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Intracellularly measured luciferases, such as Firefly luciferase and Nano luciferase, revealed good compatibility with complex body fluids. Secreted Gaussia luciferase appeared to be incompatible with complex body fluids, due to variability in inter-donor signal interference. Unstable Nano luciferase demonstrated clear inducibility, high sensitivity and compatibility with complex body fluids and therefore can be recommended for cellular signaling studies using complex body fluids.The purpose of this study was to develop a fully-automated segmentation algorithm, robust to various density enhancing lung abnormalities, to facilitate rapid quantitative analysis of computed tomography images. A polymorphic training approach is proposed, in which both specifically labeled left and right lungs of humans with COPD, and nonspecifically labeled lungs of animals with acute lung injury, were incorporated into training a single neural network. The resulting network is intended for predicting left and right lung regions in humans with or without diffuse opacification and consolidation. Performance of the proposed lung segmentation algorithm was extensively evaluated on CT scans of subjects with COPD, confirmed COVID-19, lung cancer, and IPF, despite no labeled training data of the latter three diseases. selleck kinase inhibitor Lobar segmentations were obtained using the left and right lung segmentation as input to the LobeNet algorithm. Regional lobar analysis was performed using hierarchical clustering to identify radiographic subtypes of COVID-19. The proposed lung segmentation algorithm was quantitatively evaluated using semi-automated and manually-corrected segmentations in 87 COVID-19 CT images, achieving an average symmetric surface distance of [Formula see text] mm and Dice coefficient of [Formula see text]. Hierarchical clustering identified four radiographical phenotypes of COVID-19 based on lobar fractions of consolidated and poorly aerated tissue. Lower left and lower right lobes were consistently more afflicted with poor aeration and consolidation. However, the most severe cases demonstrated involvement of all lobes. The polymorphic training approach was able to accurately segment COVID-19 cases with diffuse consolidation without requiring COVID-19 cases for training.There is significant interest in understanding the pathophysiology of Obsessive-Compulsive Disorder (OCD) using resting-state fMRI (rsfMRI). Previous studies acknowledge abnormalities within and beyond the fronto-striato-limbic circuit in OCD that require further clarifications. However, limited information could be inferred from the conventional way of investigating the functional connectivity differences between OCD and healthy controls. Here, we identified altered brain organization in patients with OCD by applying individual-based approaches to maximize the identification of underlying network-based features specific to the OCD group. rsfMRI of 20 patients with OCD and 22 controls were preprocessed, and individual-fMRI-subspace was derived for each subject within each group. We evaluated group differences in functional connectivity using individual-fMRI-subspace and established its advantage over conventional-fMRI methodology. We applied prediction-based approaches to highlight the group differences by evwe observed functional connectivity between cerebellar and visual regions, and lack of connectivity between striato-limbic and frontal areas. Inter-individual variations in the community-size of these two communities were also associated with the OCI-R score (p  less then  .005). Due to our small sample size, we further validated our results by (i) accounting for head motion, (ii) applying global signal regression (GSR) in data processing, and (iii) using an alternate atlas for parcellation. While the main results were consistently observed with accounting for head motion and using another atlas, the key findings were not reproduced with GSR application. The study demonstrated the existence of disconnectedness in fronto-striato-limbic community and connectedness between cerebellar and visual areas in OCD patients, which was also related to the clinical symptomatology of OCD.Emerging evidence has shown a link between the perturbations and development of the gut microbiota in infants with their immediate and long-term health. To better understand the assembly of the gut microbiota in preterm infants, faecal samples were longitudinally collected from the preterm (n = 19) and term (n = 20) infants from birth until month 12. 16S rRNA gene sequencing (n = 141) and metabolomics profiling (n = 141) using nuclear magnetic resonance spectroscopy identified significant differences between groups in various time points. A panel of amino acid metabolites and central metabolism intermediates significantly correlated with the relative abundances of 8 species of bacteria were identified in the preterm group. In contrast, faecal metabolites of term infants had significantly higher levels of metabolites which are commonly found in milk such as fucose and β-hydroxybutyrate. We demonstrated that the early-life factors such as gestational age, birth weight and NICU exposures, exerted a sustained effect to the dynamics of gut microbial composition and metabolism of the neonates up to one year of age. Thus, our findings suggest that intervention at this early time could provide ‘metabolic rescue’ to preterm infants from aberrant initial gut microbial colonisation and succession.The principal etiological agent of human dental caries, Streptococcus mutans is a multi-virulent pathogen that can transform commensal oral microbial community to plaque biofilms. Major virulence factors that are associated with the cariogenicity of S. mutans include adhesion, acidogenicity and acidurity. All these pathogenic traits coordinate and alter the dental plaque ecology which provide room for interaction with other similar acidogenic and aciduric bacteria. This cariogenic flora increases the possibility of enamel demineralization which headway to caries development. The present study was aimed at evaluating the antimicrobial and antiinfective potential of a lichen secondary metabolite usnic acid (UA) against S. mutans. Minimum inhibitory concentration (MIC), Minimum bactericidal concentration (MBC) and growth kinetics were evaluated to determine the antimicrobial potential of UA against S. mutans. UA at 5 µg mL-1 and 10 µg mL-1 concentration were considered as MIC and MBC respectively. Effect on biofilm formation was microscopically assessed and found to be reduced in a concentration dependent manner.