Search

Protein–oligonucleotide conjugates are increasingly used as detection probes in biological applications such as proximity sensing and spatial biology. The preparation of high-quality conjugate probes as starting reagents is critical for achieving good and consistent performance, which we demonstrate via the DNA proximity assay (DPA) for the one-pot quantification of protein targets. We first established a complete conjugation and anion-exchange chromatography purification workflow to reproducibly obtain pure subpopulations of protein probes carrying a discrete number of oligonucleotide strands. A systematic study using the purified conjugate sub-populations confirmed that the order of conjugate (number of oligonucleotides per protein) and its purity (the absence of the unconjugated antibody) were important for ensuring optimal and reproducible assay performance. The streamlined workflow was then successfully used to conjugate a pair of universal DPA initiator oligonucleotides onto a wide range of binders including antibodies, nanobodies, and antigens which enabled the versatile detection of different types of proteins such as cytokines, total antibodies, and specific antibody isotypes. The good assay robustness (the inter-assay coefficient of variation lower than 5%) and linear calibration curve was achieved across all targets with just a single mix-and-incubate reaction step and a short reaction time of 30 min. We anticipate the streamlined protein–oligonucleotide probe preparation workflow developed in this work to have broad utility across applications leveraging the specificity of protein bio-recognition with the programmability of DNA hybridization.

Point mutations are a common form of genetic variation and have been identified as important disease biomarkers. Conventional methods for analyzing point mutations, e.g., polymerase chain reaction (PCR), are based on differences in thermal stability of the DNA duplex, which require extensive optimization of the reaction condition and nontrivial design of sequence-selective primers. This motivated the design of molecular translators to convert molecular inputs into generic output sequences, which allows for the target recognition and signal generation regions to be designed independently. In this work, we propose a translator design based on the concept of split proximity circuit (SPC) to achieve both high sequence selectivity and assay robustness using a universal reaction condition, i.e., room temperature and constant ionic concentration. We discussed the design aspects of the SPC recognition regions and demonstrated its plug-and-play capability to discriminate different point mutations for both DNA (seven G6PD mutations) and RNA (let-7 microRNA family members) targets while retaining the same signal generation region. Despite its simple design and nonstringent assay condition requirements, the SPC retained good analytical performance to detect subnanomolar target concentration within a reasonable time of an hour.

DNA isothermal amplification techniques have been applied extensively for evaluating nucleic acid inputs but cannot be implemented directly on other types of biomolecules. In this work, we designed a proximity activation mechanism that converts protein input into DNA barcodes for the DNA exponential amplification reaction, which we termed PEAR. Several design parameters were identified and experimentally verified, which included the choice of enzymes, sequences of proximity probes and template strand via the NUPACK design tool, and the implementation of a hairpin lock on the proximity probe structure. Our PEAR system was surprisingly more robust against nonspecific DNA amplification, which is a major challenge faced in existing formats of the DNA-based exponential amplification reaction. The as-designed PEAR exhibited good target responsiveness for three protein models with a dynamic range of 4–5 orders of magnitude down to femtomolar input concentration. Overall, our proposed protein-to-DNA converter module led to the development of a stable and robust configuration of the DNA exponential amplification reaction to achieve high signal gain. We foresee this enabling the use of protein inputs for more complex molecular evaluation as well as ultrasensitive protein detection.

The aim of the Oakleigh Accommodation Service (Oakleigh) review, undertaken in late 2013, was to analyse service activities, including staff work hours, rosters and client episodes, to inform recommendations on how to improve the crisis and transitional accommodation service delivered to people who were homeless, at risk of homelessness, or escaping domestic violence. To achieve this aim internal evaluators collected feedback from staff, clients and external stakeholders to evaluate the homeless program's performance, and identify any program issues, opportunities, challenges and gaps in service delivery. This review also compared the Oakleigh staff roster, work hours and client episodes with another Salvation Army homeless program McCombe House (McCombe). The review found that the staff, external stakeholders and clients were generally very satisfied with the Oakleigh service, which they regard as both valuable and worthwhile. However, the review identified areas needing improvement in terms of teamwork, program planning, vehicle usage, access to tenancy information and after-care support. A key recommendation was the redrafting of the staff roster to achieve consistency across the two sites, Oakleigh and McCombe, to enhance the delivery of emergency accommodation for clients.

Based on synthesizing octonions and the R, G, B components of color image , a color image edge detection algorithm is proposed ,combining octonions with Echo State Networks(ESN) . The judged pixel and its eight-neighbourhood mean is used to calculate vector product as the feature vectors of image edge. Then the ESN is trained with training samples and the trained ESN is directly used for edge detection. Experiments show that this method has good effect of fabric edge detection with a stronger ability to keep the details.

Based on synthesizing quaternion and the R, G, B component of color image , a color image edge detection algorithm was proposed combining quaternion with Echo State Networks(ESN) in this paper . The pixel and its eight neighbourhood average is used to calculate vector product as the characteristic vectors of image edge. Then the ESN has been trained by the characteristic vectors. After training , the ESN is directly used for edge detection. Experiments show that this method has good effect of fabric edge detection, and have a stronger ability to keep the details.

This paper proposes an improved evolutionary computing method called an improved real quantum evolutionary algorithm (IRQEA) based on analysing the traditional quantum evolutionary algorithm. Quantum chromosomes are divided into real components andprobability amplitude components in IRQEA. One real component shows one candidate real solution obtained the optimal solution by gauss variation. Probability amplitude components maintain the population diversity through trigonometric function changes and realize more candidate solutions by less chromosomes, so as to achieve the algorithm’s better optimization abilities. Through the simulation experiments of seven common functions obtaining the optimal values ,it shows that IRQEA have many good characteristics,such as fast convergence rate and best performance.

Single-nucleotide polymorphism (SNP) is an important biomarker for disease diagnosis, treatment monitoring, and development of personalized medicine. Recent works focused primarily on ultrasensitive detection, while the need for rapid and label-free single-nucleotide discrimination techniques, which are crucial criteria for translation into clinical applications, remains relatively unexplored. In this work, we developed a novel SNP detection assay that integrates two complementary nanotechnology systems, namely, a highly selective nanoparticle–DNA detection system and a single-particle sensitive nanopore readout platform, for rapid detection of single-site mutations. Discrete nanoparticle–DNA structures formed in the presence of perfectly matched (PM) or single-mismatched (SM) targets exhibited distinct size differences, which were resolved on a size-tunable nanopore platform to generate corresponding “yes/no” readout signals. Leveraging the in situreaction monitoring capability of the nanopore platform, we demonstrated that real-time single-nucleotide discrimination of a model G487A mutation, responsible for glucose-6-phosphate dehydrogenase deficiency, can be achieved within 30 min with no false positives. Semiquantification of DNA samples down to picomolar concentration was carried out using a simple parameter of particle count without the need for sample labeling or signal amplification. The unique combination of nanoparticle-based detection and nanopore readout presented in this work brings forth a rapid, specific, yet simple biosensing strategy that can potentially be developed for point-of-care application.