Dietary-dependent changes in the enteric nervous system and endothelium of premature piglets

A

Decadal shift in foraging strategy of a migratory southern ocean predator

Rapid anthropogenic environmental change is expected to impact a host of ecological parameters in Southern Ocean ecosystems. Of critical concern are the consequences of these changes on the range of species that show fidelity to migratory destinations, as philopatry is hypothesized to help or hinder adaptation to climate change depending on the circumstances. Many baleen whales show philopatry to feeding grounds and are also capital breeders that meet migratory and reproductive costs through seasonal energy intake. Southern right whales (Eubalaena australis, SRWs) are capital breeders that have a strong relationship between reproductive output and foraging success. The population dynamics of South Africa's population of SRWs are characterized by two distinct periods: the 1990s, a period of high calving rates; and the late 2010s, a period associated with lowered calving rates. Here we use analyses of stable carbon (δ13C) and nitrogen (δ15N) isotope values from SRW biopsy samples (n = 122) collected during these two distinct periods to investigate foraging ecology of the South African population of SRWs over a time period coincident with the demographic shift. We show that South African SRWs underwent a dramatic northward shift, and diversification, in foraging strategy from 1990s to 2010s. Bayesian mixing model results suggest that during the 1990s, South African SRWs foraged on prey isotopically similar to South Georgia/Islas Georgias del Sur krill. In contrast, in the 2010s, South African SRWs foraged on prey isotopically consistent with the waters of the Subtropical Convergence, Polar Front and Marion Island. We hypothesize that this shift represents a response to changes in preferred habitat or prey, for example, the decrease in abundance and southward range contraction of Antarctic krill. By linking reproductive decline to changing foraging strategies for the first time in SRWs, we show that altering foraging strategies may not be sufficient to adapt to a changing ocean

32‐Channel self‐grounded bow‐tie transceiver array for cardiac MR at 7.0T

Purpose Design, implementation, evaluation, and application of a 32‐channel Self‐Grounded Bow‐Tie (SGBT) transceiver array for cardiac MR (CMR) at 7.0T. Methods The array consists of 32 compact SGBT building blocks. Transmission field (B1+) shimming and radiofrequency safety assessment were performed with numerical simulations and benchmarked against phantom experiments. In vivo B1+ efficiency mapping was conducted with actual flip angle imaging. The array’s applicability for accelerated high spatial resolution 2D FLASH CINE imaging of the heart was examined in a volunteer study (n = 7). Results B1+ shimming provided a uniform field distribution suitable for female and male subjects. Phantom studies demonstrated an excellent agreement between simulated and measured B1+ efficiency maps (7% mean difference). The SGBT array afforded a spatial resolution of (0.8 × 0.8 × 2.5) mm3 for 2D CINE FLASH which is by a factor of 12 superior to standardized cardiovascular MR (CMR) protocols. The density of the SGBT array supports 1D acceleration of up to R = 4 (mean signal‐to‐noise ratio (whole heart) ≥ 16.7, mean contrast‐to‐noise ratio ≥ 13.5) without impairing image quality significantly. Conclusion The compact SGBT building block facilitates a modular high‐density array that supports accelerated and high spatial resolution CMR at 7.0T. The array provides a technological basis for future clinical assessment of parallel transmission techniques.EC/H2020/743077/EU/Thermal Magnetic Resonance: A New Instrument to Define the Role of Temperature in Biological Systems and Disease for Diagnosis and Therapy/ThermalMRBMBF, 01QE1815, Verbundprojekt: Seeing is Believing: Revolution der bildgebenden Diagnostik und Therapiekontrolle des Körperstammes durch superaufgelöste Hochfeld-Magnetresonanztomographie; Teilprojekt: Industrielle Forschung und Entwicklung lokaler Radiofrequenz-Antennen für hochauflösende Hochfeld-MRT des Körperstamme

Community Engagement newsletter, Faculty of Veterinary Science, Autumn, May 2018

Locuming in paradise / Luke Arnot -- Real about rabies at Ribane-Laka / Sylvia-Anne Farmer, Daniel Parsons, Matthew Woods and Hendre van Zyl -- Lending a helping paw / Kgopotso Mabote -- One Health efforts in Gauteng put to the test / Lindsey Burgess, Devon Seaton and John Burgess -- Community engagement project goes viral / Andrè Els and Nydia-Lee BritsNews articles with colour photos about the various community engagement projects of the Faculty of Veterinary Science, University of Pretoria.ab201

CanScreen5, a global repository for breast, cervical and colorectal cancer screening programs

The CanScreen5 project is a global cancer screening data repository that aims to report the status and performance of breast, cervical and colorectal cancer screening programs using a harmonized set of criteria and indicators. Data collected mainly from the Ministry of Health in each country underwent quality validation and ultimately became publicly available through a Web-based portal. Until September 2022, 84 participating countries reported data for breast (n = 57), cervical (n = 75) or colorectal (n = 51) cancer screening programs in the repository. Substantial heterogeneity was observed regarding program organization and performance. Reported screening coverage ranged from 1.7% (Bangladesh) to 85.5% (England, United Kingdom) for breast cancer, from 2.1% (Côte d’Ivoire) to 86.3% (Sweden) for cervical cancer, and from 0.6% (Hungary) to 64.5% (the Netherlands) for colorectal cancer screening programs. Large variability was observed regarding compliance to further assessment of screening programs and detection rates reported for precancers and cancers. A concern is lack of data to estimate performance indicators across the screening continuum. This underscores the need for programs to incorporate quality assurance protocols supported by robust information systems. Program organization requires improvement in resource-limited settings, where screening is likely to be resource-stratified and tailored to country-specific situations.</p

Recommendations and guidelines from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 1 -- In vivo small-animal imaging

The value of in vivo preclinical diffusion MRI (dMRI) is substantial. Small-animal dMRI has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. Many of the influential works in this field were first performed in small animals or ex vivo samples. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the data. This work aims to serve as a reference, presenting selected recommendations and guidelines from the diffusion community, on best practices for preclinical dMRI of in vivo animals. In each section, we also highlight areas for which no guidelines exist (and why), and where future work should focus. We first describe the value that small animal imaging adds to the field of dMRI, followed by general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss how they are appropriate for different studies. We then give guidelines for in vivo acquisition protocols, including decisions on hardware, animal preparation, imaging sequences and data processing, including pre-processing, model-fitting, and tractography. Finally, we provide an online resource which lists publicly available preclinical dMRI datasets and software packages, to promote responsible and reproducible research. An overarching goal herein is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge.Comment: 69 pages, 6 figures, 1 tabl

The major secreted protein Msp1/p75 is O-glycosylated in Lactobacillus rhamnosus GG

Peer reviewe

Chronic rhinitis in South Africa – more than just allergy!

Chronic rhinitis is a troublesome condition for sufferers. It is tempting to label all patients with chronic nasal symptoms as having allergic rhinitis (AR), but many such patients have other causes of chronic rhinitis that need a specific diagnosis and management strategy. Even when the patient fully fits the definition of AR, their condition will be best served by combining medication with ongoing patient education.http://www.samj.org.zaam2021OtorhinolaryngologyPaediatrics and Child Healt

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches