g4 into human IgG1/κ acceptor frameworks. The selected humanized Zt/g4 subclone H1L3 was conjugated with monomethyl auristatin E using a dipeptide linker to form H-Zt/g4-MMAE. Pharmacokinetic analysis of H-Zt/g4-MMAE was determined using hydrophobic interaction chromatography and a MMAE ADC ELISA kit. Biochemical and biological assays were used for measuring RON expression, internalization, cell viability and death. Therapeutic efficacies of H-Zt/g4-MMAE were validated in vivo using three pancreatic cancer xenograft models. Toxicological activities of H-Zt/g4-MMAE were determined in mouse and cynomolgus monkey.ResultsH-Zt/g4-MMAE had a drug to antibody ratio of 3.77:1 and was highly stable in human plasma with a dissociation rate less than 5% within a 20 day period. H-Zt/g4-MMAE displayed a favorable pharmacokinetic profile in both mouse and cynomolgus monkey. In vitro, H-Zt/g4-MMAE induced RON internalization, which results in killing of pancreatic cancer cells with IC50 values at 10–20 nM. In vivo, H-Zt/g4-MMAE inhibited pancreatic cancer xenograft growth with tumoristatic concentrations at 1~3 mg/kg bodyweight. Significantly, H-Zt/g4-MMAE eradicated tumors across multiple xenograft models regardless their chemoresistant and metastatic statuses. Moreover, H-Zt/g4-MMAE inhibited and eradicated xenografts mediated by pancreatic cancer stem-like cells and by primary cells from patient-derived tumors. Toxicologically, H-Zt/g4-MMAE is well tolerated in mice up to 60 mg/kg. In cynomolgus monkey, H-Zt/g4-MMAE up to 30 mg/kg had a manageable and reversible toxicity profile.ConclusionsH-Zt/g4-MMAE is superior in eradication of pancreatic cancer xenografts with favorable pharmacokinetic profiles and manageable toxicological activities. These findings warrant the transition of H-Zt/g4-MMAE into clinical trials in the future.Electronic supplementary materialThe online version of this article (10.1186/s40425-019-0525-0) contains supplementary material, which is available to authorized users.

A series of supramolecular photosensitizers were fabricated from porphyrin derivatives (Por) containing quaternary ammonium groups with cucurbit[7]uril (CB[7]) based on host-guest interactions. The antibacterial activity of Por in the dark could be turned off upon binding with CB[7], whereas the antibacterial activity under white-light illumination could be turned on. In addition, its antibacterial efficiency could be greatly enhanced by introducing metal ions. When Pd(II) was introduced into porphyrin, its antibacterial efficiency was enhanced from 40 to 100%. It should be noted that these small molecules showed little to no cytotoxicity toward mammalian cells even at concentrations higher than those under the antibacterial condition studied. This line of research will provide a strategy for germicides consisting of quaternary ammonium groups to fight against bacterial accumulation in the long term and holds huge potential for application in the real world.