Assessment of probiotic potential and anticancer activity of newly isolated vaginal bacterium Lactobacillus plantarum 5BL

Numerous bacteria in and on its external parts protect the human body from harmful threats. This study aimed to investigate the potential beneficial effects of the vaginal ecosystem microbiota. A type of bacteria was isolated from vaginal secretions of adolescent and young adult women, cultured on an appropriate specific culture medium, and then molecularly identified through 16S rDNA gene sequencing. Results of 16S rDNA sequencing revealed that the isolate belongs to the Lactobacillus plantarum species. The isolated strain exhibited probiotic properties such as low pH and high bile salt concentration tolerance, antibiotic susceptibility and antimicrobial activity against some pathogenic bacteria. The anticancer effects of the strain on human cancer cell lines (cervical, HeLa; gastric, AGS; colon, HT‐29; breast, MCF‐7) and on a human normal cell line (human umbilical vein endothelial cells [HUVEC]) were investigated. Toxic side effects were assessed by studying apoptosis in the treated cells. The strain exhibited desirable probiotic properties and remarkable anticancer activity against the tested human cancer cell lines (P ≤ 0.05) with no significant cytotoxic effects on HUVEC normal cells (P ≤ 0.05). Overall, the isolated strain showed favorable potential as a bioactive therapeutic agent. Therefore, this strain should be subjected to the other required tests to prove its suitability for clinical therapeutic application.     

sdm: a reproducible and extensible R platform for species distribution modelling

sdm is an object‐oriented, reproducible and extensible, platform for species distribution modelling. It uses individual species and community‐based approaches, enabling ensembles of models to be fitted and evaluated, to project species potential distributions in space and time. It provides a standardized and unified structure for handling species distributions data and modelling techniques, and supports markedly different modelling approaches, including correlative, process‐based (mechanistic), agent‐based, and cellular automata. The object‐oriented design of software is such that scientists can modify existing methods, extend the framework by developing new methods or modelling procedures, and share them to be reproduced by other scientists. sdm can handle spatial and temporal data for single or multiple species and uses high performance computing solutions to speed up modelling and simulations. The framework is implemented in R, providing a flexible and easy‐to‐use GUI interface.     

Lectin microarray profiling of metastatic breast cancers

Altered protein glycosylation compared with the disease-free state is a universal feature of cancer cells. It has long been established that distinct glycan structures are associated with specific forms of cancer, but far less is known about the complete array of glycans associated with certain tumors. The cancer glycome has great potential as a source of biomarkers, but progress in this field has been hindered by a lack of available techniques for the elucidation of disease-associated glycosylation. In the present study, lectin microarrays consisting of 45 lectins with different binding preferences covering N- and O-linked glycans were coupled with evanescent-field activated fluorescent detection in the glycomic analysis of primary breast tumors and the serum and urine of patients with metastatic breast cancer. A single 50 μm section of a primary breast tumor or <1 μL of breast cancer patient serum or urine was sufficient to detect glycosylation alterations associated with metastatic breast cancer, as inferred from lectin-binding patterns. The high-throughput, sensitive and relatively simple nature of the simultaneous analysis of N- and O-linked glycosylation following minimal sample preparation and without the need for protein deglycosylation makes the lectin microarray analysis described a valuable tool for discovery phase glycomic profiling.     

Quantification of atherosclerotic plaque activity and vascular inflammation using [18-F] fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT)

Conventional non-invasive imaging modalities of atherosclerosis such as coronary artery calcium (CAC) and carotid intimal medial thickness (C-IMT) provide information about the burden of disease. However, despite multiple validation studies of CAC, and C-IMT, these modalities do not accurately assess plaque characteristics, and the composition and inflammatory state of the plaque determine its stability and, therefore, the risk of clinical events. [(18)F]-2-fluoro-2-deoxy-D-glucose (FDG) imaging using positron-emission tomography (PET)/computed tomography (CT) has been extensively studied in oncologic metabolism. Studies using animal models and immunohistochemistry in humans show that FDG-PET/CT is exquisitely sensitive for detecting macrophage activity, an important source of cellular inflammation in vessel walls. More recently, we and others have shown that FDG-PET/CT enables highly precise, novel measurements of inflammatory activity of activity of atherosclerotic plaques in large and medium-sized arteries. FDG-PET/CT studies have many advantages over other imaging modalities: 1) high contrast resolution; 2) quantification of plaque volume and metabolic activity allowing for multi-modal atherosclerotic plaque quantification; 3) dynamic, real-time, in vivo imaging; 4) minimal operator dependence. Finally, vascular inflammation detected by FDG-PET/CT has been shown to predict cardiovascular (CV) events independent of traditional risk factors and is also highly associated with overall burden of atherosclerosis. Plaque activity by FDG-PET/CT is modulated by known beneficial CV interventions such as short term (12 week) statin therapy as well as longer term therapeutic lifestyle changes (16 months). The current methodology for quantification of FDG uptake in atherosclerotic plaque involves measurement of the standardized uptake value (SUV) of an artery of interest and of the venous blood pool in order to calculate a target to background ratio (TBR), which is calculated by dividing the arterial SUV by the venous blood pool SUV. This method has shown to represent a stable, reproducible phenotype over time, has a high sensitivity for detection of vascular inflammation, and also has high inter-and intra-reader reliability. Here we present our methodology for patient preparation, image acquisition, and quantification of atherosclerotic plaque activity and vascular inflammation using SUV, TBR, and a global parameter called the metabolic volumetric product (MVP). These approaches may be applied to assess vascular inflammation in various study samples of interest in a consistent fashion as we have shown in several prior publications.     

Load-Relaxation Properties of the Human Trunk in Response to Prolonged Flexion: Measuring and Modeling the Effect of Flexion Angle

Experimental studies suggest that prolonged trunk flexion reduces passive support of the spine. To understand alterations of the synergy between active and passive tissues following such loadings, several studies have assessed the time-dependent behavior of passive tissues including those within spinal motion segments and muscles. Yet, there remain limitations regarding load-relaxation of the lumbar spine in response to flexion exposures and the influence of different flexion angles. Ten healthy participants were exposed for 16 min to each of five magnitudes of lumbar flexion specified relative to individual flexion-relaxation angles (i.e., 30, 40, 60, 80, and 100%), during which lumbar flexion angle and trunk moment were recorded. Outcome measures were initial trunk moment, moment drop, parameters of four viscoelastic models (i.e., Standard Linear Solid model, the Prony Series, Schapery''s Theory, and the Modified Superposition Method), and changes in neutral zone and viscoelastic state following exposure. There were significant effects of flexion angle on initial moment, moment drop, changes in normalized neutral zone, and some parameters of the Standard Linear Solid model. Initial moment, moment drop, and changes in normalized neutral zone increased exponentially with flexion angle. Kelvin-solid models produced better predictions of temporal behaviors. Observed responses to trunk flexion suggest nonlinearity in viscoelastic properties, and which likely reflected viscoelastic behaviors of spinal (lumbar) motion segments. Flexion-induced changes in viscous properties and neutral zone imply an increase in internal loads and perhaps increased risk of low back disorders. Kelvin-solid models, especially the Prony Series model appeared to be more effective at modeling load-relaxation of the trunk.     

Di(1‐naphthyl) methanol ester of carboxylic acids for absolute stereochemical determination

The absolute stereochemistry of chiral carboxylic acids is determined as a di(1‐naphthyl)methanol ester derivative. Computational scoring of conformations favoring either P or M helicity of the naphthyl groups, capable of exciton‐coupled circular dichroic coupling, leads to a predicted stereochemistry for the derivatized carboxylic acids.     

Changes in Soluble CD18 in Murine Autoimmune Arthritis and Rheumatoid Arthritis Reflect Disease Establishment and Treatment Response

Introduction

In rheumatoid arthritis (RA) immune activation and presence of autoantibodies may precede clinical onset of disease, and joint destruction can progress despite remission. However, the underlying temporal changes of such immune system abnormalities in the inflammatory response during treat-to-target strategies remain poorly understood. We have previously reported low levels of the soluble form of CD18 (sCD18) in plasma from patients with chronic RA and spondyloarthritis. Here, we study the changes of sCD18 before and during treatment of early RA and following arthritis induction in murine models of rheumatoid arthritis.

Methods

The level of sCD18 was analyzed with a time-resolved immunoflourometric assay in 1) plasma from early treatment naïve RA patients during a treat-to-target strategy (the OPERA cohort), 2) plasma from chronic RA patients, 3) serum from SKG and CIA mice following arthritis induction, and 4) supernatants from synovial fluid mononuclear cells (SFMCs) and peripheral blood mononuclear cells (PBMCs) from 6 RA patients cultured with TNFα or adalimumab.

Results

Plasma levels of sCD18 were decreased in chronic RA patients compared with early RA patients and in early RA patients compared with healthy controls. After 12 months of treatment the levels in early RA patients were similar to healthy controls. This normalization of plasma sCD18 levels was more pronounced in patients with very early disease who achieved an early ACR response. Plasma sCD18 levels were associated with radiographic progression. Correspondingly, the serum level of sCD18 was decreased in SKG mice 6 weeks after arthritis induction compared with healthy littermates. The sCD18 levels in both SKG and CIA mice exhibited a biphasic course after arthritis induction with an initial increase above baseline followed by a decline. Shedding of CD18 from RA SFMC and RA PBMC cultures was increased by TNFα and decreased by adalimumab.

Conclusions

The plasma sCD18 levels were altered in patients with RA, in mice with autoimmune arthritis and in cell cultures treated with TNFα and adalimumab. Decreased levels of plasma sCD18 could reflect autoimmunity in transition from early to chronic disease and normalization in response to treatment could reflect autoimmunity in remission.