Postnatally-transmitted HIV-1 Envelope variants have similar neutralization-sensitivity and function to that of nontransmitted breast milk variants.

BACKGROUND: Breastfeeding is a leading cause of infant HIV-1 infection in the developing world, yet only a minority of infants exposed to HIV-1 via breastfeeding become infected. As a genetic bottleneck severely restricts the number of postnatally-transmitted variants, genetic or phenotypic properties of the virus Envelope (Env) could be important for the establishment of infant infection. We examined the efficiency of virologic functions required for initiation of infection in the gastrointestinal tract and the neutralization sensitivity of HIV-1 Env variants isolated from milk of three postnatally-transmitting mothers (n = 13 viruses), five clinically-matched nontransmitting mothers (n = 16 viruses), and seven postnatally-infected infants (n = 7 postnatally-transmitted/founder (T/F) viruses). RESULTS: There was no difference in the efficiency of epithelial cell interactions between Env virus variants from the breast milk of transmitting and nontransmitting mothers. Moreover, there was similar efficiency of DC-mediated trans-infection, CCR5-usage, target cell fusion, and infectivity between HIV-1 Env-pseudoviruses from nontransmitting mothers and postnatal T/F viruses. Milk Env-pseudoviruses were generally sensitive to neutralization by autologous maternal plasma and resistant to breast milk neutralization. Infant T/F Env-pseudoviruses were equally sensitive to neutralization by broadly-neutralizing monoclonal and polyclonal antibodies as compared to nontransmitted breast milk Env variants. CONCLUSION: Postnatally-T/F Env variants do not appear to possess a superior ability to interact with and cross a mucosal barrier or an exceptional resistance to neutralization that define their capability to initiate infection across the infant gastrointestinal tract in the setting of preexisting maternal antibodies.

Plasma miRNAs as early biomarkers for detecting hepatocellular carcinoma.

The early detection of hepatocellular carcinoma (HCC) presents a challenge because of the lack of specific biomarkers. Serum/plasma microRNAs (miRNAs) can discriminate HCC patients from controls. We aimed to identify and evaluate HCC-associated plasma miRNAs originating from the liver as early biomarkers for detecting HCC. In this multicenter three-phase study, we first performed screening using both plasma (HCC before and after liver transplantation or liver hepatectomy) and tissue samples (HCC, para-carcinoma and cirrhotic tissues). Then, we evaluated the diagnostic potential of the miRNAs in two case-control studies (training and validation sets). Finally, we used two prospective cohorts to test the potential of the identified miRNAs for the early detection of HCC. During the screening phase, we identified ten miRNAs, eight of which (miR-20a-5p, miR-25-3p, miR-30a-5p, miR-92a-3p, miR-132-3p, miR-185-5p, miR-320a and miR-324-3p) were significantly overexpressed in the HBV-positive HCC patients compared with the HBV-positive cancer-free controls in both the training and validation sets, with a sensitivity of 0.866 and specificity of 0.646. Furthermore, we assessed the potential for early HCC detection of these eight newly identified miRNAs and three previously reported miRNAs (miR-192-5p, miR-21-5p and miR-375) in two prospective cohorts. Our meta-analysis revealed that four miRNAs (miR-20a-5p, miR-320a, miR-324-3p and miR-375) could be used as preclinical biomarkers (pmeta  < 0.05) for HCC. The expression profile of the eight-miRNA panel can be used to discriminate HCC patients from cancer-free controls, and the four-miRNA panel (alone or combined with AFP) could be a blood-based early detection biomarker for HCC screening.

The Effect of Diet-Induced Obesity and Subsequent Weight Loss on Body Composition, Glucose Clearance, Metabolite Profile and Liver Amp-Activated Protein Kinase in Mice

Obesity, currently an epidemic, is a difficult disease to combat because it is marked by both a change in body weight and an underlying dysregulation in metabolism, making consistent weight loss challenging. We sought to elucidate this metabolic dysregulation resulting from diet-induced obesity (DIO) that persists through subsequent weight loss. We hypothesized that weight gain imparts a change in “metabolic set point” persisting through subsequent weight loss and that this modification may involve a persistent change in hepatic AMP-activated protein kinase (AMPK), a key energy-sensing enzyme in the body. To test these hypotheses, we tracked metabolic perturbations through this period, measuring changes in hepatic AMPK. To further understand the role of AMPK we used AICAR, an AMPK activator, following DIO. Our findings established a more dynamic metabolic model of DIO and subsequent weight loss. We observed hepatic AMPK elevation following weight loss, but AICAR administration without similar dieting was unsuccessful in improving metabolic dysregulation. Our findings provide an approach to modeling DIO and subsequent dieting that can be built upon in future studies and hopefully contribute to more effective long-term treatments of obesity.

Model sensitivity and uncertainty analysis using roadside air quality measurements

Most of the air quality modelling work has been so far oriented towards deterministic simulations of ambient pollutant concentrations. This traditional approach, which is based on the use of one selected model and one data set of discrete input values, does not reflect the uncertainties due to errors in model formulation and input data. Given the complexities of urban environments and the inherent limitations of mathematical modelling, it is unlikely that a single model based on routinely available meteorological and emission data will give satisfactory short-term predictions. In this study, different methods involving the use of more than one dispersion model, in association with different emission simulation methodologies and meteorological data sets, were explored for predicting best CO and benzene estimates, and related confidence bounds. The different approaches were tested using experimental data obtained during intensive monitoring campaigns in busy street canyons in Paris, France. Three relative simple dispersion models (STREET, OSPM and AEOLIUS) that are likely to be used for regulatory purposes were selected for this application. A sensitivity analysis was conducted in order to identify internal model parameters that might significantly affect results. Finally, a probabilistic methodology for assessing urban air quality was proposed.

The relationship between disgust sensitivity, anxiety and obsessions

Three hundred participants, including volunteers from an obsessional support group, filled in questionnaires relating to disgust sensitivity, health anxiety, anxiety, fear of death, fear of contamination and obsessionality as part of an investigation into the involvement of disgust sensitivity in types of obsessions. Overall, the data supported the hypothesis that a relationship does exist between disgust sensitivity and the targeted variables. A significant predictive relationship was found between disgust sensitivity and total scores on the obsessive compulsive inventory (OCI; Psychological Assessment 10 (1998) 206) for both frequency and distress of symptomatology. Disgust sensitivity scores were significantly related to health anxiety scores and general anxiety scores and to all the obsessional subscales, with the exception of hoarding. Additionally, multiple regression analyses revealed that disgust sensitivity may be more specifically related to washing compulsions: frequency of washing behaviour was best predicted by disgust sensitivity scores. Washing distress scores were best predicted by health anxiety scores, though disgust sensitivity entered in the second model. It is suggested that further research on the relationship between disgust sensitivity and obsessionality could be helpful in refining the theoretical understanding of obsessions.

A comprehensive copper stockpile leach model: background and parameter sensitivity

The design and development of a comprehensive computational model of a copper stockpile leach process is summarized. The computational fluid dynamic software framework PHYSICA+ and various phenomena were used to model transport phenomena, mineral reaction kinetics, bacterial effects, and heat, energy and acid balances for the overall leach process. In this paper, the performance of the model is investigated, in particular its sensitvity to particle size and ore permeability. A combination of literature and laboratory sources was used to parameterize the model. The simulation results from the leach model are compared with closely controlled column pilot scale tests. The main performance characteristics (e.g. copper recovery rate) predicted by the model compare reasonably well with the experimental data and clearly reflect the qualitiative behavior of the process in many respects. The model is used to provide a measure of the sensitivity of ore permeability on leach behavior, and simulation results are examined for several different particle size distributions.

Effect of reflow profile and thermal cycle ageing on the intermetallic formation and growth in lead-free soldering

The formation and growth of intermetallic compound layer thickness is one of the important issues in search for reliable electronic and electrical connections. Intermetallic compounds (IMCs) are an essential part of solder joints. At low levels, they have a strengthening effect on the joint; but at higher levels, they tend to make solder joints more brittle. If the solder joint is subjected to long-standing exposure of high temperature, this could result in continuous growth of intermetallic compound layer. The brittle intermetallic compound layer formed in this way is very much prone to fracture and cold therefore lead to mechanical and electrical failure of the joint. Therefore, the primary aim of this study is to investigate the growth of intermetallic compound layer thickness subjected to five different reflow profiles. The study also looks at the effect of three different temperature cycles (with maximum cycle temperature of 25 0C, 40 0C and 60 0C) on intermetallic compound formation and their growth behaviour.. Two different Sn-Ag-Cu solder pastes (namely paste P1 and paste P2) which were different in flux medium, were used for the study. The result showed that the growth of intermetallic compound layer thickness was a function of ageing temperature. It was found that the rate of growth of intermetallic compound layer thickness of paste P1 was higher than paste P2 at the same temperature condition. This behaviour could be related to the differences in flux mediums of solder paste samples used.