Partial purification and characterization of lipase from Geobacillus stearothermophilus AH22

The lipase was partially purified by ion exchange chromatography and gel filtration column chromatography, and was characterized from Geobacillus stearothermophilus AH22 strain. The lipase was purified 18.3-folds with 19.7% recovery. The lipase activity was determined by using p-nitrophenyl esters (C₂–C₁₂) as substrates. The K_m values of the enzyme for these substrates were found as 0.16, 0.02, 0.19 and 0.55?mM, respectively, while V_max values were 0.52, 1.03, 0.72 and 0.15?U?mg^?1. The enzyme showed maximum activity at 50?°C and between pH 8.0 and 9.0. The enzyme was found to be quite stable at pH range of 4.0–10.0, and thermal stability between 50 and 60?°C. It was found that the best inhibitory effect of the enzyme activity was of Hg²⁺. The inhibitory effect as orlistat, catechin, propyl paraben, p-coumaric acid, 3,4-dihydroxy hydro-cinnamic acid was examined. These results suggest that G. stearothermophilus AH22 lipase presents very suitable properties for industrial applications.     

Predicting Future Morphological Changes of Lesions from Radiotracer Uptake in 18F-FDG-PET Images

We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on ¹⁸F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 ¹⁸F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients'' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75±1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUV_max (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUV_max. We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16).     

Naphthalocyanine-reconstituted LDL nanoparticles for in vivo cancer imaging and treatment

Low density lipoproteins (LDLs) are naturally occurring nanoparticles that are biocompatible, biodegradable and non-immunogenic. Moreover, the size of LDL particle is precisely controlled (approximately 22 nm) by its apoB-100 component, setting them apart from liposomes and lipid micelles. LDL particles have long been proposed as a nanocarrier for targeted delivery of diagnostics and therapeutics to LDL receptor (LDLR)-positive cancers. Here, we report the design and synthesis of a novel naphthalocyanine (Nc)-based photodynamic therapy (PDT) agent, SiNcBOA, and describe its efficient reconstitution into LDL core (100:1 payload). Possessing a near-infrared (NIR) absorption wavelength (> 800 nm) and extremely high extinction coefficient (> 10(5) M(-1)cm(-1)), SiNcBOA holds the promise of treating deeply seated tumors. Reconstituted LDL particles (r-Nc-LDL) maintain the size and shape of native LDL as determined by transmission electron microscopy, and also retain their LDLR-mediated uptake by cancer cells as demonstrated by confocal microscopy. Its preferential uptake by tumor vs normal tissue was confirmed in vivo by noninvasive optical imaging technique, demonstrating the feasibility of using this nanoparticle for NIR imaging-guided PDT of cancer.     

Airway Microbiota and Pathogen Abundance in Age-Stratified Cystic Fibrosis Patients

Bacterial communities in the airways of cystic fibrosis (CF) patients are, as in other ecological niches, influenced by autogenic and allogenic factors. However, our understanding of microbial colonization in younger versus older CF airways and the association with pulmonary function is rudimentary at best. Using a phylogenetic microarray, we examine the airway microbiota in age stratified CF patients ranging from neonates (9 months) to adults (72 years). From a cohort of clinically stable patients, we demonstrate that older CF patients who exhibit poorer pulmonary function possess more uneven, phylogenetically-clustered airway communities, compared to younger patients. Using longitudinal samples collected form a subset of these patients a pattern of initial bacterial community diversification was observed in younger patients compared with a progressive loss of diversity over time in older patients. We describe in detail the distinct bacterial community profiles associated with young and old CF patients with a particular focus on the differences between respective “early” and “late” colonizing organisms. Finally we assess the influence of Cystic Fibrosis Transmembrane Regulator (CFTR) mutation on bacterial abundance and identify genotype-specific communities involving members of the Pseudomonadaceae, Xanthomonadaceae, Moraxellaceae and Enterobacteriaceae amongst others. Data presented here provides insights into the CF airway microbiota, including initial diversification events in younger patients and establishment of specialized communities of pathogens associated with poor pulmonary function in older patient populations.