In vitro activity of resorcinarene–chlorambucil conjugates for therapy in human chronic myelogenous leukemia cells

A possible way of improving the activity and selectivity profile of antitumor agents is to design drug carrier systems employing soluble macromolecules. Thus, four resorcinarene-PAMAM-dendrimer conjugates of chlorambucil with different groups in the lower part of the macrocycle and different length dendritic arms showed a good stability of the chemical link between drug and spacer. Evaluation of the cytotoxicity of the resorcinarene-PAMAM-dendrimer–chlorambucil conjugate employing a sulforhodamine B (SRB) assay in K-562 (human chronic myelogenous leukemia cells) demonstrated that the conjugate was more potent as an antiproliferative agent than chlorambucil.     

Self‐Assembling Proteins as High‐Performance Substrates for Embryonic Stem Cell Self‐Renewal

The development of extracellular matrix mimetics that imitate niche stem cell microenvironments and support cell growth for technological applications is intensely pursued. Specifically, mimetics are sought that can enact control over the self‐renewal and directed differentiation of human pluripotent stem cells (hPSCs) for clinical use. Despite considerable progress in the field, a major impediment to the clinical translation of hPSCs is the difficulty and high cost of large‐scale cell production under xeno‐free culture conditions using current matrices. Here, a bioactive, recombinant, protein‐based polymer, termed ZT^Fn, is presented that closely mimics human plasma fibronectin and serves as an economical, xeno‐free, biodegradable, and functionally adaptable cell substrate. The ZT^Fn substrate supports with high performance the propagation and long‐term self‐renewal of human embryonic stem cells while preserving their pluripotency. The ZT^Fn polymer can, therefore, be proposed as an efficient and affordable replacement for fibronectin in clinical grade cell culturing. Further, it can be postulated that the ZT polymer has significant engineering potential for further orthogonal functionalization in complex cell applications.     

Investigation of Electrode Electrochemical Reactions in CH3NH3PbBr3 Perovskite Single‐Crystal Field‐Effect Transistors

Optoelectronic devices based on metal halide perovskites, including solar cells and light‐emitting diodes, have attracted tremendous research attention globally in the last decade. Due to their potential to achieve high carrier mobilities, organic–inorganic hybrid perovskite materials can enable high‐performance, solution‐processed field‐effect transistors (FETs) for next‐generation, low‐cost, flexible electronic circuits and displays. However, the performance of perovskite FETs is hampered predominantly by device instabilities, whose origin remains poorly understood. Here, perovskite single‐crystal FETs based on methylammonium lead bromide are studied and device instabilities due to electrochemical reactions at the interface between the perovskite and gold source–drain top contacts are investigated. Despite forming the contacts by a gentle, soft lamination method, evidence is found that even at such “ideal” interfaces, a defective, intermixed layer is formed at the interface upon biasing of the device. Using a bottom‐contact, bottom‐gate architecture, it is shown that it is possible to minimize such a reaction through a chemical modification of the electrodes, and this enables fabrication of perovskite single‐crystal FETs with high mobility of up to ≈15 cm² V^?1 s^?1 at 80 K. This work addresses one of the key challenges toward the realization of high‐performance solution‐processed perovskite FETs.     

Dynamics of Antimonene–Graphene Van Der Waals Growth

Van der Waals (vdW) heterostructures have recently been introduced as versatile building blocks for a variety of novel nanoscale and quantum technologies. Harnessing the unique properties of these heterostructures requires a deep understanding of the involved interfacial interactions and a meticulous control of the growth of 2D materials on weakly interacting surfaces. Although several epitaxial vdW heterostructures have been achieved experimentally, the mechanisms governing their synthesis are still nebulous. With this perspective, herein, the growth dynamics of antimonene on graphene are investigated in real time. In situ low‐energy electron microscopy reveals that nucleation predominantly occurs on 3D nuclei followed by a self‐limiting lateral growth with morphology sensitive to the deposition rate. Large 2D layers are observed at high deposition rates, whereas lower growth rates trigger an increased multilayer nucleation at the edges as they become aligned with the Z2 orientation leading to atoll‐like islands with thicker, well‐defined bands. This complexity of the vdW growth is elucidated based on the interplay between the growth rate, surface diffusion, and edges orientation. This understanding lays the groundwork for a better control of the growth of vdW heterostructures, which is critical to their large‐scale integration.     

Computational Intelligence Methods for Time Series Analysis and Forecasting: Special Issue of IWANN 2017

Neural Processing Letters - Incorporation of new knowledge into neural networks with simultaneous preservation of the previous knowledge is known to be a nontrivial problem. This problem becomes...     

Tackling business intelligence with bioinspired deep learning

To tackle the complex problem of providing business intelligence solutions based on business data, bioinspired deep learning has to be considered. This paper focuses on the application of artificial metaplasticity learning in business intelligence systems as an alternative paradigm of achieving a deeper information extraction and learning from arbitrary size data sets. As a case study, artificial metaplasticity multilayer perceptron applied to the automation of credit approval decision based on collected client data is analyzed, showing its potential and improvements over the state-of-the-art techniques. This paper successfully introduces the relevant novelty that the artificial neural network itself estimates the pdf of the input data to be used in the metaplasticity learning, so it is much closer to the biologic reality than previous implementations of artificial metaplasticity.

     

Improving deep learning performance with missing values via deletion and compensation

Neural Computing and Applications - Missing values in a dataset is one of the most common difficulties in real applications. Many different techniques based on machine learning have been proposed...     

An I&I‐Based Observer to Solve the Output‐Feedback Synchronization Problem for a Class of Chaotic Systems

A novel robust observer, intended to solve the output‐feedback chaos synchronization problem for the Master/Slave Configuration, is proposed here. Assuming that the given Master system belongs to a specific class of feedback‐linearized systems, our solution is based on the well‐known Immersion and Invariance (I&I) method. The proposed observer is devoted to the asymptotic estimation of the Master system's underlying dynamics, and its effectiveness is illustrated via computer‐based simulations that involve both the so‐called Duffing's oscillator and the Genesio & Tesi system.