Bimetallic MOF-Based Sensor for Highly Sensitive Detection of Ammonia Gases.

The demand for the detection of ultralow concentrations of ammonia gas is growing. A bimetallic metal-organic framework (MOF) comprising Prussian blue analogs (PBAs) was used to achieve highly sensitive and stable detection of ammonia gas at room temperature in this study. First, PB was enriched by using ammonia for improved gas sensing properties.

Development of Au-Pd@UiO-66-on-ZIF-L/CC as a self-supported electrochemical sensor for monitoring of cellular hydrogen peroxide.

Integrating metal-organic frameworks (MOFs) of different components or structures together and exploiting them as electrochemical sensors for electrochemical sensing has aroused great interest. Furthermore, the incorporation of noble metals with MOFs is conducive to the improvement of catalytic performance. In this work, Pd@UiO-66-on-ZIF-L nanomaterials were successfully synthesised onto a self-supported flexible carbon cloth (Pd@UiO-66-on-ZIF-L/CC) through a novel strategy called MOF-on-MOF.

Bio-orthogonal click-targeting nanocomposites for chemo-photothermal synergistic therapy in breast cancer.

Chemo-photothermal synergistic treatment has a high potential to complement traditional cancer therapy and amplify its outcome. Precision in the delivery of these therapeutic agents to tumor cells has been indicated as being key to maximizing their therapeutic effects. : We developed a bio-orthogonal copper-free click-targeting nanocomposite system (DLQ/DZ) that markedly improved specific co-delivery of the chemotherapeutic agent doxorubicin and the photosensitizer zinc phthalocyanine to breast cancer cells a two-step mechanism.

Improved Deep CNN with Parameter Initialization for Data Analysis of Near-Infrared Spectroscopy Sensors.

Near-infrared (NIR) spectral sensors can deliver the spectral response of light absorbed by materials. Data analysis technology based on NIR sensors has been a useful tool for quality identification. In this paper, an improved deep convolutional neural network (CNN) with batch normalization and MSRA (Microsoft Research Asia) initialization is proposed to discriminate the tobacco cultivation regions using data collected from NIR sensors.

A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose.

A medical electronic nose (e-nose) with 31 gas sensors is used for wound infection detection by analyzing the bacterial metabolites. In practical applications, the prediction accuracy drops dramatically when the prediction model established by laboratory data is directly used in human clinical samples. This is a key issue for medical e-nose which should be more worthy of attention.

Support Vector Machine Optimized by Genetic Algorithm for Data Analysis of Near-Infrared Spectroscopy Sensors.

Near-infrared (NIR) spectral sensors deliver the spectral response of the light absorbed by materials for quantification, qualification or identification. Spectral analysis technology based on the NIR sensor has been a useful tool for complex information processing and high precision identification in the tobacco industry. In this paper, a novel method based on the support vector machine (SVM) is proposed to discriminate the tobacco cultivation region using the near-infrared (NIR) sensors, where the genetic algorithm (GA) is employed for input subset selection to identify the effective principal components (PCs) for the SVM model.

Intracellular self-disassemble polysaccharide nanoassembly for multi-factors tumor drug resistance modulation of doxorubicin.

Drug efflux induced by multidrug resistance (MDR) overexpression, as well as secondary drug resistance caused by subtoxic drug microenvironments as a result of inefficient drug release of nanoscopic drug carriers in tumor cells, are major bottlenecks for chemotherapy. In order to overcome these limitations, we have devised a synergism-based polymer supramolecular nanoassembly (LH) by combining hyaluronic acid (HA) modified curcumin (HA-CUR) with a pH-sensitive low molecular weight heparin (LMWH) derivative modified doxorubicin (L-DOX). Our study proved that HA modification not only facilitated tumor targeting drug delivery efficiency through CD44 receptors-mediated active tumor-targeting strategy but also significantly enhanced the MDR reversion effect of CUR by improving its biological stability in different physiological environments.

A targeted nanoplatform co-delivering chemotherapeutic and antiangiogenic drugs as a tool to reverse multidrug resistance in breast cancer.

Unlabelled: Several obstacles are currently impeding the successful treatment of breast cancer, namely impaired drug accumulation into the tumor site, toxicity to normal cells and narrow therapeutic index of chemotherapy, multidrug resistance (MDR) and the metastatic spread of cancer cells through the blood and lymphatic vessels. In this regard, we designed a novel multifunctional nano-sized drug delivery system based on LyP-1 peptide-modified low-molecular-weight heparin-quercetin conjugate (PLQ). This nanosystem was developed for targeted co-delivery of multiple anticancer drugs to p32-overexpressing tumor cells and peritumoral lymphatic vessels, using LyP-1 peptide as active targeting ligand, with the aim to achieve a targeted combinatorial chemo/angiostatic therapy and MDR reversal.

Research on a Visual Electronic Nose System Based on Spatial Heterodyne Spectrometer.

Light absorption gas sensing technology has the characteristics of massive parallelism, cross-sensitivity and extensive responsiveness, which make it suitable for the sensing task of an electronic nose (e-nose). With the performance of hyperspectral resolution, spatial heterodyne spectrometer (SHS) can present absorption spectra of the gas in the form of a two dimensional (2D) interferogram which facilitates the analysis of gases with mature image processing techniques. Therefore, a visual e-nose system based on SHS was proposed.

Study on Interference Suppression Algorithms for Electronic Noses: A Review.

Electronic noses (e-nose) are composed of an appropriate pattern recognition system and a gas sensor array with a certain degree of specificity and broad spectrum characteristics. The gas sensors have their own shortcomings of being highly sensitive to interferences which has an impact on the detection of target gases. When there are interferences, the performance of the e-nose will deteriorate.

A correlated information removing based interference suppression technique in electronic nose for detection of bacteria.

A sensor array with 30 gas sensors is used in the electronic nose (e-nose) for bacteria detection in wound infection. However, the interference is an urgent problem in e-nose, since it would impact on the detection of target due to the cross-sensitivity of gas sensors, especially the background interference caused by carrier gas. The related methods to suppress the background interference are independent component analysis and orthogonal signal correction algorithm which are unreasonable, because it is difficult to obtain the so-called reference vector in complex real-world scenario.

Curcumin-carboxymethyl chitosan (CNC) conjugate and CNC/LHR mixed polymeric micelles as new approaches to improve the oral absorption of P-gp substrate drugs.

The low oral bioavailability of numerous drugs has been mostly attributed to the significant effect of P-gp-mediated efflux on intestinal drug transport. Herein, we developed mixed polymeric micelles (MPMs) comprised of curcumin-carboxymethyl chitosan (CNC) conjugate, as a potential inhibitor of P-gp-mediated efflux and gastrointestinal absorption enhancer, and low-molecular-weight heparin-all-trans-retinoid acid (LHR) conjugate, as loading material, with the aim to improve the oral absorption of P-gp substrate drugs. CNC conjugate was synthesized by chemical bonding of curcumin (Cur) and carboxymethyl chitosan (CMCS) taking advantage of the inhibition of intestinal P-gp-mediated secretion by Cur and the intestinal absorption enhancement by CMCS.

Suppression of Strong Background Interference on E-Nose Sensors in an Open Country Environment.

The feature extraction technique for an electronic nose (e-nose) applied in tobacco smell detection in an open country/outdoor environment with periodic background strong interference is studied in this paper. Principal component analysis (PCA), Independent component analysis (ICA), re-filtering and a priori knowledge are combined to separate and suppress background interference on the e-nose. By the coefficient of multiple correlation (CMC), it can be verified that a better separation of environmental temperature, humidity, and atmospheric pressure variation related background interference factors can be obtained with ICA.

A Novel Feature Extraction Approach Using Window Function Capturing and QPSO-SVM for Enhancing Electronic Nose Performance.

In this paper, a novel feature extraction approach which can be referred to as moving window function capturing (MWFC) has been proposed to analyze signals of an electronic nose (E-nose) used for detecting types of infectious pathogens in rat wounds. Meanwhile, a quantum-behaved particle swarm optimization (QPSO) algorithm is implemented in conjunction with support vector machine (SVM) for realizing a synchronization optimization of the sensor array and SVM model parameters. The results prove the efficacy of the proposed method for E-nose feature extraction, which can lead to a higher classification accuracy rate compared to other established techniques.

A new kernel discriminant analysis framework for electronic nose recognition.

Electronic nose (e-Nose) technology based on metal oxide semiconductor gas sensor array is widely studied for detection of gas components. This paper proposes a new discriminant analysis framework (NDA) for dimension reduction and e-Nose recognition. In a NDA, the between-class and the within-class Laplacian scatter matrix are designed from sample to sample, respectively, to characterize the between-class separability and the within-class compactness by seeking for discriminant matrix to simultaneously maximize the between-class Laplacian scatter and minimize the within-class Laplacian scatter.

A modified statistically optimal null filter method for recognizing protein-coding regions.

Computer-aided protein-coding gene prediction in uncharacterized genomic DNA sequences is one of the most important issues of biological signal processing. A modified filter method based on a statistically optimal null filter (SONF) theory is proposed for recognizing protein-coding regions. The square deviation gain (SDG) between the input and output of the model is used to identify the coding regions.

A novel coding method for gene mutation correction during protein translation process.

In gene expression, gene mutations often lead to negative effect of protein translation in prokaryotic organisms. With consideration of the influences produced by gene mutation, a novel method based on error-correction coding theory is proposed for modeling and detection of translation initiation in this paper. In the proposed method, combined with a one-dimensional codebook from block coding, a decoding method based on the minimum hamming distance is designed for analysis of translation efficiency.

Bilateral similarity function: a novel and universal method for similarity analysis of biological sequences.

Bilateral similarity function is designed for analyzing the similarities of biological sequences such as DNA, RNA secondary structure or protein in this paper. The defined function can perform comprehensive comparison between sequences remarkably well, both in terms of the Hamming distance of two compared sequences and the corresponding location difference. Compared with the existing methods for similarity analysis, the examination of similarities/dissimilarities illustrates that the proposed method with the computational complexity of O(N) is effective for these three kinds of biological sequences, and bears the universality for them.

A Solid Trap and Thermal Desorption System with Application to a Medical Electronic Nose.

In this paper, a solid trap/thermal desorption-based odorant gas condensation system has been designed and implemented for measuring low concentration odorant gas. The technique was successfully applied to a medical electronic nose system. The developed system consists of a flow control unit, a temperature control unit and a sorbent tube.