Hdl Levels And Oxidizability During Myocardial Infarction Are Associated With Reduced Endothelial-mediated Vasodilation And Nitric Oxide Bioavailability.

Acute phase response modifies high-density lipoprotein (HDL) into a dysfunctional particle that may favor oxidative/inflammatory stress and eNOS dysfunction. The present study investigated the impact of this phenomenon on patients presenting ST-elevation myocardial infarction (STEMI). Plasma was obtained from 180 consecutive patients within the first 24-h of onset of STEMI symptoms (D1) and after 5 days (D5). Nitrate/nitrite (NOx) and lipoproteins were isolated by gradient ultracentrifugation. The oxidizability of low-density lipoprotein incubated with HDL (HDLaoxLDL) and the HDL self-oxidizability (HDLautox) were measured after CuSO4 co-incubation. Anti-inflammatory activity of HDL was estimated by VCAM-1 secretion by human umbilical vein endothelial cells after incubation with TNF-α. Flow-mediated dilation (FMD) was assessed at the 30(th) day (D30) after STEMI. Among patients in the first tertile of admission HDL-Cholesterol (<33 mg/dL), the increment of NOx from D1 to D5 [6.7(2; 13) vs. 3.2(-3; 10) vs. 3.5(-3; 12); p = 0.001] and the FMD adjusted for multiple covariates [8.4(5; 11) vs 6.1(3; 10) vs. 5.2(3; 10); p = 0.001] were higher than in those in the second (33-42 mg/dL) or third (>42 mg/dL) tertiles, respectively. From D1 to D5, there was a decrease in HDL size (-6.3 ± 0.3%; p < 0.001) and particle number (-22.0 ± 0.6%; p < 0.001) as well as an increase in both HDLaoxLDL (33%(23); p < 0.001) and HDLautox (65%(25); p < 0.001). VCAM-1 secretion after TNF-a stimulation was reduced after co-incubation with HDL from healthy volunteers (-24%(33); p = 0.009), from MI patients at D1 (-23%(37); p = 0.015) and at D30 (-22%(24); p = 0.042) but not at D5 (p = 0.28). During STEMI, high HDL-cholesterol is associated with a greater decline in endothelial function. In parallel, structural and functional changes in HDL occur reducing its anti-inflammatory and anti-oxidant properties.

Toxicity Of Fungal-generated Silver Nanoparticles To Soil-inhabiting Pseudomonas Putida Kt2440, A Rhizospheric Bacterium Responsible For Plant Protection And Bioremediation.

Silver nanoparticles have attracted considerable attention due to their beneficial properties. But toxicity issues associated with them are also rising. The reports in the past suggested health hazards of silver nanoparticles at the cellular, molecular, or whole organismal level in eukaryotes. Whereas, there is also need to examine the exposure effects of silver nanoparticle to the microbes, which are beneficial to humans as well as environment. The available literature suggests the harmful effects of physically and chemically synthesised silver nanoparticles. The toxicity of biogenically synthesized nanoparticles has been less studied than physically and chemically synthesised nanoparticles. Hence, there is a greater need to study the toxic effects of biologically synthesised silver nanoparticles in general and mycosynthesized nanoparticles in particular. In the present study, attempts have been made to assess the risk associated with the exposure of mycosynthesized silver nanoparticles on a beneficial soil microbe Pseudomonas putida. KT2440. The study demonstrates mycosynthesis of silver nanoparticles and their characterisation by UV-vis spectrophotometry, FTIR, X-ray diffraction, nanosight LM20 - a particle size distribution analyzer and TEM. Silver nanoparticles obtained herein were found to exert the hazardous effect at the concentration of 0.4μg/ml, which warrants further detailed investigations concerning toxicity.

On The Consistency Of Monte Carlo Track Structure Dna Damage Simulations.

Monte Carlo track structures (MCTS) simulations have been recognized as useful tools for radiobiological modeling. However, the authors noticed several issues regarding the consistency of reported data. Therefore, in this work, they analyze the impact of various user defined parameters on simulated direct DNA damage yields. In addition, they draw attention to discrepancies in published literature in DNA strand break (SB) yields and selected methodologies. The MCTS code Geant4-DNA was used to compare radial dose profiles in a nanometer-scale region of interest (ROI) for photon sources of varying sizes and energies. Then, electron tracks of 0.28 keV-220 keV were superimposed on a geometric DNA model composed of 2.7 × 10(6) nucleosomes, and SBs were simulated according to four definitions based on energy deposits or energy transfers in DNA strand targets compared to a threshold energy ETH. The SB frequencies and complexities in nucleosomes as a function of incident electron energies were obtained. SBs were classified into higher order clusters such as single and double strand breaks (SSBs and DSBs) based on inter-SB distances and on the number of affected strands. Comparisons of different nonuniform dose distributions lacking charged particle equilibrium may lead to erroneous conclusions regarding the effect of energy on relative biological effectiveness. The energy transfer-based SB definitions give similar SB yields as the one based on energy deposit when ETH ≈ 10.79 eV, but deviate significantly for higher ETH values. Between 30 and 40 nucleosomes/Gy show at least one SB in the ROI. The number of nucleosomes that present a complex damage pattern of more than 2 SBs and the degree of complexity of the damage in these nucleosomes diminish as the incident electron energy increases. DNA damage classification into SSB and DSB is highly dependent on the definitions of these higher order structures and their implementations. The authors' show that, for the four studied models, different yields are expected by up to 54% for SSBs and by up to 32% for DSBs, as a function of the incident electrons energy and of the models being compared. MCTS simulations allow to compare direct DNA damage types and complexities induced by ionizing radiation. However, simulation results depend to a large degree on user-defined parameters, definitions, and algorithms such as: DNA model, dose distribution, SB definition, and the DNA damage clustering algorithm. These interdependencies should be well controlled during the simulations and explicitly reported when comparing results to experiments or calculations.

Geographical Distribution Of The Association Between El Niño South Oscillation And Dengue Fever In The Americas: A Continental Analysis Using Geographical Information System-based Techniques.

El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

Distribution Of Lutzomyia Longipalpis Chemotype Populations In São Paulo State, Brazil.

American visceral leishmaniasis (AVL) is an emerging disease in the state of São Paulo, Brazil. Its geographical expansion and the increase in the number of human cases has been linked to dispersion of Lutzomyia longipalpis into urban areas. To produce more accurate risk maps we investigated the geographic distribution and routes of expansion of the disease as well as chemotype populations of the vector. A database, containing the annual records of municipalities which had notified human and canine AVL cases as well as the presence of the vector, was compiled. The chemotypes of L. longipalpis populations from municipalities in different regions of São Paulo State were determined by Coupled Gas Chromatography - Mass Spectrometry. From 1997 to June 2014, L. longipalpis has been reported in 166 municipalities, 148 of them in the Western region. A total of 106 municipalities were identified with transmission and 99 were located in the Western region, where all 2,204 autochthonous human cases occurred. Both the vector and the occurrence of human cases have expanded in a South-easterly direction, from the Western to central region, and from there, a further expansion to the North and the South. The (S)-9-methylgermacrene-B population of L. longipalpis is widely distributed in the Western region and the cembrene-1 population is restricted to the Eastern region. The maps in the present study show that there are two distinct epidemiological patterns of AVL in São Paulo State and that the expansion of human and canine AVL cases through the Western region has followed the same dispersion route of only one of the two species of the L. longipalpis complex, (S)-9-methylgermacrene-B. Entomological vigilance based on the routes of dispersion and identification of the chemotype population could be used to identify at-risk areas and consequently define the priorities for control measures.