Ultrasensitive detection of multiple cancer biomarkers by a triple cascade amplification strategy in combination with single particle inductively coupled plasma mass spectrometry.

A versatile triple cascade amplification strategy was developed for ultrasensitive simultaneous detection of multiple cancer biomarkers using single particle inductively coupled plasma mass spectrometry (spICP-MS). The triple cascade amplification strategy consisted of an enhanced RecJf exonuclease-assisted target recycling amplification module, a hybridization chain reaction amplification module, and a signal amplification module based on DNA-templated multiple metal nanoclusters. In the enhanced RecJf exonuclease-assisted target recycling amplification module, the DNA bases at the 5' ends of aptamers for specific recognition of biomarkers were deliberately replaced by the corresponding RNA bases to enhance amplification efficiency. The signal amplification module based on DNA-templated multiple metal nanoclusters was innovatively used to amplify the signals measured by spICP-MS and at the same time effectively suppress possible background interferences. The proposed spICP-MS platform achieved satisfactory quantitative results for both carcinoembryonic antigen (CEA) and a-fetoprotein (AFP) in human serum samples with accuracy comparable to that of the commercial ELISA kits. Moreover, it has wide dynamic ranges for both CEA (0.01-100 ng/mL) and AFP (0.01-200 ng/mL). The limit of detection for CEA and AFP was 0.6 and 0.5 pg/mL, respectively. Compared with conventional biomarkers detection methods, the proposed spICP-MS platform has the advantages of operational simplicity, ultra-high sensitivity, wide dynamic range, and low background. Therefore, it is reasonable to expect that the proposed spICP-MS platform can be further developed to be a promising alternative tool for biomarker detection in fields of clinical diagnosis and biomedical research.

Highly Sensitive and Specific Mass Spectrometric Platform for miRNA Detection Based on the Multiple-Metal-Nanoparticle Tagging Strategy.

The multiple-metal-nanoparticle tagging strategy has generally been applied to the multiplexed detection of multiple analytes of interest such as microRNAs (miRNAs). Herein, it was used for the first time to improve both the specificity and sensitivity of a novel mass spectroscopic platform for miRNA detection. The mass spectroscopic platform was developed through the integration of the ligation reaction, hybridization chain reaction amplification, multiple-metal-nanoparticle tagging, and inductively coupled plasma mass spectrometry. The high specificity resulted from the adoption of the ligation reaction is further enhanced by the multiple-metal-nanoparticle tagging strategy. The combination of hybridization chain reaction amplification and metal nanoparticle tagging endows the proposed platform with the feature of high sensitivity. The proposed mass spectrometric platform achieved quite satisfactory quantitative results for Let-7a in real-world cell line samples with accuracy comparable to that of the real-time quantitative reverse-transcriptase polymerase chain reaction method. Its limit of detection and limit of quantification for Let-7a were experimentally determined to be about 0.5 and 10 fM, respectively. Furthermore, due to the unique way of utilizing the multiple-metal-nanoparticle tagging strategy, the proposed platform can unambiguously discriminate between the target miRNA and nontarget ones with single-nucleotide polymorphisms based on their response patterns defined by the relative mass spectral intensities among the multiple tagged metal elements and can also provide location information of the mismatched bases. Its unique advantages over conventional miRNA detection methods make the proposed platform a promising and alternative tool in the fields of clinical diagnosis and biomedical research.

Label-Free and Multiplexed Quantification of microRNAs by Mass Spectrometry Based on Duplex-Specific-Nuclease-Assisted Recycling Amplification.

MicroRNAs (miRNAs) are important biomarker candidates for cancer screening and early detection research. Generally, miRNAs undergo synergistic adjustments in tumor cells. Herein, a mass-spectrometric method based on a duplex-specific-nuclease (DSN)-enzyme-assisted signal-amplification technique was proposed for label-free and multiplexed detection of multiple miRNAs, and applied to the quantification of three miRNAs (i.e., miRNA-141, miRNA-21, and let-7a) in samples of HeLa and MDA-MB231 cell extracts. Experimental results showed that the digestion modes of DSN against three different DNAs complementary to miRNA-141, miRNA-21, and let-7a in their DNA-miRNA heteroduplexes were quite different, verifying the multiplexed-detection capability of the proposed method. Moreover, an advanced calibration model was derived for the quantitative analysis of the complex mass-spectral data measured during the label-free and multiplexed detection of miRNA-141, miRNA-21, and let-7a by the proposed mass-spectrometric method. With the aid of the advanced calibration model, the proposed mass-spectrometric method achieved quite reliable quantitative results for miRNA-141, miRNA-21, and let-7a in samples of HeLa and MDA-MB231 cell extracts, with recovery rates within the range of 89.2 to 111.6%. The limits of detection (LODs) of the proposed mass-spectrometric method for miRNA-141, miRNA-21, and let-7a in standard samples were estimated to be 42, 41, and 95 pM, respectively. Therefore, it is reasonable to expect that the proposed mass-spectrometric method can be a competitive alternative for the label-free and multiplexed detection of multiple miRNAs in clinical diagnosis.

Generalized ratiometric indicator based surface-enhanced Raman spectroscopy for the detection of Cd(2+) in environmental water samples.

The concept of generalized ratiometric indicator based surface-enhanced Raman spectroscopy was first introduced and successfully implemented in the detection of Cd(2+) in environmental water samples using Au nanoparticles (AuNPs) modified by trithiocyanuric acid (TMT). Without the use of any internal standard, the proposed method achieved accurate concentration predictions for Cd(2+) in environmental water samples with recoveries in the ranges of 91.8-108.1%, comparable to the corresponding values obtained by atomic absorption spectroscopy. The limit of detection and limit of quantification were estimated to be 2.9 and 8.7 nM, respectively. More importantly, other species present in water samples which cannot react with TMT and have weaker binding ability to AuNPs than TMT do not interfere with the quantification of Cd(2+). Therefore, it is expected that the combination of the generalized ratiometric indicator based surface-enhanced Raman spectroscopy with the proposed AuNP-TMT probing system can be a competitive alternative for the primary screening of Cd(2+) pollution.

A target-triggered fluorescence-SERS dual-signal nano-system for real-time imaging of intracellular telomerase activity.

Telomerase (TE) is a promising diagnostic and prognostic biomarker for many cancers. Quantification of TE activity in living cells is of great significance in biomedical and clinical research. Conventional fluorescence-based sensors for quantification of intracellular TE may suffer from problems of fast photobleaching and auto-fluorescence of some endogenous molecules, and hence are liable to produce false negative or positive results. To address this issue, a fluorescence-SERS dual-signal nano-system for real-time imaging of intracellular TE was designed by functionalizing a bimetallic Au@Ag nanostructure with 4-p-mercaptobenzoic acid (internal standard SERS tag) and a DNA hybrid complex consisted of a telomerase primer strand and its partially complimentary strand modified with Rhodamine 6G. The bimetallic Au@Ag nanostructure serves as an excellent SERS-enhancing and fluorescence-quenching substrate. Intracellular TE will trigger the extension of the primer strand and cause the shedding of Rhodamine 6G-modified complimentary strand from the nano-system through intramolecular DNA strand displacement, resulting in the recovery of the fluorescence of Rhodamine 6G and decrease in its SERS signal. Both the fluorescence of R6G and the ratio between the SERS signals of 4-p-mercaptobenzoic acid and Rhodamine 6G can be used for in situ imaging of intracellular TE. Experimental results showed that the proposed nano-system was featured with low background, excellent cell internalization efficiency, good biocompatibility, high sensitivity, good selectivity, and robustness to false positive results. It can be used to distinguish cancer cells from normal ones, identify different types of cancer cells, as well as perform absolute quantification of intracellular TE, which endows it with great potential in clinical diagnosis, target therapy and prognosis of cancer patients.

Quantitative fluorescence spectroscopy in turbid media: a practical solution to the problem of scattering and absorption.

The presence of practically unavoidable scatterers and background absorbers in turbid media such as biological tissue or cell suspensions can significantly distort the shape and intensity of fluorescence spectra of fluorophores and, hence, greatly hinder the in situ quantitative determination of fluorophores in turbid media. In this contribution, a quantitative fluorescence model (QFM) was proposed to explicitly model the effects of the scattering and absorption on fluorescence measurements. On the basis of the proposed model, a calibration strategy was developed to remove the detrimental effects of scattering and absorption and, hence, realize accurate quantitative analysis of fluorophores in turbid media. A proof-of-concept model system, the determination of free Ca(2+) in turbid media using Fura-2, was utilized to evaluate the performance of the proposed method. Experimental results showed that QFM can provide quite precise concentration predictions for free Ca(2+) in turbid media with an average relative error of about 7%, probably the best results ever achieved for turbid media without the use of advanced optical technologies. QFM has not only good performance but also simplicity of implementation. It does not require characterization of the light scattering properties of turbid media, provided that the light scattering and absorption properties of the test samples are reasonably close to those of the calibration samples. QFM can be developed and extended in many application areas such as ratiometric fluorescent sensors for quantitative live cell imaging.

Telomerase-initiated three-dimensional DNAzyme motor for monitoring of telomerase activity in living cells.

Telomerase (TE) is recognized as a potential biomarker for early diagnosis, monitoring and treatment of cancer. At present, most of the methods for TE detection are only applicable to in vitro assays, and unsuitable for in vivo applications. Though a few intracellular probes have been reported to have good specificity for TE, they do not involve signal amplification, which hinders their applicability in scenarios requiring high sensitivity. It is rather challenging to develop highly sensitive biosensors for intracellular TE detection due to the difficulty in design TE probes with both high specificity and compatibility with signal amplification in living cells. Herein, a highly sensitive and selective three-dimensional DNAzyme motor for monitoring of TE activity in living cells was developed by innovatively integrating TE-mediated chain replacement reaction with a three-dimensional DNA walker. Specifically, the DNAzyme motor was constructed by assembling both DNAzyme substrates and swing arms made up of a hairpin-structured DNAzyme and a telomeric primer onto gold nanoparticles. TE in cells can activate the DNAzyme motor to carry out continuous chain replacement and substrate cutting reactions, and hence realize signal amplification in living cells. The DNAzyme motor was successfully utilized to monitor the dynamic changes of TE activity in four types of cells. Due to the advantages of simple synthesis, good biocompatibility and high sensitivity and specificity for TE, the proposed DNAzyme motor is expected to have great application potential in the early diagnosis of cancer.

Quantitative analysis of powder mixtures by Raman spectrometry: the influence of particle size and its correction.

Particle size distribution and compactness have significant confounding effects on Raman signals of powder mixtures, which cannot be effectively modeled or corrected by traditional multivariate linear calibration methods such as partial least-squares (PLS), and therefore greatly deteriorate the predictive abilities of Raman calibration models for powder mixtures. The ability to obtain directly quantitative information from Raman signals of powder mixtures with varying particle size distribution and compactness is, therefore, of considerable interest. In this study, an advanced quantitative Raman calibration model was developed to explicitly account for the confounding effects of particle size distribution and compactness on Raman signals of powder mixtures. Under the theoretical guidance of the proposed Raman calibration model, an advanced dual calibration strategy was adopted to separate the Raman contributions caused by the changes in mass fractions of the constituents in powder mixtures from those induced by the variations in the physical properties of samples, and hence achieve accurate quantitative determination for powder mixture samples. The proposed Raman calibration model was applied to the quantitative analysis of backscatter Raman measurements of a proof-of-concept model system of powder mixtures consisting of barium nitrate and potassium chromate. The average relative prediction error of prediction obtained by the proposed Raman calibration model was less than one-third of the corresponding value of the best performing PLS model for mass fractions of barium nitrate in powder mixtures with variations in particle size distribution, as well as compactness.

Quantitative spectroscopic analysis of heterogeneous mixtures: the correction of multiplicative effects caused by variations in physical properties of samples.

Spectral measurements of complex heterogeneous types of mixture samples are often affected by significant multiplicative effects resulting from light scattering, due to physical variations (e.g., particle size and shape, sample packing, and sample surface, etc.) inherent within the individual samples. Therefore, the separation of the spectral contributions due to variations in chemical compositions from those caused by physical variations is crucial to accurate quantitative spectroscopic analysis of heterogeneous samples. In this work, an improved strategy has been proposed to estimate the multiplicative parameters accounting for multiplicative effects in each measured spectrum and, hence, mitigate the detrimental influence of multiplicative effects on the quantitative spectroscopic analysis of heterogeneous samples. The basic assumption of the proposed method is that light scattering due to physical variations has the same effects on the spectral contributions of each of the spectroscopically active chemical components in the same sample mixture. On the basis of this underlying assumption, the proposed method realizes the efficient estimation of the multiplicative parameters by solving a simple quadratic programming problem. The performance of the proposed method has been tested on two publicly available benchmark data sets (i.e., near-infrared total diffuse transmittance spectra of four-component suspension samples and near-infrared spectral data of meat samples) and compared with some empirical approaches designed for the same purpose. It was found that the proposed method provided appreciable improvement in quantitative spectroscopic analysis of heterogeneous mixture samples. The study indicates that accurate quantitative spectroscopic analysis of heterogeneous mixture samples can be achieved through the combination of spectroscopic techniques with smart modeling methodology.

Label-free and sensitive microRNA detection method based on the locked nucleic acid assisted fishing amplification strategy.

Herein, a label free and sensitive miRNA detection method with enhanced practical applicability was developed based on the locked nucleic acid (LNA) assisted repeated fishing amplification strategy. The working mechanism of the proposed method is as follows: 1) a DNA probe (i.e, L-DNA) with LNA bases is immobilized onto the surface of a gold foil. The L-DNA hybridizes with the 3' terminus of the first strands of complementary deoxyribonucleic acid (cDNA) of the target miRNA in the test samples; 2) The protruding 5' terminus of the cDNA serves as a 'fishhook' to repeatedly fish the products of a hybridization chain reaction (HCR) out from a 'reaction tube'; 3) The HCR products can be unloaded from the gold foil into a 'product tube' through temperature-controlled dehybridization; 4) The concentration of the target miRNA is determined based on the fluorescence intensity generated by the addition of SYBR-Green I (SG) into the 'product tube'. The proposed platform was applied to the detection of miRNA-122 in cell lysate samples and obtained quantitative results with accuracy comparable to the quantitative reverse transcription PCR method (qRT-PCR). It is worth pointing out that the proposed platform achieved a limit of detection value of 2.9 fM for miRNA-122 by a simple but effective LNA-assisted repeated fishing amplification strategy instead of complicated enzyme-based amplification techniques. It is reasonable to expect that the proposed method provides a competitive alternative for designing practically applicable, cost-effective and label-free miRNA detection methods.

The combined toxicity and mechanism of multi-walled carbon nanotubes and nano zinc oxide toward the cabbage.

The natural environment is a complex system, and there is never only one kind of nanomaterial entering the environment. However, many studies only considered the plant toxicity of one kind of nanomaterial and do not consider the influence of two or more kinds of nanomaterials on plant toxicity. Multi-walled carbon nanotubes (MWCNTs) and zinc oxide nanoparticles (ZnO NPs) are two common and widely used nanomaterials in water environment, so these two kinds of nanomaterials were chosen to explore the effects of their combined toxicity on cabbage. This study investigated the toxicity of MWCNTs combined with ZnO NPs on cabbage by measuring the length of roots and stems, chlorophyll content, oxidative stress, antioxidant enzyme activity, metal element content, and root scanning electron microscopy. The toxicity of single MWCNTs toward cabbage was attributed to direct oxidative damage, while the toxicity of single ZnO NPs toward cabbage was due to the high level of zinc concentration. Moreover, ZnO NPs (10 mg/L) ameliorated MWCNTs toxicity toward cabbage by improving the activity of antioxidant enzymes. ZnO NPs (50 and 100 mg/L) because of the high content of zinc disrupted the balance of other metals in the plant and increased the toxicity of MWCNTs. In conclusion, the combined toxicity of different concentrations and types of nanomaterials should be considered for a more accurate assessment of environmental risks.

Calibration model transfer in mid-infrared process analysis with in situ attenuated total reflectance immersion probes.

Process applications of mid-infrared (MIR) spectrometry may involve replacement of the spectrometer and/or measurement probe, which generally requires a calibration transfer method to maintain the accuracy of analysis. In this study, direct standardisation (DS), piecewise direct standardisation (PDS) and spectral space transformation (SST) were compared for analysis of ternary mixtures of acetone, ethanol and ethyl acetate. Three calibration transfer examples were considered: changing the spectrometer, multiplexing two probes to a spectrometer, and changing the diameter of the attenuated total reflectance (ATR) probe (as might be required when scaling up from lab to process analysis). In each case, DS, PDS and SST improved the accuracy of prediction for the test samples, analysed on a secondary spectrometer-probe combination, using a calibration model developed on the primary system. When the probe diameter was changed, a scaling step was incorporated into SST to compensate for the change in absorbance caused by the difference in ATR crystal size. SST had some advantages over DS and PDS: DS was sensitive to the choice of standardisation samples, and PDS required optimisation of the window size parameter (which also required an extra standardisation sample). SST only required a single parameter to be chosen: the number of principal components, which can be set equal to the number of standardisation samples when a low number of standards (n < 7) are used, which is preferred to minimise the time required to transfer the calibration model.

Calibration of multiplexed fiber-optic spectroscopy.

Large-scale commercial bioprocesses that manufacture biopharmaceutical products such as monoclonal antibodies generally involve multiple bioreactors operated in parallel. Spectra recorded during in situ monitoring of multiple bioreactors by multiplexed fiber-optic spectroscopies contain not only spectral information of the chemical constituents but also contributions resulting from differences in the optical properties of the probes. Spectra with variations induced by probe differences cannot be efficiently modeled by the commonly used multivariate linear calibration models or effectively removed by popular empirical preprocessing methods. In this study, for the first time, a calibration model is proposed for the analysis of complex spectral data sets arising from multiplexed probes. In the proposed calibration model, the spectral variations introduced by probe differences are explicitly modeled by introducing a multiplicative parameter for each optical probe, and then their detrimental effects are effectively mitigated through a "dual calibration" strategy. The performance of the proposed multiplex calibration model has been tested on two multiplexed spectral data sets (i.e., MIR data of ternary mixtures and NIR data of bioprocesses). Experimental results suggest that the proposed calibration model can effectively mitigate the detrimental effects of probe differences and hence provide much more accurate predictions than commonly used multivariate linear calibration models (such as PLS) with and without empirical data preprocessing methods such as orthogonal signal correction, standard normal variate, or multiplicative signal correction.

Systematic prediction error correction: a novel strategy for maintaining the predictive abilities of multivariate calibration models.

The development of reliable multivariate calibration models for spectroscopic instruments in on-line/in-line monitoring of chemical and bio-chemical processes is generally difficult, time-consuming and costly. Therefore, it is preferable if calibration models can be used for an extended period, without the need to replace them. However, in many process applications, changes in the instrumental response (e.g. owing to a change of spectrometer) or variations in the measurement conditions (e.g. a change in temperature) can cause a multivariate calibration model to become invalid. In this contribution, a new method, systematic prediction error correction (SPEC), has been developed to maintain the predictive abilities of multivariate calibration models when e.g. the spectrometer or measurement conditions are altered. The performance of the method has been tested on two NIR data sets (one with changes in instrumental responses, the other with variations in experimental conditions) and the outcomes compared with those of some popular methods, i.e. global PLS, univariate slope and bias correction (SBC) and piecewise direct standardization (PDS). The results show that SPEC achieves satisfactory analyte predictions with significantly lower RMSEP values than global PLS and SBC for both data sets, even when only a few standardization samples are used. Furthermore, SPEC is simple to implement and requires less information than PDS, which offers advantages for applications with limited data.

Ultrasensitive detection of protein biomarkers by MALDI-TOF mass spectrometry based on ZnFe2O4 nanoparticles and mass tagging signal amplification.

A facile MALDI-TOF mass spectrometric platform for quantitative analysis of protein biomarkers was developed based on magnetic ZnFe2O4 nanoparticles and mass tagging signal amplification. In this platform, magnetic ZnFe2O4 nanoparticles functionalized with an aptamer of the biomarker of interest was used to magnetically separate silica nanoparticles modified with another aptamer of the target biomarker and a barcoding peptide from solution phase in the presence of the biomarker of interest. After the silica nanoparticles were dissolved by KHF2, the released barcoding peptide was detected by MALDI-TOF mass spectrometry with magnetic ZnFe2O4 nanoparticles used as assisting matrix of laser desorption ionization. Since the mass spectral intensity of the barcoding peptide is directly related to the concentration of the target biomarker, the proposed platform can be applied to the quantification of the target biomarker in complex biological samples. The effectiveness of the proposed platform was tested on the detection of carcinoembryonic antigen (CEA) in serum. Experimental results revealed that the proposed platform could achieve quite reliable quantitative results for CEA in human serum samples with accuracy comparable to a commercial CEA ELISA Kit. Its limit of detection and limit of quantification for CEA were estimated to be 0.6 × 10-3 and 1.8 × 10-3 ng/mL, respectively, considerably lower than the corresponding values reported in literature. Due to its features of simplicity in design, extremely low background signal, high sensitivity and selectivity, the proposed method can be further developed to be a competitive alternative for the quantification of CEA and other protein biomarkers as well.

Label-free microRNA detection through analyzing the length distribution pattern of the residual fragments of probe DNA produced during exonuclease III assisted signal amplification by mass spectrometry.

Biosensors based on various spectroscopic techniques discriminate the target microRNA (miRNA) from non-target ones with single nucleotide polymorphisms (SNPs) according to the differences in signal intensities which can be caused by other factors besides SNPs. As a result, they are liable to produce false positive results. Herein, we report an attempt to develop a false-positive resistance, sensitive and reliable mass spectrometric platform for miRNA detection. In the proposed platform, the qualitative and quantitative information of the target miRNA was obtained through analyzing mass spectral responses of the multiply charged ions of the residual fragments of the probe DNA produced during exonuclease III assisted signal amplification reaction using an advanced data analysis method. The proposed platform could achieve sensitive and accurate quantitative results for the target miRNA (e.g., miRNA-141) in complex medium with a detection limit of about 1 pM, and unambiguously identify non-target miRNAs with SNPs based on the length distribution patterns of residual fragments of probe DNA. The findings obtained in this study might open an avenue for the design of new miRNA detection methods based on mass spectrometry in combination with various nuclease assisted signal amplification strategies.

A novel ratiometric fluorescent sensing method based on MnO2 nanosheet for sensitive detection of alkaline phosphatase in serum.

Alkaline phosphatase (ALP) is an important biomarker for clinical diagnosis. Abnormal levels of ALP are closely related to many diseases. In this contribution, a ratiometric fluorescent sensing method based on the competition between two oxidation-reduction reactions related to MnO2 nanosheets was developed for ALP detection. Moreover, an advanced model was derived for the quantitative analysis of the fluorescence measurements obtained by the proposed ratiometric fluorescent sensing method. With the aid of the advanced model, the proposed method achieved satisfactory quantitative results for ALP in real-world serum samples, with accuracy comparable to the corresponding results obtained by an automatic biochemical analyzer. Its recovery rates for the spiked serum samples were in the range of 98.4-115.0%, which were quite satisfactory considering the complexity of the matrices of the samples. The limit of detection and limit of quantification were estimated to be 0.09 and 0.30 U L-1, respectively. Therefore, it is reasonable to expect that the proposed ratiometric fluorescent sensing method can be further developed to be a competitive alternative for ALP detection.

A Review of Carbon Dots Produced from Biomass Wastes.

The fluorescent carbon dot is a novel type of carbon nanomaterial. In comparison with semiconductor quantum dots and fluorescence organic agents, it possesses significant advantages such as excellent photostability and biocompatibility, low cytotoxicity and easy surface functionalization, which endow it a wide application prospect in fields of bioimaging, chemical sensing, environmental monitoring, disease diagnosis and photocatalysis as well. Biomass waste is a good choice for the production of carbon dots owing to its abundance, wide availability, eco-friendly nature and a source of low cost renewable raw materials such as cellulose, hemicellulose, lignin, carbohydrates and proteins, etc. This paper reviews the main sources of biomass waste, the feasibility and superiority of adopting biomass waste as a carbon source for the synthesis of carbon dots, the synthetic approaches of carbon dots from biomass waste and their applications. The advantages and deficiencies of carbon dots from biomass waste and the major influencing factors on their photoluminescence characteristics are summarized and discussed. The challenges and perspectives in the synthesis of carbon dots from biomass wastes are also briefly outlined.

An assumption-free quantitative polymerase chain reaction method with internal standard.

In real-time quantitative polymerase chain reaction (PCR), the standard curve between threshold cycle and logarithm of template concentration is currently the gold standard for template quantification. The efficacy of this approach is limited by the necessary assumption that all samples are amplified with the same efficiency. To overcome this limitation, a new method has been proposed in this contribution for quantitative PCR with internal standard. Unlike existing methods based upon analysis of amplification profile position, the new method tries to determine the initial quantity of the target template in a sample from the fluorescence spectrum measured at a certain point during its PCR reaction. There is no unrealistic prerequisite (e.g., constant amplification efficiency) for the successful application of the new method. The performance of the new method was evaluated by the quantification of KRAS gene in HepG2 samples. Quantitative results with recovery rates in the range of 91.2-118% were achieved by the new method. It is reasonable to expect that the new method would have a place in real-time quantitative PCR, thanks to its features of no unrealistic prerequisite, sound theoretical basis, good performance, and implementation simplicity.

Detection of microRNAs by the combination of Exonuclease-III assisted target recycling amplification and repeated-fishing strategy.

A simple but effective method for the detection of miRNAs was proposed by integrating exonuclease-III assisted target recycling amplification and repeated-fishing strategy. In the proposed method, exonuclease-III assisted target recycling amplification reaction is adopted to produce a large amount of DNA fragments with fluorescence group at its 5' end in the presence of the target miRNA, which are then repeatedly fished out from the reaction mixture by a gold foil modified with a capture probe and transferred into a so-called 'product tube'. The amount of the target miRNA can then be determined from the fluorescence measurement of the solution in the 'product tube'. Application to the detection of miRNA-155 in samples of KH-2 and BRSA-2B cells revealed that the proposed method could achieve sensitive and accurate quantification of the target miRNA with a limit of detection of 36 fM and recovery rates in the range from 96.2% to 105%. Its simplicity, sensitivity and resistance to possible fluorescence interferences in complex biological samples make the proposed method a potentially competitive alternative for miRNAs detection in complex biological samples.