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Objective To compare the effects of early and delayed cord clamping on the haemoglobin levels of neonates delivered at term. Methods This randomized controlled trial enrolled pregnant women during the second stage of labour. They were randomized into either the early cord clamping (ECC) group or the delayed cord clamping (DCC) group in the ratio of 1:1. Following delivery of the baby, the umbilical cords of participants in the ECC group were clamped within 30 s of delivery of the neonate while those of participants in the DCC group were clamped after 2 min from the delivery of the neonate. The primary outcome measure was the effect of ECC and DCC on the haemoglobin levels of neonates delivered at term. Results A total of 270 pregnant women were enrolled in the study. Their baseline sociodemographic and clinical characteristics were similar in both groups. There was no significant difference in the mean haemoglobin level between ECC and DCC groups at birth. The mean haemoglobin level of the neonates at 48 h postpartum was significantly higher in the DCC group than the ECC group. Conclusion DCC at birth was associated with a significant increase in neonatal haemoglobin levels at 48 h postpartum when compared with ECC. Trial Registration: The trial was registered at Pan African Clinical Trial Registry with approval number PACTR202206735622089.

Land modified for human use alters matrix shape and composition and is a leading contributor to global biodiversity loss. It can also play a key role in facilitating range expansion and ecosystem invasion by anthrophilic species, as it can alter food abundance and distribution while also influencing predation risk; the relative roles of these processes are key to habitat selection theory. We researched these relative influences by examining human footprint, natural habitat, and predator occurrence on seasonal habitat selection by range-expanding boreal white-tailed deer (Odocoileus virginianus) in the oil sands of western Canada. We hypothesized that polygonal industrial features (e.g. cutblocks, well sites) drive deer distributions as sources of early seral forage, while linear features (e.g. roads, trails, and seismic lines) and habitat associated with predators are avoided by deer. We developed seasonal 2nd -order resource selection models from three years of deer GPS-telemetry data, a camera-trap-based model of predator occurrence, and landscape spatial data to weigh evidence for six competing hypotheses. Deer habitat selection was best explained by the combination of polygonal and linear features, intact deciduous forest, and wolf (Canis lupus) occurrence. Deer strongly selected for linear features such as roads and trails, despite a potential increased risk of wolf encounters. Linear features may attract deer by providing high density forage opportunity in heavily exploited landscapes, facilitating expansion into the boreal north., (© 2022. The Author(s).)

Microarray for transcriptomics experiments often suffer from limited statistical power due to small sample size. Quantile discretization (QD) maps expression values for a sample into a series of equivalently sized 'bins' that represent a discrete numerical range, e.g. 4 to 4, which enables normalized data from multiple experiments and/or expression platforms to be combined for re-analysis. We found, however, that informal selection of bin numbers often resulted in loss of the underlying correlation structure in the data through assigning of the same numerical value to genes that are in reality expressed at significantly different levels within a sample. Here we report a procedure for determining an optimal bin number for dataset. Applying this to integrated public breast cancer datasets enabled statistical identification of several differentially expressed tumorigenesis-related genes that were not found when analyzing the individual datasets, and also several cancer biomarkers not previously indicated as having utility in the disease. Notably, differential modulation of translational control and protein synthesis via multiple pathways were found to potentially have central roles in breast cancer development and progression. These findings suggest that our protocol has significant utility in making meaningful novel biomedical discoveries by leveraging the large public expression data repositories. [ABSTRACT FROM AUTHOR]

HL7 International's Fast Healthcare Interoperability Resources (FHIR) standard provides a common format for sharing health data (eg, FHIR resources) and a RESTful Application Programming Interface (eg, FHIR API) for accessing those resources via a FHIR server connected to an electronic health record system or any other system storing clinical data. Substitutable Medical Applications and Reusable Technologies (SMART) leverages FHIR to create an electronic health record (EHR) agnostic app platform. It utilizes the OAuth standard to provide for authorization and authentication. This paper describes the development and informal evaluation of Case Based Learning on FHIR (CBL on FHIR), a prototype EHR-connected FHIR/SMART platform to provide interactive digital cases for use in medical education. The project goals were to provide a more interactive form of CBL than is possible on paper to more realistically simulate clinical decision making and to expose medical students to modern informatics systems and tools for use in patient care., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Biologging data allow animal ecologists to directly measure species' fine-scale spatiotemporal responses to environments, such as movement - critical for our understanding of biodiversity declines in the Anthropocene. Animal movement between resource patches is a behavioral expression of multiple ecological processes that affect individual fitness. Protected area (PA) networks are a tool used to conserve biodiversity by sustaining habitat patches across vast heterogeneous landscapes. However, our ability to design PA networks that conserve biodiversity relies on our accurate understanding of animal movement and functional connectivity; this understanding is rarely tested in real-world situations due to the large geographic expanse of most PA networks. Using a tractable PA network mesocosm, we employ cutting-edge biologging technology to analyze animal movement decisions in response to a highly heterogeneous landscape. We analyze these data to test, in a novel way, three common hypotheses about functional connectivity - structural corridors, least cost paths, and stepping stones. Consistently, animals moved along structurally self-similar corridors. In reference to the Aichi 2020 Biodiversity Targets, relying on species to "stepping stone" across habitat remnants may not achieve protected area network conservation objectives.