Structure of the Cytoplasmic Loop between Putative Helices II and III of the Mannitol Permease of Escherichia coli: A Tryptophan and 5-Fluorotryptophan Spectroscopy Study

In this work, four single tryptophan (Trp) mutants of the dimeric mannitol transporter of Escherichia coli, EIImtl, are characterized using Trp and 5-fluoroTrp (5-FTrp) fluorescence spectroscopy. The four positions, 97, 114, 126, and 133, are located in a region shown by recent studies to be involved in the mannitol translocation process. To spectroscopically distinguish between the Trp positions in each subunit of dimeric EIImtl, 5-FTrp was biosynthetically incorporated because of its much simpler photophysics compared to those of Trp. The steady-state and time-resolved fluorescence methodologies used point out that all four positions are in structured environments, both in the absence and in the presence of a saturating concentration of mannitol. The fluorescence decay of all 5-FTrp-containing mutants was highly homogeneous, suggesting similar microenvironments for both probes per dimer. However, Stern-Volmer quenching experiments using potassium iodide indicate different solvent accessibilities for the two probes at positions 97 and 133. A 5 Å two-dimensional (2D) projection map of the membrane-embedded IICmtl dimer showing 2-fold symmetry is available. The results of this work are in better agreement with a 7 Å projection map from a single 2D crystal on which no symmetry was imposed.

Detecting Regulatory Mechanisms in Endocrine Time Series Measurements

The regulatory mechanisms underlying pulsatile secretion are complex, especially as it is partly controlled by other hormones and the combined action of multiple agents. Regulatory relations between hormones are not directly observable but may be deduced from time series measurements of plasma hormone concentrations. Variation in plasma hormone levels are the resultant of secretion and clearance from the circulation. A strategy is proposed to extract inhibition, activation, thresholds and circadian synchronicity from concentration data, using particular association methods. Time delayed associations between hormone concentrations and/or extracted secretion pulse profiles reveal the information on regulatory mechanisms. The above mentioned regulatory mechanisms are illustrated with simulated data. Additionally, data from a lean cohort of healthy control subjects is used to illustrate activation (ACTH and cortisol) and circadian synchronicity (ACTH and TSH) in real data. The simulation and the real data both consist of 145 equidistant samples per individual, matching a 24-hr time span with 10 minute intervals. The results of the simulation and the real data are in concordance

Infection with Pythium flevoense in a harbour porpoise (Phocoena phocoena) as a novel cause of dermatitis in marine mammals

The oomycete Pythium flevoense was diagnosed as the cause of dermatitis in a young adult female harbour porpoise (Phocoena phocoena) that had been trapped in a pound net in a temperate saltwater environment. Disease from Pythium sp. infection-pythiosis-is infrequently diagnosed in humans, horses, dogs, cattle, and few other mammalian species. Pythiosis is typically associated with exposure to tropical or subtropical freshwater conditions, and typically caused by Pythium insidiosum. However, until now, pythiosis has been reported in neither marine mammals nor temperate saltwater conditions, and P. flevoense is not known as a cause of pythiosis in mammals. This porpoise developed generalised dermatitis despite treatment and euthanasia was necessary. Histopathological evaluation revealed a chronic active erosive dermatitis, with intralesional hyphae morphologically consistent with a Pythium sp. PCR analysis and sequencing of affected skin matched Pythium flevoense with a 100% similarity to the reference strain. Additional diagnostics excluded other pathogens. Based on this case report, P. flevoense needs to be considered as a mammalian pathogen. Furthermore, harbour porpoises and possibly other marine mammals may be at risk of infection with P. flevoense, and pythiosis should be included in the differential diagnosis of dermatitis in marine mammals.</p

Deep learning body-composition analysis of clinically acquired CT-scans estimates creatinine excretion with high accuracy in patients and healthy individuals

Assessment of daily creatinine production and excretion plays a crucial role in the estimation of renal function. Creatinine excretion is estimated by creatinine excretion equations and implicitly in eGFR equations like MDRD and CKD-EPI. These equations are however unreliable in patients with aberrant body composition. In this study we developed and validated equations estimating creatinine production using deep learning body-composition analysis of clinically acquired CT-scans. We retrospectively included patients in our center that received any CT-scan including the abdomen and had a 24-h urine collection within 2 weeks of the scan (n = 636). To validate the equations in healthy individuals, we included a kidney donor dataset (n = 287). We used a deep learning algorithm to segment muscle and fat at the 3rd lumbar vertebra, calculate surface areas and extract radiomics parameters. Two equations for CT-based estimate of RenAl FuncTion (CRAFT 1 including CT parameters, age, weight, and stature and CRAFT 2 excluding weight and stature) were developed and compared to the Cockcroft-Gault and the Ix equations. CRAFT1 and CRAFT 2 were both unbiased (MPE = 0.18 and 0.16 mmol/day, respectively) and accurate (RMSE = 2.68 and 2.78 mmol/day, respectively) in the patient dataset and were more accurate than the Ix (RMSE = 3.46 mmol/day) and Cockcroft-Gault equation (RMSE = 3.52 mmol/day). In healthy kidney donors, CRAFT 1 and CRAFT 2 remained unbiased (MPE = − 0.71 and − 0.73 mmol/day respectively) and accurate (RMSE = 1.86 and 1.97 mmol/day, respectively). Deep learning-based extraction of body-composition parameters from abdominal CT-scans can be used to reliably estimate creatinine production in both patients as well as healthy individuals. The presented algorithm can improve the estimation of renal function in patients who have recently had a CT scan. The proposed methods provide an improved estimation of renal function that is fully automatic and can be readily implemented in routine clinical practice

Dutch dairy farmers' perspectives on culling reasons and strategies

Since the abolishment of the milk quota system in Europe in 2014 and the introduction of environmental policies such as the phosphate rights system in the Netherlands, the reasons for culling dairy cows might have changed. The aim of this study was to determine the culling reasons for dairy cattle and to identify farmers' culling strategies and their intentions regarding the alteration of indicated culling strategies. To this end, an online questionnaire was distributed among dairy farmers nationally that resulted in 207 responses. Results showed that the most frequent culling reasons were related to problems with reproduction, udder, and hoof health. Primiparous cows were primarily culled for miscellaneous reasons such as injury, reproduction failure, and low milk yield. Multiparous cows were culled predominantly for reproduction failure, udder health and hoof health reasons. Most respondents indicated that they consider formulating a culling strategy, based on certain rules of thumb regarding the most common reasons for culling. Most farmers also reported that culling decisions on their farms were perceived to be unavoidable, though reproductive culling decisions are primarily voluntary. Most respondents stated that they intended to reduce the culling rate for better economic gain did not intend to alter the amount of replacement stock reared. The applied rules of thumb regarding culling strategies do not seem to have changed since the policy changes in dairy farming. The question remains whether farmers' rules of thumb might have made them unaware of the actual economic consequences of their culling strategies under the altered situation

Qualitative Evaluation of Common Quantitative Metrics for Clinical Acceptance of Automatic Segmentation:a Case Study on Heart Contouring from CT Images by Deep Learning Algorithms

Organs-at-risk contouring is time consuming and labour intensive. Automation by deep learning algorithms would decrease the workload of radiotherapists and technicians considerably. However, the variety of metrics used for the evaluation of deep learning algorithms make the results of many papers difficult to interpret and compare. In this paper, a qualitative evaluation is done on five established metrics to assess whether their values correlate with clinical usability. A total of 377 CT volumes with heart delineations were randomly selected for training and evaluation. A deep learning algorithm was used to predict the contours of the heart. A total of 101 CT slices from the validation set with the predicted contours were shown to three experienced radiologists. They examined each slice independently whether they would accept or adjust the prediction and if there were (small) mistakes. For each slice, the scores of this qualitative evaluation were then compared with the Sørensen-Dice coefficient (DC), the Hausdorff distance (HD), pixel-wise accuracy, sensitivity and precision. The statistical analysis of the qualitative evaluation and metrics showed a significant correlation. Of the slices with a DC over 0.96 (N = 20) or a 95% HD under 5 voxels (N = 25), no slices were rejected by the readers. Contours with lower DC or higher HD were seen in both rejected and accepted contours. Qualitative evaluation shows that it is difficult to use common quantification metrics as indicator for use in clinic. We might need to change the reporting of quantitative metrics to better reflect clinical acceptance

Dynamical Supersymmetry Breaking

Supersymmetry is one of the most plausible and theoretically motivated frameworks for extending the Standard Model. However, any supersymmetry in Nature must be a broken symmetry. Dynamical supersymmetry breaking (DSB) is an attractive idea for incorporating supersymmetry into a successful description of Nature. The study of DSB has recently enjoyed dramatic progress, fueled by advances in our understanding of the dynamics of supersymmetric field theories. These advances have allowed for direct analysis of DSB in strongly coupled theories, and for the discovery of new DSB theories, some of which contradict early criteria for DSB. We review these criteria, emphasizing recently discovered exceptions. We also describe, through many examples, various techniques for directly establishing DSB by studying the infrared theory, including both older techniques in regions of weak coupling, and new techniques in regions of strong coupling. Finally, we present a list of representative DSB models, their main properties, and the relations between them.Comment: 113 pages, Revtex. Minor changes, references added and corrected. To appear in Reviews of Modern Physic