16S rRNA, metagenomics and 2bRAD-M sequencing to decode human thanatomicrobiome.

Microorganisms are essential in the decomposition of corpses and play a significant role in forensic science. However, previous studies have primarily focused on animal remains, specifically the gut, skin, and burial environment. Insufficient research has been conducted on the microbiota of human cadavers, especially in cases of advanced decomposition and additional tissues, resulting in a lack of relevant reference data. In this study, the microbiota of eight cadavers at different stages of decomposition were detected using 16S rRNA, metagenomic sequencing and 2bRAD-M sequencing. Nine different sites, including oral and nasal cavities, heart, liver, spleen, lung, kidney, muscle and gut, were analysed and the efficacy of these methods was evaluated. The results showed that 16S rRNA sequencing was the most cost-effective method for the study of cadavers in the early stages of decomposition, whereas for cadaveric tissues in the late stages of decomposition, 2bRAD-M could overcome host contamination more effectively than metagenomic sequencing. This paves the way for new opportunities in data retrieval and promotes in-depth investigations into the microbiota.

Antimicrobial and anti-biofilm activity of Polygonum chinense L.aqueous extract against Staphylococcus aureus.

Polygonum chinense Linn. (Polygonum chinense L.) is one of the main raw materials of Chinese patent medicines such as Guangdong herbal tea. The increasing antibiotic resistance of S. aureus and the biofilm poses a serious health threat to humans, and there is an urgent need to provide new antimicrobial agents. As a traditional Chinese medicine, the antibacterial effect of Polygonum chinense L. has been reported, but the antibacterial mechanism of Polygonum chinense L.aqueous extract and its effect on biofilm have not been studied in great detail, which hinders its application as an effective antibacterial agent. In this study, the mechanism of action of Polygonum chinense L.aqueous extract on Staphylococcus aureus (S. aureus) and its biofilm was mainly evaluated by morphological observation, flow cytometry and laser confocal experiments. Our findings demonstrate that Polygonum chinense L.aqueous extract has a significant bacteriostatic effect on S. aureus. The result of growth curve exhibits that Polygonum chinense L.aqueous extract presents a significant inhibitory effect against S. aureus. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) reveals that Polygonum chinense L.aqueous extract exerts a potent destruction of the cell wall of S. aureus and a significant inhibitory effect on the formation of S. aureus biofilm. In addition, flow cytometry showed the ability of Polygonum chinense L.aqueous extract to promote apoptosis by disrupting cell membranes of S. aureus. Notably, confocal laser scanning microscopy (CLSM) images illustrated the ability of Polygonum chinense L.aqueous to inhibit the formation of S. aureus biofilms in a dose-dependent manner. These results suggested that Polygonum chinense L.aqueous is a promising alternative antibacterial and anti-biofilm agent for combating infections caused by planktonic and biofilm cells of S. aureus.

Effect of a feeder layer composed of mouse embryonic and human foreskin fibroblasts on the proliferation of human embryonic stem cells.

The aim of the present study was to investigate the effects of feeder layers composed of various ratios of mouse embryonic fibroblasts (MEFs) and human foreskin fibroblasts (hFFs) on the growth of human embryonic stem cells (hESCs). In addition, the secretion levels of basic fibroblast growth factor (bFGF) by the feeder layers was detected. MEFs and hFFs were treated with mitomycin C and seeded onto gelatin-coated plates at a density of 1×108 cells/l. The hFFs and MEFs were combined and plated at the following ratios: 0:1, 1:2, 1:1, 2:1 and 1:0. The secretion of bFGF by the various hFF/MEF ratio feeder layers was detected using an enzyme-linked immunosorbent assay. Subsequently, hESCs were cultured on top of the various feeder layers. The differences in the cellular morphology of the hESCs were observed using microscopy, and the expression levels alkaline phosphatase (AKP) and octamer-binding transcription factor 4 (OCT-4) were detected using immunohistochemical analysis as indicators of differentiation status. The results showed that the hFFs secreted substantial quantities of bFGF, while no bFGF was secreted by the MEFs. The clones of hESC growing on the feeder layer containing MEF or hFF alone were flat. By contrast, hESC clones grown on a mixed feeder layer containing hFFs + MEFs at a ratio of 1:1 exhibited an accumulated growth with a clear edge, as compared with the other ratios. In addition, hESCs growing on the feeder layer were positive for the expression of AKP and OCT-4. In summary, feeder layer hFFs secreted bFGF, while MEFs did not, indicating that bFGF is not the only factor that supports the growth and differentiation of hESCs. The optimal growth of hESCs was achieved using a mixed feeder layer composed of hFFs + MEFs at a ratio of 1:1.

Clinical application of a novel computer-aided detection system based on three-dimensional CT images on pulmonary nodule.

The aim of this study was to investigate the clinical application effects of a novel computer-aided detection (CAD) system based on three-dimensional computed tomography (CT) images on pulmonary nodule. 98 cases with pulmonary nodule (PN) in our hospital from Jun, 2009 to Jun, 2013 were analysed in this study. All cases underwent PN detection both by the simple spiral CT scan and by the computer-aided system based on 3D CT images, respectively. Postoperative pathological results were considered as the "gold standard", for both two checking methods, the diagnostic accuracies for determining benign and malignant PN were calculated. Under simple spiral CT scan method, 63 cases is malignant, including 50 true positive cases and 13 false positive cases from the "gold standard"; 35 cases is benign, 16 true negative case and 19 false negative cases, the Sensitivity 1 (Se1)=0.725, Specificity1 (Sp1)=0.448, Agreement rate1 (Kappa 1)=0.673, J1 (Youden's index 1)=0.173, LR(+)1=1.616, LR(-)1=0.499. Kappa 1=0.673 between the 0.4 and 0.75, has a moderate consistency. Underwent computer-aided detection (CAD) based on 3D CT method, 67cases is malignant, including 62 true positive cases and 7 false positive cases; 31 cases is benign, 24 true negative case and 7 false negative cases, Sensitivity 2 (Se2)=0.899, Specificity2 (Sp2)=0.828, Agreement rate (Kappa 2)=0.877, J2 (Youden's index 2)=0.727, LR(+)2=5.212, LR(-)2=0.123. Kappa 2=0.877 >0.75, has a good consistency. Computer-aided PN detecting system based on 3D CT images has better clinical application value, and can help doctor carry out early diagnosis of lung disease (such as cancer, etc.) through CT images.

Hybrid segmentation of mass in mammograms using template matching and dynamic programming.

RATIONALE AND OBJECTIVES: Accurate image segmentation for breast lesions is a critical step in computer-aided diagnosis systems. The objective of this study was to develop a robust method for the automatic segmentation of breast masses on mammograms to extract feasible features for computer-aided diagnosis systems. MATERIALS AND METHODS: The data set used in this study consisted of 483 regions of interest extracted from 328 patients. A hybrid method for segmenting breast masses was proposed on the basis of the template-matching and dynamic programming techniques. First, a template-matching technique was used to locate and obtain the rough region of masses. Then, on the basis of this rough region, a local cost function for dynamic programming was defined. Finally, the optimal contour was derived by applying dynamic programming as an optimization technique. The performance of this proposed segmentation method was evaluated using area-based and boundary distance-based similarity measures based on radiologists' manually marked annotations. A comparison with three different segmentation algorithms on the data set was provided. RESULTS: The mean overlap percentage for our proposed hybrid method was 0.727 ± 0.127, whereas those for Timp and Karssemeijer's dynamic programming method, Song et al's plane-fitting and dynamic programming method, and the normalized cut segmentation method were 0.657 ± 0.216, 0.636 ± 0.190, and 0.562 ± 0.199, respectively. All P values for the measure distribution of our proposed method and the other three algorithms were <.001. CONCLUSIONS: A hybrid method based on the template-matching and dynamic programming techniques was proposed to segment breast masses on mammograms. Evaluation results indicate that the proposed segmentation method can improve the accuracy of mass segmentation compared to three other algorithms. The proposed segmentation method shows better performance and has great potential in improving the accuracy of computer-aided diagnosis systems in interpreting mammograms.