Metabolism-Triggered Plasmonic Nanosensor for Bacterial Detection and Antimicrobial Susceptibility Testing of Clinical Isolates.

Antimicrobial resistance (AMR) is predicted to become the leading cause of death worldwide in the coming decades. Rapid and on-site antibiotic susceptibility testing (AST) is crucial for guiding appropriate antibiotic choices to combat AMR. With this in mind, we have designed a simple and efficient plasmonic nanosensor consisting of Cu2+ and cysteine-modified AuNP (Au/Cys) that utilizes the metabolic activity of bacteria toward Cu2+ for bacterial detection and AST. When Cu2+ is present, it induces the aggregation of Au/Cys. However, in the presence of bacteria, Cu2+ is metabolized to varying extents, resulting in distinct levels of aggregation. Moreover, the metabolic activity of bacteria can be influenced by their antibiotic susceptibility, allowing us to differentiate between susceptible and resistant strains through direct color changes from the Cu2+-Au/Cys platform over approximately 3 h. These color changes can be easily detected using naked-eye observation, smartphone analysis, or absorption readout. We have validated the platform using four clinical isolates and six types of antibiotics, demonstrating a clinical sensitivity and specificity of 95.8%. Given its simplicity, low cost, high speed, and high accuracy, the plasmonic nanosensor holds great potential for point-of-care detection of antibiotic susceptibility across various settings.

Python-assisted detection and photothermal inactivation of Salmonella typhimurium and Staphylococcus aureus on a background-free SERS chip.

In this study, a background-free surface-enhanced Raman scattering (SERS) chip with a sandwich configuration was fabricated to enable reliable detection and photothermal inactivation of multiple bacteria. The SERS chip consists of a graphene-coated, phenylboronic-modified plasmonic gold substrate (pAu/G/PBA), and two aptamer-functionalized core (gold)-shell (Prussian blue/Poly-L-lysine and 4-mercaptobenzonitrile/polydopamine) SERS tags (Au@PB@PLL@Apt and Au@MB@PDA@Apt). The detection signals rely on the characteristic and nonoverlapping Raman bands of the SERS tags within the Raman-silent region (1800-2800 cm-1), where no background signals from the sample matrix are observed, leading to improved detection sensitivity and accuracy. Considering the relatively large size of bacteria (e.g., micron level), a rapid Raman mapping technique was chosen over conventional point-scan methods to achieve more reliable quantitative analysis of bacteria. This technique involves collecting and analyzing intensity signals of SERS tags from all the scattering points with an average ensemble effect, which is facilitated by the use of Python. As a proof-of-concept, model bacterium of Salmonella typhimurium and Staphylococcus aureus were successfully detected using the SERS chip with a dynamic range of 10-107 CFU/mL. Additionally, the SERS chip demonstrated successful detection of these bacteria in whole blood samples. Moreover, the photothermal effect of pAu/G led to efficient bacteria elimination, achieving approximately 100% eradication. This study integrated a background-free SERS chip with a Python-assisted rapid Raman mapping technique, resulting in a reliable, rapid and accurate method for detecting and eliminating multiple bacteria, which may provide a promising alternative for multiple screening of bacteria in real samples.

Interobserver Variations in Target Delineation in Intensity-Modulated Radiation Therapy for Nasopharyngeal Carcinoma and its Impact on Target Dose Coverage.

BACKGROUND: To investigate the differences between physicians in target delineation in intensity-modulated radiation therapy for nasopharyngeal carcinoma as well as their impact on target dose coverage. METHODS: Ninety-nine in-hospital patients were randomly selected for retrospective analysis, and the target volumes were delineated by 2 physicians. The target volumes were integrated with the original plans, and the differential parameters, including the Dice similarity coefficient (DSC), Hausdorff distance (HD), and Jaccard similarity coefficient (JSC) were recorded. The dose-volume parameters to evaluate target dose coverage were analyzed by superimposing the same original plan to the 2 sets of images on which the target volumes were contoured by the 2 physicians. The significance of differences in target volumes and dose coverage were evaluated using statistical analysis. RESULTS: The target dose coverage for different sets of target volumes showed statistically significant differences, while the similarity metrics to evaluate geometric target volume differences did not. More specifically, for PGTVnx, the median DSC, JSC, and HD were 0.85, 0.74, and 11.73, respectively; for PCTV1, the median values were 0.87, 0.77, and 11.78, respectively; for PCTV2, the median values were 0.90, 0.82, and 16.12, respectively. For patients in stages T3-4, DSC, and JSC were reduced but HD was increased compared to those in stages T1-2. Dosimetric analysis indicated that, for the target volumes, significant differences between the 2 physicians were found in D95, D99, and V100 for all the target volumes (ie, PGTVnx, PCTV1, and PCTV2) across the whole group of patients, as well as in patients with disease stages T3-4 and T1-2. CONCLUSIONS: The target volumes delineated by the 2 physicians had a high similarity, but the maximal distances between the outer contours of the 2 sets were significantly different. In patients with advanced T stages, significant differences in dose distributions were found, stemming from the deviations of target delineation.

Human papillomavirus infection can alter the level of tumour stemness and T cell infiltration in patients with head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) usually has a poor prognosis and is associated with a high mortality rate. Its etiology is mainly the result from long-term exposure to either alcohol, tobacco or human papillomavirus (HPV) infection or a combination of these insults. However, HNSCC patients with HPV have been found to show a survival advantage over those without the virus, but the mechanism that confers this advantage is unclear. Due to the large number of HPV-independent HNSCC cases, there is a possibility that the difference in prognosis between HPV-positive (HPV+) and negative (HPV-) patients is due to different carcinogens. To clarify this, we used scRNA data and viral tracking methods in order to identify HPV+ and HPV- cells in the tumour tissues of patients infected with HPV. By comparing HPV+ and HPV- malignant cells, we found a higher level of tumour stemness in HPV- tumour cells. Using tumour stemness-related genes, we established a six-gene prognostic signature that was used to divide the patients into low- and high-risk groups. It was found that HPV patients who were at low-risk of contracting HNSCC had a higher number of CD8+ T-cells as well as a higher expression of immune checkpoint molecules. Correspondingly, we found that HPV+ tumour cells expressed higher levels of CCL4, and these were highly correlated with CD8+ T cells infiltration and immune checkpoint molecules. These data suggest that the stemness features of tumour cells are not only associated with the prognostic risk, but that it could also affect the immune cell interactions and associated signalling pathways.