Whole genome sequencing reveals stepping-stone dispersal buffered against founder effects in a range expanding seabird.

Many species are shifting their ranges in response to climate-driven environmental changes, particularly in high-latitude regions. However, the patterns of dispersal and colonization during range shifting events are not always clear. Understanding how populations are connected through space and time can reveal how species navigate a changing environment. Here, we present a fine-scale population genomics study of gentoo penguins (Pygoscelis papua), a presumed site-faithful colonial nesting species that has increased in population size and expanded its range south along the Western Antarctic Peninsula. Using whole genome sequencing, we analysed 129 gentoo penguin individuals across 12 colonies located at or near the southern range edge. Through a detailed examination of fine-scale population structure, admixture, and population divergence, we inferred that gentoo penguins historically dispersed rapidly in a stepping-stone pattern from the South Shetland Islands leading to the colonization of Anvers Island, and then the adjacent mainland Western Antarctica Peninsula. Recent southward expansion along the Western Antarctic Peninsula also followed a stepping-stone dispersal pattern coupled with limited post-divergence gene flow from colonies on Anvers Island. Genetic diversity appeared to be maintained across colonies during the historical dispersal process, and range-edge populations are still growing. This suggests large numbers of migrants may provide a buffer against founder effects at the beginning of colonization events to maintain genetic diversity similar to that of the source populations before migration ceases post-divergence. These results coupled with a continued increase in effective population size since approximately 500-800 years ago distinguish gentoo penguins as a robust species that is highly adaptable and resilient to changing climate.

Increasing the impact of vertebrate scientific collections through 3D imaging: The openVertebrate (oVert) Thematic Collections Network.

The impact of preserved museum specimens is transforming and increasing by three-dimensional (3D) imaging that creates high-fidelity online digital specimens. Through examples from the openVertebrate (oVert) Thematic Collections Network, we describe how we created a digitization community dedicated to the shared vision of making 3D data of specimens available and the impact of these data on a broad audience of scientists, students, teachers, artists, and more. High-fidelity digital 3D models allow people from multiple communities to simultaneously access and use scientific specimens. Based on our multiyear, multi-institution project, we identify significant technological and social hurdles that remain for fully realizing the potential impact of digital 3D specimens.

Marine sulfated glycans inhibit the interaction of heparin with S-protein of SARS-CoV-2 Omicron XBB variant.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide COVID-19 pandemic, leading to 6.8 million deaths. Numerous variants have emerged since its outbreak, resulting in its significantly enhanced ability to spread among humans. As with many other viruses, SARS­CoV­2 utilizes heparan sulfate (HS) glycosaminoglycan (GAG) on the surface of host cells to facilitate viral attachment and initiate cellular entry through the ACE2 receptor. Therefore, interfering with virion-HS interactions represents a promising target to develop broad-spectrum antiviral therapeutics. Sulfated glycans derived from marine organisms have been proven to be exceptional reservoirs of naturally existing HS mimetics, which exhibit remarkable therapeutic properties encompassing antiviral/microbial, antitumor, anticoagulant, and anti-inflammatory activities. In the current study, the interactions between the receptor-binding domain (RBD) of S-protein of SARS-CoV-2 (both WT and XBB.1.5 variants) and heparin were applied to assess the inhibitory activity of 10 marine-sourced glycans including three sulfated fucans, three fucosylated chondroitin sulfates and two fucoidans derived from sea cucumbers, sea urchin and seaweed Saccharina japonica, respectively. The inhibitory activity of these marine derived sulfated glycans on the interactions between RBD of S-protein and heparin was evaluated using Surface Plasmon Resonance (SPR). The RBDs of S-proteins from both Omicrion XBB.1.5 and wild-type (WT) were found to bind to heparin, which is a highly sulfated form of HS. All the tested marine-sourced sulfated glycans exhibited strong inhibition of WT and XBB.1.5 S-protein binding to heparin. We believe the study on the molecular interactions between S-proteins and host cell glycosaminoglycans provides valuable insight for the development of marine-sourced, glycan-based inhibitors as potential anti-SARS-CoV-2 agents.

The Complete Genome Sequences of 23 Finch Species (Fringillidae, Passeriformes).

We present complete genome sequences of 23 species of finches from 6 genera.

The Complete Genome Sequences of 37 Bird Species from the Ecuadorian Andes.

We present the complete genome sequences of 37 Ecuadorian bird species widespread throughout the tropical Andes.

Serological assessment of the durability of vaccine-mediated protection against SARS-CoV-2 infection.

Virus-neutralizing antibodies are often accepted as a correlate of protection against infection, though questions remain about which components of the immune response protect against SARS-CoV-2 infection. In this small observational study, we longitudinally measured spike receptor binding domain (RBD)-specific and nucleocapsid (NP)-specific serum IgG in a human cohort immunized with the Pfizer BNT162b2 vaccine. NP is not encoded in the vaccine, so an NP-specific response is serological evidence of natural infection. A greater than fourfold increase in NP-specific antibodies was used as the serological marker of infection. Using the RBD-specific IgG titers prior to seroconversion for NP, we calculated a protective threshold for RBD-specific IgG. On average, the RBD-specific IgG response wanes below the protective threshold 169 days following vaccination. Many participants without a history of a positive test result for SARS-CoV-2 infection seroconverted for NP-specific IgG. As a group, participants who seroconverted for NP-specific IgG had significantly higher levels of RBD-specific IgG following NP-seroconversion. RBD-specific IgG titers may serve as one correlate of protection against SARS-CoV-2 infection. These titers wane below the proposed protective threshold approximately six months following immunization. Based on serological evidence of infection, the frequency of breakthrough infections and consequently the level of SARS-CoV-2-specific immunity in the population may be higher than what is predicted based on the frequency of documented infections.

New onset diabetes in children during the COVID-19 Pandemic: an assessment of biomarkers and psychosocial risk factors at play in Mississippi.

Purpose: The COVID-19 pandemic has shown a rise in pediatric diabetes. Studies have indicated an increased likelihood of children with COVID-19 infection developing diabetes. Our objective was to assess not only for an increase in pediatric diabetes at our hospital and identify possible risk factors but also to correlate psychosocial changes resulting from the pandemic with new-onset diabetes during this time. Methods: We analyzed data from 58 children aged 1-18 years admitted to our hospital with new-onset diabetes between March 2020 and December 2021, including inflammatory biomarkers and SARS-CoV-2 antibodies (Ab), as well as results of a lifestyle questionnaire. Results: Average monthly hospital admissions for new-onset diabetes rose from 10 to 18 with the start of the pandemic. Of the 58 children in our analysis, 33% had positive SARS-CoV-2 IgG Ab, 31% had type 1 diabetes mellitus (T1DM), and 62% had type 2 diabetes mellitus (T2DM). More than half (54%) were in DKA. Those with T2DM were older, majority African American, had higher median BMI percentiles, and lower Vitamin D levels. There were no significant correlations between any psychosocial risk factors and either diabetes type or SARS-CoV2 Ab status. Conclusions: Despite the increased incidence of new-onset diabetes among children in Mississippi during the pandemic, this study was unable to demonstrate significant correlations between COVID-19 infection and new-onset diabetes. This study highlighted the correlation between increased BMI and type 2 diabetes, which speaks to the significant problem of obesity and diabetes in Mississippi and the need for further research.

Evidence of SARS-CoV-2 Antibody in Mississippi White-Tailed Deer.

Background: Early detection and monitoring of SARS-CoV-2 infections in animal populations living in close proximity to humans is crucial for preventing reverse zoonosis of new viral strains. Evidence accumulated has revealed widespread SARS-CoV-2 infection among white-tailed deer (WTD), (Odocoileus virginianus) populations in the United States except in the southeast region. Therefore, the objective was to conduct surveillance for evidence of SARS-CoV-2 infection among WTD in Mississippi. Materials and Methods: Blood, kidney tissues, and nasal swab samples were collected in 17 counties from hunter-harvested deer during 2021-2022 and 2022-2023.Samples of kidney tissue were collected to evaluate for detecting antibody as a possible alternative to blood that is not always available from dead WTD. Nasal swab samples were tested for SARS-CoV-2 viral RNA by a RT-PCR assay. Sera and kidney tissue samples were tested for SARS-CoV-2 antibody by an enzyme-linked immunoassay (ELISA) and sera by a plaque reduction neutralization test (PRNT80). Results: The results of testing sera and kidney homogenate samples provided the first evidence of SARS-CoV-2 infection among WTD in Mississippi. The infection rate during 2021-2022 was 67% (10/15) based on the detection of neutralizing antibody by the PRNT80 and 26%(16/62) based on the testing of kidney tissue homogenates by an ELISA, and viral RNA was detected in 25% (3/12) of nasal swab samples. In 2022 to 2023, neutralizing antibody was detected in 62% (28/45) of WTD serum samples. In contrast, antibodies were not detected in 220 kidney homogenates by an ELISA nor was viral RNA detected in 220 nasal swab samples. Evidence of WTD activity was common in urban areas during the survey. Conclusion: Overall, the findings documented the first SARS-CoV-2 infection among WTD in Mississippi and showed that WTD commonly inhabited urban areas as a possible source of acquiring infection from humans infected with this virus.

Sulfated Glycans Inhibit the Interaction of MERS-CoV Receptor Binding Domain with Heparin.

Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic virus with high contagion and mortality rates. Heparan sulfate proteoglycans (HSPGs) are ubiquitously expressed on the surface of mammalian cells. Owing to its high negatively charged property, heparan sulfate (HS) on the surface of host cells is used by many viruses as cofactor to facilitate viral attachment and initiate cellular entry. Therefore, inhibition of the interaction between viruses and HS could be a promising target to inhibit viral infection. In the current study, the interaction between the receptor-binding domain (RBD) of MERS-CoV and heparin was exploited to assess the inhibitory activity of various sulfated glycans such as glycosaminoglycans, marine-sourced glycans (sulfated fucans, fucosylated chondroitin sulfates, fucoidans, and rhamnan sulfate), pentosan polysulfate, and mucopolysaccharide using Surface Plasmon Resonance. We believe this study provides valuable insights for the development of sulfated glycan-based inhibitors as potential antiviral agents.

A pilot feasibility study comparing large language models in extracting key information from ICU patient text records from an Irish population.

BACKGROUND: Artificial intelligence, through improved data management and automated summarisation, has the potential to enhance intensive care unit (ICU) care. Large language models (LLMs) can interrogate and summarise large volumes of medical notes to create succinct discharge summaries. In this study, we aim to investigate the potential of LLMs to accurately and concisely synthesise ICU discharge summaries. METHODS: Anonymised clinical notes from ICU admissions were used to train and validate a prompting structure in three separate LLMs (ChatGPT, GPT-4 API and Llama 2) to generate concise clinical summaries. Summaries were adjudicated by staff intensivists on ability to identify and appropriately order a pre-defined list of important clinical events as well as readability, organisation, succinctness, and overall rank. RESULTS: In the development phase, text from five ICU episodes was used to develop a series of prompts to best capture clinical summaries. In the testing phase, a summary produced by each LLM from an additional six ICU episodes was utilised for evaluation. Overall ability to identify a pre-defined list of important clinical events in the summary was 41.5 ± 15.2% for GPT-4 API, 19.2 ± 20.9% for ChatGPT and 16.5 ± 14.1% for Llama2 (p = 0.002). GPT-4 API followed by ChatGPT had the highest score to appropriately order a pre-defined list of important clinical events in the summary as well as readability, organisation, succinctness, and overall rank, whilst Llama2 scored lowest for all. GPT-4 API produced minor hallucinations, which were not present in the other models. CONCLUSION: Differences exist in large language model performance in readability, organisation, succinctness, and sequencing of clinical events compared to others. All encountered issues with narrative coherence and omitted key clinical data and only moderately captured all clinically meaningful data in the correct order. However, these technologies suggest future potential for creating succinct discharge summaries.

Major trauma patients and their outcomes - A retrospective observational study of critical care trauma admissions to a trauma unit with special services.

INTRODUCTION: International data describes a changing pattern to trauma over the last decade, with an increasingly comorbid population presenting challenges to trauma management and resources. In Ireland, resource provision and management of trauma is being transformed to deliver a trauma network, in line with international best practice. Our hospital plays a crucial role within this network and is designated a Trauma Unit with Specialist Services (TUSS) to distinguish it from standard trauma units. METHODS: This study aims to describe the characteristics of patients and injuries and assess trends in mortality rates. It is a retrospective observational study of adult ICU trauma admissions from August 2010 to July 2021. Primary outcome was all-cause mortality at 30-days, 90-days, and 1 year. Secondary outcomes included length of stay, disposition, and complications. Patients were categorised by age, injury severity score (ISS), and mechanism of injury. RESULTS: In all, 709 patients were identified for final analysis. Annual admissions doubled since 2010/11, with a trough of 41 admissions, increasing to peak at 95 admissions in 2017/18. Blunt trauma accounted for 97.6% of cases. Falls <2 m (45.4%) and RTAs (29.2%) were the main mechanisms of injury. Polytrauma comprised 41.9% of admissions. Traumatic brain injury accounted for 30.2% of cases; 18.8% of these patients were transferred to a neurosurgical centre. The majority of patients, 58.1%, were severely injured (ISS ≥ 16). Patients ≥ 65 years of age accounted for 45.7% of admissions, with falls <2 m their primary mechanism of injury. The primary outcome of all-cause mortality reduced with an absolute risk reduction (ARR) of 8.0% (95% CI: -8.37%, 24.36%), 12.9% (95% CI: -4.19%, 29.94%) and 8.2% (95% CI: -9.64%, 26.09%) for 30-day, 90-day and 1-year respectively. Regression analysis demonstrated a significant reduction in mortality for 30-days and 90-days post presentation to hospital (P-values of 0.018, 0.033 and 0.152 for 30-day, 90-day and 1-year respectively). CONCLUSION: The burden of major trauma in our hospital is considerable and increasing over time. Substantial changes in demographics, injury mechanism and mortality were seen, with outcomes improving over time. This is consistent with international data where trauma systems have been adopted.

Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction.

Although high-dimensional clinical data (HDCD) are increasingly available in biobank-scale datasets, their use for genetic discovery remains challenging. Here we introduce an unsupervised deep learning model, Representation Learning for Genetic Discovery on Low-Dimensional Embeddings (REGLE), for discovering associations between genetic variants and HDCD. REGLE leverages variational autoencoders to compute nonlinear disentangled embeddings of HDCD, which become the inputs to genome-wide association studies (GWAS). REGLE can uncover features not captured by existing expert-defined features and enables the creation of accurate disease-specific polygenic risk scores (PRSs) in datasets with very few labeled data. We apply REGLE to perform GWAS on respiratory and circulatory HDCD-spirograms measuring lung function and photoplethysmograms measuring blood volume changes. REGLE replicates known loci while identifying others not previously detected. REGLE are predictive of overall survival, and PRSs constructed from REGLE loci improve disease prediction across multiple biobanks. Overall, REGLE contain clinically relevant information beyond that captured by existing expert-defined features, leading to improved genetic discovery and disease prediction.