Phage based magnetic capture method as an aid for real time RPA detection of Salmonella spp. in milk.

Salmonella is a major cause of foodborne diseases worldwide. Conventional rapid assays for detecting Salmonella in real samples often encounter severe matrix interference or detect the limited number of species of a genus, resulting the inaccuracy of detection. In this study, we developed a method that combined phage-based magnetic capture with real time recombinase polymerase amplification (RPA) for the rapid, highly sensitive, and specific detection of Salmonella in milk with an ultra-low detection limit. The Felix O-1 phage-conjugated magnetic beads (O-1 pMBs) synthesized in this method showed excellent capture ability for Salmonella spp. and ideal specificity for non-Salmonella strains. After O-1 pMBs-based magnetic separation, the limit of detection (LOD) of the real time RPA assay was 50 cfu/mL in milk samples, which was significantly increased by a magnitude of 3-4 orders. The method exhibited a high sensitivity (compatibility) of 100% (14/14) for all tested Salmonella serotype strains and an ideal specificity (exclusivity) of 100% (7/7) for the tested non-Salmonella strains. The entire detection process including Salmonella capture, DNA extraction, and real time RPA detection was completed within 1.5 h. Furthermore, milk samples spiked with 10 cfu/25 mL of Salmonella were detected positive after cultured in buffered peptone water for only 3 h. Therefore, the proposed method could be an alternative for the rapid and accurate detection of Salmonella.

High-resolution melting real-time PCR assays for subtyping of five diarrheagenic Escherichia coli by a single well in milk.

Diarrheagenic Escherichia coli (DEC) is a kind of foodborne pathogen that poses a significant threat to both food safety and human health. To address the current challenges of high prevalence and difficult subtyping of DEC, this study developed a method that combined multiplex polymerase chain reaction (PCR) with high resolution melting (HRM) analysis for subtyping 5 kinds of DEC. The target genes are amplified by multiplex PCR in a single well, and HRM curve analysis was applied for distinct amplicons based on different melting temperature (Tm) values. The method enables discrimination of different DEC types based on characteristic peaks and distinct Tm values in the thermal melting curve. The assay exhibited 100% sensitivity and 100% specificity with a detection limit of 0.5-1 ng/µL. The results showed that different DNA concentrations did not influence the subtyping results, demonstrating this method owed high reliability and stability. In addition, the method was also used for the detection and subtyping of DEC in milk. This method streamlines operational procedures, shorts the detection time, and offers a novel tool for subtyping DEC.

Establishment and validation of a novel risk model based on CD8T cell marker genes to predict prognosis in thyroid cancer by integrated analysis of single-cell and bulk RNA-sequencing.

Papillary thyroid cancer (PTC) is a histological type of thyroid cancer, and CD8T is important for the immune response. The single-cell RNA data were acquired from Gene Expression Omnibus. SingleR package was used for cluster identification, and CellChat was exploited to evaluate the interaction among several cell types. Bulk RNA data obtained from the cancer genome atlas were used for determination of prognosis using Kaplan-Meier and Receiver Operating Characteristic curve. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis were applied for assessment of function enrichment. The drug sensitivity was calculated in Gene Set Cancer Analysis. The regulatory network was constructed by STRING and Cytoscape. We identified 23 cell clusters and 10 cell types. Cell communication results showed CD8T cell was vital among all immune cell types. Enrichment analysis found the marker genes of CD8T cell was enriched in some signal pathways related to tumor development. Overall, FAM107B and TUBA4A were considered as hub genes and used to construct a risk model. Most immune checkpoint expressions were upregulated in tumor group. Tumor mutation burden results indicated that prognosis of PTC was not related to the mutation of hub genes. Drug sensitivity analysis showed some drugs could be effectively used for the treatment of PTC, and regulatory network identified some targets for the immunotherapy. A 2-gene model of PTC was developed based on the single-cell RNA and bulk RNA data. Besides, we found CD8T was essential for the immune response in PTC.

Enhanced Differential Evolution Algorithm with Local Search Based on Hadamard Matrix.

Differential evolution (DE) is a robust algorithm of global optimization which has been used for solving many of the real-world applications since it was proposed. However, binomial crossover does not allow for a sufficiently effective search in local space. DE's local search performance is therefore relatively poor. In particular, DE is applied to solve the complex optimization problem. In this case, inefficiency in local research seriously limits its overall performance. To overcome this disadvantage, this paper introduces a new local search scheme based on Hadamard matrix (HLS). The HLS improves the probability of finding the optimal solution through producing multiple offspring in the local space built by the target individual and its descendants. The HLS has been implemented in four classical DE algorithms and jDE, a variant of DE. The experiments are carried out on a set of widely used benchmark functions. For 20 benchmark problems, the four DE schemes using HLS have better results than the corresponding DE schemes, accounting for 80%, 75%, 65%, and 65% respectively. Also, the performance of jDE with HLS is better than that of jDE on 50% test problems. The experimental results and statistical analysis have revealed that HLS could effectively improve the overall performance of DE and jDE.

Label-free electrochemical immunosensor based on gold nanoparticle/polyethyleneimine/reduced graphene oxide nanocomposites for the ultrasensitive detection of cancer biomarker matrix metalloproteinase-1.

Matrix metalloproteinase-1 (MMP-1) is associated with many types of cancers, including oral, colorectal, and brain cancers. This paper describes the fabrication of an MMP-1 immunosensor based on a gold nanoparticle/polyethyleneimine/reduced graphene oxide (AuNP/PEI/rGO)-modified disposable screen-printed electrode (SPE). A microwave-assisted single-step method was employed for the simultaneous reduction of gold and graphene oxide in a PEI environment to avoid AuNP agglomeration. The crystal structure, chemical composition, optical properties, and interior morphology of the materials were probed by X-ray diffraction, Raman spectroscopy, UV-visible spectrometry, and transmission electron microscopy techniques. To assemble a label-free MMP-1 immunosensor layer-by-layer, 3-mercaptopropionic acid was utilized due to its strong sulfur-gold bonding ability, and its tail end was attached to a carboxyl group, allowing the MMP-1 antibody (anti-MMP-1) to be subsequently cross-linked using the traditional N-(3-dimethylaminopropyl) and N' ethylcarbodiimide hydrochloride method. Differential pulse voltammetry analysis showed a linear relationship with MMP-1 concentration in the range of 1-50 ng ml-1 with an R2 value of ∼0.996 (n = 5, RSD < 5%). This immunosensor was successfully applied for MMP-1 detection in urine, saliva, bovine serum, and cell culture media (HSC-3 & C6) of oral and brain cancers showing results comparable to those of the credible ELISA method.