Anaerobic digestion of dried/shredded food waste in a periodic anaerobic baffled reactor.

The objective of the current work is to study the impact of the operational parameters' variation (HRT, OLR and T) on biomethane productivity in a periodic anaerobic baffled reactor (PABR). The feedstock used was a biomass product named food residue biomass (FORBI), which is dried and shredded source-separated household food waste. The PABR is an innovative, high-rate bioreactor. Apart from the hydraulic retention time (HRT) and the organic loading rate (OLR), an important operational parameter is the switching period (T) of the feeding compartment: when T is high, the bioreactor operation is similar to an anaerobic baffled reactor (ABR), while when it is low, the operation approaches that of an upflow anaerobic sludge blanket reactor (UASBR). Nine distinct experimental phases were conducted, during which the operational parameters of the PABR were consecutively modified: the HRT varied from 9 to 2.5 days, T between 2 days and 1 and finally the OLR from 1.24 gCOD/Lbioreactor*d to 8.08 gCOD/Lbioreactor*d. The maximum biomethane yield was 384 LCH4/kgFORBI corresponding to the operation at HRT = 5 d, OLR = 2.14 gCOD/Lbioreactor*d and T = 2 days. Similar efficiency (333 LCH4/kg-FORBI) was achieved at higher OLR (4.53 gCOD/Lbioreactor*d).

Exploring the role of extracellular matrix proteins to develop biomarkers of plaque vulnerability and outcome.

Cardiovascular disease (CVD) is the most common cause of death in industrialized countries. One underlying cause is atherosclerosis, which is a systemic disease characterized by plaques of retained lipids, inflammatory cells, apoptotic cells, calcium and extracellular matrix (ECM) proteins in the arterial wall. The biologic composition of an atherosclerotic plaque determines whether the plaque is more or less vulnerable, that is prone to rupture or erosion. Here, the ECM and tissue repair play an important role in plaque stability, vulnerability and progression. This review will focus on ECM remodelling in atherosclerotic plaques, with focus on how ECM biomarkers might predict plaque vulnerability and outcome.

A Bayesian approach to estimate changes in condom use from limited human immunodeficiency virus prevalence data.

Evaluation of large-scale intervention programmes against human immunodeficiency virus (HIV) is becoming increasingly important, but impact estimates frequently hinge on knowledge of changes in behaviour such as the frequency of condom use over time, or other self-reported behaviour changes, for which we generally have limited or potentially biased data. We employ a Bayesian inference methodology that incorporates an HIV transmission dynamics model to estimate condom use time trends from HIV prevalence data. Estimation is implemented via particle Markov chain Monte Carlo methods, applied for the first time in this context. The preliminary choice of the formulation for the time varying parameter reflecting the proportion of condom use is critical in the context studied, because of the very limited amount of condom use and HIV data available. We consider various novel formulations to explore the trajectory of condom use over time, based on diffusion-driven trajectories and smooth sigmoid curves. Numerical simulations indicate that informative results can be obtained regarding the amplitude of the increase in condom use during an intervention, with good levels of sensitivity and specificity performance in effectively detecting changes. The application of this method to a real life problem demonstrates how it can help in evaluating HIV interventions based on a small number of prevalence estimates, and it opens the way to similar applications in different contexts.