Background: The aim of this study is to present the first United Arab Emirates pulmonary hypertension registry of patients’ clinical characteristics, hemodynamic parameters and treatment outcomes. Method: This is a retrospective study describing all the adult patients who underwent a right heart catheterization for evaluation of pulmonary hypertension (PH) between January 2015 and December 2021 in a tertiary referral center in Abu Dhabi, United Arab Emirates. Results: A total of 164 consecutive patients were diagnosed with PH during the five years of the study. Eighty-three patients (50.6%) were World Symposium PH Group 1-PH; nineteen patients (11.6%) were Group 2-PH due to left heart disease; twenty-three patients (14.0%) were Group 3-PH due to chronic lung disease; thirty-four patients (20.7%) were Group 4-PH due to chronic thromboembolic lung disease, and five patients (3.0%) were Group 5-PH. Among Group 1-PH, twenty-five (30%) had idiopathic, twenty-seven (33%) had connective tissue disease, twenty-six (31%) had congenital heart disease, and five patients (6%) had porto-pulmonary hypertension. The median follow-up was 55.6 months. Most of the patients were started on dual then sequentially escalated to triple combination therapy. The 1-, 3- and 5-year cumulative probabilities of survival for Group 1-PH were 86% (95% CI, 75–92%), 69% (95% CI, 54–80%) and 69% (95% CI, 54–80%). Conclusions: This is the first registry of Group 1-PH from a single tertiary referral center in the UAE. Our cohort was younger with a higher percentage of patients with congenital heart disease compared to cohorts from Western countries but similar to registries from other Asian countries. Mortality is comparable to other major registries. Adopting the new guideline recommendations and improving the availability and adherence to medications are likely to play a significant role in improving outcomes in the future.
Genomic sequencing is the first step in a systems level study of an algal species, and sequencing studies have grown steadily in recent years. Completed sequences can be tied to algal phenotypes at a systems level through constructing genome-scale metabolic network models. Those models allow the prediction of algal phenotypes and genetic or metabolic modifications, and are constructed by tying the genes to reactions using enzyme databases, then representing those reactions in a concise mathematical form by means of stoichiometric matrices. This is followed by experimental validation using gene deletion or proteomics and metabolomics studies that may result in adding reactions to the model and filling phenotypic gaps. In this chapter, we offer a summary of completed and ongoing algal genomic projects before proceeding to holistically describing the process of constructing genome-scale metabolic models. Relevant examples of algal metabolic models are presented and discussed. The analysis of an alga's emergent properties from metabolic models is also demonstrated using flux balance analysis (FBA) and related constraint-based approaches to optimize a given metabolic phenotype, or sets of phenotypes such as algal biomass. We also summarize readily available optimization tools rooted in constraint-based modeling that allow for optimizing bioproduction and algal strains. Examples include tools used to develop knockout strategies, identify optimal bioproduction strains, analyze gene deletions, and Joseph Koussa and Bushra Saeed Dohai contributed equally to this work.
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