Springer Nature

Before the COVID-19 pandemic, the use of telemedicine was limited in pediatric primary care. Then, in 2020 it increased exponentially. However, early COVID-19 reports described inequities in telemedicine use across multiple specialties.

In this episode, we meet Early Career Investigator, Kelsey Schweiberger from the University of Pittsburgh. In a recent paper, she describes the factors associated with scheduling and attendance of telemedicine appointments for pediatric primary care throughout the first year of the COVID-19 pandemic to identify priorities for enhanced equity in access.

Read the full paper here: https://www.nature.com/articles/s41390-023-02481-w

In this episode, Richard Bernstein (Institute for Bee Research Hohen Neuendorf) discusses the development of the first genomic prediction model for honey bees. Genomic prediction is well established in the breeding of many commercial species, but wasn’t possible in honey bees until now. Richard fills us in on what genomic prediction actually is, why its useful and why prediction for bees is so tricky.

In-person treatment for substance use disorders is an incredibly important tool, but there’s a high failure rate — more than 50 percent of people who enter drop out within the first month. There hasn’t been a highly accurate method of identifying who might leave and who might succeed, and knowing this could help centers allocate resources to give the right type of assistance to the right people at the right time. One tool available is called the Addiction Severity Index, which is used to help identify the severity of the addiction and thus customize treatment, but it wasn’t developed to gauge whether a patient might drop out entirely. So a team of researchers decided to mine something known as a digital phenotype.

Dr. Brenda Curtis is a clinical researcher at the National Institute on Drug Abuse Intramural Research Program, and she’s one of the paper’s authors.

Read the full study here: https://www.nature.com/articles/s41386-023-01585-5

Heart rate characteristics and demographic factors have long been used to aid early detection of late-onset sepsis, however respiratory data may contain additional signatures of infection.

In this episode we meet Early Career Investigator Brynne Sullivan from the University of Virginia. She and her team developed machine learning models to predict late-onset sepsis that were trained on heart rate and respiratory data to provide a cardiorespiratory early warning system which outperformed models using heart rate or demographics alone.

Read the full article here: https://www.nature.com/articles/s41390-022-02444-7

In this episode, Prof Thomas Madsen (Deakin University) discusses how a long-term study of an adder population has provided evidence that polyandry and non-random fertilisation can have positive effects on genetic diversity. Thomas argues that factoring in mating dynamics could help to improve conservation genetic analyses.

Antisocial personality disorder, or ASPD, is a difficult disorder to study. There have been studies on psychopathic individuals, and on youth with psychopathic traits, but most studies on ASPD to date have been on incarcerated adults. A team of researchers at Heidelberg University wanted to study individuals who are not incarcerated and see what these findings could elucidate about the brains, in particular the amygdalas, of individuals with ASPD.

Haang Jeung-Maarse is a medical doctor at Bielfeld University in Germany and is one of the authors of the paper in the journal Neuropsychopharmacology, on the effects of oxytocin on amygdala reactivity to angry faces in males and females with antisocial personality disorder.

Read the full study here: https://www.nature.com/articles/s41386-023-01549-9

In this episode, Anna Hewett discusses how different factors have led to the patterns of homozygosity observed in a population of red deer living on the Scottish Isle of Rum.

Bronchopulmonary dysplasia (BPD) is the most common morbidity among very preterm infants.

Commonly, nutritional interventions are focused on achieving optimal body weight gain. However, very preterm infants with evolving lung disease often experience disproportionate growth in the neonatal period, which may contribute to the odds of developing BPD.

In this episode of Pediapod, we speak to Early Career Investigator Marc Beltempo from McGill University, Montréal, Canada who has investigated the link between change in body mass index and evolving BPD in very preterm infants.

Read the full study here: https://www.nature.com/articles/s41390-022-02358-4

After five years with the journal, James Burgon is leaving the Heredity Podcast. But fear not! Because the podcast is being left in a pair of safe and familiar hands. In this episode we meet our new host: Michael Pointer. Also joining the episode is new Editor-in-Chief Prof. Sara Goodacre.

Kawasaki disease is a common childhood vasculitis and its global incidence appears to be increasing. Although this disease is self-limiting, the associated vasculopathy can cause cardiovascular complications.

In this episode of Pediapod, we meet Early Career Investigator Cal Robinson at the Hospital for Sick Children, Toronto, Canada who performed a population-based cohort study using Ontario health administrative databases to determine the risk of cardiovascular events and mortality after Kawasaki disease.

Read the full study here: https://www.nature.com/articles/s41390-022-02391-3