Artemisinin derivative-based combination therapy is expected to suppress the development of Plasmodium falciparum drug resistance in Africa. We have performed an artemether-lumefantrine (Coartem; Novartis) follow-up clinical trial in Zanzibar, in which pfcrt K76T and pfmdr1 N86Y frequencies were determined before drug administration and in all recurrent parasites during a follow-up period of 42 days. A significant increase in pfmdr1 86N was observed after exposure to the drug. This points to 86N as a potential marker of lumefantrine resistance in vivo, while suggesting that Coartem is not robust enough to avoid selection of resistance-associated mutations in some malarial settings.

Background The cerebrospinal fluid (CSF) biomarkers amyloid beta 1–42, total tau, and phosphorylated tau are used increasingly for Alzheimer’s disease (AD) research and patient management. However, there are large variations in biomarker measurements among and within laboratories. Methods Data from the first nine rounds of the Alzheimer’s Association quality control program was used to define the extent and sources of analytical variability. In each round, three CSF samples prepared at the Clinical Neurochemistry Laboratory (Mölndal, Sweden) were analyzed by single-analyte enzyme-linked immunosorbent assay (ELISA), a multiplexing xMAP assay, or an immunoassay with electrochemoluminescence detection. Results A total of 84 laboratories participated. Coefficients of variation (CVs) between laboratories were around 20% to 30%; within-run CVs, less than 5% to 10%; and longitudinal within-laboratory CVs, 5% to 19%. Interestingly, longitudinal within-laboratory CV differed between biomarkers at individual laboratories, suggesting that a component of it was assay dependent. Variability between kit lots and between laboratories both had a major influence on amyloid beta 1–42 measurements, but for total tau and phosphorylated tau, between-kit lot effects were much less than between-laboratory effects. Despite the measurement variability, the between-laboratory consistency in classification of samples (using prehoc-derived cutoffs for AD) was high (>90% in 15 of 18 samples for ELISA and in 12 of 18 samples for xMAP). Conclusions The overall variability remains too high to allow assignment of universal biomarker cutoff values for a specific intended use. Each laboratory must ensure longitudinal stability in its measurements and use internally qualified cutoff levels. Further standardization of laboratory procedures and improvement of kit performance will likely increase the usefulness of CSF AD biomarkers for researchers and clinicians.

Background Artemether-lumefantrine (AL) is a major and highly effective artemisinin-based combination therapy that is becoming increasingly important as a new first-line therapy against Plasmodium falciparum malaria. However, recrudescences occurring after AL treatment have been reported. Identification of drug-specific parasite determinants that contribute to treatment failures will provide important tools for the detection and surveillance of AL resistance. Method The findings from a 42-day follow-up efficacy trial in Tanzania that compared AL with sulfadoxine-pyrimethamine (SP) were analyzed to identify candidate markers for lumefantrine tolerance/resistance in the chloroquine resistance transporter gene (pfcrt) and multidrug resistance gene 1 (pfmdr1). The findings were corroborated in vitro with genetically modified isogenic P. falciparum parasite lines. Results Treatment with AL selected for the chloroquine-susceptible pfcrt K76 allele (P < .0001) and, to a lesser extent, the pfmdr1 N86 (P = .048) allele among recurrent infections. These genotypes were not selected during SP treatment. No pfmdr1 gene amplifications were observed. Isogenic pfcrt-modified parasite lines demonstrated a 2-fold increase in susceptibility to lumefantrine, which was directly attributable to the K76T mutation. Conclusions Our findings suggest that the pfcrt K76T mutation is a drug-specific contributor to enhanced P. falciparum susceptibility to lumefantrine in vivo and in vitro, and they highlight the benefit of using AL in areas affected by chloroquine-resistant P. falciparum malaria.

Summaryobjective Artemether-lumefantrine (AL), presently the most favoured combination therapy against uncomplicated Plasmodium falciparum malaria in Africa, has recently shown to select for the pfmdr1 86N allele. The objective of this study was to search for the selection of other mutations potentially involved in artemether-lumefantrine tolerance and/or resistance, i.e. pfmdr1 gene amplification, pfmdr1 Y184F, S1034C, N1042D, D1246Y, pfcrt S163R and PfATP6 S769N.methods The above mentioned SNPs were analysed by PCR-restriction fragment length polymorphism and pfmdr1 gene amplification by real-time PCR based protocols in parasites from 200 children treated with AL for uncomplicated P. falciparum malaria in Zanzibar.results A statistically significant selection of pfmdr1 184F mostly in combination with 86N was seen in reinfections after treatment. No pfmdr1 gene amplification was found.conclusion The results suggest that different pfmdr1 alleles are involved in the development of tolerance/resistance to lumefantrine.

Both treatments were highly efficacious, but AL provided stronger prevention against reinfection. The high proportion of recrudescences found after day 28 and the genetic selection by the long-acting partner drug underlines the importance of long follow-up periods in clinical trials. A long follow-up duration and performance of PCR genotyping should be implemented in programmatic surveillance of antimalarial drugs.

Plasmodium falciparum response mechanisms to the major artemisinin-based combination therapies (ACTs) are largely unknown. Multidrug-resistance protein (MRP)-like adenosine triphosphate (ATP)-binding cassette transporters are known to be related to multidrug resistance in many organisms. Therefore, we hypothesized that sequence variation in pfmrp1 can contribute to decreased parasite sensitivity to ACT. Through sequencing of the pfmrp1 open reading frame for 103 geographically diverse P. falciparum infections, we identified 27 single-nucleotide polymorphisms (SNPs), of which 21 were nonsynonymous and 6 synonymous. Analyses of clinical efficacy trials with artesunate-amodiaquine and artemether-lumefantrine detected a specific selection of the globally prevalent I876V SNP in recurrent infections after artemether-lumefantrine treatment. Additional in silico studies suggested an influence of variation in amino acid 876 on the ATP hydrolysis cycle of pfMRP1 with potential impact on protein functionality. Our data suggest for the first time, to our knowledge, the involvement of pfMRP1 in P. falciparum in vivo response to ACT.

The in vitro activity of the prodrug amodiaquine and its metabolite monodesethyl-amodiaquine has been studied for three strains of Plasmodium falciparum: LS-2, LS-3, and LS-1. Both compounds showed significant activity against all three strains; the activity of amodiaquine was slightly higher than that of the metabolite. By use of a checkerboard design, interaction studies with both compounds yielded evidence of significant synergism; means of the sums of the fractional inhibitory concentrations were 0.0392 to 0.0746 for strain LS-2, 0.1567 to 0.3102 for strain LS-3, and 0.025 to 0.3369 for strain LS-1. In further investigations, the interaction of amodiaquine with monodesethyl-amodiaquine was tested at clinically relevant concentrations of both compounds. In these studies, involving amodiaquine at picomolar and femtomolar concentrations, the compound was found to exert high potentiating activity on monodesethyl-amodiaquine. This interaction produced mean ratios of observed to expected activity of 0.0505 to 0.0642 for strain LS-2, 0.0882 to 0.3820 for strain LS-3, and 0.0752 to 0.2924 for strain LS-1. The synergistic activity was most marked at monodesethyl-amodiaquine/ amodiaquine ratios up to 100,000:1 but was still evident at higher ratios.The widespread increase of resistance to chloroquine in Plasmodium falciparum has resulted in renewed interest in amodiaquine (AQ) as a replacement for chloroquine in the treatment of malaria, especially in sub-Saharan Africa. Although AQ belongs to the same chemical class of compounds as chloroquine, the 4-aminoquinolines, this drug often shows adequate clinical-parasitological efficacy in chloroquine-resistant infections. Furthermore, adverse reactions reported previously, such as agranulocytosis (14) and hepatitis (20), were mainly associated with the prophylactic use of AQ, and more recent reports show that therapeutic regimens are well tolerated (22). Therefore, the World Health Organization has again listed AQ as a drug for treatment of chloroquine-resistant falciparum malaria (40).During and after absorption, orally administered AQ is rapidly metabolized to desethylamodiaquine (DAQ) and other derivatives of lesser antimalarial significance (9). Clinically, the antimalarial activity of AQ is exerted mainly through DAQ (37). Earlier in vitro studies indicated that DAQ and AQ have equal activity against P. falciparum (8). Other observations suggest that the two compounds possess independent modes of action (7,27). However, recent comparative in vitro studies with fresh isolates of P. falciparum showed a significant correlation between the activities of the two compounds that indicates similarities in the way they act against the parasite (12).Chloroquine-resistant falciparum malaria on the African continent was first detected in Kenya and Tanzania. During the past 2 decades it has extended to practically all parts of tropical Africa (32,39). AQ has been shown to maintain high efficacy in the areas of malaria endemicity in the continent where chloroquine resistance is st...

Purpose: Hemoglobin A1c (HbA1c) is an essential marker for assessment of glycemic control in diabetes patients. The aim of this study was to evaluate the agreement between different HbA1c methods. Methodology: We used blood samples to compare HbA1c results analyzed with Capillarys 3 Tera, Roche Tina-Quant HbA1c Gen 3, BioRad Variant II Turbo (3 sites), Mono S® and Abbott Architect enzymatic method. The comparisons were made as paired instrument comparisons with Capillarys 3 Tera. Results: The linear correlations between the HbA1c methods were as follows: Cobas 6000 = 0.982 x Capillarys 3 Tera + 0.975, R² = 0.994; Architect c8000 = 0.982 x Capillarys 3 Tera + 1.064, R² = 0.994; Mono S® = 0.916 x Capillarys 3 Tera + 3.397, R² = 0.965; BioRad Variant II Turbo = 0.923 x Capillarys 3 Tera + 4.062, R² = 0.990; Tosoh G8 = 0.963 x Capillarys 3 Tera + 3.895, R² = 0.996. Conclusions: The different instrument platforms showed the best agreement in the 50-70 mmol/mol interval. Above and below this range the methods separated into 2 groups, one consisting of Capillarys 3 Tera, Roche Tina-Quant and Abbott enzymatic method and the other group consisting of BioRad Variant II Turbo, Tosoh G8 and Mono S®.