Two-dimensional metal-organic framework nanozyme-mediated portable paper-based analytical device for dichlorophen assay.

The metal-organic frameworks (MOFs) nanozyme-mediated paper-based analytical devices (PADs) have shown great potential in portable visual determination of phenolic compounds in the environment. However, most MOF nanozymes suffer from poor dispersibility and block-like structure, which often prompts deposition and results in diminished enzymatic activity, severely hindering their environmental applications. Here, we proposed colorimetric PADs for the visual detection of dichlorophen (Dcp) based on its significant inhibitory effect on the two-dimensional (2D) MOF nanozyme activity. Specifically, we synthesized a 2D Cu TCPP (Fe) (defined as 2D-CTF) MOF nanozyme exhibiting excellent dispersibility and remarkable peroxidase-like (POD-like) activity, which could catalyze the oxidation and subsequent color change of 3,3',5,5'-tetramethylbenzidine even under neutral conditions. Notably, the POD-like activity of 2D-CTF demonstrated a unique response to Dcp because of the occupation of Fe-N4 active sites on the 2D-CTF. This property enables the use of 2D-CTF as a highly efficient catalyst to develop colorimetric PADs for naked-eye and portable detection of Dcp. We believe that the proposed colorimetric PADs offer an efficient method for Dcp assay and open fresh avenues for the advancement of colorimetric sensors for analyzing of phenolic toxic substances in real samples.

Direct and Specific Detection of Glyphosate Using a Phosphatase-like Nanozyme-Mediated Chemiluminescence Strategy.

Most organophosphorus pesticide (OP) sensors reported in the literature rely on the inhibition effect of OPs on the activity of acetylcholinesterase (AChE), which suffer from the drawbacks of lack of selective recognition of OPs, high cost, and poor stability. Herein, we proposed a novel chemiluminescence (CL) strategy for the direct detection of glyphosate (an organophosphorus herbicide) with high sensitivity and specificity, which is based on the porous hydroxy zirconium oxide nanozyme (ZrOX-OH) obtained via a facile alkali solution treatment of UIO-66. ZrOX-OH displayed excellent phosphatase-like activity, which could catalyze the dephosphorylation of 3-(2'-spiroadamantyl)-4-methoxy-4-(3'-phosphoryloxyphenyl)-1,2-dioxetane (AMPPD) to generate strong CL. The experimental results showed that the phosphatase-like activity of ZrOX-OH is closely related to the content of hydroxyl groups on their surface. Interestingly, ZrOX-OH with phosphatase-like properties exhibited a unique response to glyphosate because of the consumption of the surface hydroxyl group by the unique carboxyl group of glyphosates and was thus employed to develop a CL sensor for direct and selective detection of glyphosate without using bio-enzymes. The recovery for glyphosate detection of cabbage juice ranged from 96.8 to 103.0%. We believe that the as-proposed CL sensor based on ZrOX-OH with phosphatase-like properties supplies a simpler and more highly selective approach for OP assay and provides a new method for the development of CL sensors for the direct analysis of OPs in real samples.

Impact of the segment ratio on a donor-acceptor all-conjugated block copolymer in single-component organic solar cells.

The development of single-component organic solar cells (SCOSCs) using only one photoactive component with a chemically bonded D/A structure has attracted increasing research attention in recent years. At represent, most relevant studies focus on comparing the performance difference between a donor-acceptor (D-A) conjugated block copolymer (CBC) and the commensurate blending systems based on the same donor and acceptor segments, and still there are no reports on the impact of the segment ratio for a certain D-A CBC on the resultant photovoltaic performance. In this study, we synthesized a D-A all-conjugated polymers based on an n-type PNDI2T block and a p-type PBDB-T donor block but with three different segment ratios (P1-P3) and demonstrate the significance of the D/A segment ratio on photovoltaic performance. Our results reveal that the n-type PNDI2T block plays a more critical role in the inter/intra-chain charge transfer. P1 with a higher content of PNDI2T delivers superior exciton dissociation and charge transfer behavior than P2 and P3, benefitting from its more balanced hole/electron mobility. In addition, a higher packing regularity associated with a more dominant face-on orientation is also observed for P1. As a result, SCOSC based on P1 exhibits the highest PCE among the synthesized CBCs. It also possesses a minimal energy loss due to the better suppressed non-radiative recombination loss. This work provides the first discussion of the impact of the segment ratio for a D-A all-conjugated block copolymer and signifies the critical role of the n-type segment in designing high-performance single-component CBCs.

Two-Dimensional Cobalt-Doped Ti3C2 MXene Nanozyme-Mediated Homogeneous Electrochemical Strategy for Pesticides Assay Based on In Situ Generation of Electroactive Substances.

Common homogeneous electrochemical (HEC) sensors usually suffer from the drawbacks of high background signal, low signal-to-noise ratio, and even false positive results due to the preaddition of electroactive substances. Thus, it is necessary to develop novel HEC sensors based on in situ generation of electroactive substances to overcome these shortcomings, which, however, is underexplored. In this work, two-dimensional (2D) nanozymes, i.e., cobalt-doped 2D Ti3C2 MXene nanosheets (CMNSs), with excellent peroxidase-like properties were utilized to develop HEC sensors based on the in situ generation of electroactive substances for organophosphate pesticides (OPs) detection. The 2D CMNSs were synthesized via a template-directed wet chemical approach and displayed outstanding features of hydrophilia and water dispersibility, which could catalyze the oxidation of o-phenylenediamine (OPD) to generate significantly increased reduction current. Interestingly, the 2D CMNSs with peroxidase-like properties exhibited a unique response to thiol compounds and were thus employed as highly efficient catalysts to develop HEC sensors for OPs based on the hydrolysis of acetylthiocholine (ATCh) to form thiocholine catalyzed by acetylcholinesterase (AChE) and the inhibition of AChE activity by OPs. The recovery for OPs analysis of pakchoi extract solutions ranged from 97.4% to 103.3%. The as-proposed HEC sensor based on in situ generation of electroactive substances will provide a new way for the development of high-performance electrochemical sensors and demonstrate potential applicability for the determination of pesticide residues in real samples.

One-Step Synthesis of Methylene Blue-Encapsulated Zeolitic Imidazolate Framework for Dual-Signal Fluorescent and Homogeneous Electrochemical Biosensing.

In vitro diagnosis requires target biomarkers to be reliably detected at an ultralow level. A dual-signal strategy permits self-calibration to overcome the interferences of experimental and environmental factors, and thus is regarded as a promising approach. However, currently reported works mainly concentrated on the same forms of energy of output signals. Herein, we propose a one-step strategy for synthesis of methylene blue-encapsulated zeolitic imidazolate framework-90 (MB@ZIF-90) with high loading, unique dual-signal property, exceptional recognition capability, and good stability, and we further pioneer MB@ZIF-90 as a dual-signal biosensor for label-free, enzyme-free, and ultrasensitive detection of adenosine triphosphate (ATP) by integration of fluorescence and homogeneous electrochemical techniques. The recognition of MB@ZIF-90 by target ATP spurs the decomposition of ZIF-90, subsequently permitting MB to be released into a supernatant. As compared to the case where ATP does not exist, obviously increased intensities in fluorescence and differential pulse voltammetry current are observed and both signals are directly proportional to ATP concentrations. Thus, the MB@ZIF-90-based biosensor achieved dual-signal detection of ATP in an ultrasensitive manner and displayed a more reliable diagnosis result than previously reported ATP biosensors. This dual-signal strategy provides a new opportunity to develop high-performance biosensors for in vitro diagnosis and demonstrates great potential for future applications in bioinformatics and clinical medicine.

Diffusivity and intercalation of electroactive dyes-mediated truly ratiometric homogeneous electrochemical strategy for highly sensitive biosensing.

A truly ratiometric homogeneous electrochemical biosensor has been developed for sensitive miRNA detection based on the unique diffusion/intercalation properties of electroactive dyes without the need for electrode modification or materials preparation.

Nucleic Acid-Functionalized Metal-Organic Framework-Based Homogeneous Electrochemical Biosensor for Simultaneous Detection of Multiple Tumor Biomarkers.

Simultaneous detection of multiple tumor biomarkers is in great demand for early and accurate cancer diagnosis. A homogeneous electrochemical biosensor has been proven to possess high sensitivity, but achieving simultaneous detection of multiple tumor biomarkers is still a challenge. Herein, we develop a novel homogeneous electrochemical biosensor for simultaneous detection of multiple tumor biomarkers based on the functionalized metal-organic frameworks (MOFs). The functionalized MOFs were prepared by using porous UIO-66-NH2 as nanocontainer to load electroactive dyes and dsDNA as a gatekeeper to cap MOFs. In this context, two functionalized MOFs (MB@UIO and TMB@UIO) were fabricated and applied to simultaneous detection of let-7a and miRNA-21, used as the proof-of-concept analytes. The recognition and hybridization of PX with target miRNAs impel the generation of RNA-DNA complexes, which separated from MOFs and allowed the electroactive dyes to be released. In comparison with the case when target miRNAs are absent, two stronger signals are recorded, and dependent on target miRNA concentrations. Thus, simultaneous detection of let-7a and minRNA-21 is achieved, with detection limits down to 3.6 and 8.2 fM, respectively, comparable or lower than those of reported strategies that concentrated on single miRNA detection. Moreover, the proposed biosensor has also been successfully applied for simultaneous detection of target miRNAs spiked in serum samples. Therefore, the proposed strategy was expected to provide more information for early and accurate cancer diagnosis and was an useful application in disease diagnosis and clinical biomedicine.

Target-induced diffusivity enhancement for rapid and highly sensitive homogeneous electrochemical detection of BLM in human serum.

A simple, rapid, and sensitive homogeneous electrochemical bleomycin (BLM) bioassay has been successfully developed through the target-induced specific/efficient cleavage reaction. The designed probe, denoted as MB-DNA, contains both methylene blue (MB) and target recognizable sequences, and presents relatively low electrochemical signal. Upon the addition of BLM, the recognition/cleavage reaction occurs and leads to the in-situ generation of MB tag (MB-DNA-1), leading to the reduced electrostatic repulsive force. As a result, an obvious enhancement in differential pulse voltammetry (DPV) current is determined, which is relied on the amount of BLM. Thus, a turn on homogeneous electrochemical method for BLM is really achieved, and exhibits high sensitivity of 33 pM, and the shortest response time of 20 min. Furthermore, this electrochemical bioassay presents excellent sensing performance in the analysis of BLM in real samples. Comparing with other sensing strategies for BLM, this proposed electrochemical platform is just consisted of one DNA probe alone, and affords a really rapid and sensitive strategy for BLM analysis.

Label-Free and Ultrasensitive Biomolecule Detection Based on Aggregation Induced Emission Fluorogen via Target-Triggered Hemin/G-Quadruplex-Catalyzed Oxidation Reaction.

Fluorescence biosensing strategy has drawn substantial attention due to their advantages of simplicity, convenience, sensitivity, and selectivity, but unsatisfactory structure stability, low fluorescence quantum yield, high cost of labeling, and strict reaction conditions associated with current fluorescence methods severely prohibit their potential application. To address these challenges, we herein propose an ultrasensitive label-free fluorescence biosensor by integrating hemin/G-quadruplex-catalyzed oxidation reaction with aggregation induced emission (AIE) fluorogen-based system. l-Cysteine/TPE-M, which is carefully and elaborately designed and developed, obviously contributes to strong fluorescence emission. In the presence of G-rich DNA along with K+ and hemin, efficient destruction of l-cysteine occurs due to hemin/G-quadruplex-catalyzed oxidation reactions. As a result, highly sensitive fluorescence detection of G-rich DNA is readily realized, with a detection limit down to 33 pM. As a validation for the further development of the proposed strategy, we also successfully construct ultrasensitive platforms for microRNA by incorporating the l-cysteine/TPE-M system with target-triggered cyclic amplification reaction. Thus, this proposed strategy is anticipated to find use in basic biochemical research and clinical diagnosis.

Paper-based fluorescent sensor via aggregation induced emission fluorogen for facile and sensitive visual detection of hydrogen peroxide and glucose.

Hydrogen peroxide (H2O2), an important reactive oxygen species (ROS), is related to the oxidative stress in organisms, and plays important roles in a variety of cellular activities as well. So it is of crucial importance to develop sensitive and accurate sensing strategies to detect H2O2 in biological systems. Herein, by taking advantage of the unique emission characteristics of aggregation induced emission (AIE) fluorogens, we proposed a non-enzymatic fluorescence platform for facile and sensitive detection of H2O2, both in solution state using fluorescence spectrometer and on paper-based sensor via visual inspection. Through the reaction between L-cysteine and H2O2, the fluorescence of TPE-M-L, an AIE fluorogen formed between maleimide-functionalized tetraphenylethene (TPE-M) and L-cysteine, is quenched, and highly sensitive non-enzymatic H2O2 assay is readily carried out. The limit of detection (LOD) of 10nM in solution state and 2.5µM on paper-based sensor were obtained for H2O2 detection, which were superior or comparable to those previously reported in literature. Moreover, by integrating glucose oxidase with the AIE fluorogen of TPE-M-L, highly sensitive and selective glucose detection was also conveniently achieved both in solution state and on paper-based sensor by the as-proposed strategy, with the LODs of 50nM in solution state and 10µM via visual observation, much better than those obtained by other fluorescence methods. The as-proposed sensing strategy was also successfully applied to assay glucose in human serum samples. Therefore, the paper-based fluorescence sensor exhibits the advantages of simple fabrication, high sensitivity and portability, and has great potential to be applied in on-site assay of H2O2 and glucose in real samples.

HRP-Mimicking DNAzyme-Catalyzed in Situ Generation of Polyaniline To Assist Signal Amplification for Ultrasensitive Surface Plasmon Resonance Biosensing.

It is well-known that the horseradish peroxidase- (HRP-) mimicking DNAzyme, namely, hemin/G-quadruplex, can effectively catalyze the polymerization of aniline to form DNA-guided polyaniline. Meanwhile, polyaniline exhibits extraordinary electrical, electrochemical, and redox properties, as well as excellent SPR signal-enhancing ability. Herein, we report a novel ultrasensitive surface plasmon resonance (SPR) biosensor based on HRP-mimicking DNAzyme-catalyzed in situ formation of polyaniline for signal amplification, using bleomycin (BLM) as the proof-of-concept analyte. The recognition and the subsequent cleavage of DNA probe P1 by BLM switches off the hybridization between P1 and the G-rich DNA probe P2, resulting in less hemin/G-quadruplex complexes and reduced DNA-guided polyaniline deposition on the SPR Au disk surface. As compared to the case when BLM is absent, a significant shift in SPR angle is observed, which is dependent on the BLM concentration. Therefore, ultrasensitive SPR detection of the target BLM is realized, with a detection limit down to 0.35 pM, much lower than those reported in the literature. Moreover, the proposed SPR biosensor has been successfully applied for the detection of BLM spiked in human serum samples. The HRP-mimicking DNAzyme-catalyzed in situ polyaniline deposition and polyaniline-assisted signal amplification not only significantly improves the specificity and the sensitivity of the BLM assay but also allows the ultrasensitive detection of other biomolecules by simply changing the specific target recognition DNA sequences, thus providing a versatile SPR biosensing platform for the ultrasensitive detection of a variety of analytes and showing great potential for application in the fields of bioanalysis and clinical biomedicine.

A facile, sensitive, and highly specific trinitrophenol assay based on target-induced synergetic effects of acid induction and electron transfer towards DNA-templated copper nanoclusters.

Reliable, selective and sensitive approaches for trinitrophenol (TNP) detection are highly desirable with respect to national security and environmental protection. Herein, a simple and novel fluorescent strategy for highly sensitive and specific TNP assay has been successfully developed, which is based on the quenching of the fluorescent poly(thymine)-templated copper nanoclusters (DNA-CuNCs), through the synergetic effects of acid induction and electron transfer. Upon the addition of TNP, donor-acceptor complexes between the electron-deficient nitro-groups in TNP and the electron-donating DNA templates are formed, resulting in the close proximity between TNP and CuNCs. Moreover, the acidity of TNP contributes to the pH decrease of the system. These factors combine to dramatically quench the fluorescence of DNA-CuNCs, providing a "signal-off" strategy for TNP sensing. The as-proposed strategy demonstrates high sensitivity for TNP assay, and a detection limit of 0.03µM is obtained, which is lower than those reported by using organic fluorescent materials. More significantly, this approach shows outstanding selectivity over a number of TNP analogues, such as 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (DNT), 2,4-dinitrophenol (DNP), 3-nitrophenol (NP), nitrobenzene (NB), phenol (BP), and toluene (BT). Compared with previous studies, this method does not need complex DNA sequence design, fluorescent dye labeling, or sophisticated organic reactions, rendering the strategy with additional advantages of simplicity and cost-effectiveness. In addition, the as-proposed strategy has been adopted for the detection of TNP in natural water samples, indicating its great potential to be applied in the fields of public safety and environmental monitoring.

Paper-based fluorescent sensor for rapid naked-eye detection of acetylcholinesterase activity and organophosphorus pesticides with high sensitivity and selectivity.

Various strategies have been proposed for the sensing of acetylcholinesterase (AChE) activity and organophosphorus pesticides (OPs). However, the practical application of most methods is restricted by their intrinsic drawbacks such as complexity, long analysis time, and high cost. Thus, it is highly desirable to develop simple, fast and sensitive approaches for AChE activity and OPs detection. Herein, we reported a simple paper-based fluorescent sensor (PFS) based on the aggregation induced emission (AIE) effect of tetraphenylethylene (TPE) and the addition reaction capability of maleimide, which has been used as a powerful tool for rapid naked-eye detection of AChE activity and OPs. The introduction of TPE provides the probe with unique fluorescence property in solid state and is of great importance for improving the sensitivity of PFS. The hydrolysis product of acetylthiocholine catalyzed by AChE induced the maleimide ring destruction and activated the fluorescence performance of TPE. Given that AChE activity can be specifically inhibited by OPs, the as-proposed PFS can also be utilized for sensitive detection of OPs. Meanwhile, the variation of fluorescence signal can be readily detected by naked eyes, and low detection limits of 2.5mUmL(-1) and 0.5ngmL(-1) for AChE activity and OPs are obtained, respectively. Moreover, it has been successfully applied for AChE activity and OPs detection in diluted human serum samples, showing its great potential to be applied in real samples. Thus, this strategy possesses considerable advantages of simplicity, rapid detection, portability, cost efficiency and visualization.

Aggregation induced emission amphiphile with an ultra low critical micelle concentration: fabrication, self assembling, and cell imaging.

A novel aggregation induced emission amphiphile is constructed, containing a tetraphenylethene hydrophobic moiety connected to a hydrophilic quarternary ammonium salt. Owing to an ultra low critical micelle concentration in water, the amphiphile tends to self assemble into well-defined organic nanoaggregates that exhibit intense fluorescence, stable dispersibility in dilute solutions, and excellent biocompatibility for cell imaging.

Fast co-pyrolysis of biomass and lignite in a micro fluidized bed reactor analyzer.

The co-pyrolysis characteristic of biomass and lignite were investigated in a Micro Fluidized Bed Reaction Analyzer under isothermal condition. The synergetic effect was evaluated by comparing the experimental gas yields and distributions with the calculated values, and iso-conversional method was used to calculate the kinetic parameters of formation of each gas component. The results showed that synergetic effect was manifested in co-pyrolysis. For the range of conversion investigated, the activation energies for H2, CH4, CO and CO2 were 72.90 kJ/mol, 43.90 kJ/mol, 18.51 kJ/mol and 13.44 kJ/mol, respectively; the reactions for CH4 and CO2 conformed to 2 order chemical reaction model, and for H2 and CO conformed to 1.5 order chemical reaction model; the pre-exponential factors for CH4, CO2, H2 and CO were 249.0 S(-1), 5.290 S(-1), 237.4 S(-1) and 2.693 S(-1), respectively. The discrepancy of the kinetic parameters implied that there were different pathways for forming the different gas.

Automated extraction of precise protein expression patterns in lymphoma by text mining abstracts of immunohistochemical studies.

BACKGROUND: In general, surgical pathology reviews report protein expression by tumors in a semi-quantitative manner, that is, -, -/+, +/-, +. At the same time, the experimental pathology literature provides multiple examples of precise expression levels determined by immunohistochemical (IHC) tissue examination of populations of tumors. Natural language processing (NLP) techniques enable the automated extraction of such information through text mining. We propose establishing a database linking quantitative protein expression levels with specific tumor classifications through NLP. MATERIALS AND METHODS: Our method takes advantage of typical forms of representing experimental findings in terms of percentages of protein expression manifest by the tumor population under study. Characteristically, percentages are represented straightforwardly with the % symbol or as the number of positive findings of the total population. Such text is readily recognized using regular expressions and templates permitting extraction of sentences containing these forms for further analysis using grammatical structures and rule-based algorithms. RESULTS: Our pilot study is limited to the extraction of such information related to lymphomas. We achieved a satisfactory level of retrieval as reflected in scores of 69.91% precision and 57.25% recall with an F-score of 62.95%. In addition, we demonstrate the utility of a web-based curation tool for confirming and correcting our findings. CONCLUSIONS: The experimental pathology literature represents a rich source of pathobiological information, which has been relatively underutilized. There has been a combinatorial explosion of knowledge within the pathology domain as represented by increasing numbers of immunophenotypes and disease subclassifications. NLP techniques support practical text mining techniques for extracting this knowledge and organizing it in forms appropriate for pathology decision support systems.

PhenoPhyte: a flexible affordable method to quantify 2D phenotypes from imagery.

BACKGROUND: Accurate characterization of complex plant phenotypes is critical to assigning biological functions to genes through forward or reverse genetics. It can also be vital in determining the effect of a treatment, genotype, or environmental condition on plant growth or susceptibility to insects or pathogens. Although techniques for characterizing complex phenotypes have been developed, most are not cost effective or are too imprecise or subjective to reliably differentiate subtler differences in complex traits like growth, color change, or disease resistance. RESULTS: We designed an inexpensive imaging protocol that facilitates automatic quantification of two-dimensional visual phenotypes using computer vision and image processing algorithms applied to standard digital images. The protocol allows for non-destructive imaging of plants in the laboratory and field and can be used in suboptimal imaging conditions due to automated color and scale normalization. We designed the web-based tool PhenoPhyte for processing images adhering to this protocol and demonstrate its ability to measure a variety of two-dimensional traits (such as growth, leaf area, and herbivory) using images from several species (Arabidopsis thaliana and Brassica rapa). We then provide a more complicated example for measuring disease resistance of Zea mays to Southern Leaf Blight. CONCLUSIONS: PhenoPhyte is a new cost-effective web-application for semi-automated quantification of two-dimensional traits from digital imagery using an easy imaging protocol. This tool's usefulness is demonstrated for a variety of traits in multiple species. We show that digital phenotyping can reduce human subjectivity in trait quantification, thereby increasing accuracy and improving precision, which are crucial for differentiating and quantifying subtle phenotypic variation and understanding gene function and/or treatment effects.

Data mining in healthcare and biomedicine: a survey of the literature.

As a new concept that emerged in the middle of 1990's, data mining can help researchers gain both novel and deep insights and can facilitate unprecedented understanding of large biomedical datasets. Data mining can uncover new biomedical and healthcare knowledge for clinical and administrative decision making as well as generate scientific hypotheses from large experimental data, clinical databases, and/or biomedical literature. This review first introduces data mining in general (e.g., the background, definition, and process of data mining), discusses the major differences between statistics and data mining and then speaks to the uniqueness of data mining in the biomedical and healthcare fields. A brief summarization of various data mining algorithms used for classification, clustering, and association as well as their respective advantages and drawbacks is also presented. Suggested guidelines on how to use data mining algorithms in each area of classification, clustering, and association are offered along with three examples of how data mining has been used in the healthcare industry. Given the successful application of data mining by health related organizations that has helped to predict health insurance fraud and under-diagnosed patients, and identify and classify at-risk people in terms of health with the goal of reducing healthcare cost, we introduce how data mining technologies (in each area of classification, clustering, and association) have been used for a multitude of purposes, including research in the biomedical and healthcare fields. A discussion of the technologies available to enable the prediction of healthcare costs (including length of hospital stay), disease diagnosis and prognosis, and the discovery of hidden biomedical and healthcare patterns from related databases is offered along with a discussion of the use of data mining to discover such relationships as those between health conditions and a disease, relationships among diseases, and relationships among drugs. The article concludes with a discussion of the problems that hamper the clinical use of data mining by health professionals.