Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.

Establishment of quantitative evaluation system for cochlear implant effectiveness for hearing-impaired children

Introduction:Cochlear implant is currently the most widely proven interventions for auditory rehabilitation for children with severe sensorineural hearing impairment.However,there are obvious limitations in these current evaluation methods.This study aims to develop an evaluation system for quantitatively evaluating the effectiveness of cochlear implants for hearing-impaired children.Methods:A correspondence questionnaire was developed based on an initial indicator system that was developed based on the literature focused on the evaluation of cochlear implant outcomes in children.Twenty-five experts in otology,clinical audiology,rehabilitation audiology,and mental health from nine provinces in China were consulted.The degree of authority and coordination of experts and the indicators and weights of the quantitative evaluation system were analyzed.Seventy-eight children aged 3–11 years after cochlear implantation were recruited from two centers in Hubei province to evaluate the reliability and validity of the quantitative evaluation system.Results:The opinions of experts converged after the second round of correspondence,and the coordination and authority of the expert consensus were met.The recall rate of the questionnaire was 100%for both rounds.Five secondary indicators,including auditory ability,verbal ability,behavioral assessment,learning capabilities,and quality of life,and 13 tertiary indicators were reserved for the evaluation of cochlear implant effectiveness.The weight of each indicator was calculated.The Cronbach’sαcoefficient of the quantitative evaluation system based on the standardized items was 0.930,and the three extracted common factors could explain 78.86%of the total variance.Conclusions:An expert consensus-based evaluation system that can quantitatively evaluate the effectiveness of cochlear implants in children has been developed with good reliability and validity.

Atomic-level quantitative analysis of electronic functional materials by aberration-corrected STEM

The stable sub-angstrom resolution of the aberration-corrected scanning transmission electron microscope(ACSTEM)makes it an advanced and practical characterization technique for all materials.Owing to the prosperous advancement in computational technology,specialized software and programs have emerged as potent facilitators across the entirety of electron microscopy characterization process.Utilizing advanced image processing algorithms promotes the rectification of image distortions,concurrently elevating the overall image quality to superior standards.Extracting high-resolution,pixel-level discrete information and converting it into atomic-scale,followed by performing statistical calculations on the physical matters of interest through quantitative analysis,represent an effective strategy to maximize the value of electron microscope images.The efficacious utilization of quantitative analysis of electron microscope images has become a progressively prominent consideration for materials scientists and electron microscopy researchers.This article offers a concise overview of the pivotal procedures in quantitative analysis and summarizes the computational methodologies involved from three perspectives:contrast,lattice and strain,as well as atomic displacements and polarization.It further elaborates on practical applications of these methods in electronic functional materials,notably in piezoelectrics/ferroelectrics and thermoelectrics.It emphasizes the indispensable role of quantitative analysis in fundamental theoretical research,elucidating the structure–property correlations in high-performance systems,and guiding synthesis strategies.

Accurate method based on data filtering for quantitative multi-element analysis of soils using CF-LIBS

To obtain more stable spectral data for accurate quantitative analysis of multi-element,especially for the large-area in-situ elements detection of soils, we propose a method for a multielement quantitative analysis of soils using calibration-free laser-induced breakdown spectroscopy(CF-LIBS) based on data filtering. In this study, we analyze a standard soil sample doped with two heavy metal elements, Cu and Cd, with a specific focus on the line of Cu I324.75 nm for filtering the experimental data of multiple sample sets. Pre-and post-data filtering,the relative standard deviation for Cu decreased from 30% to 10%, The limits of detection(LOD)values for Cu and Cd decreased by 5% and 4%, respectively. Through CF-LIBS, a quantitative analysis was conducted to determine the relative content of elements in soils. Using Cu as a reference, the concentration of Cd was accurately calculated. The results show that post-data filtering, the average relative error of the Cd decreases from 11% to 5%, indicating the effectiveness of data filtering in improving the accuracy of quantitative analysis. Moreover, the content of Si, Fe and other elements can be accurately calculated using this method. To further correct the calculation, the results for Cd was used to provide a more precise calculation. This approach is of great importance for the large-area in-situ heavy metals and trace elements detection in soil, as well as for rapid and accurate quantitative analysis.

Research on batch multielement rapid quantitative analysis based on the standard curve-assisted calibration-free laserinduced breakdown spectroscopy method

This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve(SC)and calibration-free laser-induced breakdown spectroscopy(CF-LIBS)technology to achieve synchronous,rapid,and accurate measurement of elements in a large number of samples,namely,SC-assisted CF-LIBS.Al alloy standard samples,divided into calibration and test samples,were applied to validate the proposed method.SC was built based on the characteristic line of Pb and Cr in the calibration sample,and the contents of Pb and Cr in the test sample were calculated with relative errors of 6%and 4%,respectively.SC built using Cr with multiple characteristic lines yielded better calculation results.The relative contents of ten elements in the test sample were calculated using CF-LIBS.Subsequently,the SC-assisted CF-LIBS was executed,with the majority of the calculation relative errors falling within the range of 2%-5%.Finally,the Al and Na contents of the Al alloy were predicted.The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multiple elements after a single-element SC analysis of the tested samples.Furthermore,this quantitative analysis method was successfully applied to soil and Astragalus samples,realizing an accurate calculation of the contents of multiple elements.Thus,it is important to advance the LIBS quantitative analysis and its related applications.

Simplified quantitative analysis method and its application in the insitu synthesized copper-based azide chips

Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.

Novel damage constitutive models and new quantitative identification method for stress thresholds of rocks under uniaxial compression

Four key stress thresholds exist in the compression process of rocks,i.e.,crack closure stress(σ_(cc)),crack initiation stress(σ_(ci)),crack damage stress(σ_(cd))and compressive strength(σ_(c)).The quantitative identifications of the first three stress thresholds are of great significance for characterizing the microcrack growth and damage evolution of rocks under compression.In this paper,a new method based on damage constitutive model is proposed to quantitatively measure the stress thresholds of rocks.Firstly,two different damage constitutive models were constructed based on acoustic emission(AE)counts and Weibull distribution function considering the compaction stages of the rock and the bearing capacity of the damage element.Then,the accumulative AE counts method(ACLM),AE count rate method(CRM)and constitutive model method(CMM)were introduced to determine the stress thresholds of rocks.Finally,the stress thresholds of 9 different rocks were identified by ACLM,CRM,and CMM.The results show that the theoretical stress−strain curves obtained from the two damage constitutive models are in good agreement with that of the experimental data,and the differences between the two damage constitutive models mainly come from the evolutionary differences of the damage variables.The results of the stress thresholds identified by the CMM are in good agreement with those identified by the AE methods,i.e.,ACLM and CRM.Therefore,the proposed CMM can be used to determine the stress thresholds of rocks.

Study on Quantitative Precipitation Estimation by Polarimetric Radar Using Deep Learning

Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.

Artificial Immune Detection for Network Intrusion Data Based on Quantitative Matching Method

Artificial immune detection can be used to detect network intrusions in an adaptive approach and proper matching methods can improve the accuracy of immune detection methods.This paper proposes an artificial immune detection model for network intrusion data based on a quantitative matching method.The proposed model defines the detection process by using network data and decimal values to express features and artificial immune mechanisms are simulated to define immune elements.Then,to improve the accuracy of similarity calculation,a quantitative matching method is proposed.The model uses mathematical methods to train and evolve immune elements,increasing the diversity of immune recognition and allowing for the successful detection of unknown intrusions.The proposed model’s objective is to accurately identify known intrusions and expand the identification of unknown intrusions through signature detection and immune detection,overcoming the disadvantages of traditional methods.The experiment results show that the proposed model can detect intrusions effectively.It has a detection rate of more than 99.6%on average and a false alarm rate of 0.0264%.It outperforms existing immune intrusion detection methods in terms of comprehensive detection performance.

Clinical Value of the Quantitative Flow Ratio to Predict Long-term Target Vessel Failure in Patients with In-stent Restenosis after Drug-coated Balloon Angioplasty

Objective The study sought to investigate the clinical predictive value of quantitative flow ratio(QFR)for the long-term target vessel failure(TVF)outcome in patients with in-stent restenosis(ISR)by using drug-coated balloon(DCB)treatment after a long-term follow-up.Methods This was a retrospective study.A total of 186 patients who underwent DCB angioplasty for ISR in two hospitals from March 2014 to September 2019 were enrolled.The QFR of the entire target vessel was measured offline.The primary endpoint was TVF,including target vessel-cardiac death(TV-CD),target vessel-myocardial infarction(TV-MI),and clinically driven-target vessel revascularization(CD-TVR).Results The follow-up time was 3.09±1.53 years,and 50 patients had TVF.The QFR immediately after percutaneous coronary intervention(PCI)was significantly lower in the TVF group than in the no-TVF group.Multivariable Cox regression analysis indicated that the QFR immediately after PCI was an excellent predictor for TVF after the long-term follow-up[hazard ratio(HR):5.15×10−5(6.13×10−8−0.043);P<0.01].Receiver-operating characteristic(ROC)curve analysis demonstrated that the optimal cut-off value of the QFR immediately after PCI for predicting the long-term TVF was 0.925(area under the curve:0.886,95%confidence interval:0.834–0.938;sensitivity:83.40%,specificity:88.00;P<0.01).In addition,QFR≤0.925 post-PCI was strongly correlated with the TVF,including TV-MI and CD-TVR(P<0.01).Conclusion The QFR immediately after PCI showed a high predictive value of TVF after a long-term follow-up in ISR patients who underwent DCB angioplasty.A lower QFR immediately after PCI was associated with a worse TVF outcome.

Quantitative hepatitis B core antibody and quantitative hepatitis B surface antigen:Novel viral biomarkers for chronic hepatitis B management

The management of hepatitis B virus(HBV)infection now involves regular and appropriate monitoring of viral activity,disease progression,and treatment response.Traditional HBV infection biomarkers are limited in their ability to predict clinical outcomes or therapeutic effectiveness.Quantitation of HBV core antibodies(qAnti-HBc)is a novel non-invasive biomarker that may help with a variety of diagnostic issues.It was shown to correlate strongly with infection stages,hepatic inflammation and fibrosis,chronic infection exacerbations,and the presence of occult infection.Furthermore,qAnti-HBc levels were shown to be predictive of spontaneous or treatment-induced HBeAg and HBsAg seroclearance,relapse after medication termination,re-infection following liver transplantation,and viral reactivation in the presence of immunosuppression.qAnti-HBc,on the other hand,cannot be relied on as a single diagnostic test to address all problems,and its diagnostic and prognostic potential may be greatly increased when paired with qHBsAg.Commercial qAnti-HBc diagnostic kits are currently not widely available.Because many methodologies are only semi-quantitative,comparing data from various studies and defining universal cut-off values remains difficult.This review focuses on the clinical utility of qAnti-HBc and qHBsAg in chronic hepatitis B management.

Real-time Quantitative PCR Analysis of Vascular Endothelial Growth Factor Receptor-2(VEGFR-2) Expression at Zebrafish Different Developmental Stages

[Objective]To investigate the expression of zebrafish vascular endothelial growth factor-2（VEGFR-2） at different developmental stages.[Method]Total RNAs were extracted from 12,24,48,72 and 96 hpf stage zebrafish embryos and larvae.Real-time quantitative RT-PCR was performed to examine the expression of VEGFR-2.The data were analyzed by 2^-△△Ct method.[Result]The expression level of VEGFR-2 gene increased gradually from 12 to 72 hpf,and subsequently decreased at 96 hpf.The expression level was lowest at 12 hpf,highest at 72 hpf,and had significant differences when compared with that of other developmental stages.[Conclusion]The expression level of VEGFR-2 increases gradually before blood vessel maturation and decreases as blood vessels mature.

Macroinvertebrate Community Index (MCI) and Quantitative Macroinvertebrate Community Index (QMCI) Analysis: A Comparative Study between Le Afe and Mulivaifagatoloa Rivers, Upolu Island, Samoa

The diversity of Samoa’s freshwater macroinvertebrates remains largely unexplored, with past studies focusing on specific species without comprehensive cataloguing. This research evaluated the health of Upolu Island’s rural rivers through macroinvertebrate analysis, particularly in the Le Afe and Mulivaifagatoloa Rivers. Collaborating with Samoa’s Water Resources Division in the Ministry of Natural Resources and Environment (MNRE), three sites along each river were sampled, representing a gradient from pristine to anthropogenically impacted areas. A total of 2953 macroinvertebrates were collected and classified into five categories using established identification keys. The Macroinvertebrate Community Index (MCI) and Quantitative Macroinvertebrate Community Index (QMCI) were applied for analysis. The results showed no clear pattern of pollutant-sensitive species prevalence or decline in less disturbed rivers. High MCI scores with low QMCI values indicated numerous low-scoring species, while the opposite suggested a richness of high-scoring taxa. Although MCI and QMCI are tools for monitoring freshwater health, this study lays the groundwork for future research to categorize Samoan macroinvertebrates and assign tolerance scores based on their presence in varying river conditions. .

Application of Real-time Fluorescent Quantitative PCR in Plant

Real-time fluorescent quantitative PCR （RQ-PCR） is a detection method by adding fluorescent dye or fluorescent probe into the PCR reaction system, using fluorescent signal accumulation to monitor amplification reactions of PCR reaction process, and finally the unknown template can be quantitatively analyzed through the standard curve. So the detection level of PCR has improved from the qualitative to the quantitative. In order to provide a theoretical reference for further application, the principle, classification, advantages and disadvantages of RQ-PCR were intro- duced, and its application and progress in plants in recent years were reviewed.

Determining the Copy Number of Exogenous Gene in Transgenic Plant by SYBR Green Real-time Quantitative PCR

[Objective] To explore the feasibility of using SYBR Green real-time quantitative PCR technique to estimate the copy numbers of exogenous gene in a transgenic plant.[Methods] Using SYBR Green real-time quantitative PCR technique,we have determined the copy numbers of the exogenous CYCD3;1 in transgenic Arabidopsis by comparing an endogenous single copy reference gene with CYCD3;1 copy numbers in transgenic plant,meanwhile comparing CYCD3;1 copy numbers between wild plant and transgenic plant.[Results]The exogenous CYCD3;1 copy numbers calculated by this method is identical with results of traditional Southern blot analysis which is highly accurate.[Conclusion]This method is simple,effective and safe for estimating transgene copy numbers.

Prevalence and Study of the Clonality of Extended-Spectrum Beta-Lactamase-Producing Klebsiella pneumoniae Strains in Neonatology at the University Hospitals of Abidjan by the Pulsed Field Gel Electrophoresis and the Quantitative Antibiogram

Background: ESBL-producing strains of Klebsiella pneumoniae, one of the main causes of nosocomial and hospital-acquired infections, are commonly associated with therapeutic impasses. Surveillance of these multidrug-resistant pathogens is a crucial tool for controlling and preventing infections. This surveillance involves the use of appropriate molecular and phenotypic typing techniques. The choice of techniques is based on criteria such as discriminatory power, intra- and inter-laboratory reproducibility, epidemiological concordance, ease of use and cost. The aim of our study was to identify clusters of Extended-Spectrum Beta-Lactamase-producing Klebsiella pneumoniae (ESBL-K. pneumoniae) strains circulating in neonatology using quantitative antibiogram (QA) and Pulsed Field Gel Electrophoresis (PFGE). Materials and Methods: This cross-sectional study included 55 K. pneumoniae strains isolated from a total of 513 samples. These various samples are taken from newborns, healthcare personnel, and the environment. K. pneumoniae identification followed standard bacteriological procedures and was confirmed using the Vitek® 2 (bioMérieux). The detection of the ESBL phenotype was performed using the synergy test. QA and PFGE were used to identify clonal relationships between the various strains isolated. Concordance between these two methods was assessed by calculating Cohen’s KAPPA coefficient and Simpson’s diversity index. Results: Among the 55 K. pneumoniae strains included in this study, 58.2% (32/55) were found to be Extended-Spectrum Beta-Lactamase (ESBL) producers. Most of these strains were isolated from neonatal samples (blood samples and rectal swabs). The quantitative antibiogram method applied to 28 out of the 32 ESBL-producing strains revealed that the isolates were grouped into 5 clusters. Pulsed Field Gel Electrophoresis performed on a total of 16 ESBL-producing strains showed the existence of four profiles. A perfect concordance was observed between the two methods. Conclusion: The results of this study highlighted the existence of clonal strains of various origins within neonatology units.

“Second quantitative characterization”and its application in fractured-vuggy carbonate reservoirs

The Ordovician fracture-vug carbonate reservoirs of Tarim Basin,are featured by developed vugs,caves and fractures.The strong heterogeneity results in huge uncertainty when these reservoirs are quantitatively characterized using merely static seismic data.The effective quantitative characterization of the reservoirs has been an urgent problem to be solved.This study creatively proposes the"second quantitative characterization"technique with the combination of dynamic and static data based on the primary static quantitative characterization and fully considering lots of key influence factors when conducting characterization.In this technique,dynamic analysis methods such as well testing,production rate transient analysis,dynamic reserve evaluation and dynamic connectivity evaluation are used to get understandings on this kind of reservoir.These understandings are used as statistical parameters to constrain the inversion of seismic wave impedance to improve the relationship between wave impedance and porosity and determine the fracture-vug morphology,calculate dynamic reserves,and then a more accurate fracture-vugmodel can be selected and used to calculate the oil-water contact inversely based on the results of"second quantitative characterization".This method can lower the uncertainties in the primary quantitative characterization of fracture-vug reservoirs,enhance the accuracy of characterization results significantly,and has achieved good application results in the fracture-vug carbonate reservoirs of Tarim Basin.

Identification of Quantitative Trait Loci for Anthesis-Silking Interval and Yield Components Under Drought Stress in Maize

A genetic linkage map with 89 SSR marker loci was constructed based on a maize (Zea mays L.) population consisting of 184 F-2 individuals from the cross, Huangzao 4 X Ye 107. The 184 F-3 families were evaluated in the field under well-watered and drought-stressed regimes in Shanxi Province of China. The objectives of the study were to identify genetic segments responsible for the expression of anthesis-silking interval (ASI), ear setting and grain yield, and to examine if the quantitative trait loci (QTLs) for ASI or yield components can be used in marker-assisted selection (MAS) to improve grain yield under drought conditions. Results showed that under well-watered and drought-stressed regimes, three and two QTLs involved in the expression of ASI were detected on chromosomes 1, 2 and 3, and 2 and 5, respectively. Under well-watered regime, two QTLs for ear setting were detected on chromosomes 3 and 6, explaining about 19.9% of the phenotypic variance, and displayed additive and partial dominant effects, respectively. Under drought-stressed condition, four QTLs for ear setting were detected on chromosomes 3, 7 and 10, which were responsible for interpreting 60.4% of the phenotypic variance, and showed dominant or partial dominant effects. Under well-watered condition, four QTLs controlling grain yield were identified on chromosomes 3, 6 and 7, while five QTLs were identified under drought stress on chromosomes 1, 2, 4 and 8. The gene action was of additive or partial dominant effects, and each QTL could explain 7.3% to 22.0% of the phenotypic variance, respectively. Under drought conditions, ASI and ear setting percentage were highly correlated with grain yield, which can be used as secondary traits for grain yield selection. Based on linked markers detected and gene action analyzed, an MAS strategy for yield improvement under drought condition could be established, which consists of QTLs contributing to decreased ASI and to increased ear setting and grain yield, respectively.

Strategies on Sample Size Determination and Qualitative and Quantitative Traits Integration to Construct Core Collection of Rice (Oryza sativa)

The development of a core collection could enhance the utilization of germplasm collections in crop improvement programs and simplify their management. Selection of an appropriate sampling strategy is an important prerequisite to construct a core collection with appropriate size in order to adequately represent the genetic spectrum and maximally capture the genetic diversity in available crop collections. The present study was initiated to construct nested core collections to determine the appropriate sample size to represent the genetic diversity of rice landrace collection based on 15 quantitative traits and 34 qualitative traits of 2 262 rice accessions. The results showed that 50-225 nested core collections, whose sampling rate was 2.2%-9.9%, were sufficient to maintain the maximum genetic diversity of the initial collections. Of these, 150 accessions （6.6%） could capture the maximal genetic diversity of the initial collection. Three data types, i.e. qualitative traits （QT1）, quantitative traits （QT2） and integrated qualitative and quantitative traits （QTT）, were compared for their efficiency in constructing core collections based on the weighted pair-group average method combined with stepwise clustering and preferred sampling on adjusted Euclidean distances. Every combining scheme constructed eight rice core collections （225, 200, 175, 150, 125, 100, 75 and 50）. The results showed that the QTT data was the best in constructing a core collection as indicated by the genetic diversity of core collections. A core collection constructed only on the information of QT1 could not represent the initial collection effectively. QTT should be used together to construct a productive core collection.

Establishment of a new quantitative detection approach to adefovir-resistant HBV and its clinical application

AIM:To establish the more feasible and sensitive assessment approach to the detection of adefovir (ADV) resistance-associated hepatitis B virus (HBV) quasispecies.METHODS: Based on the characteristics of rtA181V/T and rtN236T mutations, a new approach based on real-time fluorescent quantitative polymerase chain reaction (RT-PCR) was established for the detection of ADV-resistant HBV quasispecies, total HBV DNA, rtA181 and rtN236 mutations in blood samples from 32 chronic hepatitis B (CHB) patients with unsatisfactory curative effect on ADV and compared with routine HBV DNA sequencing.RESULTS: Both the sensitivity and specificity of this new detection approach to ADV-resistant HBV quasispecies were 100%, which were much higher than those of direct HBV DNA sequencing. The approach was able to detect 0.1% of mutated strains in a total plasmid population. Among the 32 clinical patients, single rtA181 and rtN236T mutation and double rtA181T and rtN236T mutations were detected in 20 and 8, respectively, while ADV-resistant mutations in 6 (including, rtA181V/T mutation alone in 5 patients) and no associated mutations in 26.CONCLUSION: This new approach is more feasible and efficient to detect ADV-resistant mutants of HBV and ADV-resistant mutations before and during ADV treatment with a specificity of 100% and a sensitivity of 100%.