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Special Issue on the Challenges for family and child well‐being in the new era

Citation: Li J, Rönkä A, Han WJ. Special Issue on the Challenges for family and child well‐being in the new era. International Journal of Social

Powerful promotions: An investigation of the teen-directed marketing power of outdoor food advertisements located near schools in Australia

Adolescents are heavily exposed to unhealthy outdoor food advertisements near schools, however, the marketing power of these advertisements among adolescents has not yet been explored. This study aimed to investigate the teen-directed marketing features present and quantify the overall marketing power of outdoor food advertisements located near schools to explore any differences by content (ie, alcohol, discretionary, core and miscellaneous foods) school type (ie, primary, secondary, K-12) and area-level socio-economic status (SES; ie, low vs high).

Movement behavior policies in the early childhood education and care setting: An international scoping review

Meeting 24-h movement behavior guidelines for the early years is associated with better health and development outcomes in young children. Early childhood education and care (ECEC) is a key intervention setting however little is known about the content and implementation of movement behavior polices in this context. To inform policy development this international scoping review examined the prevalence, content, development and implementation of ECEC-specific movement behavior policies.

No association between in utero exposure to emissions from a coalmine fire and post-natal lung function

Studies linking early life exposure to air pollution and subsequent impaired lung health have focused on chronic, low-level exposures in urban settings. We aimed to determine whether in utero exposure to an acute, high-intensity air pollution episode impaired lung function 7-years later.

Blinatumomab Added to Chemotherapy in Infant Lymphoblastic Leukemia

KMT2A-rearranged acute lymphoblastic leukemia (ALL) in infants is an aggressive disease with 3-year event-free survival below 40%. Most relapses occur during treatment, with two thirds occurring within 1 year and 90% within 2 years after diagnosis. Outcomes have not improved in recent decades despite intensification of chemotherapy.

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.

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.