12 research outputs found

    Motor-Based Autonomous Microsensor for Motion and Counting Immunoassay of Cancer Biomarker

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    A motor-based autonomous microsensor is proposed for in situ visualization immunoassay of cancer biomarkers through motion readout or tag counting. The microsensor is prepared by functionalizing a newly designed gold-nanoparticle-modified self-propelled polyaniline/Pt (AuNP/PANI/Pt) micromotor with capture antibody. The autonomous movement of the microsensor in the fuel-enhanced sample mixture results in the fast and selective recognition of the protein target and subsequent loading of the secondary-antibody-modified glycidyl methacrylate microspheres (GMA), which slows down the movement of the sensing microengine. The velocity of the microsensor and the number of GMA conjugated on the microsensor can be conveniently visualized using optical microscopy. They are negatively and positively correlated with the target concentration, respectively. Therefore, the microsensor can conveniently distinguish the concentration of carcinoembryonic antigen in a range of 1–1000 ng/mL. The motor-based microsensor can be easily prepared in batch using AuNP/PANI/Pt. The whole detection procedure for protein target can be completed in 5 min without any washing and separation step. This method shows considerable promise for diverse clinical and diagnostic applications

    Motor-Based Autonomous Microsensor for Motion and Counting Immunoassay of Cancer Biomarker

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    A motor-based autonomous microsensor is proposed for in situ visualization immunoassay of cancer biomarkers through motion readout or tag counting. The microsensor is prepared by functionalizing a newly designed gold-nanoparticle-modified self-propelled polyaniline/Pt (AuNP/PANI/Pt) micromotor with capture antibody. The autonomous movement of the microsensor in the fuel-enhanced sample mixture results in the fast and selective recognition of the protein target and subsequent loading of the secondary-antibody-modified glycidyl methacrylate microspheres (GMA), which slows down the movement of the sensing microengine. The velocity of the microsensor and the number of GMA conjugated on the microsensor can be conveniently visualized using optical microscopy. They are negatively and positively correlated with the target concentration, respectively. Therefore, the microsensor can conveniently distinguish the concentration of carcinoembryonic antigen in a range of 1–1000 ng/mL. The motor-based microsensor can be easily prepared in batch using AuNP/PANI/Pt. The whole detection procedure for protein target can be completed in 5 min without any washing and separation step. This method shows considerable promise for diverse clinical and diagnostic applications

    Table1_Fitness costs of resistance to insecticide pymetrozine combined with antimicrobial zhongshengmycin in Nilaparvata lugens (Stål).docx

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    The brown planthopper, Nilaparvata lugens (Stål), is a major pest of rice crops, and its control is critical for food security. Pymetrozine has been recommended as an alternative to imidacloprid for controlling N. lugens, but the pest has developed high resistance to it, making its prohibition and restriction urgent. To address this issue, we conducted a study using a mixture of pymetrozine and zhongshengmycin with the effective ratio of 1:40, to evaluate the fitness costs in N. lugens. Our results showed that N. lugens had a relative fitness of 0.03 under this ratio, with significantly reduced longevity, female and male adult periods, total pre-oviposition days, and fecundity. Moreover, the expression levels of the uricase gene (EC1.7.3.3) and farnesyl diphosphate farnesyl transferase gene (EC2.5.1.21) were reduced in N. lugens. These genes are involved in urea metabolism and steroid biosynthesis pathway, respectively, and their suppression can interfere with the normal nutritional function of N. lugens. Our study demonstrates that the combination of chemical insecticides and antimicrobials can delay the development of resistance and improve the efficiency of pest control. This information is valuable for researchers developing management strategies to delay the development of pymetrozine resistance in N. lugens.</p

    Label-Free Microchannel Immunosensor Based on Antibody–Antigen Biorecognition-Induced Charge Quenching

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    Pursuing convenient operations and precise testing have become an urgent requirement in clinical diagnosis, treatment, and prognosis. Label-free detection is desirable for obviating the labeling process while maintaining high sensitivity and efficiency. Here, we used the dual properties of highly selective antibody–antigen recognition and potential signaling of biomolecules to construct a label-free electroosmotic flow-driven microchannel (LF-EMB) biosensor based on an antibody–antigen biorecognition-induced charge quenching theory proposed herein. The LF-EMB consists of a one-step immune-reaction, one-button portable device, and supporting microfluidic chip, providing a high-powered tool for rapid on-site testing. The LF-EMB quantified interleukin-6 and kanamycin levels down to 1 pg/mL and 5 pg/mL, respectively, with the whole analysis completed within 35 min. The outstanding sensitivity and detection speed of the constructed LF-EMB provide a convenient option for the quantitative detection of inflammatory markers and antibiotics

    DataSheet_1_Comparison of preoperative CT- and MRI-based multiparametric radiomics in the prediction of lymph node metastasis in rectal cancer.docx

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    ObjectiveTo compare computed tomography (CT)- and magnetic resonance imaging (MRI)-based multiparametric radiomics models and validate a multi-modality, multiparametric clinical-radiomics nomogram for individual preoperative prediction of lymph node metastasis (LNM) in rectal cancer (RC) patients.Methods234 rectal adenocarcinoma patients from our retrospective study cohort were randomly selected as the training (n = 164) and testing (n = 70) cohorts. The radiomics features of the primary tumor were extracted from the non-contrast enhanced computed tomography (NCE-CT), the enhanced computed tomography (CE-CT), the T2-weighted imaging (T2WI) and the gadolinium contrast-enhanced T1-weighted imaging (CE-TIWI) of each patient. Three kinds of models were constructed based on training cohort, including the Clinical model (based on the clinical features), the radiomics models (based on NCE-CT, CE-CT, T2WI, CE-T1WI, CT, MRI, CT combing with MRI) and the clinical-radiomics models (based on CT or MRI radiomics model combing with clinical data) and Clinical-IMG model (based on CT and MRI radiomics model combing with clinical data). The performances of the 11 models were evaluated via the area under the receiver operator characteristic curve (AUC), accuracy, sensitivity, and specificity in the training and validation cohort. Differences in the AUCs among the 11 models were compared using DeLong’s test. Finally, the optimal model (Clinical-IMG model) was selected to create a radiomics nomogram. The performance of the nomogram to evaluate clinical efficacy was verified by ROC curves and decision curve analysis (DCA).ResultsThe MRI radiomics model in the validation cohort significantly outperformed than CT radiomics model (AUC, 0.785 vs. 0.721, pConclusionMRI radiomics model performed better than both CT radiomics model and Clinical model in predicting LNM of RC. The clinical-radiomics nomogram that combines the radiomics features obtained from both CT and MRI along with preoperative clinical characteristics exhibits the best diagnostic performance.</p
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