Maternal pre-pregnancy obesity and timing of puberty in sons and daughters: a population-based cohort study.

BackgroundIn many countries, an increased prevalence of obesity in pregnancy has coincided with a declining pubertal age. We aimed to explore the potential effect of maternal pre-pregnancy overweight and obesity on timing of puberty in sons and daughters.MethodsBetween 2012 and 2018, 15 819 of 22 439 invited children from the Danish National Birth Cohort, born 2000-03, provided half-yearly information from the age of 11 years on the pubertal milestones: Tanner stages, voice break, first ejaculation, menarche, acne and axillary hair. We estimated adjusted mean monthly differences (with 95% confidence intervals) in age at attaining the pubertal milestones for children exposed to maternal pre-pregnancy obesity [body mass index (BMI) ≥30.0 kg/m2] or overweight (BMI 25.0 to 29.9 kg/m2) with normal weight (BMI 18.5 to 24.9 kg/m2) as reference. In mediation analysis, we explored whether childhood BMI at age 7 years mediated the associations.ResultsMaternal pre-pregnancy obesity was associated with earlier age at attaining most pubertal milestones in sons, and pre-pregnancy overweight and obesity were associated with earlier age at attaining all pubertal milestones in daughters. When combining all pubertal milestones, pre-pregnancy obesity [sons: -1.5 (-2.5, -0.4) months; daughters: -3.2 (-4.2, -2.1) months] and overweight [daughters only: -2.6 (-3.3, -1.8) months] were associated with earlier timing of puberty. The associations in sons were completely mediated by higher childhood BMI and partly so in daughters.ConclusionsMaternal pre-pregnancy obesity appears to lower timing of puberty through childhood obesity in sons and mainly through other mechanisms in daughters

Risk of selection bias due to non-participation in a cohort study on pubertal timing.

BackgroundNon-participation in aetiologic studies of pubertal timing is frequent. However, little effort has been given to explore the risk and potential impact of selection bias in studies of pubertal timing.ObjectiveWe aimed to explore the risk of selection bias due to non-participation in a newly established puberty cohort.MethodsWe evaluated whether three maternal exposures chosen a priori (pre-pregnancy obesity, smoking, and alcohol drinking during pregnancy) were associated with participation, whether pubertal timing was associated with participation, and whether selection bias influenced the associations between these exposures and pubertal timing. In total, 22 439 children from the Danish National Birth Cohort born 2000-2003 were invited to the Puberty Cohort and 15 819 (70%) participated. Exposures were self-reported during pregnancy. Pubertal timing was measured using a previously validated marker, "the height difference in standard deviations" (HD:SDS), which is the difference between pubertal height and adult height, both in standard deviations. For this study, pubertal height at around 13 years in sons and around 11 years in daughters was obtained from an external database, and adult height was predicted based on parental height reported by mothers.ResultsParticipation was associated with most exposures but not with pubertal timing, measured by HD:SDS. The associations between exposures and HD:SDS were comparable for participants only and all invited for participation.ConclusionIn conclusion, the risk of selection bias in aetiologic studies on pubertal timing in the Puberty Cohort appears minimal

Improving the tokenisation of identifier names

Identifier names are the main vehicle for semantic information during program comprehension. For tool-supported program comprehension tasks, including concept location and requirements traceability, identifier names need to be tokenised into their semantic constituents. In this paper we present an approach to the automated tokenisation of identifier names that improves on existing techniques in two ways. First, it improves the tokenisation accuracy for single-case identifier names and for identifier names containing digits, which existing techniques largely ignore. Second, performance gains over existing techniques are achieved using smaller oracles, making the approach easier to deploy. Accuracy was evaluated by comparing our algorithm to manual tokenizations of 28,000 identifier names drawn from 60 well-known open source Java projects totalling 16.5 MSLOC. Moreover, the projects were used to perform a study of identifier tokenisation features (single case, camel case, use of digits, etc.) per object-oriented construct (class names, method names, local variable names, etc.), thus providing an insight into naming conventions in industrial-scale object-oriented code. Our tokenisation tool and datasets are publicly available

Pregnancy serum concentrations of perfluorinated alkyl substances and offspring behaviour and motor development at age 5-9 years--a prospective study

Background: In animal studies, perfluorinated alkyl substances affect growth and neuro-behavioural outcomes. Human epidemiological studies are sparse. The aim was to investigate the association between pregnancy serum concentrations of perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS) and offspring behaviour and motor development at 5-9 years of age. Methods: Maternal sera from the INUENDO cohort (2002-2004) comprising 1,106 mother-child pairs from Greenland, Kharkiv (Ukraine) and Warsaw (Poland) were analysed for PFOS and PFOA, using liquid-chromatography-tandem-mass-spectrometry. Exposures were grouped into country specific as well as pooled tertiles as well as being used as continuous variables for statistical analyses. Child motor development and behaviour at follow-up (2010-2012) were measured by the Developmental Coordination Disorder Questionnaire 2007 (DCDQ) and Strength and Difficulties Questionnaire (SDQ), respectively. Exposure-outcome associations were analysed by multiple logistic and linear regression analyses. Results: In the pooled analysis, odds ratio (OR) (95% confidence interval (CI)) for hyperactivity was 3.1 (1.3, 7.2) comparing children prenatally exposed to the highest PFOA tertile with those exposed to the lowest PFOA tertile. Comparing children in the highest PFOS tertile with those in the lowest PFOS tertile showed elevated but statistically non-significant OR of hyperactivity (OR (95% CI) 1.7 (0.9, 3.2)). In Greenland, elevated PFOS was associated with higher SDQ-total scores indicating more behavioural problems (beta (95% CI) = 1.0 (0.1, 2.0)) and elevated PFOA was associated with higher hyperactivity sub-scale scores indicating more hyperactive behaviour (beta (95% CI) = 0.5 (0.1, 0.9)). Prenatal PFOS and PFOA exposures were not associated with motor difficulties. Conclusions: Prenatal exposure to PFOS and PFOA may have a small to moderate effect on children's neuro-behavioural development, specifically in terms of hyperactive behaviour. The associations were strongest in Greenland where exposure contrast is largest

A highly magnified candidate for a young galaxy seen when the Universe was 500 Myrs old

The early Universe at redshift z\sim6-11 marks the reionization of the intergalactic medium, following the formation of the first generation of stars. However, those young galaxies at a cosmic age of \lesssim 500 million years (Myr, at z \gtrsim 10) remain largely unexplored as they are at or beyond the sensitivity limits of current large telescopes. Gravitational lensing by galaxy clusters enables the detection of high-redshift galaxies that are fainter than what otherwise could be found in the deepest images of the sky. We report the discovery of an object found in the multi-band observations of the cluster MACS1149+22 that has a high probability of being a gravitationally magnified object from the early universe. The object is firmly detected (12 sigma) in the two reddest bands of HST/WFC3, and not detected below 1.2 {\mu}m, matching the characteristics of z\sim9 objects. We derive a robust photometric redshift of z = 9.6 \pm 0.2, corresponding to a cosmic age of 490 \pm 15Myr (i.e., 3.6% of the age of the Universe). The large number of bands used to derive the redshift estimate make it one of the most accurate estimates ever obtained for such a distant object. The significant magnification by cluster lensing (a factor of \sim15) allows us to analyze the object's ultra-violet and optical luminosity in its rest-frame, thus enabling us to constrain on its stellar mass, star-formation rate and age. If the galaxy is indeed at such a large redshift, then its age is less than 200 Myr (at the 95% confidence level), implying a formation redshift of zf \lesssim 14. The object is the first z>9 candidate that is bright enough for detailed spectroscopic studies with JWST, demonstrating the unique potential of galaxy cluster fields for finding highly magnified, intrinsically faint galaxies at the highest redshifts.Comment: Submitted to the Nature Journal. 39 Pages, 13 figure

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Application of GRADE: Making evidence-based recommendations about diagnostic tests in clinical practice guidelines

<p>Abstract</p> <p>Background</p> <p>Accurate diagnosis is a fundamental aspect of appropriate healthcare. However, clinicians need guidance when implementing diagnostic tests given the number of tests available and resource constraints in healthcare. Practitioners of health often feel compelled to implement recommendations in guidelines, including recommendations about the use of diagnostic tests. However, the understanding about diagnostic tests by guideline panels and the methodology for developing recommendations is far from completely explored. Therefore, we evaluated the factors that guideline developers and users need to consider for the development of implementable recommendations about diagnostic tests.</p> <p>Methods</p> <p>Using a critical analysis of the process, we present the results of a case study using the Grading of Recommendations Applicability, Development and Evaluation (GRADE) approach to develop a clinical practice guideline for the diagnosis of Cow Milk Allergy with the World Allergy Organization.</p> <p>Results</p> <p>To ensure that guideline panels can develop informed recommendations about diagnostic tests, it appears that more emphasis needs to be placed on group processes, including question formulation, defining patient-important outcomes for diagnostic tests, and summarizing evidence. Explicit consideration of concepts of diagnosis from evidence-based medicine, such as pre-test probability and treatment threshold, is required to facilitate the work of a guideline panel and to formulate implementable recommendations.</p> <p>Discussion</p> <p>This case study provides useful guidance for guideline developers and clinicians about what they ought to demand from clinical practice guidelines to facilitate implementation and strengthen confidence in recommendations about diagnostic tests. Applying a structured framework like the GRADE approach with its requirement for transparency in the description of the evidence and factors that influence recommendations facilitates laying out the process and decision factors that are required for the development, interpretation, and implementation of recommendations about diagnostic tests.</p