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Measures of Early-life Behavior and Later Psychopathology in the LifeCycle Project-EU Child Cohort Network: A Cohort Description

The EU LifeCycle Project was launched in 2017 to combine, harmonize, and analyze data from more than 250,000 participants across Europe and Australia, involving cohorts participating in the EU-funded LifeCycle Project. The purpose of this cohort description is to provide a detailed overview of the major measures within mental health domains that are available in 17 European and Australian cohorts participating in the LifeCycle Project.

Detection of bile acids in bronchoalveolar lavage fluid defines the inflammatory and microbial landscape of the lower airways in infants with cystic fibrosis

Cystic Fibrosis (CF) is a genetic condition characterized by neutrophilic inflammation and recurrent infection of the airways. How these processes are initiated and perpetuated in CF remains largely unknown. We have demonstrated a link between the intestinal microbiota-related metabolites bile acids and inflammation in the bronchoalveolar lavage fluid from children with stable CF lung disease.

Arcuate fasciculus and pre-reading language development in children with prenatal alcohol exposure

Prenatal alcohol exposure (PAE) contributes to widespread neurodevelopmental challenges, including reading, and has been associated with altered white matter. Here, we aimed to investigate whether arcuate fasciculus development is associated with pre-reading language skills in young children with PAE.

The effect of the COVID-19 pandemic on paediatric anaesthesia research as evidenced by the contrasting recruitment experiences of centres in Australia and Scotland

At two hospitals in Western Australia, we conducted a prospective, open-label, randomised, controlled trial of 240 patients undergoing tonsillectomy to investigate the effect of chewing a confectionery jelly snake on postoperative nausea and vomiting. The results were published in Anaesthesia Critical Care & Pain Medicine. Recruitment for this study was completed uneventfully between July 2018 and August 2019.

The effect of CFTR modulators on structural lung disease in cystic fibrosis

Newly developed quantitative chest computed tomography (CT) outcomes designed specifically to assess structural abnormalities related to cystic fibrosis (CF) lung disease are now available. CFTR modulators potentially can reduce some structural lung abnormalities. We aimed to investigate the effect of CFTR modulators on structural lung disease progression using different quantitative CT analysis methods specific for people with CF (PwCF).

Copy number variation in tRNA isodecoder genes impairs mammalian development and balanced translation

The number of tRNA isodecoders has increased dramatically in mammals, but the specific molecular and physiological reasons for this expansion remain elusive. To address this fundamental question we used CRISPR editing to knockout the seven-membered phenylalanine tRNA gene family in mice, both individually and combinatorially.

Multi-omic profiling reveals an RNA processing rheostat that predisposes to prostate cancer

Prostate cancer is the most commonly diagnosed malignancy and the third leading cause of cancer deaths. GWAS have identified variants associated with prostate cancer susceptibility; however, mechanistic and functional validation of these mutations is lacking.

From Deficit to Strength-Based Aboriginal Health Research—Moving toward Flourishing

Aboriginal Australians have a fundamental human right to opportunities that lead to healthy and flourishing lives. While the impact of trauma on Aboriginal Australians is well-documented, a pervasive deficit narrative that focuses on problems and pathology persists in research and policy discourse.

Gene filtering strategies for machine learning guided biomarker discovery using neonatal sepsis RNA-seq data

Machine learning (ML) algorithms are powerful tools that are increasingly being used for sepsis biomarker discovery in RNA-Seq data. RNA-Seq datasets contain multiple sources and types of noise (operator, technical and non-systematic) that may bias ML classification. Normalisation and independent gene filtering approaches described in RNA-Seq workflows account for some of this variability and are typically only targeted at differential expression analysis rather than ML applications.