Two clusters of Plasmodium knowlesi cases in a malaria elimination area, Sabang Municipality, Aceh, Indonesia.

In malaria elimination areas, malaria cases are sporadic and consist predominantly of imported cases. Plasmodium knowlesi cases have been reported throughout Southeast Asia where long-tailed and pig-tailed macaques and Anopheles leucosphyrus group mosquitoes are sympatric. The limitation of microscopic examination to diagnose P. knowlesi is well known. In consequence, no P. knowlesi case has previously been reported from routine health facility-based case finding activities in Indonesia. This report describes two clusters of unexpected locally acquired P. knowlesi cases found in an area where Plasmodium falciparum and Plasmodium vivax infection had been eliminated in Sabang Municipality, Aceh, Indonesia. The difficulties in diagnosis and response illustrate challenges that Southeast Asian countries will increasingly face as the formerly common malaria parasites P. falciparum and P. vivax are gradually eliminated from the region.

The combination of Fourier-transform infrared spectroscopy with pattern recognition techniques for classification and discrimination of red snapper fish oils.

Fish oils are good sources for essential fatty acids such as omega-3 and omega-6 fatty acids needed to human growth. Indonesia is rich in fish species and among this, red snapper fish (Lutjanus sp.) can be extracted to get red snapper fish oils (RSFOs). The aim of this study was to classify and discriminate RSFO from different origins using Fourier-transform infrared (FTIR) spectra and pattern recognition techniques. All of the RSFO's FTIR spectra were very similar. The FTIR vibrations showed the presence of triglycerides as the main composition in fish oils. Principal component analysis (PCA) could separate the RSFO according to sample origin. Supervised pattern recognition of partial least square-discriminant analysis (PLS-DA) and sparse PLS-DA (sPLS-DA) successfully discriminated and classified different Lutjanus species of fish oils obtained from different origins. The vibration of functional groups at 1711, 1653, 1745, and 3012 per cm were considered for their important contributions in discriminating of Lutjanus species (variable importance in projection, variable importance in the projection score >1). Fish oils obtained from the same species were classified into the same class indicating similar chemical compositions. Among the three pattern recognition techniques used, sPLS-DA offers the best model for the discrimination and classification of Lutjanus fish oils. It can be concluded that FTIR spectroscopy in combination with the pattern recognition technique is the potential to be used for of fish oil authentication to verify the quality of the fish oils. It can be further developed as a rapid and effective method for fish oil authentication.