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Plasmodium vivax is the most geographically widespread species responsible for malaria in humans. Our study focused on identifying highly expressed parasite proteins using a shotgun proteomics approach. Parasites (P. vivax) are isolated from seven patient samples using saponin lysis. Protein extracts from these parasites are processed and subjected to LC-MS/MS analysis. An overall proteome coverage of 605 P. vivax proteins along with 1670 human host proteins are obtained upon combining the data from LC-MS/MS runs. While a major proportion of the P. vivax proteins are either hypothetical or involved in basic cellular activities, few proteins such as tryptophan-rich antigen (Pv-fam-a; PVX_090265), Pv-fam-d protein (PVX_101520), Plasmodium exported protein (PVX_003545), Pvstp1 (PVX_094303) and hypothetical protein (PVX_083555) are detected in more than 80% of the clinical isolates and found to be unique to P. vivax without orthologs in P. falciparum. Our proteomics study on individual parasite isolates reveals highly expressed P. vivax proteins, few of which may be good candidates for vivax malaria diagnosis due to their abundance and absence in P. falciparum. This study represents the first step towards the identification of biomarkers for P. vivax malaria. In future, their clinical diagnostic values must be explored and validated on large patient cohorts.

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Anaemia control programmes in India are hampered by a lack of representative evidence on anaemia prevalence, burden and associated factors for adolescents. The aim of this study was to: (1) describe the national and subnational prevalence, severity and burden of anaemia among Indian adolescents; (2) examine factors associated with anaemia at national and regional levels. Data (n = 14,673 individuals aged 10-19 years) were from India's Comprehensive National Nutrition Survey (CNNS, 2016(CNNS, -2018. CNNS used a multistage, stratified, probability proportion to size cluster sampling design. Prevalence was estimated using globally comparable age-and sex-specific cutoffs, using survey weights for biomarker sample collection.Burden analysis used prevalence estimates and projected population from 2011 Census data. Multivariable logistic regression models were used to analyse factors (diet, micronutrient deficiencies, haemoglobinopathies, sociodemographic factors, environment) associated with anaemia. Anaemia was present in 40% of girls and 18% of boys, equivalent to 72 million adolescents in 2018, and varied by region (girls 29%-46%; boys 11%-28%) and state (girls 7%-62%; boys 4%-32%). Iron deficiency