On the Use of Bootstrapped Topologies in Coalescent-Based Bayesian MCMC Inference: A Comparison of Estimation and Computational Efficiencies

Coalescent-based Bayesian Markov chain Monte Carlo (MCMC) inference generates estimates of evolutionary parameters and their posterior probability distributions. As the number of sequences increases, the length of time taken to complete an MCMC analysis increases as well. Here, we investigate an approach to distribute the MCMC analysis across a cluster of computers. To do this, we use bootstrapped topologies as fixed genealogies, perform a single MCMC analysis on each genealogy without topological rearrangements, and pool the results across all MCMC analyses. We show, through simulations, that although the standard MCMC performs better than the bootstrap-MCMC at estimating the effective population size (scaled by mutation rate), the bootstrap-MCMC returns better estimates of growth rates. Additionally, we find that our bootstrap-MCMC analyses are, on average, 37 times faster for equivalent effective sample sizes

Effect of treatment of clinical seizures vs electrographic seizures in full-term and near-term neonates : a randomized clinical trial

Importance: Seizures in the neonatal period are associated with increased mortality and morbidity. Bedside amplitude-integrated electroencephalography (aEEG) has facilitated the detection of electrographic seizures; however, whether these seizures should be treated remains uncertain. Objective: To determine if the active management of electrographic and clinical seizures in encephalopathic term or near-term neonates improves survival free of severe disability at 2 years of age compared with only treating clinically detected seizures. Design, Setting, and Participants: This randomized clinical trial was conducted in tertiary newborn intensive care units recruited from 2012 to 2016 and followed up until 2 years of age. Participants included neonates with encephalopathy at 35 weeks’ gestation or more and younger than 48 hours old. Data analysis was completed in April 2021. Interventions: Randomization was to an electrographic seizure group (ESG) in which seizures detected on aEEG were treated in addition to clinical seizures or a clinical seizure group (CSG) in which only seizures detected clinically were treated. Main Outcomes and Measures: Primary outcome was death or severe disability at 2 years, defined as scores in any developmental domain more than 2 SD below the Australian mean assessed with Bayley Scales of Neonate and Toddler Development, 3rd ed (BSID-III), or the presence of cerebral palsy, blindness, or deafness. Secondary outcomes included magnetic resonance imaging brain injury score at 5 to 14 days, time to full suck feeds, and individual domain scores on BSID-III at 2 years. Results: Of 212 randomized neonates, the mean (SD) gestational age was 39.2 (1.7) weeks and 122 (58%) were male; 152 (72%) had moderate to severe hypoxic-ischemic encephalopathy (HIE) and 147 (84%) had electrographic seizures. A total of 86 neonates were included in the ESG group and 86 were included in the CSG group. Ten of 86 (9%) neonates in the ESG and 4 of 86 (4%) in the CSG died before the 2-year assessment. The odds of the primary outcome were not significantly different in the ESG group compared with the CSG group (ESG, 38 of 86 [44%] vs CSG, 27 of 86 [31%]; odds ratio [OR], 1.83; 95% CI, 0.96 to 3.49; P = .14). There was also no significant difference in those with HIE (OR, 1.77; 95% CI, 0.84 to 3.73; P = .26). There was evidence that cognitive outcomes were worse in the ESG (mean [SD] scores, ESG: 97.4 [17.7] vs CSG: 103.8 [17.3]; mean difference, −6.5 [95% CI, −1.2 to −11.8]; P = .01). There was little evidence of a difference in secondary outcomes, including time to suck feeds, seizure burden, or brain injury score. Conclusions and Relevance: Treating electrographic and clinical seizures with currently used anticonvulsants did not significantly reduce the rate of death or disability at 2 years in a heterogeneous group of neonates with seizures

On the Use of Bootstrapped Topologies in Coalescent-Based Bayesian MCMC Inference: A Comparison of Estimation and Computational Efficiencies

Coalescent-based Bayesian Markov chain Monte Carlo (MCMC) inference generates estimates of evolutionary parameters and their posterior probability distributions. As the number of sequences increases, the length of time taken to complete an MCMC analysis increases as well. Here, we investigate an approach to distribute the MCMC analysis across a cluster of computers. To do this, we use bootstrapped topologies as fixed genealogies, perform a single MCMC analysis on each genealogy without topological rearrangements, and pool the results across all MCMC analyses. We show, through simulations, that although the standard MCMC performs better than the bootstrap-MCMC at estimating the effective population size (scaled by mutation rate), the bootstrap-MCMC returns better estimates of growth rates. Additionally, we find that our bootstrap-MCMC analyses are, on average, 37 times faster for equivalent effective sample sizes

The perils of plenty: what are we going to do with all these genes?

This new century's biology promises more of everything—more genes, more organisms, more species and, in short, more data. The flood of data challenges us to find better and quicker ways to summarize and analyse. Here, we present preliminary results and proofs of concept from three of our research projects that are motivated by our search for solutions to the perils of plenty. First, we discuss how models of evolution can accommodate change to better reflect the dynamics of sequence diversity, particularly when it is becoming a lot easier to obtain sequences at different times and across intervals where the probability of new mutations contributing to this diversity is high. Second, we describe our work on the use of a single locus for species delimitation; this research targets the new DNA-barcoding approach that aims to catalogue the entirety of life. We have developed a single-locus test based on the coalescent that tests the null hypothesis of panmixis. Finally, we discuss new sequencing technologies, the types of data available and the efficacy of alignment-free methods to estimate pairwise distances for phylogenetic analyses

High intensity interval training in a real world setting: a randomized controlled feasibility study in overweight inactive adults, measuring change in maximal oxygen uptake.

BACKGROUND: In research clinic settings, overweight adults undertaking HIIT (high intensity interval training) improve their fitness as effectively as those undertaking conventional walking programs but can do so within a shorter time spent exercising. We undertook a randomized controlled feasibility (pilot) study aimed at extending HIIT into a real world setting by recruiting overweight/obese, inactive adults into a group based activity program, held in a community park. METHODS: Participants were allocated into one of three groups. The two interventions, aerobic interval training and maximal volitional interval training, were compared with an active control group undertaking walking based exercise. Supervised group sessions (36 per intervention) were held outdoors. Cardiorespiratory fitness was measured using VO2max (maximal oxygen uptake, results expressed in ml/min/kg), before and after the 12 week interventions. RESULTS: On ITT (intention to treat) analyses, baseline (N = 49) and exit (N = 39) [Formula: see text]O2 was 25.3±4.5 and 25.3±3.9, respectively. Participant allocation and baseline/exit VO2max by group was as follows: Aerobic interval training N =  16, 24.2±4.8/25.6±4.8; maximal volitional interval training N = 16, 25.0±2.8/25.2±3.4; walking N = 17, 26.5±5.3/25.2±3.6. The post intervention change in VO2max was +1.01 in the aerobic interval training, -0.06 in the maximal volitional interval training and -1.03 in the walking subgroups. The aerobic interval training subgroup increased VO2max compared to walking (p = 0.03). The actual (observed, rather than prescribed) time spent exercising (minutes per week, ITT analysis) was 74 for aerobic interval training, 45 for maximal volitional interval training and 116 for walking (p =  0.001). On descriptive analysis, the walking subgroup had the fewest adverse events. CONCLUSIONS: In contrast to earlier studies, the improvement in cardiorespiratory fitness in a cohort of overweight/obese participants undertaking aerobic interval training in a real world setting was modest. The most likely reason for this finding relates to reduced adherence to the exercise program, when moving beyond the research clinic setting. TRIAL REGISTRATION: ACTR.org.au ACTRN12610000295044

Schematic representation of the three exercise prescriptions allocated 1:1∶1 at randomisation.

<p>^§ Number of repetitions in MVIT group increased over twelve weeks, as participant's fitness levels improved. WALK  =  walking, AIT  =  aerobic interval training, MVIT  =  maximal volitional intensity training.</p

Baseline characteristics for the entire cohort and the subgroup completing the exercise protocol.

<p>^a WALK  =  Low intensity walking, AIT  =  Aerobic interval training, MVIT  =  Maximal volitional intensity training.</p><p>^b ITT (intention to treat) includes all 49 randomized participants, PP (per protocol) includes the 32 participants who completed >70% of their exercise prescription (see text for more detail).</p><p>^c A positive response indicates possible health problems, with the recommendation that a medical screen is undertaken prior to increased physical activity.</p

Changes (post minus pre) in primary and secondary outcome measures and comparison between low intensity exercise and high intensity interval and maximal volitional intensity training.

<p>Values are means (SD).</p><p>^a WALK  =  low intensity walking, AIT  =  aerobic interval training, MVIT  =  maximal volitional intensity training.</p><p>^b Per protocol population WALK n = 14, AIT n = 9, MVIT n = 9.</p><p>^c Intention to treat population WALK n = 17, AIT n = 16, MVIT n = 16.</p