Evaluation of progress toward universal health coverage in Myanmar: A national and subnational analysis

BackgroundUniversal health coverage (UHC) encompasses 2 main components: access to essential healthcare services and protection from financial hardship when using healthcare. This study examines Myanmar’s efforts to achieve UHC on a national and subnational level. It is a primer of studying the concept of UHC on a subnational level, and it also establishes a baseline for assessing future progress toward reaching UHC in Myanmar.Methods and findingsThe study uses the Demographic and Health Survey (2015) and the Myanmar Living Conditions Survey (MLCS; 2017) and adapts a previously developed UHC index to provide insights into the main barriers preventing the country’s progress toward UHC. We find a negative correlation between the UHC index and the state/region poverty levels. The equity of access analysis reveals significant pro-rich inequity in access to all essential healthcare services. Socioeconomic status and limited availability of healthcare infrastructure are the main driving forces behind the unequal access to interventions that are crucial to achieving UHC by 2030. Finally, financial risk protection analysis shows that the poor are less likely to use healthcare services, and, once they do, they are at a greater risk of suffering financial catastrophe. Limitations of this study revolve around its correlational, rather than causal, nature.ConclusionsWe suggest a 2-pronged approach to help Myanmar achieve UHC: Government and state authorities should reduce the financial burden of seeking healthcare, and, coupled with this, significant investment in and expansion of health infrastructure and the health workforce should be made, particularly in the poorer and more remote states.

Zlatko Nikoloski and colleagues provide analytical insight into Myanmar’s efforts to achieve universal health coverage on a national and sub-national level.     

Comparative genomic analysis of T-box regulatory systems in bacteria

T-box antitermination is one of the main mechanisms of regulation of genes involved in amino acid metabolism in Gram-positive bacteria. T-box regulatory sites consist of conserved sequence and RNA secondary structure elements. Using a set of known T-box sites, we constructed the common pattern and used it to scan available bacterial genomes. New T-boxes were found in various Gram-positive bacteria, some Gram-negative bacteria (delta-proteobacteria), and some other bacterial groups (Deinococcales/Thermales, Chloroflexi, Dictyoglomi). The majority of T-box-regulated genes encode aminoacyl-tRNA synthetases. Two other groups of T-box-regulated genes are amino acid biosynthetic genes and transporters, as well as genes with unknown function. Analysis of candidate T-box sites resulted in new functional annotations. We assigned the amino acid specificity to a large number of candidate amino acid transporters and a possible function to amino acid biosynthesis genes. We then studied the evolution of the T-boxes. Analysis of the constructed phylogenetic trees demonstrated that in addition to the normal evolution consistent with the evolution of regulated genes, T-boxes may be duplicated, transferred to other genes, and change specificity. We observed several cases of recent T-box regulon expansion following the loss of a previously existing regulatory system, in particular, arginine regulon in Clostridium difficile and methionine regulon in Lactobacillaceae. Finally, we described a new structural class of T-boxes containing duplicated terminator-antiterminator elements and unusual reduced T-boxes regulating initiation of translation in the Actinobacteria.     

Towards a systems level analysis of health and nutrition

Although theoretical systems analysis has been available for over half a century, the recent advent of omic high-throughput analytical platforms along with the integration of individual tools and technologies has given rise to the field of modern systems biology. Coupled with information technology, bioinformatics, knowledge management and powerful mathematical models, systems biology has opened up new vistas in our understanding of complex biological systems. Currently there are two distinct approaches that include the inductively driven computational systems biology (bottom-up approach) and the deductive data-driven top-down analysis. Such approaches offer enormous potential in the elucidation of disease as well as defining key pathways and networks involved in optimal human health and nutrition. The tools and technologies now available in systems biology analyses offer exciting opportunities to develop the emerging areas of personalized medicine and individual nutritional profiling.     

Comparative analysis of inducible expression systems in transient transfection studies

Ectopic protein expression in mammalian cells is a valuable tool to analyze protein functions. Increasingly, inducible promoters are being used for regulated gene expression. Here, we compare expression maxima, induction rates, and "leakiness" of the following promoter systems: (I) two tetracycline-responsive Tet systems (Tet-On, Tet-Off), (II) the glucocorticoid-responsive mouse mammary tumor virus promoter (MMTVprom), (III) the ecdysone-inducible promoter (EcP), and (IV) the T7 promoter/T7 RNA polymerase system (T7P). The systems were analyzed by expressing an enhanced green fluorescent protein (EGFP) luciferase fusion reporter protein in transiently transfected cells. Expression was assessed qualitatively by fluorescence microscopy of the EGFP component and quantitatively by measuring the enzymatic activity of the luciferase component of the fusion protein. Basal expression levels ("leakiness") were ranked Tet-On>Tet-Off>MMTVprom>EcP>T7P. Induction rates were EcP>MMTVprom>T7P>Tet-Off>Tet-On. Expression maxima were ranked. Tet-On>Tet-Off>MMTVprom>EcP>T7P. To increase T7-promoter-mediated expression we inserted an internal ribosomal entry site element into the T7 expression cassette. In presence of T7 RNA polymerase this modified T7 promoter achieved expression levels of 42% of a Rous Sarcoma virus promoter, while keeping basal expression extremely low.     

Comparative model analysis of central shunts in vertebrate cardiovascular systems

The incomplete double circulation of air-breathing fishes and lungfishes, amphibians, reptiles and embryonic birds and mammals has been analyzed using a simplified mode comprising the intra- and extracardiac shunts and compartments for the gas exchange (gills, lungs, skin, etc.) as well as systemic tissue gas exchange. The intracardiac shunting is defined and given common symbols for all species of animals analyzed. Two types of equations, fluid-flow and mass-flow equations, are derived for each model, which are solved to give shunting rate as a function of blood O2 content of the principal cardiac compartments and vessels. The model analysis not only offers possibility for an overall average evaluation of central shunts, but also suggests which blood samples must be determined for evaluation of the shunt patterns.     

Comparative genetic analysis: the utility of mouse genetic systems for studying human monogenic disease

One of the long-term goals of mutagenesis programs in the mouse has been to generate mutant lines to facilitate the functional study of every mammalian gene. With a combination of complementary genetic approaches and advances in technology, this aim is slowly becoming a reality. One of the most important features of this strategy is the ability to identify and compare a number of mutations in the same gene, an allelic series. With the advent of gene-driven screening of mutant archives, the search for a specific series of interest is now a practical option. This review focuses on the analysis of multiple mutations from chemical mutagenesis projects in a wide variety of genes and the valuable functional information that has been obtained from these studies. Although gene knockouts and transgenics will continue to be an important resource to ascertain gene function, with a significant proportion of human diseases caused by point mutations, identifying an allelic series is becoming an equally efficient route to generating clinically relevant and functionally important mouse models.