Matching Tabular Data to Knowledge Graph with Effective Core Column Set Discovery.

Matching tabular data to a knowledge graph (KG) is critical for understanding the semantic column types, column relationships, and entities of a table. Existing matching approaches rely heavily on core columns that represent primary subject entities on which other columns in the table depend. However, discovering these core columns before understanding the table’s semantics is challenging. Most prior works use heuristic rules, such as the leftmost column, to discover a single core column, while an insightful discovery of the core column set that accurately captures the dependencies between columns is often overlooked. To address these challenges, we introduce Dependency-aware Core Column Set Discovery (DaCo), an iterative method that uses a novel rough matching strategy to identify both inter-column dependencies and the core column set. Additionally, DaCo can be seamlessly integrated with pre-trained language models, as proposed in the optimization module. Unlike other methods, DaCo does not require labeled data or contextual information, making it suitable for real-world scenarios. In addition, it can identify multiple core columns within a table, which is common in real-world tables. We conduct experiments on six datasets, including five datasets with single core columns and one dataset with multiple core columns. Our experimental results show that DaCo outperforms existing core column set detection methods, further improving the effectiveness of table understanding tasks

Colorimetric detection of paraquat in aqueous and fruit juice samples based on functionalized gold nanoparticles

Paraquat (PQ) is a kind of herbicide, which is highly toxic to human body. In this work, we proposed a fast and simple detection method for PQ in aqueous samples based on electrostatic interactions between modified gold nanoparticles (Au NPs) and PQ. Au NPs were first modified with sodium 3-mercapto-1-propanesulfonate (Au NPs-3MPS). 3MPS with negative charge can interact with nitrogen atoms of PQ with positive charge via electrostatic force. As a result, Au NPs-3MPS aggregated together. Accordingly, the color of Au NPs-3MPS colloid changed from red to blue-gray, and the UV-vis absorption spectrum changed accordingly. The detection limit of PQ is 0.1 mg/L by naked eyes, and 0.001 mg/L by UV-vis spectroscopy. Moreover, this detection method has good specific selectivity and anti-interference performance, and it has been successfully used for detecting PQ in real environmental samples and fruit juice samples

Rapid colorimetric detection of potassium ions based on crown ether modified Au NPs sensor

Rapid colorimetric detection of potassium ions based on crown ether modified Au NPs senso

Colorimetric detection of Ba2+, Cd2+ and Pb2+ based on a multifunctionalized Au NP sensor

Colorimetric detection of Ba2+, Cd2+ and Pb2+ based on a multifunctionalized Au NP senso

Detection of circulating tumor cells based on improved SERS-active magnetic nanoparticles

Detection of circulating tumor cells based on improved SERS-active magnetic nanoparticle

Inhibitory effect of zinc oxide nanorod arrays on breast cancer cells profiled through real‐time cytokines screening by a single‐cell microfluidic platform

Abstract Zinc oxide nanorods have been extensively studied for the specific killing of breast cancer (BC) cells, and their killing mechanism and anticancer effects have been initially demonstrated. However, systematic studies at the single‐cell level are still necessary to explore cellular functions in detail. In this work, a hydrothermal method was used to synthesize zinc oxide nanorod arrays (ZnO NRs). Their effect on BC cells was demonstrated at single‐cell resolution for the first time through microfluidic chips and a single‐cell analysis platform. The inhibitory effects of ZnO NRs were observed. First, ZnO NRs suppressed cell proliferation and migration abilities. Moreover, Interferon‐γ, Tumor Necrosis Factor‐α, and Granzyme B in BC cells turned out to be antitumor instead of tumorigenic under ZnO NRs stimulation. Furthermore, ZnO NRs inhibition altered cellular functions and thus weakened intercellular and intercluster correlations. More importantly, MDA‐MB‐231 cells (strongly metastatic) showed much greater resistance to ZnO NRs than MCF‐7 cells (nonmetastatic). The experiments complemented the findings at the single‐cell level and provided a more comprehensive consideration of the potential risks and applications of ZnO NRs in breast cancer therapy, which is of great importance for biomedical research on nanomaterials

A Sensitive and Portable Double-Layer Microfluidic Biochip for Harmful Algae Detection

Harmful algal blooms (HABs) are common disastrous ecological anomalies in coastal waters. An effective algae monitoring approach is important for natural disaster warning and environmental governance. However, conducting rapid and sensitive detection of multiple algae is still challenging. Here, we designed an ultrasensitive, rapid and portable double-layer microfluidic biochip for the simultaneous quantitative detection of six species of algae. Specific DNA probes based on the 18S ribosomal DNA (18S rDNA) gene fragments of HABs were designed and labeled with the fluorescent molecule cyanine-3 (Cy3). The biochip had multiple graphene oxide (GO) nanosheets-based reaction units, in which GO nanosheets were applied to transfer target DNA to the fluorescence signal through a photoluminescence detection system. The entire detection process of multiple algae was completed within 45 min with the linear range of fluorescence recovery of 0.1 fM–100 nM, and the detection limit reached 108 aM. The proposed approach has a simple detection process and high detection performance and is feasible to conduct accurate detection with matched portable detection equipment. It will have promising applications in marine natural disaster monitoring and environmental care