AI-assisted smartphone-based colorimetric biosensor for visualized, rapid and sensitive detection of pathogenic bacteria.

Accurate and effective detection is essential to against bacterial infection and contamination. Novel biosensors, which detect bacterial bioproducts and convert them into measurable signals, are attracting attention. We developed an artificial intelligence (AI)-assisted smartphone-based colorimetric biosensor for the visualized, rapid, sensitive detection of pathogenic bacteria by measuring the bacteria secreted hyaluronidase (HAase). The biosensor consists of the chlorophenol red-ß-D-galactopyranoside (CPRG)-loaded hyaluronic acid (HA) hydrogel as the bioreactor and the ß-galactosidase (ß-gal)-loaded agar hydrogel as the signal generator. The HAase degrades the bioreactor and subsequently determines the release of CPRG, which could further react with ß-gal to generate signal colors. The self-developed YOLOv5 algorithm was utilized to analyze the signal colors acquired by smartphone. The biosensor can provide a report within 60 min with an ultra-low limit of detection (LoD) of 10 CFU/mL and differentiate between gram-positive (G+) and gram-negative (G-) bacteria. The proposed biosensor was successfully applied in various areas, especially the evaluation of infections in clinical samples with 100% sensitivity. We believe the designed biosensor has the potential to represent a new paradigm of "ASSURED" bacterial detection, applicable for broad biomedical uses.

Serum CYFRA21-1 and SCC-Ag levels in women during pregnancy and their diagnostic value for cervical cancer.

OBJECTIVES: The incidence of cervical cancer increases every year during pregnancy. Cervical cytology in pregnant women has a unique morphology and liquid-based cytology methods are prone to cause false positives. The aim of this study was to investigate the serum cytokeratin 19 fragment antigen 21-1 (CYFRA21-1) and squamous cell carcinoma associated antigen (SCC-Ag) concentrations in healthy pregnant women during pregnancy and to assess their diagnostic value for cervical cancer in pregnancy. METHODS: In this prospective study, 165 healthy non-pregnant women, 441 healthy pregnant women and 22 patients with cervical cancer in pregnancy were recruited. The healthy pregnant women group included 143 women in the first trimester (T1), 147 in the second (T2) and 151 in the third (T3). RESULTS: Both SCC-Ag and CYFRA21-1 levels were significantly different in the healthy pregnant women group compared to the control group. The CYFRA21-1 and SCC-Ag were higher in the T1 and T3 than in the control groups. However, there was no statistically significant difference in serum CYFRA21-1 and SCC-Ag levels in the T2 group compared to the control group. The AUCs of CYFRA21-1, SCC-Ag and CYFRA21-1 combined with SCC-Ag were 0.674, 0.792, and 0.805, respectively. The cut-off values of CYFRA21-1 and SCC-Ag were 6.64 ng/mL and 1.75 ng/mL, respectively. CONCLUSIONS: Serum CYFRA21-1 and SCC-Ag levels were higher in pregnant women during early and late pregnancy compared to non-pregnant individuals, while they were not statistically different from non-pregnant women during mid-trimester. CYFRA21-1 and SCC-Ag have diagnostic value for cervical cancer in pregnancy.

Emerging technologies for engineering of extracellular vesicles.

Extracellular vesicles (EVs) are lipid-bilayer membrane-enclosed vesicles that are secreted by all cell types. Natural EVs contain biological information such as proteins, nucleic acids, and lipids from their parent cells. Therefore, EVs have been extensively studied as diagnostic biomarkers and therapeutic tools under normal and pathological conditions. However, some drawbacks, including low yield, poor therapeutic effects, lack of imaging, and targeting capacity of natural EVs, still need to be improved. Emerging engineering technologies have rendered EVs new properties or functionalities that broadened their applications in the biomedical field. Herein, in this review, we gave a brief overview of advanced strategies for EV engineering. We focused on pre-treatment of parent cells to regulate their released EVs. Meanwhile, we summarized and discussed the direct modification of EVs to achieve drug loading, imaging, and targeting functionalities for downstream applications.

circRNA-AKT1 Sequesters miR-942-5p to Upregulate AKT1 and Promote Cervical Cancer Progression.

Statistics show that the prognosis of cervical cancer (CC) is poor, and the death rate of CC in advanced stage has been rising in recent years. Increasing evidence has demonstrated that circular RNAs (circRNAs) serve as promising biomarkers in human cancers, including CC. The present study planned to find out the circRNA involved in CC and to explore its regulatory mechanism in CC. We discovered the new circRNA, circ-0033550, upregulated in CC. Its associated gene was AKT (also known as protein kinase B) serine/threonine kinase 1 (AKT1), so we renamed circ-0033550 as circ-AKT1. We confirmed the high expression of circ-AKT1 in CC samples and cell lines, as well as the circle structure of circ-AKT1. Functionally, gain- and loss-of-function experiments indicated that circ-AKT1 and AKT1 promoted CC cell proliferation and invasion. Moreover, circ-AKT1 and AKT1 were induced by transforming growth factor beta (TGF-ß) and facilitated EMT (epithelial-mesenchymal transition) in CC. Mechanically, we illustrated that circ-AKT1 upregulated AKT1 by sponging miR-942-5p. Rescue assays confirmed the role of the circ-AKT1/miR-942-5p/AKT1 axis in CC progression. In vivo assays validated that circ-AKT1 promoted tumor growth in CC. Overall, circRNA-AKT1 sequestered miR-942-5p to upregulate AKT1 and promote CC progression, which may offer a new molecular target for the treatment improvement of CC.