How to work with intangible software in public health systems: some experiences from India.

This commentary focuses on "intangible software", defined as the range of ideas, norms, values and issues of power or trust that affect the performance of health systems. While the need to work with intangible software within health systems is increasingly being recognized, the practical hows of doing so have been given less attention. In this commentary, we, a team of researchers and implementers from India, have tried to deliberate on these hows through a practice lens. We engage with four questions of current relevance to intangible software in the field of health policy and systems research (HPSR): (1) Is it possible to rewire intangible software in health systems? (2) What approaches have been attempted in the Indian public health system to rewire intangibles? (3) Have such approaches been evaluated? (4) What practical lessons can we offer from our experience on rewiring intangibles? From our perspective, approaches to rewiring intangible software recognize that people in health systems are capable of visioning, thinking, adapting to and leading change. These approaches attempt to challenge the often-unchallenged power hierarchies in health systems by allowing people to engage deeply with widely accepted norms and routinized actions. In this commentary, we have reported on such approaches from India under six categories: approaches intended to enable visioning and leading; approaches targeted at engaging with evidence better; approaches intended to help health workers navigate contextual complexities; approaches intended to build the cultural competence; approaches that recognize and reward performance; and approaches targeted at enabling collaborative work and breaking power hierarchies. Our collective experiences suggest that intangible software interventions work best when they are codesigned with various stakeholders, are contextually adapted in an iterative manner and are implemented in conjunction with structural improvements. Also, such interventions require long-term investments. Based on our experiences, we highlight the need for the following: (1) fostering more dialogue on this category of interventions among all stakeholders for cross-learning; (2) evaluating and publishing evidence on such interventions in nonconventional ways, with a focus on participatory learning; and (3) building ecosystems that allow experiential learnings on such interventions to be shared.

Circulating fetal cell-free DNA fractions differ in autosomal aneuploidies and monosomy X.

BACKGROUND: Noninvasive prenatal testing based on massively parallel sequencing (MPS) of cell-free DNA in maternal plasma has become rapidly integrated into clinical practice for detecting fetal chromosomal aneuploidy. We directly determined the fetal fraction (FF) from results obtained with MPS tag counting and examined the relationships of FF to such biological parameters as fetal karyotype and maternal demographics. METHODS: FF was determined from samples previously collected for the MELISSA (Maternal Blood Is Source to Accurately Diagnose Fetal Aneuploidy) study. Samples were resequenced, analyzed blindly, and aligned to the human genome (assembly hg19). FF was calculated in pregnancies with male or aneuploid fetuses by means of an equation that incorporated the ratio of the tags in these samples to those of a euploid training set. RESULTS: The mean (SD) FF from euploid male pregnancies was 0.126 (0.052) (n = 160). Weak but statistically significant correlations were found between FF and the maternal body mass index (r(2) = 0.18; P = 2.3 × 10(-8)) and between FF and gestational age (r(2) = 0.02; P = 0.047). No relationship with maternal ethnicity or age was observed. Mean FF values for trisomies 21 (n = 90), 18 (n = 38), and 13 (n = 16) and for monosomy X (n = 20) were 0.135 (0.051), 0.089 (0.039), 0.090 (0.062), and 0.106 (0.045), respectively. CONCLUSIONS: MPS tag-count data can be used to determine FF directly and accurately. Compared with male euploid fetuses, the FF is higher in maternal plasma when the fetus has trisomy 21 and is lower when the fetus has trisomy 18, 13, or monosomy X. The different biologies of these aneuploidies have practical implications for the determination of cutoff values, which in turn will affect the diagnostic sensitivity and specificity of the test.

Noninvasive detection of fetal subchromosome abnormalities via deep sequencing of maternal plasma.

The purpose of this study was to determine the deep sequencing and analytic conditions needed to detect fetal subchromosome abnormalities across the genome from a maternal blood sample. Cell-free (cf) DNA was isolated from the plasma of 11 pregnant women carrying fetuses with subchromosomal duplications and deletions, translocations, mosaicism, and trisomy 20 diagnosed by metaphase karyotype. Massively parallel sequencing (MPS) was performed with 25-mer tags at approximately 10(9) tags per sample and mapped to reference human genome assembly hg19. Tags were counted and normalized to fixed genome bin sizes of 1 Mb or 100 kb to detect statistically distinct copy-number changes compared to the reference. All seven cases of microdeletions, duplications, translocations, and the trisomy 20 were detected blindly by MPS, including a microdeletion as small as 300 kb. In two of these cases in which the metaphase karyotype showed additional material of unknown origin, MPS identified both the translocation breakpoint and the chromosomal origin of the additional material. In the four mosaic cases, the subchromosomal abnormality was not demonstrated by MPS. This work shows that in nonmosaic cases, it is possible to obtain a fetal molecular karyotype by MPS of maternal plasma cfDNA that is equivalent to a chromosome microarray and in some cases is better than a metaphase karyotype. This approach combines the advantage of enhanced fetal genomic resolution with the improved safety of a noninvasive maternal blood test.

Substrate cleavage analysis of furin and related proprotein convertases. A comparative study.

We present the data and the technology, a combination of which allows us to determine the identity of proprotein convertases (PCs) related to the processing of specific protein targets including viral and bacterial pathogens. Our results, which support and extend the data of other laboratories, are required for the design of effective inhibitors of PCs because, in general, an inhibitor design starts with a specific substrate. Seven proteinases of the human PC family cleave the multibasic motifs R-X-(R/K/X)-R downward arrow and, as a result, transform proproteins, including those from pathogens, into biologically active proteins and peptides. The precise cleavage preferences of PCs have not been known in sufficient detail; hence we were unable to determine the relative importance of the individual PCs in infectious diseases, thus making the design of specific inhibitors exceedingly difficult. To determine the cleavage preferences of PCs in more detail, we evaluated the relative efficiency of furin, PC2, PC4, PC5/6, PC7, and PACE4 in cleaving over 100 decapeptide sequences representing the R-X-(R/K/X)-R downward arrow motifs of human, bacterial, and viral proteins. Our computer analysis of the data and the follow-on cleavage analysis of the selected full-length proteins corroborated our initial results thus allowing us to determine the cleavage preferences of the PCs and to suggest which PCs are promising drug targets in infectious diseases. Our results also suggest that pathogens, including anthrax PA83 and the avian influenza A H5N1 (bird flu) hemagglutinin precursor, evolved to be as sensitive to PC proteolysis as the most sensitive normal human proteins.