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Background: Determining the source of infection is significant for the treatment of bloodstream infections (BSI). The gold standard of blood infection detection, blood cultures, have low positive rates to meet clinical needs. In this study, we investigated the ability of hybrid capture-based next generation sequencing technology to detect pathogens in peripheral blood samples collected from patients with suspected BSI. Blood cultures and capture sequencing assays were also analyzed against the final clinical diagnoses. Methods: In this study, peripheral blood samples were collected from patients with fever, chills, and suspected BSI at Jinshazhou Hospital of Guangzhou University of Chinese Medicine from March 2023 to January 2024. All samples were tested by three different technologies: plasma capture sequencing technology, white blood cell capture sequencing technology, and blood culture. Relevant clinical diagnostic information was also collected. The performances of the blood cultures were then compared to those of both plasma capture sequencing technology and white blood cell capture sequencing technology. Results: A total of 98 patients were included in this study. The positive rates of probe capture next generation sequencing (NGS technology) in plasma and white blood cells were 81.63% and 65.31%, respectively, which were both significantly higher than that of the blood culture, which was 21.43% (p < 0.001). Taking blood culture as the standard control, the sensitivity and specificity of plasma capture sequencing were 85.71% and 71.43%, respectively, while the sensitivity and specificity of white blood cell sequencing were 76.19% and 81.82%, respectively. Upon final clinical diagnosis, the clinical agreement rates of the blood cultures, plasma capture sequencing, and white blood cell capture sequencing were 39.80%, 83.67%, and 73.47%, respectively. Conclusion: Our study demonstrates the high accuracy of probe capture sequencing technology compared to blood cultures in the identification of pathogenic microorganisms in BSI upon final clinical diagnosis. Among the different sample types, white blood cell samples had a lower clinical compliance rate compared to plasma samples, possibly due to the higher host rate in cell samples, which impairs the sensitivity of pathogen detection. [ABSTRACT FROM AUTHOR]

In this study, we report a rapid and efficient strategy by cyclic square wave voltammetry (CSWV), a novel voltammetric technique, to detect dopamine (DA) and epinephrine (EP) separately and simultaneously with an unmodified graphene-based integrated electrode. The CSWV method, with high sensitivity and capability of mechanistic study, is achieved by controlling an inexpensive modified open-source potentiostat (MOSP) that has a superior performance comparable to commercial benchtop electrochemical workstations. Based on the different intramolecular cyclization reaction rates of DA and EP depending on pH, the concentration of DA could be derived from the cathodic peak at +0.12 V, and the concentration of EP could be calculated from the negative cathodic peak at −0.26 V. The CSW voltammogram presented that the linear range of both DA and EP was 5–70 μM, with a detection limit of 2.14 μM and 1.94 μM (S/N = 3) at neutral pH, respectively. In addition, the cathodic currents of CSWV were 12.68 and 10.72 times higher than those of cyclic voltammetry (CV) and 1.53 and 1.24 times higher than those of cathodic square wave voltammetry (cSWV). The proposed method showed a strong anti-interference capability and can be applied to detect DA and EP in the real sample (calf serum sample), with a recovery rate in the range of 100.05–108.25%. The introduced electrochemical determination method can provide a promising application prospect for point-of-care testing (POCT) of neurotransmitters. [ABSTRACT FROM AUTHOR]

Railway fastener recognition and detection is an important task for railway operation safety. However, the current automatic inspection methods based on computer vision can effectively detect the intact or completely missing fasteners, but they have weaker ability to recognize the partially worn ones. In our method, we exploit the EA-HOG feature fastener image, generate two symmetrical images of original test image and turn the detection of the original test image into the detection of two symmetrical images, then integrate the two recognition results of symmetrical image to reach exact recognition of original test image. The potential advantages of the proposed method are as follows: First, we propose a simple yet efficient method to extract the fastener edge, as well as the EA-HOG feature of the fastener image. Second, the symmetry images indeed reflect some possible appearance of the fastener image which are not shown in the original images, these changes are helpful for us to judge the status of the symmetry samples based on the improved sparse representation algorithm and then obtain an exact judgment of the original test image by combining the two corresponding judgments of its symmetry images. The experiment results show that the proposed approach achieves a rather high recognition result and meets the demand of railway fastener detection. [ABSTRACT FROM AUTHOR]