Optimal protamine dosing after cardiopulmonary bypass: The PRODOSE adaptive randomised controlled trial.

BackgroundThe dose of protamine required following cardiopulmonary bypass (CPB) is often determined by the dose of heparin required pre-CPB, expressed as a fixed ratio. Dosing based on mathematical models of heparin clearance is postulated to improve protamine dosing precision and coagulation. We hypothesised that protamine dosing based on a 2-compartment model would improve thromboelastography (TEG) parameters and reduce the dose of protamine administered, relative to a fixed ratio.Methods and findingsWe undertook a 2-stage, adaptive randomised controlled trial, allocating 228 participants to receive protamine dosed according to a mathematical model of heparin clearance or a fixed ratio of 1 mg of protamine for every 100 IU of heparin required to establish anticoagulation pre-CPB. A planned, blinded interim analysis was undertaken after the recruitment of 50% of the study cohort. Following this, the randomisation ratio was adapted from 1:1 to 1:1.33 to increase recruitment to the superior arm while maintaining study power. At the conclusion of trial recruitment, we had randomised 121 patients to the intervention arm and 107 patients to the control arm. The primary endpoint was kaolin TEG r-time measured 3 minutes after protamine administration at the end of CPB. Secondary endpoints included ratio of kaolin TEG r-time pre-CPB to the same metric following protamine administration, requirement for allogeneic red cell transfusion, intercostal catheter drainage at 4 hours postoperatively, and the requirement for reoperation due to bleeding. The trial was listed on a clinical trial registry (ClinicalTrials.gov Identifier: NCT03532594). Participants were recruited between April 2018 and August 2019. Those in the intervention/model group had a shorter mean kaolin r-time (6.58 [SD 2.50] vs. 8.08 [SD 3.98] minutes; p = 0.0016) post-CPB. The post-protamine thromboelastogram of the model group was closer to pre-CPB parameters (median pre-CPB to post-protamine kaolin r-time ratio 0.96 [IQR 0.78-1.14] vs. 0.75 [IQR 0.57-0.99]; p 120 kg, and patients requiring therapeutic hypothermia to ConclusionsUsing a mathematical model to guide protamine dosing in patients following CPB improved TEG r-time and reduced the dose administered relative to a fixed ratio. No differences were detected in postoperative mediastinal/pleural drainage or red blood cell transfusion requirement in our cohort of low-risk patients.Trial registrationClinicalTrials.gov Unique identifier NCT03532594

Bottom Reflectance in Ocean Color Satellite Remote Sensing for Coral Reef Environments

Most ocean color algorithms are designed for optically deep waters, where the seafloor has little or no effect on remote sensing reflectance. This can lead to inaccurate retrievals of inherent optical properties (IOPs) in optically shallow water environments. Here, we investigate in situ hyperspectral bottom reflectance signatures and their separability for coral reef waters, when observed at the spectral resolutions of MODIS and SeaWiFS sensors. We use radiative transfer modeling to calculate the effects of bottom reflectance on the remote sensing reflectance signal, and assess detectability and discrimination of common coral reef bottom classes by clustering modeled remote sensing reflectance signals. We assess 8280 scenarios, including four IOPs, 23 depths and 45 bottom classes at MODIS and SeaWiFS bands. Our results show: (i) no significant contamination (Rrscorr 17 m for MODIS and >19 m for SeaWiFS for the brightest spectral reflectance substrate (light sand) in clear reef waters; and (ii) bottom cover classes can be combined into two distinct groups, “light” and “dark”, based on the modeled surface reflectance signals. This study establishes that it is possible to efficiently improve parameterization of bottom reflectance and water-column IOP retrievals in shallow water ocean color models for coral reef environments

Blocking endothelial apoptosis revascularises the retina in a model of ischemic retinopathy

Aberrant, neovascular retinal blood vessel growth is a vision-threatening complication in ischemic retinal diseases. It is driven by retinal hypoxia frequently caused by capillary nonperfusion and endothelial cell (EC) loss. We investigated the role of EC apoptosis in this process using a mouse model of ischemic retinopathy, in which vessel closure and EC apoptosis cause capillary regression and retinal ischemia followed by neovascularization. Protecting ECs from apoptosis in this model did not prevent capillary closure or retinal ischemia. Nonetheless, it prevented the clearance of ECs from closed capillaries, delaying vessel regression and allowing ECs to persist in clusters throughout the ischemic zone. In response to hypoxia, these preserved ECs underwent a vessel sprouting response and rapidly reassembled into a functional vascular network. This alleviated retinal hypoxia, preventing subsequent pathogenic neovascularization. Vessel reassembly was not limited by VEGFA neutralization, suggesting it was not dependent on the excess VEGFA produced by the ischemic retina. Neutralization of ANG2 did not prevent vessel reassembly, but did impair subsequent angiogenic expansion of the reassembled vessels. Blockade of EC apoptosis may promote ischemic tissue revascularization by preserving ECs within ischemic tissue that retain the capacity to reassemble a functional network and rapidly restore blood supply

Transcriptome dynamics of CD4⁺ T cells during malaria maps gradual transit from effector to memory

The dynamics of CD4⁺ T cell memory development remain to be examined at genome scale. In malaria-endemic regions, antimalarial chemoprevention protects long after its cessation and associates with effects on CD4⁺ T cells. We applied single-cell RNA sequencing and computational modelling to track memory development during Plasmodium infection and treatment. In the absence of central memory precursors, two trajectories developed as T helper 1 (T_H1) and follicular helper T (T_(FH)) transcriptomes contracted and partially coalesced over three weeks. Progeny of single clones populated T_H1 and T_(FH) trajectories, and fate-mapping suggested that there was minimal lineage plasticity. Relationships between T_(FH) and central memory were revealed, with antimalarials modulating these responses and boosting T_H1 recall. Finally, single-cell epigenomics confirmed that heterogeneity among effectors was partially reset in memory. Thus, the effector-to-memory transition in CD4⁺ T cells is gradual during malaria and is modulated by antiparasitic drugs. Graphical user interfaces are presented for examining gene-expression dynamics and gene–gene correlations (http://haquelab.mdhs.unimelb.edu.au/cd4_memory/)

Transcriptome dynamics of CD4⁺ T cells during malaria maps gradual transit from effector to memory

The dynamics of CD4⁺ T cell memory development remain to be examined at genome scale. In malaria-endemic regions, antimalarial chemoprevention protects long after its cessation and associates with effects on CD4⁺ T cells. We applied single-cell RNA sequencing and computational modelling to track memory development during Plasmodium infection and treatment. In the absence of central memory precursors, two trajectories developed as T helper 1 (T_H1) and follicular helper T (T_(FH)) transcriptomes contracted and partially coalesced over three weeks. Progeny of single clones populated T_H1 and T_(FH) trajectories, and fate-mapping suggested that there was minimal lineage plasticity. Relationships between T_(FH) and central memory were revealed, with antimalarials modulating these responses and boosting T_H1 recall. Finally, single-cell epigenomics confirmed that heterogeneity among effectors was partially reset in memory. Thus, the effector-to-memory transition in CD4⁺ T cells is gradual during malaria and is modulated by antiparasitic drugs. Graphical user interfaces are presented for examining gene-expression dynamics and gene–gene correlations (http://haquelab.mdhs.unimelb.edu.au/cd4_memory/)

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

Prevalence and architecture of de novo mutations in developmental disorders.

The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Large-scale discovery of novel genetic causes of developmental disorders

Despite three decades of successful, predominantly phenotype-driven discovery of the genetic causes of monogenic disorders1, up to half of children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis. Particularly challenging are those disorders rare enough to have eluded recognition as a discrete clinical entity, those with highly variable clinical manifestations, and those that are difficult to distinguish from other, very similar, disorders. Here we demonstrate the power of using an unbiased genotype-driven approach2 to identify subsets of patients with similar disorders. By studying 1,133 children with severe, undiagnosed developmental disorders, and their parents, using a combination of exome sequencing3,4,5,6,7,8,9,10,11 and array-based detection of chromosomal rearrangements, we discovered 12 novel genes associated with developmental disorders. These newly implicated genes increase by 10% (from 28% to 31%) the proportion of children that could be diagnosed. Clustering of missense mutations in six of these newly implicated genes suggests that normal development is being perturbed by an activating or dominant-negative mechanism. Our findings demonstrate the value of adopting a comprehensive strategy, both genome-wide and nationwide, to elucidate the underlying causes of rare genetic disorders

Prevalence, phenotype and architecture of developmental disorders caused by de novo mutation: The Deciphering Developmental Disorders Study

Individuals with severe, undiagnosed developmental disorders (DDs) are enriched for damaging de novo mutations (DNMs) in developmentally important genes. We exome sequenced 4,293 families with individuals with DDs, and meta-analysed these data with published data on 3,287 individuals with similar disorders. We show that the most significant factors influencing the diagnostic yield of de novo mutations are the sex of the affected individual, the relatedness of their parents and the age of both father and mother. We identified 94 genes enriched for damaging de novo mutation at genome-wide significance (P < 7 × 10−7), including 14 genes for which compelling data for causation was previously lacking. We have characterised the phenotypic diversity among these genetic disorders. We demonstrate that, at current cost differentials, exome sequencing has much greater power than genome sequencing for novel gene discovery in genetically heterogeneous disorders. We estimate that 42% of our cohort carry pathogenic DNMs (single nucleotide variants and indels) in coding sequences, with approximately half operating by a loss-of-function mechanism, and the remainder resulting in altered-function (e.g. activating, dominant negative). We established that most haplo insufficient developmental disorders have already been identified, but that many altered-function disorders remain to be discovered. Extrapolating from the DDD cohort to the general population, we estimate that developmental disorders caused by DNMs have an average birth prevalence of 1 in 213 to 1 in 448 (0.22-0.47% of live births), depending on parental age