Research articles

Filter By:

Article Type
  • Levi and Ubaldi et al. evaluate SARS-CoV-2 seroprevalence in a cohort of 4735 healthcare workers in northern Italy. In seropositive individuals, they show that antibodies are maintained over a period of 8 to 10 months and associate changes in antibody levels over this period with symptoms and specific subgroups of participants.

    • Riccardo Levi
    • Leonardo Ubaldi
    • Maria Rescigno
    Article Open Access
  • Nemira et al. study the genomic epidemiology and phylodynamics of SARS-CoV-2 in Belarus. They identify potential introduction routes of the virus from other countries, determine that during the first wave of the pandemic the number of infections was likely several times higher than reported case numbers, and estimate the impact of early non-pharmaceutical interventions on SARS-CoV-2 transmission.

    • Alina Nemira
    • Ayotomiwa Ezekiel Adeniyi
    • Pavel Skums
    Article Open Access
  • de Figueiredo et al. perform a global exploratory study to estimate COVID-19 vaccination acceptance and its determinants based on a survey across 32 countries. With some exceptions, they find that factors associated with increased vaccine acceptance are male sex, age over 65, being highly educated, and a belief that their government is handling the pandemic well.

    • Alexandre de Figueiredo
    • Heidi J. Larson
    Article Open Access
  • Hanlon et al. study the prevalence of frailty and multimorbidity in a cohort of 20,566 UK Biobank participants with type 2 diabetes aged between 40 and 72 years. They observe that, even in this relatively young population, people living with frailty and/or multimorbidity are at increased risk of adverse outcomes including mortality, major adverse cardiovascular events, and hypoglycaemia.

    • Peter Hanlon
    • Bhautesh D. Jani
    • Frances S. Mair
    Article Open Access
  • Wang et al. characterize the tissue distribution of SARS-CoV-2 viral infection and replication as well as the expression of host cell entry factors in postmortem samples from six patients with COVID-19. They report the co-existence of SARS-CoV-2 infection and host entry factors in multiple pulmonary and non-pulmonary tissues.

    • Xiao-Ming Wang
    • Rahul Mannan
    • Rohit Mehra
    Article Open Access
  • Singh et al. perform a breath-metabolomics study on patients with epilepsy taking antiseizure medications. They find that systemic valproic acid concentrations, along with risk estimates for drug responses and side effects, can be predicted by measuring metabolites in the breath, which might help to guide therapeutic dosing and manage side effects.

    • Kapil Dev Singh
    • Martin Osswald
    • Pablo Sinues
    Article Open Access
  • Mascheroni et al. develop a method for individual clinical predictions by combining mathematical modelling and machine learning in a Bayesian framework (BaM3). By using both synthetic and real clinical datasets, they show the potential of the method to predict tumour growth in the context of clinical data sparsity and limited knowledge of disease mechanisms.

    • Pietro Mascheroni
    • Symeon Savvopoulos
    • Haralampos Hatzikirou
    Article Open Access
  • De Salazar et al. quantify the impact of BNT162b2 mRNA vaccination on COVID-19 transmission and deaths in residents of long-term care facilities in Catalonia, Spain using statistical modelling. They find that high vaccination coverage results in a substantial reduction in transmission amongst residents, preventing around 3 in 4 documented infections and COVID-19-related deaths.

    • Pablo M. De Salazar
    • Nicholas B. Link
    • Mauricio Santillana
    Article Open Access
  • Wagner et al. carry out a longitudinal seroepidemiological study of SARS-CoV-2 antibodies in a cohort of adults from a large company in Vienna, Austria. In individuals positive for S1-reactive antibodies at baseline, RBD-specific antibodies are most likely to persist for six months and correlate most closely with SARS-CoV-2 neutralizing ability.

    • Angelika Wagner
    • Angela Guzek
    • Ursula Wiedermann
    Article Open Access
  • Mu et al. utilize a deep learning natural language processing model as part of an active learning approach to extract diagnostically relevant semantic information from bone marrow pathology synopses. Their findings demonstrate the potential for artificial intelligence in assisting clinicians in assessing, cataloging and triaging medical text datasets such as pathology synopses.

    • Youqing Mu
    • Hamid R. Tizhoosh
    • Clinton J. V. Campbell
    Article Open Access
  • Jun et al. evaluate sex-stratified clinical outcomes in two cohorts of patients hospitalized with COVID-19 in New York. While male sex risk is a risk factor for poor outcome in both cohorts – one from earlier and one from later on in the pandemic – some of the sex-specific risk factors observed initially are not observed later on.

    • Tomi Jun
    • Sharon Nirenberg
    • Kuan-lin Huang
    Article Open Access
  • MacLeod et al. evaluate the mechanical safety of 3D-printed personalised high tibial osteotomy (HTO) plates in an in silico clinical trial. Using this novel methodology, they find no increased risk of mechanical failure for personalised devices compared to conventional plates, supporting further studies to assess clinical outcomes in patients treated with personalised HTO.

    • Alisdair R. MacLeod
    • Nicholas Peckham
    • Harinderjit S. Gill
    Article Open Access
  • Knabl et al. perform a seroepidemiological study in the Austrian ski resort Ischgl, where a super-spreader event lead to a SARS-CoV-2 outbreak. Through mathematical modelling, they find that the subsequent decline in viral transmission was most likely a combined effect of high seropositivity and the implementation of non-pharmaceutical interventions.

    • Ludwig Knabl
    • Tanmay Mitra
    • Dorothee von Laer
    Article Open Access
  • Wulczyn et al. utilise a deep learning-based Gleason grading model to predict prostate cancer-specific mortality in a retrospective cohort of radical prostatectomy patients. Their model enables improved risk stratification compared to pathologists’ grading and demonstrates the potential for computational pathology in the management of prostate cancer.

    • Ellery Wulczyn
    • Kunal Nagpal
    • Craig H. Mermel
    Article Open Access