The Imaginary Part of Nucleon Self-energy in hot nuclear matter

A semiphenomenological approach to the nucleon self-energy in nuclear matter at finite temperatures is followed. It combines elements of Thermo Field Dynamics for the treatment of finite temperature with a model for the self-energy, which evaluates the second order diagrams taking the needed dynamics of the NN interaction from experiment. The approach proved to be accurate at zero temperature to reproduce Im(Sigma) and other properties of nucleons in matter. In the present case we apply it to determine Im(Sigma) at finite temperatures. An effective NN cross section is deduced which can be easily used in analyses of heavy ion reactions.Comment: 15 pages, 6 postscripts figures, to be published in Nucl. Phys.

Robust automatic hexahedral cartilage meshing framework enables population-based computational studies of the knee

Osteoarthritis of the knee is increasingly prevalent as our population ages, representing an increasing financial burden, and severely impacting quality of life. The invasiveness of in vivo procedures and the high cost of cadaveric studies has left computational tools uniquely suited to study knee biomechanics. Developments in deep learning have great potential for efficiently generating large-scale datasets to enable researchers to perform population-sized investigations, but the time and effort associated with producing robust hexahedral meshes has been a limiting factor in expanding finite element studies to encompass a population. Here we developed a fully automated pipeline capable of taking magnetic resonance knee images and producing a working finite element simulation. We trained an encoder-decoder convolutional neural network to perform semantic image segmentation on the Imorphics dataset provided through the Osteoarthritis Initiative. The Imorphics dataset contained 176 image sequences with varying levels of cartilage degradation. Starting from an open-source swept-extrusion meshing algorithm, we further developed this algorithm until it could produce high quality meshes for every sequence and we applied a template-mapping procedure to automatically place soft-tissue attachment points. The meshing algorithm produced simulation-ready meshes for all 176 sequences, regardless of the use of provided (manually reconstructed) or predicted (automatically generated) segmentation labels. The average time to mesh all bones and cartilage tissues was less than 2 min per knee on an AMD Ryzen 5600X processor, using a parallel pool of three workers for bone meshing, followed by a pool of four workers meshing the four cartilage tissues. Of the 176 sequences with provided segmentation labels, 86% of the resulting meshes completed a simulated flexion-extension activity. We used a reserved testing dataset of 28 sequences unseen during network training to produce simulations derived from predicted labels. We compared tibiofemoral contact mechanics between manual and automated reconstructions for the 24 pairs of successful finite element simulations from this set, resulting in mean root-mean-squared differences under 20% of their respective min-max norms. In combination with further advancements in deep learning, this framework represents a feasible pipeline to produce population sized finite element studies of the natural knee from subject-specific models

Assessing Nutrient Limitation in Complex Forested Ecosystems : Alternatives to Large-Scale Fertilization Experiments

Quantifying nutrient limitation of primary productivity is a fundamental task of terrestrial ecosystem ecology, but in a high carbon dioxide environment it is even more critical that we understand potential nutrient constraints on plant growth. Ecologists often manipulate nutrients with fertilizer to assess nutrient limitation, yet for a variety of reasons, nutrient fertilization experiments are either impractical or incapable of resolving ecosystem responses to some global changes. The challenges of conducting large, in situ fertilization experiments are magnified in forests, especially the high-diversity forests common throughout the lowland tropics. A number of methods, including fertilization experiments, could be seen as tools in a toolbox that ecologists may use to attempt to assess nutrient limitation, but there has been no compilation or synthetic discussion of those methods in the literature. Here, we group these methods into one of three categories (indicators of soil nutrient supply, organismal indicators of nutrient limitation, and lab-based experiments and nutrient depletions), and discuss some of the strengths and limitations of each. Next, using a case study, we compare nutrient limitation assessed using these methods to results obtained using large-scale fertilizations across the Hawaiian Archipelago. We then explore the application of these methods in high-diversity tropical forests. In the end, we suggest that, although no single method is likely to predict nutrient limitation in all ecosystems and at all scales, by simultaneously utilizing a number of the methods we describe, investigators may begin to understand nutrient limitation in complex and diverse ecosystems such as tropical forests. In combination, these methods represent our best hope for understanding nutrient constraints on the global carbon cycle, especially in tropical forest ecosystems

PIK3CA mutation enrichment and quantitation from blood and tissue

PIK3CA is one of the two most frequently mutated genes in breast cancers, occurring in 30-40% of cases. Four frequent 'hotspot' PIK3CA mutations (E542K, E545K, H1047R and H1047L) account for 80-90% of all PIK3CA mutations in human malignancies and represent predictive biomarkers. Here we describe a PIK3CA mutation specific nuclease-based enrichment assay, which combined with a low-cost real-time qPCR detection method, enhances assay detection sensitivity from 5% for E542K and 10% for E545K to 0.6%, and from 5% for H1047R to 0.3%. Moreover, we present a novel flexible prediction method to calculate initial mutant allele frequency in tissue biopsy and blood samples with low mutant fraction. These advancements demonstrated a quick, accurate and simple detection and quantitation of PIK3CA mutations in two breast cancer cohorts (first cohort n = 22, second cohort n = 25). Hence this simple, versatile and informative workflow could be applicable for routine diagnostic testing where quantitative results are essential, e.g. disease monitoring subject to validation in a substantial future study

Target population of environments for bean breeding in Africa

The target population of environments (TPE) approach aims at enhancing the effectiveness of crop improvement programs to achieve yield and/or genetic gains by helping to classify and prioritize regions based on stress patterns (frequency, onset, intensity and duration) and uses it to recommend improvement in the selection strategy. The beangrowing environments in Ethiopia, Tanzania, and Uganda can be categorized into six different environmental groups (EGs) on the basis of seasonal variation of drought stress under historical and future climates projected using crop-climate prediction models (Jha et al, under review). This brief is based on the results from that study

Delayed diagnosis and recovery of fulminant immune checkpoint inhibitor-associated myocarditis on VA-ECMO support

[Figure: see text

A paleoepidemiological approach to the osteological paradox : Investigating stress, frailty and resilience through cribra orbitalia

Open Access via the Jisc Wiley Agreement Funder: British Academy (GrantNumber(s): GP2\190224)Peer reviewedPublisher PD

Bone-specific alkaline phosphatase concentrations are less variable than those of parathyroid hormone in stable hemodialysis patients

Abnormalities of bone mineral metabolism and vascular calcification are prevalent in patients with kidney failure. Clinical management is based on biochemical targets, in particular parathyroid hormone (PTH) concentrations, but this has many limitations including high biological variation. A possible alternative is bone-specific alkaline phosphatase (ALP); therefore, we evaluated the biological variation of this marker in patients undergoing hemodialysis. Bone ALP was measured in non-fasting serum samples taken twice a week over a 6-week period in 22 stable hemodialysis patients and 12 healthy volunteers. The within-individual coefficients of variance were calculated and used to derive the critical difference required to be certain that an observed change was significant. The coefficient of variance for bone ALP was significantly higher in hemodialysis patients compared to healthy individuals. Seven samples were required to estimate the homeostatic set point of bone ALP, within 10%, in a hemodialysis patient. The concentration of serial bone ALP measurements would need to change by 36% between any two measurements before it can be considered a significant change. Since the biological variation of bone ALP is less than half that reported for PTH, our study provides further support for the use of bone ALP as an alternative marker of bone mineral metabolism in the setting of chronic kidney disease–mineral and bone disorder