Secular Trends on Birth Parameters, Growth, and Pubertal Timing in Girls with Turner Syndrome.

BACKGROUND: Whether children with chromosomal disorders of growth and puberty are affected by secular trends (STs) as observed in the general population remains unanswered, but this question has relevance for expectations of spontaneous development and treatment responses. OBJECTIVES: The aim of the study was to evaluate STs in birth parameters, growth, and pubertal development in girls with Turner syndrome (TS). STUDY DESIGN: Retrospective analysis of KIGS data (Pfizer International Growth Database). We included all TS patients who entered KIGS between 1987 and 2012 and were born from 1975 to 2004, who were prepubertal and growth treatment naïve at first entry (total number: 7,219). Pretreatment height and ages at the start of treatment were compared across 5-year birth year groups, with subgroup analyses stratified by induced or spontaneous puberty start. RESULTS: We observed significant STs across the birth year groups for birth weight [+0.18 SD score (SDS), p < 0.001], pretreatment height at mean age 8 years (+0.73 SDS, p < 0.001), height at the start of growth hormone (GH) therapy (+0.38 SDS, p < 0.001) and start of puberty (+0.42 SDS, p < 0.001). Spontaneous puberty onset increased from 15 to 30% (p < 0.001). Mean age at the start of GH treatment decreased from 10.8 to 7.4 years (-3.4 years; p < 0.001), and substantial declines were seen in ages at onset of spontaneous and induced puberty (-2.0 years; p < 0.001) and menarche (-2.1 years; p < 0.001). CONCLUSION: Environmental changes leading to increased height and earlier and also more common, spontaneous puberty are applicable in TS as in normal girls. In addition, greater awareness for TS may underlie trends to earlier start of GH therapy and induction of puberty at a more physiological age

Spanning tree approximations for conditional random fields

Abstract In this work we show that one can train Conditional Random Fields of intractable graphs effectively and efficiently by considering a mixture of random spanning trees of the underlying graphical model. Furthermore, we show how a maximum-likelihood estimator of such a training objective can subsequently be used for prediction on the full graph. We present experimental results which improve on the state-of-the-art. Additionally, the training objective is less sensitive to the regularization than pseudo-likelihood based training approaches. We perform the experimental validation on two classes of data sets where structure is important: image denoising and multilabel classification

Near-optimal experimental design for model selection in systems biology

Motivation: Biological systems are understood through iterations of modeling and experimentation. Not all experiments, however, are equally valuable for predictive modeling. This study introduces an efficient method for experimental design aimed at selecting dynamical models from data. Motivated by biological applications, the method enables the design of crucial experiments: it determines a highly informative selection of measurement readouts and time points. Results: We demonstrate formal guarantees of design efficiency on the basis of previous results. By reducing our task to the setting of graphical models, we prove that the method finds a near-optimal design selection with a polynomial number of evaluations. Moreover, the method exhibits the best polynomial-complexity constant approximation factor, unless P = NP. We measure the performance of the method in comparison with established alternatives, such as ensemble non-centrality, on example models of different complexity. Efficient design accelerates the loop between modeling and experimentation: it enables the inference of complex mechanisms, such as those controlling central metabolic operation. Availability: Toolbox ‘NearOED' available with source code under GPL on the Machine Learning Open Source Software Web site (mloss.org). Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

A Cross-Sectional Study of People with Epilepsy and Neurocysticercosis in Tanzania: Clinical Characteristics and Diagnostic Approaches.

Neurocysticercosis (NCC) is a major cause of epilepsy in regions where pigs are free-ranging and hygiene is poor. Pork production is expected to increase in the next decade in sub-Saharan Africa, hence NCC will likely become more prevalent. In this study, people with epilepsy (PWE, n=212) were followed up 28.6 months after diagnosis of epilepsy. CT scans were performed, and serum and cerebrospinal fluid (CSF) of selected PWE were analysed. We compared the demographic data, clinical characteristics, and associated risk factors of PWE with and without NCC. PWE with NCC (n=35) were more likely to be older at first seizure (24.3 vs. 16.3 years, p=0.097), consumed more pork (97.1% vs. 73.6%, p=0.001), and were more often a member of the Iraqw tribe (94.3% vs. 67.8%, p=0.005) than PWE without NCC (n=177). PWE and NCC who were compliant with anti-epileptic medications had a significantly higher reduction of seizures (98.6% vs. 89.2%, p=0.046). Other characteristics such as gender, seizure frequency, compliance, past medical history, close contact with pigs, use of latrines and family history of seizures did not differ significantly between the two groups. The number of NCC lesions and active NCC lesions were significantly associated with a positive antibody result. The electroimmunotransfer blot, developed by the Centers for Disease Control and Prevention, was more sensitive than a commercial western blot, especially in PWE and cerebral calcifications. This is the first study to systematically compare the clinical characteristics of PWE due to NCC or other causes and to explore the utility of two different antibody tests for diagnosis of NCC in sub-Saharan Africa

Cardiovascular Risk Reduction After Renal Denervation According to Time in Therapeutic Systolic Blood Pressure Range

Background: Renal denervation (RDN) has been shown to lower blood pressure (BP), but its effects on cardiovascular events have only been preliminarily evaluated. Time in therapeutic range (TTR) of BP is associated with cardiovascular events. Objectives: This study sought to assess the impact of catheter-based RDN on TTR and its association with cardiovascular outcomes in the GSR (Global SYMPLICITY Registry). Methods: Patients with uncontrolled hypertension were enrolled and treated with radiofrequency RDN. Office and ambulatory systolic blood pressure (OSBP and ASBP) were measured at 3, 6, 12, 24, and 36 months postprocedure and used to derive TTR. TTR through 6 months was assessed as a predictor of cardiovascular events from 6 to 36 months using a Cox proportional hazard regression model. Results: As of March 1, 2022, 3,077 patients were enrolled: 42.2% were female; mean age was 60.5 ± 12.2 years; baseline OSBP was 165.6 ± 24.8 mm Hg; and baseline ASBP was 154.3 ± 18.7 mm Hg. Patients were prescribed 4.9 ± 1.7 antihypertensive medications at baseline and 4.8 ± 1.9 at 36 months. At 36 months, mean changes were −16.7 ± 28.4 and −9.0 ± 20.2 mm Hg for OSBP and ASBP, respectively. TTR through 6 months was 30.6%. A 10% increase in TTR after RDN through 6 months was associated with significant risk reductions from 6 to 36 months of 15% for major adverse cardiovascular events (P < 0.001), 11% cardiovascular death (P = 0.010), 15% myocardial infarction (P = 0.023), and 23% stroke (P < 0.001). Conclusions: There were sustained BP reductions and higher TTR through 36 months after RDN. A 10% increase in TTR through 6 months was associated with significant risk reductions in major cardiovascular events from 6 to 36 months. (Global SYMPLICITY Registry [GSR] DEFINE; NCT01534299

Multiwavelength Observations of LS I +61 303 with VERITAS, Swift and RXTE

We present results from a long-term monitoring campaign on the TeV binary LSI +61 303 with VERITAS at energies above 500 GeV, and in the 2-10 keV hard X-ray bands with RXTE and Swift, sampling nine 26.5 day orbital cycles between September 2006 and February 2008. The binary was observed by VERITAS to be variable, with all integrated observations resulting in a detection at the 8.8 sigma (2006/2007) and 7.3 sigma (2007/2008) significance level for emission above 500 GeV. The source was detected during active periods with flux values ranging from 5 to 20% of the Crab Nebula, varying over the course of a single orbital cycle. Additionally, the observations conducted in the 2007-2008 observing season show marginal evidence (at the 3.6 sigma significance level) for TeV emission outside of the apastron passage of the compact object around the Be star. Contemporaneous hard X-ray observations with RXTE and Swift show large variability with flux values typically varying between 0.5 and 3.0*10^-11 ergs cm^-2 s^-1 over a single orbital cycle. The contemporaneous X-ray and TeV data are examined and it is shown that the TeV sampling is not dense enough to detect a correlation between the two bands.Comment: 30 pages, 5 figures, 2 table, Accepted for publication in The Astrophysical Journa

Generative Embedding for Model-Based Classification of fMRI Data

Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in ‘hidden’ physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups

New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism.

Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood. Previous genome-wide association studies of birth weight identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes and a second variant, near CCNL1, with no obvious link to adult traits. In an expanded genome-wide association meta-analysis and follow-up study of birth weight (of up to 69,308 individuals of European descent from 43 studies), we have now extended the number of loci associated at genome-wide significance to 7, accounting for a similar proportion of variance as maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes, ADRB1 with adult blood pressure and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism

Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits

The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located nearNEDD4LandSLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (R(g)ranging from 0.11 to 0.76, P-values Author summary Although twin studies have shown that body mass index (BMI) is highly heritable, many common genetic variants involved in the development of BMI have not yet been identified, especially in children. We studied associations of more than 40 million genetic variants with childhood BMI in 61,111 children aged between 2 and 10 years. We identified 25 genetic variants that were associated with childhood BMI. Two of these have not been implicated for BMI previously, located close to the genesNEDD4LandSLC45A3. We also show that the genetic background of childhood BMI overlaps with that of birth weight, adult BMI, waist-to-hip-ratio, diastolic blood pressure, type 2 diabetes, and age at menarche. Our results suggest that the biological processes underlying childhood BMI largely overlap with those underlying adult BMI. However, the overlap is not complete. Additionally, the genetic backgrounds of childhood BMI and other cardio-metabolic phenotypes are overlapping. This may mean that the associations of childhood BMI and later cardio-metabolic outcomes are partially explained by shared genetics, but it could also be explained by the strong association of childhood BMI with adult BMI.Peer reviewe