Monitoring of Medical Wastewater by Sensitive, Convenient, and Low-Cost Determination of Small Extracellular Vesicles Using a Glycosyl-Imprinted Sensor.

The monitoring of small extracellular vesicles (sEVs) in medical waste is of great significance for the prevention of the spread of infectious diseases and the treatment of environmental pollutants in medical waste. Highly sensitive and selective detection methods are urgently needed due to the low content of sEVs in waste samples and the complex sample composition. Herein, a glycosyl-imprinted electrochemical sensor was constructed and a novel strategy for rapid, sensitive, and selective sEVs detection was proposed. The characteristic trisaccharide at the end of the glycosyl chain of the glycoprotein carried on the surface of the sEVs was used as the template molecule. The glycosyl-imprinted polymer films was then prepared by electropolymerization with o-phenylenediamine (o-PD) and 3-aminophenylboronic acid (m-APBA) as functional monomers. sEVs were captured by the imprinted cavities through the recognition and adsorption of glycosyl chains of glycoproteins on sEVs. The m-APBA molecule also acted as a signal probe and was then attached on the immobilized glycoprotein on the surface of sEVs by boric acid affinity. The electrochemical signal of m-APBA was amplificated due to the abundant glycoproteins on the surface of sEVs. The detection range of the sensor was 2.1 × 104 to 8.7 × 107 particles/mL, and the limit of detection was 1.7 × 104 particles/mL. The sensor was then applied to the determination of sEVs in medical wastewater and urine, which showed good selectivity, low detection cost, and good sensitivity.

An Electrochemiluminescent Sensor Based on Glycosyl Imprinting and Aptamer for the Detection of Cancer-Related Extracellular Vesicles.

Cancer-related extracellular vesicles (EVs) are considered important biomarkers for cancer diagnosis because they can convey a large amount of information about tumor cells. In order to detect cancer-related EVs efficiently, an electrochemiluminescence (ECL) sensor for the specific identification and highly sensitive detection of EVs in the plasma of cancer patients was constructed based on dual recognitions by glycosyl-imprinted polymer (GIP) and aptamer. The characteristic glycosyl Neu5Ac-α-(2,6)-Gal-ß-(1-4)-GlcNAc trisaccharide on the surface of EVs was used as a template molecule and 3-aminophenylboronic acid as a functional monomer to form a glycosyl-imprinted polymer by electropolymerization. After glycosyl elution, the imprinted film specifically recognized and adsorbed the EVs in the sample, and then the CD63 aptamer-bipyridine ruthenium (Aptamer-Ru(bpy)) was added to combine with the CD63 glycoprotein on the extracellular vesicle's surface, thus providing secondary recognition of the EVs. Finally, the EVs were quantitatively detected according to the ECL signal produced by the labeled bipyridine ruthenium. When more EVs were captured by the imprinted film, more probes were obtained after incubation, and the ECL signal was stronger. Under the optimized conditions, the ECL signal showed a good linear relationship with the concentration of EVs in the range of 9.5 × 102 to 9.5 × 107 particles/mL, and the limit of detection was 641 particles/mL. The GIP sensor can discriminate between the EV contents of cancer patients and healthy controls with high accuracy. Because of its affordability, high sensitivity, and ease of use, it is anticipated to be employed for cancer early detection and diagnosis.

Innovative integration of augmented reality and optical surface imaging: A coarse-to-precise system for radiotherapy positioning.

BACKGROUND: Traditional methods of radiotherapy positioning have shortcomings such as fragile skin-markers, additional doses, and lack of information integration. Emerging technologies may provide alternatives for the relevant clinical practice. PURPOSE: To propose a noninvasive radiotherapy positioning system integrating augmented reality (AR) and optical surface, and to evaluate its feasibility in clinical workflow. METHODS: AR and structured light-based surface were integrated to implement the coarse-to-precise positioning through two coherent steps, the AR-based coarse guidance and the optical surface-based precise verification. To implement quality assurance, recognition of face and pattern was used for patient authentication, case association, and accessory validation in AR scenes. The holographic images reconstructed from simulation computed tomography (CT) images, guided the initial posture correction by virtual-real alignment. The point clouds of body surface were fused, with the calibration and pose estimation of structured light cameras, and segmented according to the preset regions of interest (ROIs). The global-to-local registration for cross-source point clouds was achieved to calculate couch shifts in six degrees-of-freedom (DoF), which were ultimately transmitted to AR scenes. The evaluation based on phantom and human-body (4 volunteers) included, (i) quality assurance workflow, (ii) errors of both steps and correlation analysis, (iii) receiver operating characteristic (ROC), (iv) distance characteristics of accuracy, and (v) clinical positioning efficiency. RESULTS: The maximum errors in phantom evaluation were 3.4 ± 2.5 mm in Vrt and 1.4 ± 1.0° in Pitch for the coarse guidance step, while 1.6 ± 0.9 mm in Vrt and 0.6 ± 0.4° in Pitch for the precise verification step. The Pearson correlation coefficients between precise verification and cone beam CT (CBCT) results were distributed in the interval [0.81, 0.85]. In ROC analysis, the areas under the curve (AUC) were 0.87 and 0.89 for translation and rotation, respectively. In human body-based evaluation, the errors of thorax and abdomen (T&A) were significantly greater than those of head and neck (H&N) in Vrt (2.6 ± 1.1 vs. 1.7 ± 0.8, p < 0.01), Lng (2.3 ± 1.1 vs. 1.4 ± 0.9, p < 0.01), and Rtn (0.8 ± 0.4 vs. 0.6 ± 0.3, p = 0.01) while relatively similar in Lat (1.8 ± 0.9 vs. 1.7 ± 0.8, p = 0.07). The translation displacement range, after coarse guidance step, required for high accuracy of the optical surface component of the integrated system was 0-42 mm, and the average positioning duration of the integrated system was significantly less than that of conventional workflow (355.7 ± 21.7 vs. 387.7 ± 26.6 s, p < 0.01). CONCLUSIONS: The combination of AR and optical surface has utility and feasibility for patient positioning, in terms of both safety and accuracy.

MRE: A translational knowledge graph completion model based on multiple relation embedding.

Knowledge graph completion (KGC) has attracted significant research interest in applying knowledge graphs (KGs). Previously, many works have been proposed to solve the KGC problem, such as a series of translational and semantic matching models. However, most previous methods suffer from two limitations. First, current models only consider the single form of relations, thus failing to simultaneously capture the semantics of multiple relations (direct, multi-hop and rule-based). Second, the data-sparse problem of knowledge graphs would make part of relations challenging to embed. This paper proposes a novel translational knowledge graph completion model named multiple relation embedding (MRE) to address the above limitations. We attempt to embed multiple relations to provide more semantic information for representing KGs. To be more specific, we first leverage PTransE and AMIE+ to extract multi-hop and rule-based relations. Then, we propose two specific encoders to encode extracted relations and capture semantic information of multiple relations. We note that our proposed encoders can achieve interactions between relations and connected entities in relation encoding, which is rarely considered in existing methods. Next, we define three energy functions to model KGs based on the translational assumption. At last, a joint training method is adopted to perform KGC. Experimental results illustrate that MRE outperforms other baselines on KGC, demonstrating the effectiveness of embedding multiple relations for advancing knowledge graph completion.

Advantages of IMRT optimization with MCO compared to IMRT optimization without MCO in reducing small bowel high dose index for cervical cancer patients-individualized treatment options.

Background: Traditional intensity-modulated radiation therapy (IMRT) planning for cervical cancer is time-consuming and require iterative repeated optimization. In this study, we focused on leveraging multi-criteria optimization (MCO) to reduce the impact of small bowel high-dose indices on other optimization targets, thereby providing a rapid approach to individualized IMRT for cervical cancer patients. Methods: Our research involved a cohort of 25 cervical cancer patients who underwent IMRT radiotherapy. The patient inclusion criteria were as follows: (I) histopathological confirmation of cervical cancer, (II) underwent IMRT radiation therapy, and (III) a prescribed dose of 180 cGy/28 fractions for the patient. All plans were replanned by an experienced dosimetrist without the MCO (W-IMRT). On the basis of the W-IMRT plan, the individualized IMRT (I-IMRT) plan was generated under the priority trade-off of reducing the D2cc (D2cc is the minimal dose to the 2 cm3 of the small bowel receiving the maximal dose) index of the small bowel using the MCO method, maintaining target coverage and protecting other organs at risk (OARs) as much as possible. Statistical analysis was performed using the Wilcoxon signature rank test. Results: When the MCO method was applied to the IMRT plan, the high dose index decreased in the overlapping area between the small bowel and the planning treatment volume (PTV) (P<0.001, respectively). The D2cc index of the small bowel decreased to below 5,200 cGy in all I-IMRT plans. On the other hand, in PTV, the I-IMRT plan achieved a better homogeneity index (HI) compared to the W-IMRT plan. Significant dose reductions were also observed in the bladder (Dmean 144.8 cGy and V40 1.45%) (P<0.001, respectively), rectum (Dmean 43.9 cGy and V40 2.7%) (P<0.001, respectively) and bilateral femur heads (Dmean 150 cGy) (P<0.001, respectively). Conclusions: Dosimetric differences suggest that the I-IMRT plan using the MCO method provides better protection of other OARs and equivalently in PTV coverage, while lowering the high-dose index in the small bowel as much as possible for patients with cervical cancer, thus providing a rapid approach to achieving individualized IMRT for cervical cancer patients.

Identification and Dissipation of Chlorpyrifos and Its Main Metabolite 3,5,6-TCP during Wheat Growth with UPLC-QTOF/MS.

Ultrahigh-performance liquid chromatography system coupled to a hybrid quadrupole time-of-flight mass spectrometer (UPLC-QTOF/MS) technology was used to investigate the degradation and metabolism of chlorpyrifos during wheat growth by spraying plants with different doses of chlorpyrifos 7 days after the flowering and filling stage. We analyzed and identified chlorpyrifos metabolites in different parts of wheat in full-scan MSE mode, and established a chlorpyrifos metabolite screening library using UNIFI software. The results show that the residues of chlorpyrifos in wheat ears, leaves, and stems exhibited a decreasing trend with the prolongation of application time, and the degradation kinetics could be fitted with the first-order kinetic equation Ct = C0 e−kt. The initial residues of chlorpyrifos in different parts of the wheat were different, in the order of leaves > wheat ears > stems. The degradation rate of chlorpyrifos under field conditions is relatively fast, and the half-life value is 2.33−5.05 days. Chlorpyrifos can undergo a nucleophilic addition substitution reaction under the action of hydrolase to generate secondary metabolite 3,5,6-trichloro-2-pyridinol (3,5,6-TCP). The residual amount of 3,5,6-TCP in each part of wheat first showed an increasing trend and then decreased over time. It reached the maximum on the 3rd, 7th, or 11th day after application, and then gradually degraded. Considering that 3,5,6-TCP is a biomarker with potential threats to humans and animals, it is recommended that 3,5,6-TCP be included in the relevant regulations for dietary exposure risk assessment.

Combined-Vernier effect based on hybrid fiber interferometers for ultrasensitive temperature and refractive index sensing.

A kind of hybrid fiber interferometer consisting of a fiber Sagnac interferometer (FSI), a closed-cavity Fabry-Perot interferometer (FPI), and an open-cavity FPI is proposed for generating combined-Vernier-effect. Through adjusting the polarization-maintaining fiber (PMF) length of the FSI, the free spectral range (FSR) is tailored to be similar to that of the parallel-connected reference FPI for producing the first Vernier effect, of which the spectrum is used to match the sensing FPI spectrum for obtaining the second Vernier effect. Noticeable lower and upper spectral envelopes are achieved in the first and second Vernier effects, respectively, so called the combined-Vernier spectrum. Accessibly, the upper envelope is only sensitive to the refractive index (RI) owing to the characteristics of the open-cavity FPI, while the lower one is immune to the RI and employed to detect the temperature by taking advantage of the FSI. Most importantly, the sensitivities of RI and temperature can be significantly improved simultaneously without crosstalk. The experimental results show that the RI sensitivity is -19844.67 nm/RIU and the temperature sensitivity is -46.14 nm/°C, which can be used for high-precision temperature and RI simultaneous measurement.

A versatile and ultrasensitive molecularly imprinted electrochemiluminescence sensor with HRP-encapsulated liposome labeled by light-triggered click reaction for pesticide residues.

A novel approach for trace detection of fipronil with a molecularly imprinted electrochemiluminescence sensor (MIECLS) is proposed. The sensitivity is significantly improved via signal amplification of the enzymatic reaction of horseradish peroxidase (HRP) released from encapsulated liposomes which linked onto the template molecules after rebinding. The molecularly imprinted polymer membrane was prepared through the electropolymerization of monomers with fipronil as a template. After the elution of the template molecules, the analyte fipronil was reabsorbed into the cavities. HRP-encapsulated liposomes were linked to the target molecules by light-triggered click reaction. The higher the concentration of the target was, the more HRP-encapsulated liposomes were present on the molecularly imprinted polymer (MIP) sensor. Then, HRP was liberated from liposomes, and the catalytic degradation of hydrogen peroxide (H2O2) by HRP occurs, which changed the electrochemiluminescence intensity of luminol significantly. The change of the ∆ECL intensity was linearly proportional to the logarithm of the fipronil concentration ranging from 1.00 × 10-14 to 1.00 × 10-9 mol/L, and the detection limit was 7.77 × 10-16 mol/L. The recoveries obtained ranged from 95.7 to 105.8% with RSD < 5%. The sensitivity of the detection was significantly improved, and the analysis process was simplified in that the incubation step required in the conventional method was avoided. The sensor proposed provides a feasible platform for ultra-trace amount determination.

Recent Progress on the Isolation and Detection Methods of Exosomes.

Exosomes are known as one of extracellular vesicles, which are found in various body fluids and released by cells. As transport carrier, exosomes participate actively in intercellular communication and reflect their characteristics uniquely to the origin cells. Due to their unique biological physical properties and physiological functions, exosomes are considered to be one of best biomarkers of cancer diagnosis. At the same time, exosomes are potential therapeutic targets and drug delivery carriers. Therefore, the characteristics, functions and analytical methods of exosomes have increasingly attracted wide attention among scientists. In this review, the recent research progress on the basic characteristics and functional applications of exosomes are summarized. Furthermore and importantly, this review focuses on the recent advance in the purification and test methods of exosomes in recent years. Finally, issues pertaining to exosome detection are presented. Based on newly discovered characteristic of exosomes, the opportunities and challenges for future research of the purification and quantitative detection methods are outlined.

Fluorescence immunoassay for multiplex detection of organophosphate pesticides in agro-products based on signal amplification of gold nanoparticles and oligonucleotides.

Herein, we developed a multi-analyte fluorescence immunoassay for detection of three organophosphate pesticides (triazophos, parathion, and chlorpyrifos) in various agro-products (rice, wheat, cucumber, cabbage, and apple) using fluorescently labeled oligonucleotide and gold nanoparticle (AuNP) signal amplification technology. The AuNP probes for the three analytes were constructed by simultaneously modifying the corresponding antibodies and fluorescently labeled oligonucleotides on the probe surface. Three fluorophores (6-FAM, Cy3, and Texas red) with high fluorescence intensity and little overlap of excitation/emission wavelengths were selected. The method showed satisfactory linearity for triazophos, parathion, and chlorpyrifos in the ranges of 0.01-20, 0.05-50, and 0.5-1000 µg/L, respectively. For the 3 analytes, the limits of detection (LODs) were 0.007, 0.009, and 0.087 µg/L, respectively. The average recoveries were 77.7-113.6%, with relative standard deviations (RSDs) of 7.1-17.1% in various food matrices. The proposed method offers great potential in food safety surveillance, and could be used as well as a reference for multi-residue analysis of other small-molecule contaminants.

Performance evaluation of texture analysis based on kinetic parametric maps from breast DCE-MRI in classifying benign from malignant lesions.

BACKGROUND AND OBJECTIVES: To investigate the performance of texture analysis based on enhancement kinetic parametric maps derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in discriminating benign from malignant tumors. METHODS: A total of 192 cases confirmed by histopathology were retrospectively selected from our Picture Archiving and Communication System, including 93 benign and 99 malignant tumors. Lesion areas were delineated semi-automatically, and six kinetic parametric maps reflecting the perfusion information were generated, namely the maximum slope of increase (MSI), slope of signal intensity (SIslope ), initial percentage of peak enhancement (Einitial ), percentage of peak enhancement (Epeak ), early signal enhancement ratio (ESER), and second enhancement percentage (SEP) maps. A total of 286 texture features were extracted from those quantitative parametric maps. The Student t test or Mann-Whitney U test was used to select features that were statistically significantly different between the benign and malignant groups. A support vector machine was employed with a leave-one-out cross-validation method to establish the classification model. Classification performance was evaluated according to the receiver operating characteristic (ROC) theory. RESULTS: The areas under ROC curves (AUCs) indicating the diagnostic performance were 0.925 for MSI, 0.854 for SIslope , 0.756 for Einitial , 0.923 for Epeak , 0.871 for ESER and 0.881 for SEP. Significant differences in AUCs were found between Einitial vs MSI, Einitial vs Epeak and Einitial vs SEP (P < .05). There were no significant differences in other pairwise comparisons. CONCLUSION: Texture analysis of the kinetic parametric maps derived from breast DCE-MRI can contribute to the discrimination between malignant and benign lesions. It can be considered as a supplementary tool for breast diagnosis.

Cross-priming isothermal amplification combined with nucleic acid test strips for detection of meat species.

Adulteration of high-quality meat with their cheaper counterparts can be minimized by rapid and reliable methods for detecting meat species. Here an isothermal cross-primer amplification (CPA) technique combined with colloidal gold nucleic acid test strips (CPA strips) was developed to differentiate cow, sheep, arctic fox, and pig meat. A simple primer design for multiplex differentiation using a universal single-labeled CPA primer system and four detection-level species-specific labeling primers were analyzed by colloidal gold-based test strip assay. Moreover, simultaneous detection of fox and pig meat on a double-test line strip was feasible. The CPA strip assay indicated a lower amounts sensitivity of 0.3 ng DNA when one targeted species was tested and a detection limit of 1% when arctic fox meat was detected in the meat mixtures. Using a minimal set of primers, this study provides a promising tool for detecting the species of different types of meat using a constant temperature amplification technology.

Synthesis of molecularly imprinted polymer adsorbents for solid-phase extraction of strobilurin fungicides from agricultural products.

Molecularly imprinted polymers for strobilurin fungicides were prepared by precipitation polymerization employing azoxystrobin as template molecular together with methacrylic acid monomer and trimethylolpropane triacrylate cross-linker. Morphological characterization showed molecularly imprinted polymers were uniform spherical particles with about 0.2 µm in diameter, while the morphologies of nonimprinted polymers were irregular bulk. The equilibrium binding and selective experiments proved that molecularly imprinted polymers possessed a higher affinity toward four fungicides compared to nonimprinted polymers and heterogeneous binding sites were found in the molecularly imprinted polymers. Molecularly imprinted solid-phase extraction conditions, including sample loading solvents, selective washing, and elution solvents, were carefully optimized. The developed method showed good recoveries (70.0-114.0%) with relative standard deviations in range of 1.0-9.8% (n  = â€¯3) for samples (cucumber and peach) spiked at three different levels (10, 50, and 100 µg/ kg). The detection limit (signal/noise = 3) ranged from 0.01 to 0.08 µg/kg. The results demonstrated good potential use of this convenient and highly efficient method for determining trace strobilurin fungicides in agricultural products.

Enhancing the Sensitivity of the Bio-barcode Immunoassay for Triazophos Detection Based on Nanoparticles and Droplet Digital Polymerase Chain Reaction.

An ultrasensitive bio-barcode competitive immunoassay method based on droplet digital polymerase chain reaction (ddPCR) was developed for the determination of triazophos. Gold nanoparticles (AuNPs) were coated with monoclonal antibodies (mAbs) and complementary double-stranded DNA (dsDNA), which included bio-barcode DNA and thiol-capped DNA. Magnetic nanoparticle (MNP) probes were constructed by modifying the MNPs with ovalbumin-hapten conjugates (OVA-hapten). The target pesticide and OVA-hapten on the surface of the MNP probes competed with the AuNP probes simultaneously, and then the bio-barcode DNA was released for quantification by ddPCR. The concentration of released DNA was inversely proportional to the concentration of pesticide to be tested. Under the optimum conditions, the competitive immunoassay exhibited a wide linear range of 0.01-20 ng/mL and a low detection limit of 0.002 ng/mL. Spike recovery tests were carried out using apple, rice, cabbage, and cucumber samples to verify the feasibility of the method. The recovery and relative standard deviations (RSDs) of the technique ranged from 76.9 to 94.4% and from 10.8 to 19.9%, respectively. To further validate the results, a linear correlation analysis was performed between the proposed method and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Consequently, the bio-barcode immunoassay based on nanoparticles and ddPCR, an ultrasensitive method, showed great potential for the determination of target pesticides in real samples.

The determination of patulin from food samples using dual-dummy molecularly imprinted solid-phase extraction coupled with LC-MS/MS.

A molecularly imprinted polymer (MIP) with specific adsorption for patulin was successfully polymerized by precipitation polymerization using 2-oxindole (2-oxin) and 6-hydroxynicotinic acid (6-HNA) as dummy template molecules, methylacrylic acid (MAA) as a functional monomer, trimethylolpropane trimethacrylate (TRIM) as a crosslinker, 2,2-azobis-(2-methylpropionitrile) (AIBN) as a initiator, and methanol as a porogen solvent. The molecularly imprinted solid phase extraction (MI-SPE) column was prepared using the polymer as a sorbent and applied for the selective extraction of patulin from real samples. The results showed that the MI-SPE method had high selectivity and specific adsorption towards patulin with mean recoveries ranged between 81.3% and 106.3% and a relative standard deviation (RSD) < 4.5%. Additionally, the developed MI-SPE method coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) exhibited good linearity in the range of 1-100 ng mL-1 with correlation coefficients (R2) >0.998. The limits of detection (LODs, S/N = 3) were 0.05-0.2 ng g-1, and the limits of quantification (LOQs, S/N = 10) were 0.2-0.5 ng g-1. The developed method showed a better purification and higher patulin recovery for real samples than the quick, easy, cheap, effective, rugged, safe "QuEChERS" method.

The Potential Use of DCE-MRI Texture Analysis to Predict HER2 2+ Status.

Purpose: To evaluate the ability of texture analysis of breast dynamic contrast enhancement-magnetic resonance (DCE-MR) images in differentiating human epidermal growth factor receptor 2 (HER2) 2+ status of breast tumors. Methods: A total of 73 cases were retrospectively selected. HER2 2+ status was confirmed by fluorescence in situ hybridization. For each case, 279 textural features were derived. A student's t-test or Mann-Whitney U test was used to select features with statistically significant differences between HER2 2+ positive and negative groups. A principal component analysis was applied to eliminate feature correlation. Three machine learning classifiers, logistic regression (LR), quadratic discriminant analysis (QDA), and a support vector machine (SVM), were trained and tested using a leave-one-out cross-validation method. The area under a receiver operating characteristic curve (AUC) was measured to assess the classifier's performance. Results: The AUCs for the different classifiers were satisfactory, ranging from 0.808 to 0.865. The classification methods derived with LR and SVM demonstrated similarly high performances, and the accuracy levels were 81.06 and 81.18%, respectively. The AUC for the classifier derived with SVM was the highest (0.865), and a marked specificity (88.90%) was presented. For the classifier with LR, the AUC was 0.851, and the corresponding sensitivity (94.44%) was the highest. Conclusion: The texture analysis for breast DCE-MRI proposed in this study demonstrated potential utility in HER2 2+ status discrimination.

Classification of breast mass lesions on dynamic contrast-enhanced magnetic resonance imaging by a computer-assisted diagnosis system based on quantitative analysis.

The aim of the current study was to develop a semi-automatic and quantitative method for the analysis of a time-intensity curve (TIC) from breast dynamic contrast-enhanced magnetic resonance imaging. The performance of the proposed method, based on the level set segmentation algorithm, was evaluated by comparison with the traditional method. In the traditional method, the lesion area is delineated manually and the corresponding mean TIC is classified subjectively as one of three washout patterns. In addition, only one quantitative parameter, the maximum slope of increase (MSI), is calculated. In the proposed method, the lesion region was determined semi-automatically and the corresponding mean TIC was categorized quantitatively. In addition to MSI, a number of quantitative parameters were derived from the mean TIC and lesion area, including signal intensity slope (SIslope), initial percentage of enhancement (Einitial), percentage of peak enhancement (Epeak), early signal enhancement ratio (ESER) and second enhancement percentage (SEP). Wilcoxon signed-rank test and receiver operating characteristic analyses were performed for statistical analysis. For TIC categorization the accuracy was 61.54% for the traditional method and 82.05% for the proposed method. Using the proposed method, mean curve accuracies were 84.0% for SIslope, 66.7% for MSI, 66.0% for Einitial, 66.0% for Epeak, 68.0% for ESER and 44.9% for SEP. In the lesion region, the accuracies for the aforementioned parameters were 80.8, 65.4, 66.7, 62.2, 69.2 and 57.1%, respectively. Accuracy of the MSI value derived from the traditional method was 63.4%. Compared with the traditional method, the proposed semi-automatic method in the current study may provide results with a higher accuracy to differentiate benign and malignant lesions. Therefore, the proposed method should be considered as a supplementary tool for the diagnosis of breast lesions.

Occurrences of the Typical Agricultural Non-ionic Surfactants Tristyrylphenol Ethoxylates in Cherries ( Cerasus pseudocerasus), Peaches ( Amygdalus persica), and Kiwifruit ( Actinidia chinensis) and the Implications of Human Exposure in China.

Tristyrylphenol ethoxylates (TSP nEOs) are widely used as non-ionic surfactants in pesticide formulations in China. However, limited information is available regarding the occurrences of TSP nEOs in fruits. In this study, 361 fruit samples were collected from the main growing areas in China from 2016 to 2017 and analyzed for TSP nEO contamination using gel permeation chromatography-high-performance liquid chromatography-tandem mass spectrometry. TSP nEOs were detected in all samples, with a total concentration range of 0.5-14786.0 µg/kg (median of 85.0 µg/kg). The total concentrations were significantly but weakly correlated with the residues of acetamiprid ( r = 0.119; p < 0.05) and carbendazim ( r = -0.170; p < 0.01), suggesting that the TSP nEO residues are probably associated with the use of these pesticides during fruit growth. A risk assessment showed that there were little or no risks to human health. However, the risks to health associated with exposure to TSP nEOs should not be ignored because of their ubiquitousness in fruit samples.