Structome: a tool for the rapid assembly of datasets for structural phylogenetics.

Summary: Protein structures carry signal of common ancestry and can therefore aid in reconstructing their evolutionary histories. To expedite the structure-informed inference process, a web server, Structome, has been developed that allows users to rapidly identify protein structures similar to a query protein and to assemble datasets useful for structure-based phylogenetics. Structome was created by clustering ∼94% of the structures in RCSB PDB using 90% sequence identity and representing each cluster by a centroid structure. Structure similarity between centroid proteins was calculated, and annotations from PDB, SCOP, and CATH were integrated. To illustrate utility, an H3 histone was used as a query, and results show that the protein structures returned by Structome span both sequence and structural diversity of the histone fold. Additionally, the pre-computed nexus-formatted distance matrix, provided by Structome, enables analysis of evolutionary relationships between proteins not identifiable using searches based on sequence similarity alone. Our results demonstrate that, beginning with a single structure, Structome can be used to rapidly generate a dataset of structural neighbours and allows deep evolutionary history of proteins to be studied. Availability and Implementation: Structome is available at: https://structome.bii.a-star.edu.sg.

Assessing the effectiveness and cost-effectiveness of a solution-focused resource-orientated approach (DIALOG+) to improving the quality of life for people with psychosis in India and Pakistan-a cluster RCT.

BACKGROUND: Severe mental illness (SMI) presents a major challenge worldwide, affecting approximately 5-8% of the world's population. It causes significant distress to affected people, families and wider communities, generating high costs through loss of productivity and ongoing healthcare use. Over 75% of patients with psychosis receive inadequate care and experience a negative financial impact and reduced quality of life (QoL). It is therefore a priority to reduce the treatment gap by providing low-cost, effective interventions for people with psychosis. Our research project, PIECEs, is designed to explore, adapt and test a low-cost, approach (DIALOG+) that makes use of existing resources to improve community-based care for patients with psychosis. The research will be conducted in two urban sites: Karachi, Pakistan and Chennai, India. DIALOG+ is a novel, technology-assisted and resource-oriented intervention, based on QoL research, concepts of patient-centred communication, IT developments and solution-focused therapy. However, the approach has not been rigorously tested within India and Pakistan. Our randomised controlled trial (RCT) aims to test the effectiveness and cost-effectiveness of DIALOG+ in improving the QoL and clinical outcomes for individuals with long-term psychosis being treated in the community in India and Pakistan. METHODS: To assess the acceptability, feasibility, and cost effectiveness of DIALOG+, we will conduct a cluster RCT with 210 patients and 14 clinicians in each country. The intervention will be used during a routine interaction between a clinician and a patient. It consists of a patient-centred assessment (the DIALOG scale) whereby the clinician invites the patient to rate their satisfaction with different life domains and treatment aspects, which forms the active control group. The intervention group will follow this up with a four-step solution-focused approach to identify the patient's resources and develop solutions to deal with the patient's concerns (DIALOG+). DISCUSSION: If shown to be effective DIALOG+ has the potential to improve community-based care and the QoL for millions of people within India and Pakistan who experience psychosis. TRIAL REGISTRATION: The trial was registered prospectively on the ISRCTN Registry: ISRCTN13022816 on 9 February 2022.

Spatiotemporal variation and socioeconomic factors of financial hardships of out-of-pocket health expenditure in Pakistan.

BACKGROUND: Financial hardships of out-of-pocket health expenditure (OPHE) is a growing concern for health policy makers in many low and middle-income countries. Spatiotemporal variation between Pakistan's four provinces over 2001-2015 is discussed, which would help comparing existing health services delivery and financial risk protection plans. AIMS: In this paper, we estimate financial hardship of OPHE in Pakistan. METHODS: We use the data sets of the household integrated economic surveys 2001-02, 2005-06, 2010-11 and 2015-16. We estimate OPHE share in household total and non-subsistence expenditure, catastrophic headcount at the threshold of OPHE ≥ 10% of total expenditure or OPHE ≥ 25% of non-subsistence expenditure. We estimate impoverishment of OPHE using national poverty lines. Finally, we explore socioeconomic factors of financial hardships of OPHE. RESULTS: Over the years, catastrophic headcount and impoverishment of OPHE had decreased at national level (-1.3% points) and in the provinces of Sindh (-7.8% points) and Khyber Pukhtoonkhawa (KPK), (-2.8% points). The province of KPK and the year 2005-06 witnessed the highest incidence of financial catastrophe (26.89% points) and impoverishment (4.8% points) of OPHE. Households in rural areas, in the middle and rich quintiles and those headed by a male were more likely to encounter financial catastrophe and impoverishment due to OPHE. CONCLUSION: Inter-provincial variation in financial hardships of OPHE provide aide to provincial level priority setting. The high impact of OPHE in the non-poor, in rural areas, and in KPK calls for enhanced targeting of financial risk protection plans.

DStabilize: A Web Resource to Generate Mirror Images of Biomolecules.

Peptides comprising D-amino acids have been shown to be resistant to proteolysis. This makes them potential candidates as probes of cellular interactions, notably protein-biomolecule interactions. However, the empirical conversion of the amino acids that constitute a peptide from L-forms to D-forms will result in abrogation of the normal interactions made by the L-amino acids due to side-chain orientation changes that are associated with the changes in chirality. These interactions can be preserved by reversing the sequence of the D-peptide. We present a web server (http://dstabilize.bii.a-star.edu.sg/) that allows users to convert between L-proteins and D-proteins and for sequence reversal of D-peptides, along with the capability of performing other empirical geometric transforms. This resource allows the user to generate structures of interest easily for subsequent in silico processing.

Structural Phylogenetics with Confidence.

For evaluating the deepest evolutionary relationships among proteins, sequence similarity is too low for application of sequence-based homology search or phylogenetic methods. In such cases, comparison of protein structures, which are often better conserved than sequences, may provide an alternative means of uncovering deep evolutionary signal. Although major protein structure databases such as SCOP and CATH hierarchically group protein structures, they do not describe the specific evolutionary relationships within a hierarchical level. Structural phylogenies have the potential to fill this gap. However, it is difficult to assess evolutionary relationships derived from structural phylogenies without some means of assessing confidence in such trees. We therefore address two shortcomings in the application of structural data to deep phylogeny. First, we examine whether phylogenies derived from pairwise structural comparisons are sensitive to differences in protein length and shape. We find that structural phylogenetics is best employed where structures have very similar lengths, and that shape fluctuations generated during molecular dynamics simulations impact pairwise comparisons, but not so drastically as to eliminate evolutionary signal. Second, we address the absence of statistical support for structural phylogeny. We present a method for assessing confidence in a structural phylogeny using shape fluctuations generated via molecular dynamics or Monte Carlo simulations of proteins. Our approach will aid the evolutionary reconstruction of relationships across structurally defined protein superfamilies. With the Protein Data Bank now containing in excess of 158,000 entries (December 2019), we predict that structural phylogenetics will become a useful tool for ordering the protein universe.

Socio-economic determinants of household out-of-pocket payments on healthcare in Pakistan.

BACKGROUND: Out-of-pocket (OOP) payment on healthcare is dominant mode of financing in developing countries. In Pakistan it is 67% of total expenditure on healthcare. Analysis of determinants of OOP health expenditure is a key aspect of equity in healthcare financing. It helps to formulate an effective health policy. Evidence on OOP in Pakistan is sparse. This paper attempts to fill this research gap. METHODS: We estimated determinants of OOP payments on healthcare in Pakistan. We used data sets of Pakistan Household Integrated Economic Survey (HIES) and Pakistan Standard of Living Measurement (PSLM) Survey for the year 2004-05. We developed a multiple regression model for the determinants of OOP payments using methods of Ordinary Least Square (OLS). We mainly used social, economic, demographic and health variables in our analysis. RESULTS: Median household OOP healthcare in the year 2004-05 was Pakistani Rupees (PKR) 2500 (US$ 41.99) in 2004-05. Household non-food expenditure was the single highest significant predictor of household OOP health expenditure. Household features like literate head and spouse, at least one obstetric delivery in last three years, unsafe water, unhygienic toilet and household belonging to Khyber Pukhtonkhwa (KPK) province were significant positive predictors of OOP payments. Households with male head, bricks used in housing construction, household with at least one child and no elderly, and head of household in a white collar profession were negative predictors of OOP payments. CONCLUSION: Our analysis confirms earlier findings that economic status and number of old aged members are significant positive predictors of OOP payments. This association can direct government to enhance allocations to healthcare and to include program focusing on non-communicable diseases. Our findings suggest further research to explore beneficiaries of government healthcare programs and determinants of high OOP payments by household residing in KPK province than other province. The interaction between white collar profession and their economic status in predicting OOP payments is also an area for further research.