The labour ward analgesic service at King Edward VIII Hospital, Durban

The provision of analgesic services to the labour ward at King Edward VIII Hospital was studied during a 1-week period. Of 249 patients, 113 (45%) received no analgesia whatsoever. Intramuscular pethidine was the commonest form of analgesia and was used in 97 patients (39%). Thirty-six patients (14%) received epidural analgesia and only 4 inhalational analgesia using nitrous oxide and oxygen (Entonox). A significant proportion of patients who received pethidine were given the drug between 1 and 3 hours before delivery, increasing the potential for opiate-related neonatal depression. Of the patients given opiate analgesia, 22 (23%) proceeded to caesarean section and could have been at increased risk of aspiration of gastric contents owing to delayed gastric emptying caused by the opiate. One hundred and eleven mothers (76%) who had an obstetric indication for epidural analgesia were denied it because of lack of medical staffing

Questioning the rise of gelatinous zooplankton in the World's oceans

During the past several decades, high numbers of gelatinous zooplankton species have been reported in many estuarine and coastal ecosystems. Coupled with media-driven public perception, a paradigm has evolved in which the global ocean ecosystems are thought to be heading toward being dominated by “nuisance” jellyfish. We question this current paradigm by presenting a broad overview of gelatinous zooplankton in a historicalcontext to develop the hypothesis that population changes reflect the human-mediated alteration of global ocean ecosystems. To this end, we synthesize information related to the evolutionary context of contemporary gelatinous zooplankton blooms, the human frame of reference forchanges in gelatinous zooplankton populations, and whether sufficient data are available to have established the paradigm. We conclude that the current paradigm in which it is believed that there has been a global increase in gelatinous zooplankton is unsubstantiated, and we develop a strategy for addressing the critical questions about long-term, human-related changes in the sea as they relate to gelatinous zooplankton blooms

Conserved novel ORFs in the mitochondrial genome of the ctenophore Beroe forskalii

To date, five ctenophore species’ mitochondrial genomes have been sequenced, and each contains open reading frames (ORFs) that if translated have no identifiable orthologs. ORFs with no identifiable orthologs are called unidentified reading frames (URFs). If truly protein-coding, ctenophore mitochondrial URFs represent a little understood path in early-diverging metazoan mitochondrial evolution and metabolism. We sequenced and annotated the mitochondrial genomes of three individuals of the beroid ctenophore Beroe forskalii and found that in addition to sharing the same canonical mitochondrial genes as other ctenophores, the B. forskalii mitochondrial genome contains two URFs. These URFs are conserved among the three individuals but not found in other sequenced species. We developed computational tools called pauvre and cuttlery to determine the likelihood that URFs are protein coding. There is evidence that the two URFs are under negative selection, and a novel Bayesian hypothesis test of trinucleotide frequency shows that the URFs are more similar to known coding genes than noncoding intergenic sequence. Protein structure and function prediction of all ctenophore URFs suggests that they all code for transmembrane transport proteins. These findings, along with the presence of URFs in other sequenced ctenophore mitochondrial genomes, suggest that ctenophores may have uncharacterized transmembrane proteins present in their mitochondria

Panspermia, Past and Present: Astrophysical and Biophysical Conditions for the Dissemination of Life in Space

Astronomically, there are viable mechanisms for distributing organic material throughout the Milky Way. Biologically, the destructive effects of ultraviolet light and cosmic rays means that the majority of organisms arrive broken and dead on a new world. The likelihood of conventional forms of panspermia must therefore be considered low. However, the information content of dam-aged biological molecules might serve to seed new life (necropanspermia).Comment: Accepted for publication in Space Science Review

Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Creep behavior of copper-chromium in-situ composite

Creep deformation and fracture behaviors were investigated on a deformation-processed Cu-Cr in-situ composite over a temperature range of 200 °C to 650 °C. It was found that the creep resistance increases significantly with the introduction of Cr fibers into Cu. The stress exponent and the activation energy for creep of the composite at high temperatures (≥400 °C) were observed to be 5.5 and 180 to 216 kJ/mol, respectively. The observation that the stress exponent and the activation energy for creep of the composite at high temperatures (≥400 °C) are close to those of pure Cu suggests that the creep deformation of the composite is dominated by the deformation of the Cu matrix. The high stress exponent at low temperatures (200 °C and 300 °C) is thought be associated with the as-swaged microstructure, which contains elongated dislocation cells and subgrains that are stable and act as strong athermal obstacles at low temperatures. The mechanism of damage was found to be similar for all the creep tests performed, but the distribution and extent of damage were found to be very sensitive to the test temperature

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations