3D genital shape complexity in female marine mammals

Comparisons of 3D shapes have recently been applied to diverse anatomical structures using landmarking techniques. However, discerning evolutionary patterns can be challenging for structures lacking homologous landmarks. We used alpha shape analyses to quantify vaginal shape complexity in 40 marine mammal specimens including cetaceans, pinnipeds, and sirenians. We explored phylogenetic signal and the potential roles of natural and sexual selection on vaginal shape evolution. Complexity scores were consistent with qualitative observations. Cetaceans had a broad range of alpha complexities, while pinnipeds were comparatively simple and sirenians were complex. Intraspecific variation was found. Three‐dimensional surface heat maps revealed that shape complexity was driven by invaginations and protrusions of the vaginal wall. Phylogenetic signal was weak and metrics of natural selection (relative neonate size) and sexual selection (relative testes size, sexual size dimorphism, and penis morphology) did not explain vaginal complexity patterns. Additional metrics, such as penile shape complexity, may yield interesting insights into marine mammal genital coevolution. We advocate for the use of alpha shapes to discern patterns of evolution that would otherwise not be possible in 3D anatomical structures lacking homologous landmarks

“This doesn’t feel like living”: How the COVID-19 Pandemic Affected the Mental Health of Vulnerable University Students in the United Kingdom

Introduction: Concerns about student mental health have been rising globally. The COVID-19 pandemic triggered unprecedented disruption in higher education as universities were forced to close and adapt their education delivery. Understanding the impact of this on vulnerable students can inform higher education’s response to future similar events. Aims: To understand the lived experience of first year university students studying in the United Kingdom, who had a history of poor mental health and lived on a low income, we examined the inter-relatedness between mental health, financial strain, remote learning and engagement, and well-being. Methods: At the start of their first year of study, whilst the UK was in periods of lockdown, we conducted in-depth semi-structured interviews with 20 diverse first-year university students. We analyzed data using interpretative phenomenological analysis. Results: The pandemic’s impact on student mental health, engagement and learning remained pervasive and serious. Key themes conveyed how isolation triggered past mental health difficulties and a perception that the universities – and government – had forgotten about them. Students also experienced greater difficulty in navigating the liminal threshold between being a child and an adult, and having the additional worry of financial instability left students with fewer coping resources. Conclusions: To mitigate the impact of future pandemic responses, constant and effective communication is needed between faculty and students to safeguard against isolation and low motivation. Vulnerable students need guidance in coping skills to manage mental health risks when they are away from family and familiar support network

Molecular determinants and intracellular targets of taurine signalling in pancreatic islet β‐cells

AbstractAimDespite its abundance in pancreatic islets of Langerhans and proven antihyperglycemic effects, the impact of the essential amino acid, taurine, on islet β‐cell biology has not yet received due consideration, which prompted the current studies exploring the molecular selectivity of taurine import into β‐cells and its acute and chronic intracellular interactions.MethodsThe molecular aspects of taurine transport were probed by exposing the clonal pancreatic BRIN BD11 β‐cells and primary mouse and human islets to a range of the homologs of the amino acid (assayed at 2–20 mM), using the hormone release and imaging of intracellular signals as surrogate read‐outs. Known secretagogues were employed to profile the interaction of taurine with acute and chronic intracellular signals.ResultsTaurine transporter TauT was expressed in the islet β‐cells, with the transport of taurine and homologs having a weak sulfonate specificity but significant sensitivity to the molecular weight of the transporter. Taurine, hypotaurine, homotaurine, and β‐alanine enhanced insulin secretion in a glucose‐dependent manner, an action potentiated by cytosolic Ca2+ and cAMP. Acute and chronic β‐cell insulinotropic effects of taurine were highly sensitive to co‐agonism with GLP‐1, forskolin, tolbutamide, and membrane depolarization, with an unanticipated indifference to the activation of PKC and CCK8 receptors. Pre‐culturing with GLP‐1 or KATP channel inhibitors sensitized or, respectively, desensitized β‐cells to the acute taurine stimulus.ConclusionTogether, these data demonstrate the pathways whereby taurine exhibits a range of beneficial effects on insulin secretion and β‐cell function, consistent with the antidiabetic potential of its dietary low‐dose supplementation

The dispersion time of random walks on finite graphs

We study two random processes on an $n$-vertex graph inspired by the internal diffusion limited aggregation (IDLA) model. In both processes $n$ particles start from an arbitrary but fixed origin. Each particle performs a simple random walk until first encountering an unoccupied vertex, and at which point the vertex becomes occupied and the random walk terminates. In one of the processes, called $\textit{Sequential-IDLA}$, only one particle moves until settling and only then does the next particle start whereas in the second process, called $\textit{Parallel-IDLA}$, all unsettled particles move simultaneously. Our main goal is to analyze the so-called dispersion time of these processes, which is the maximum number of steps performed by any of the $n$ particles. In order to compare the two processes, we develop a coupling that shows the dispersion time of the Parallel-IDLA stochastically dominates that of the Sequential-IDLA; however, the total number of steps performed by all particles has the same distribution in both processes. This coupling also gives us that dispersion time of Parallel-IDLA is bounded in expectation by dispersion time of the Sequential-IDLA up to a multiplicative $\log n$ factor. Moreover, we derive asymptotic upper and lower bound on the dispersion time for several graph classes, such as cliques, cycles, binary trees, $d$-dimensional grids, hypercubes and expanders. Most of our bounds are tight up to a multiplicative constant.ERC Grant Dynamic Marc

ASAS–NANP Symposium: Mathematical Modeling in Animal Nutrition: Opportunities and Challenges of Confned and Extensive Precision Livestock Production

Modern animal scientists, industry, and managers have never faced a more complex world. Precision livestock technologies have altered management in confned operations to meet production, environmental, and consumer goals. Applications of precision technologies have been limited in extensive systems such as rangelands due to lack of infrastructure, electrical power, communication, and durability. However, advancements in technology have helped to overcome many of these challenges. Investment in precision technologies is growing within the livestock sector, requiring the need to assess opportunities and challenges associated with implementation to enhance livestock production systems. In this review, precision livestock farming and digital livestock farming are explained in the context of a logical and iterative fve-step process to successfully integrate precision livestock measurement and management tools, emphasizing the need for precision system models (PSMs). This fve-step process acts as a guide to realize anticipated benefts from precision technologies and avoid unintended consequences. Consequently, the synthesis of precision livestock and modeling examples and key case studies help highlight past challenges and current opportunities within confned and extensive systems. Successfully developing PSM requires appropriate model(s) selection that aligns with desired management goals and precision technology capabilities. Therefore, it is imperative to consider the entire system to ensure that precision technology integration achieves desired goals while remaining economically and managerially sustainable. Achieving long-term success using precision technology requires the next generation of animal scientists to obtain additional skills to keep up with the rapid pace of technology innovation. Building workforce capacity and synergistic relationships between research, industry, and managers will be critical. As the process of precision technology adoption continues in more challenging and harsh, extensive systems, it is likely that confned operations will beneft from required advances in precision technology and PSMs, ultimately strengthening the benefts from precision technology to achieve short- and long-term goals

An exploratory study into the use of Lean Six Sigma to reduce medication errors in the Norwegian public healthcare context

Purpose: Medication errors are a significant cause of injury in Norwegian hospitals. The purpose of this study is to explore how Lean Six Sigma (LSS) has been used in the Norwegian public health-care context to reduce medication errors. Design/methodology/approach: A mixed method approach was used to gather data from participants working in the four regions served by the Norway health authorities. A survey questionnaire was distributed to 38 health-care practitioners and semi-structured interviews were conducted with 12 health-care practitioners. Findings: The study finds that the implementation of LSS in the Norwegian public health-care context is still in its infancy. This is amidst several challenges faced by Norwegian hospitals such as the lack of top-management support, lack of LSS training and coaching and a lack of awareness around the benefits of LSS in health care. Research limitations/implications: Because of the large geographical area, it was difficult to reach participants from all health regions in Norway. However, the study managed to assess the current status of LSS implementation through the participants’ perspectives. This is a fruitful area for future research whereby an action research methodology could be used. Originality/value: To the best of the authors’ knowledge, this is the first empirical study into the use of LSS methodology in reducing medication errors. In addition, this study is valuable for health-care practitioners and professionals as a guideline to achieve the optimal benefit of LSS implementation to reduce medication errors

Improved computational epitope profiling using structural models identifies a broader diversity of antibodies that bind to the same epitope

The function of an antibody is intrinsically linked to the epitope it engages. Clonal clustering methods, based on sequence identity, are commonly used to group antibodies that will bind to the same epitope. However, such methods neglect the fact that antibodies with highly diverse sequences can exhibit similar binding site geometries and engage common epitopes. In a previous study, we described SPACE1, a method that structurally clustered antibodies in order to predict their epitopes. This methodology was limited by the inaccuracies and incomplete coverage of template-based modeling. In addition, it was only benchmarked at the level of domain-consistency on one virus class. Here, we present SPACE2, which uses the latest machine learning-based structure prediction technology combined with a novel clustering protocol, and benchmark it on binding data that have epitope-level resolution. On six diverse sets of antigen-specific antibodies, we demonstrate that SPACE2 accurately clusters antibodies that engage common epitopes and achieves far higher dataset coverage than clonal clustering and SPACE1. Furthermore, we show that the functionally consistent structural clusters identified by SPACE2 are even more diverse in sequence, genetic lineage, and species origin than those found by SPACE1. These results reiterate that structural data improve our ability to identify antibodies that bind to the same epitope, adding information to sequence-based methods, especially in datasets of antibodies from diverse sources. SPACE2 is openly available on GitHub (https://github.com/oxpig/SPACE2)