Chronic ethanol ingestion induces oxidative kidney injury through taurine-inhibitable inflammation

Chronic ethanol ingestion mildly damages liver through oxidative stress and lipid oxidation, which is ameliorated by dietary supplementation with the anti-inflammatory β-amino acid taurine. Kidney, like liver, expresses cytochrome P450 2E1 that catabolizes ethanol with free radical formation, and so also may be damaged by ethanol catabolism. Sudden loss of kidney function, and not liver disease itself, foreshadows mortality in patients with alcoholic hepatitis [J. Altamirano, Clin. Gastroenterol. Hepatol. 2012, 10:65]. We found that ethanol ingestion in the Lieber-deCarli rat model increased kidney lipid oxidation, 4-hydroxynonenal protein adduction, and oxidatively truncated phospholipids that attract and activate leukocytes. Chronic ethanol ingestion increased myeloperoxidase-expressing cells in kidney and induced an inflammatory cell infiltrate. Apoptotic terminal deoxynucleotidyl transferase nick-end labeling-positive cells and active caspase-3 increased in kidney after ethanol ingestion, with reduced filtration with increased circulating blood urea nitrogen (BUN) and creatinine. These events were accompanied by release of albumin, myeloperoxidase, and the acute kidney injury biomarkers kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin, and cystatin c into urine. Taurine sequesters HOCl from myeloperoxidase of activated leukocytes, and taurine supplementation reduced renal lipid oxidation, reduced leukocyte infiltration, and reduced the increase in myeloperoxidase-positive cells during ethanol feeding. Taurine supplementation also normalized circulating BUN and creatinine levels and suppressed enhanced myeloperoxidase, albumin, KIM-1, and cystatin c in urine. Thus, chronic ethanol ingestion oxidatively damages kidney lipids and proteins, damages renal function, and induces acute kidney injury through an inflammatory cell infiltrate. The anti-inflammatory nutraceutical taurine effectively interrupts this ethanol-induced inflammatory cycle in kidney.     

Force and torque modelling of drilling simulation for orthopaedic surgery

The advent of haptic simulation systems for orthopaedic surgery procedures has provided surgeons with an excellent tool for training and preoperative planning purposes. This is especially true for procedures involving the drilling of bone, which require a great amount of adroitness and experience due to difficulties arising from vibration and drill bit breakage. One of the potential difficulties with the drilling of bone is the lack of consistent material evacuation from the drill's flutes as the material tends to clog. This clogging leads to significant increases in force and torque experienced by the surgeon. Clogging was observed for feed rates greater than 0.5 mm/s and spindle speeds less than 2500 rpm. The drilling simulation systems that have been created to date do not address the issue of drill flute clogging. This paper presents force and torque prediction models that account for this phenomenon. The two coefficients of friction required by these models were determined via a set of calibration experiments. The accuracy of both models was evaluated by an additional set of validation experiments resulting in average R² regression correlation values of 0.9546 and 0.9209 for the force and torque prediction models, respectively. The resulting models can be adopted by haptic simulation systems to provide a more realistic tactile output.     

Decision analysis approach to risk/benefit evaluation in the ethical review of controlled human infection studies

Risks and benefit evaluation for controlled human infection studies, where healthy volunteers are deliberately exposed to infectious agents to evaluate vaccine efficacy, should be explicit, systematic, thorough, and non-arbitrary. Decision analysis promotes these qualities using four steps: (1) determining explicit criteria and measures for evaluation, (2) identifying alternatives to the study, (3) defining the models used to estimate the measures for each alternative, and (4) running the models to produce the estimates and compare the alternatives. In this paper, we describe how decision analysis might be applied by funders and regulators, as well as by others contemplating the use of novel controlled human infection studies for vaccine development and evaluation.     

An intelligent system for estimating frog community calling activity and species richness

Over the past decade, dramatic declines in frog populations have been noticed worldwide. To examine this decline, monitoring frogs is becoming increasingly important. Compared to traditional field survey methods, recent advances in acoustic sensor technology have greatly extended spatial and temporal scales for monitoring animal populations. In this paper, we examine the problem of monitoring frog populations by analysing acoustic sensor data, where the population is reflected by community calling activity and species richness. Specifically, a novel acoustic event detection (AED) algorithm is first proposed to filter out those recordings without frog calls. Then, multi-label learning is used to classify each individual recording with six acoustic features: linear predictive coding coefficients, Mel-frequency cepstral coefficients, linear-frequency cepstral coefficients, acoustic complexity index, acoustic diversity index, and acoustic evenness index. Next, frog community calling activity and species richness are estimated by accumulating the results of AED and multi-label learning, respectively. Finally, ordinary least squares regression (OLS) is conducted to reveal the relationship between frog populations (frog calling activity and species richness) and weather variables (maximum temperature and rainfall). Experimental results demonstrate that our proposed intelligent system can significantly facilitate the effort to estimate frog community calling activity and species richness with comparable accuracies. The statistical results of OLS indicate that rainfall pattern has a lagged impact on frog community calling activity (significant in the first day after rainy day) and species richness (significant in the fourth day after rainy day). Temperature is shown to affect species richness but is less likely to change calling activity.