Universal Digital High-Resolution Melt Analysis for the Diagnosis of Bacteremia.

Fast and accurate diagnosis of bloodstream infection is necessary to inform treatment decisions for septic patients, who face hourly increases in mortality risk. Blood culture remains the gold standard test but typically requires approximately 15 hours to detect the presence of a pathogen. We, therefore, assessed the potential for universal digital high-resolution melt (U-dHRM) analysis to accomplish faster broad-based bacterial detection, load quantification, and species-level identification directly from whole blood. Analytical validation studies demonstrated strong agreement between U-dHRM load measurement and quantitative blood culture, indicating that U-dHRM detection is highly specific to intact organisms. In a pilot clinical study of 17 whole blood samples from pediatric patients undergoing simultaneous blood culture testing, U-dHRM achieved 100% concordance when compared with blood culture and 88% concordance when compared with clinical adjudication. Moreover, U-dHRM identified the causative pathogen to the species level in all cases where the organism was represented in the melt curve database. These results were achieved with a 1-mL sample input and sample-to-answer time of 6 hours. Overall, this pilot study suggests that U-dHRM may be a promising method to address the challenges of quickly and accurately diagnosing a bloodstream infection.

Universal digital high resolution melt analysis for the diagnosis of bacteremia.

Fast and accurate diagnosis of bloodstream infection is necessary to inform treatment decisions for septic patients, who face hourly increases in mortality risk. Blood culture remains the gold standard test but typically requires ∼15 hours to detect the presence of a pathogen. Here, we assess the potential for universal digital high-resolution melt (U-dHRM) analysis to accomplish faster broad-based bacterial detection, load quantification, and species-level identification directly from whole blood. Analytical validation studies demonstrated strong agreement between U-dHRM load measurement and quantitative blood culture, indicating that U-dHRM detection is highly specific to intact organisms. In a pilot clinical study of 21 whole blood samples from pediatric patients undergoing simultaneous blood culture testing, U-dHRM achieved 100% concordance when compared with blood culture and 90.5% concordance when compared with clinical adjudication. Moreover, U-dHRM identified the causative pathogen to the species level in all cases where the organism was represented in the melt curve database. These results were achieved with a 1 mL sample input and sample-to-answer time of 6 hrs. Overall, this pilot study suggests that U-dHRM may be a promising method to address the challenges of quickly and accurately diagnosing a bloodstream infection. Universal digital high resolution melt analysis for the diagnosis of bacteremia: April Aralar, Tyler Goshia, Nanda Ramchandar, Shelley M. Lawrence, Aparajita Karmakar, Ankit Sharma, Mridu Sinha, David Pride, Peiting Kuo, Khrissa Lecrone, Megan Chiu, Karen Mestan, Eniko Sajti, Michelle Vanderpool, Sarah Lazar, Melanie Crabtree, Yordanos Tesfai, Stephanie I. Fraley.

Induction of epithelial to mesenchymal transition in HPV16 E6/E7 oncogene transfected C33A cell line.

This study focuses on the induction of EMT by HPV16 in the C33A cell line. Expression of ß-catenin, EMT-transcription factors (EMT-TFs), and c-myc in the nuclei of HPV16 E6/E7 oncogene transfected and non-transfected C33A cells were investigated through immunofluorescence and RT-PCR. Microphotographs of ß-catenin, c-myc, and DAPI-stained nuclei were processed and analyzed by Python and ImageJ respectively. Microphotographs of immunocytochemically stained transfected and control cells were then processed and analyzed with the help of ImageJ and Python programming. The intensity and the integrated density of ß-catenin were computed at the cell membrane area as well as the cytoplasmic area along with the integrated density of c-myc and Renyi entropy of DAPI-stained nuclei was quantified by ImageJ software. Python programming was implemented to determine the total percentage of white pixels depicting the presence of ß-catenin in the cytoplasmic area of cells. The signal of ß-catenin at the cytoplasmic area was found significantly higher in transfected samples which implies the nuclear accumulation of ß-catenin. The expression of the c-myc protein was found significantly higher in transfected cells along with significantly higher nuclear entropy. RT-PCR result shows two folds of up-regulation of EMT-TFs Snail1, Twist1, and Zeb2 and down-regulation of Snail2 and Twist2. The study concludes that HPV16 E6/E7 oncogene can induce EMT.

Simple formulation and characterization of double emulsion variant designed to carry three bioactive agents.

Multiple emulsions are thermodynamically stable systems that mark applications in various fields including drug delivery systems. They allow enhanced availability of drugs, greater absorption, and present reduced toxicity, among other desirable properties. In this work, we aimed to formulate a unique double emulsion (O1/W + W1/O2/W/W) with three bioactive components viz. Ocimum tenuiflorum oil, Cocos nucifera oil and crystalline Cinnamomum camphora. Three surfactants with different HLB values viz. Tween-20, Tween-80 and Triton X-100 were used for the emulsification process. The method followed was simple as compared to current methods employed for formulating multiple emulsions. Formulation was characterized using techniques of bright field microscopy, Dynamic Light Scattering (DLS), High-Resolution Transmission Electron Microscopy (HR-TEM) and Fourier-transform infrared spectroscopy (FTIR). Image processing tools were also used to characterize the formulation, which reliably cross-verified the observations from conventional characterization techniques. The potency of individual components of emulsion was compared with the prepared double emulsion model by testing the activity on two pathologically relevant bacterial strains: Fusobacterium nucleatum (FN) and Porphyromonas gingivalis (PG).