Epigenetic mechanisms of endocrine-disrupting chemicals in obesity

The incidence of obesity has dramatically increased over the last decades. Recently, there has been a growing interest in the possible association between the pandemics of obesity and some endocrine-disrupting chemicals (EDCs), termed “obesogens”. These are a heterogeneous group of exogenous compounds that can interfere in the endocrine regulation of energy metabolism and adipose tissue structure. Oral intake, inhalation, and dermal absorption represent the major sources of human exposure to these EDCs. Recently, epigenetic changes such as the methylation of cytosine residues on DNA, post-translational modification of histones, and microRNA expression have been considered to act as an intermediary between deleterious effects of EDCs and obesity development in susceptible individuals. Specifically, EDCs exposure during early-life development can detrimentally affect individuals via inducing epigenetic modifications that can permanently change the epigenome in the germline, enabling changes to be transmitted to the next generations and predisposing them to a multitude of diseases. The purpose of this review is to analyze the epigenetic alterations putatively induced by chemical exposures and their ability to interfere with the control of energy metabolism and adipose tissue regulation, resulting in imbalances in the control of body weight, which can lead to obesity

Thyroid nodules treated with percutaneous radiofrequency thermal ablation: a comparative study

Percutaneous radiofrequency thermal ablation (RTA) was reported as an effective tool for the management of thyroid nodules (TNs). The aim of this study was to investigate the effects of RTA and to establish whether they were treatment-related by comparison with a matched, untreated control group

Public Shelter Admission Rates in Philadelphia and New York City: The Implications of Turnover for Sheltered Population Counts

Previous estimates of the size and composition of the U.S. homeless population have been based on cross-sectional survey methodologies. National enumeration efforts have yielded point-prevalence estimates ranging from 0.11 to 0.25 percent of the population. This study reports data from shelter databases in Philadelphia and New York City that record identifiers for all persons admitted and so make possible unduplicated counts of users. Unduplicated counts of shelter users yield annual rates for 1992 of about 1 percent for both cities and rates near 3 percent over three years in Philadelphia (1990–92) and over five years (1988–92) in New York City. The annual rates are three times greater than rates documented by point-prevalence studies. Shelter bed turnover rates are reported, as are average monthly first admission and readmission counts over a two-year period. Implications for future research and public policy are discussed

A new catalytic and enantioselective desymmetrization of symmetrical methylidene cycloalkene oxides

Chiral copper complexes of C2-symmetrical hosphoroamidites were found to be highly effective catalysts for both kinetic resolution and novel desymmetrization reactions of new methylidene epoxycycloalkanes.

Unprecedented catalytic enantioselective trapping of arene oxides with dialkylzinc reagents

The first catalytic enantioselective trapping of symmetrical and racemic arene oxides with organometallic reagents is reported.

Effectiveness of Lactobacillus-containing vaginal tablets in the treatment of symptomatic bacterial vaginosis

AbstractThe purpose of this study was to determine the effectiveness of Lactobacillus-containing vaginal tablets in the treatment of bacterial vaginosis (BV) and in the restoration of a healthy vaginal flora. Thirty-nine women with BV were enrolled in a double-blind, placebo-controlled clinical trial. Patients received either one Lactobacillus-containing tablet or placebo daily for 7 days. Clinical criteria, vaginal Gram stain scores and symptoms were compared with those at the initial visit and those at completion of therapy and 2 weeks later. After completion of therapy, all of the patients in the Lactobacillus-treated group (n = 18) were free of BV, showing a normal (83%) or intermediate (17%) vaginal flora, as compared with only two patients free of BV with intermediate flora (12%) from among the 16 placebo-treated women (p <0.001). Two weeks after completion of therapy, treatment was successful (score <7) in 61% of Lactobacillus-treated patients as compared with 19% of those in the placebo group (p <0.05). In the treatment group, the total number of symptomatic patients and the intensity of their symptoms, in particular vaginal malodour, were significantly reduced at both follow-up visits. The data indicate that intravaginal administration of exogenous selected strains of lactobacilli can restore a normal vaginal microbiota and be used in treating bacterial vaginosis

Investigation of fennel protein extracts by shot-gun Fourier transform ion cyclotron resonance mass spectrometry

A rapid shot-gun method by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is proposed for the characterization of fennel proteins. After enzymatic digestion with trypsin, few microliters of extract were analyzed by direct infusion in positive ion mode. A custom-made non-redundant fennel-specific proteome database was derived from the well-known NCBI database; additional proteins belonging to recognized allergenic sources (celery, carrot, parsley, birch, and mugwort) were also included in our database, since patients hypersensitive to these plants could also suffer from fennel allergy. The peptide sequence of each protein from that derived list was theoretically sequenced to produce calculated m/z lists of possible m/z ions after tryptic digestions. Then, by using a home-made Matlab algorithm, those lists were matched with the experimental FT-ICR mass spectrum of the fennel peptide mixture. Finally, Peptide Mass Fingerprint searches confirmed the presence of the matched proteins inside the fennel extract with a total of 70 proteins (61 fennel specific and 9 allergenic proteins)

Surface plasmon resonance assay for label-free and selective detection of hiv-1 p24 protein

The early detection of the human immunodeficiency virus (HIV) is of paramount importance to achieve efficient therapeutic treatment and limit the disease spreading. In this perspective, the assessment of biosensing assay for the HIV-1 p24 capsid protein plays a pivotal role in the timely and selective detection of HIV infections. In this study, multi-parameter-SPR has been used to develop a reliable and label-free detection method for HIV-1 p24 protein. Remarkably, both physical and chemical immobilization of mouse monoclonal antibodies against HIV-1 p24 on the SPR gold detecting surface have been characterized for the first time. The two immobilization techniques returned a capturing antibody surface coverage as high as (7.5 ± 0.3) × 1011 molecule/cm2 and (2.4 ± 0.6) × 1011 molecule/cm2, respectively. However, the covalent binding of the capturing antibodies through a mixed self-assembled monolayer (SAM) of alkanethiols led to a doubling of the p24 binding signal. Moreover, from the modeling of the dose-response curve, an equilibrium dissociation constant KD of 5.30 × 10−9 M was computed for the assay performed on the SAM modified surface compared to a much larger KD of 7.46 × 10−5 M extracted for the physisorbed antibodies. The chemically modified system was also characterized in terms of sensitivity and selectivity, reaching a limit of detection of (4.1 ± 0.5) nM and an unprecedented selectivity ratio of 0.02

Thyroid disease treatment prediction with machine learning approaches

The thyroid is an endocrine gland located in the anterior region of the neck: its main task is to produce thyroid hormones, which are functional to our entire body. Its possible dysfunction can lead to the production of an insufficient or excessive amount of thyroid hormone. Therefore, the thyroid can become inflamed or swollen due to one or more swellings forming inside it. Some of these nodules can be the site of malignant tumors. One of the most used treatments is sodium levothyroxine, also known as LT4, a synthetic thyroid hormone used in the treatment of thyroid disorders and diseases. Predictions about the treatment can be important for supporting endocrinologists' activities and improve the quality of the patients' life. To date, there are numerous studies in the literature that focus on the prediction of thyroid diseases on the trend of the hormonal parameters of people. This work, differently, aims to predict the LT4 treatment trend for patients suffering from hypothyroidism. To this end, a dedicated dataset was built that includes medical information related to patients being treated in the”AOU Federico II” hospital of Naples. For each patient, the clinical history is available over time, and therefore on the basis of the trend of the hormonal parameters and other attributes considered it was possible to predict the course of each patient's treatment in order to understand if this should be increased or decreased. To conduct this study, we used different machine learning algorithms. In particular, we compared the results of 10 different classifiers. The performances of the different algorithms show good results, especially in the case of the Extra-Tree Classifier, where the accuracy reaches 84%

EP-1176: Three years of VMAT patient quality assurance with the PTW seven29 ionization chamber array and Octavius phantom

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