The Problem of Mixing up of Leishmania Isolates in the Laboratory: Suggestion of ITS1 Gene Sequencing for Verification of Species

Background: Leishmaniasis is endemic in Iran. Different species of Leishmania (L.) parasites are causative agents of this disease. Correct identification of Leishmania species is important for clinical studies,prevention, and control of the diseases. Mix up of Leishmania isolates is possible in the laboratory, so there is need for verification of species for isolates of uncertain identity. Different methods may be used for this purpose including isoenzyme electrophoresis and molecular methods. The isoenzyme lectrophoresis, due to its drawbacks, is feasible only in specialized laboratories while molecular methods may be more feasible. The aim of this research was to study the application of the internal transcribedspacer 1 (ITS1) sequencing method, in comparison to isoenzyme electrophoresis method, for verification of Leishmania species.Methods: Six Leishmania isolates were received from different research institutions in Iran. The species of these isolates were known by donating institution according to their isoenzyme profile. The species of these isolates were re-identified in Pasteur Institute of Iran by PCR amplification of ITS1 followed bysequencing and comparison of these sequences with Leishmania sequences in GenBank. Isoenzyme electrophoresis was performed for confirmation of the results of ITS1.Results: ITS1 sequence showed that some isolates were mixed up or contaminated with Crithidia. Isoenzyme electrophoresis confirmed the results of ITS1 sequences.Conclusion: ITS1 sequencing is relatively more feasible than the traditional isoenzyme electrophoresismethod and is suggested for verification of Leishmania species

Interleukin-33 modulates inflammation in endometriosis

Abstract Endometriosis is a debilitating condition that is categorized by the abnormal growth of endometrial tissue outside the uterus. Although the pathogenesis of this disease remains unknown, it is well established that endometriosis patients exhibit immune dysfunction. Interleukin (IL)-33 is a danger signal that is a critical regulator of chronic inflammation. Although plasma and peritoneal fluid levels of IL-33 have been associated with deep infiltrating endometriosis, its contribution to the disease pathophysiology is unknown. We investigated the role of IL-33 in the pathology of endometriosis using patient samples, cell lines and a syngeneic mouse model. We found that endometriotic lesions produce significantly higher levels of IL-33 compared to the endometrium of healthy, fertile controls. In vitro stimulation of endometrial epithelial, endothelial and endometriotic epithelial cells with IL-33 led to the production of pro-inflammatory and angiogenic cytokines. In a syngeneic mouse model of endometriosis, IL-33 injections caused systemic inflammation, which manifested as an increase in plasma pro-inflammatory cytokines compared to control mice. Furthermore, endometriotic lesions from IL-33 treated mice were highly vascularized and exhibited increased proliferation. Collectively, we provide convincing evidence that IL-33 perpetuates inflammation, angiogenesis and lesion proliferation, which are critical events in the lesion survival and progression of endometriosis

The spatial evolution of young massive clusters - I. A new tool to quantitatively trace stellar clustering

Context. There are a number of methods that identify stellar sub-structure in star forming regions, but these do not quantify the degree of association of individual stars – something which is required if we are to better understand the mechanisms and physical processes that dictate structure. Aims. We present the new novel statistical clustering tool “INDICATE” which assesses and quantifies the degree of spatial clustering of each object in a dataset, discuss its applications as a tracer of morphological stellar features in star forming regions, and to look for these features in the Carina Nebula (NGC 3372). Methods. We employ a nearest neighbour approach to quantitatively compare the spatial distribution in the local neighbourhood of an object with that expected in an evenly spaced uniform (i.e. definitively non-clustered) field. Each object is assigned a clustering index (“I”) value, which is a quantitative measure of its clustering tendency. We have calibrated our tool against random distributions to aid interpretation and identification of significant I values. Results. Using INDICATE we successfully recover known stellar structure of the Carina Nebula, including the young Trumpler 14-16, Treasure Chest and Bochum 11 clusters. Four sub-clusters contain no, or very few, stars with a degree of association above random which suggests these sub-clusters may be fluctuations in the field rather than real clusters. In addition we find: (1) Stars in the NW and SE regions have significantly different clustering tendencies, which is reflective of differences in the apparent star formation activity in these regions. Further study is required to ascertain the physical origin of the difference; (2) The different clustering properties between the NW and SE regions are also seen for OB stars and are even more pronounced; (3) There are no signatures of classical mass segregation present in the SE region – massive stars here are not spatially concentrated together above random; (4) Stellar concentrations are more frequent around massive stars than typical for the general population, particularly in the Tr14 cluster; (5) There is a relation between the concentration of OB stars and the concentration of (lower mass) stars around OB stars in the centrally concentrated Tr14 and Tr15, but no such relation exists in Tr16. We conclude this is due to the highly sub-structured nature of Tr16. Conclusions. INDICATE is a powerful new tool employing a novel approach to quantify the clustering tendencies of individual objects in a dataset within a user-defined parameter space. As such it can be used in a wide array of data analysis applications. In this paper we have discussed and demonstrated its application to trace morphological features of young massive clusters

A code to Make Your Own Synthetic ObservaTIonS (MYOSOTIS)

We introduce our new code MYOSOTIS (Make Your Own Synthetic ObservaTIonS) which is designed to produce synthetic observations from simulated clusters. The code can synthesize observations from both ground-and spaced-based observatories, for a range of different filters, observational conditions and angular/spectral resolution. In this paper, we highlight some of the features of MYOSOTIS, creating synthetic observations from young massive star clusters. Our model clusters are simulated using NBODY6 code and have different total masses, halfmass radii, and binary fractions. The synthetic observations are made at the age of 2 Myr with Solar metallicity and under different extinction conditions. For each cluster, we create synthetic images of the Hubble Space Telescope (HST) in the visible (WFPC2/F555W) as well as Very Large Telescopes in the nearIR (SPHERE/IRDIS/Ks). We show how MYOSOTIS can be used to look at mass function (MF) determinations. For this aim we re-estimate stellar masses using a photometric analysis on the synthetic images. The synthetic MF slopes are compared to their actual values. Our photometric analysis demonstrate that depending on the adopted filter, extinction, angular resolution, and pixel sampling of the instruments, the power-law index of the underlying MFs can be shallower than the observed ones by at least ±0.25 dex which is in agreement with the observed discrepancies reported in the literature, specially for young star clusters

Adaptive access and rate control of CSMA for energy, rate and delay optimization

In this article, we present a cross-layer adaptive algorithm that dynamically maximizes the average utility function. A per stage utility function is defined for each link of a carrier sense multiple access-based wireless network as a weighted concave function of energy consumption, smoothed rate, and smoothed queue size. Hence, by selecting weights we can control the trade-off among them. Using dynamic programming, the utility function is maximized by dynamically adapting channel access, modulation, and coding according to the queue size and quality of the time-varying channel. We show that the optimal transmission policy has a threshold structure versus the channel state where the optimal decision is to transmit when the wireless channel state is better than a threshold. We also provide a queue management scheme where arrival rate is controlled based on the link state. Numerical results show characteristics of the proposed adaptation scheme and highlight the trade-off among energy consumption, smoothed data rate, and link delay.This study was supported in part by the Spanish Government, Ministerio de Ciencia e Innovación (MICINN), under projects COMONSENS (CSD2008-00010, CONSOLIDER-INGENIO 2010 program) and COSIMA (TEC2010-19545-C04-03), in part by Iran Telecommunication Research Center under contract 6947/500, and in part by Iran National Science Foundation under grant number 87041174. This study was completed while M. Khodaian was at CEIT and TECNUN (University of Navarra)