RESUMEN
Malaria is the most common vector-borne parasitic disease in Malaysia and Thailand, especially in Malayan Borneo and along the Thailand border areas, but little is known about the genetic diversity of the parasite. Present study aims to investigate the genetic diversity of Plasmodium falciparum isolates in these two countries and eventually contributes to more effective malaria control strategies, particularly in vaccine and antimalarial treatment. One hundred and seventy three P. falciparum isolates were collected from Malaysia (n = 67) and Thailand (n = 106) and genotyped using nested PCR targeting the polymorphic region of MSP-1, block 2. Sequence analysis was conducted to investigate the allele diversity of the isolates. Three allelic families were identified in Malaysian and Thailand P. falciparum isolates, MAD20, K1 and RO33. Sequence analysis revealed that there were 5 different MAD20, 1 K1 and 2 different RO33 for Malaysian isolates. Thailand isolates exhibited greater polymorphism because there were 13 different MAD20, 6 different K1 and 2 different RO33 identified in this study. Multiclonal infections were observed for the isolates in both countries, however, low multiplicity of infection (MOI) was observed for Malaysian (1.1) and Thailand (1.2) isolates. Phylogenetic analysis showed that P. falciparum isolates of Malaysia and Thailand were clustered in the same group for all the allelic families. Population structure of P. falciparum isolates in Malaysia and Thailand exhibit extensive genetic polymorphism but showed high similarities as well as comparable MOI.
RESUMEN
@#Malaria is the most common vector-borne parasitic disease in Malaysia and Thailand, especially in Malayan Borneo and along the Thailand border areas, but little is known about the genetic diversity of the parasite. Present study aims to investigate the genetic diversity of Plasmodium falciparum isolates in these two countries and eventually contributes to more effective malaria control strategies, particularly in vaccine and antimalarial treatment. One hundred and seventy three P. falciparum isolates were collected from Malaysia (n = 67) and Thailand (n = 106) and genotyped using nested PCR targeting the polymorphic region of MSP-1, block 2. Sequence analysis was conducted to investigate the allele diversity of the isolates. Three allelic families were identified in Malaysian and Thailand P. falciparum isolates, MAD20, K1 and RO33. Sequence analysis revealed that there were 5 different MAD20, 1 K1 and 2 different RO33 for Malaysian isolates. Thailand isolates exhibited greater polymorphism because there were 13 different MAD20, 6 different K1 and 2 different RO33 identified in this study. Multiclonal infections were observed for the isolates in both countries, however, low multiplicity of infection (MOI) was observed for Malaysian (1.1) and Thailand (1.2) isolates. Phylogenetic analysis showed that P. falciparum isolates of Malaysia and Thailand were clustered in the same group for all the allelic families. Population structure of P. falciparum isolates in Malaysia and Thailand exhibit extensive genetic polymorphism but showed high similarities as well as comparable MOI.
RESUMEN
WHAT IS KNOWN AND OBJECTIVE: Treatment adherence is an essential component in ensuring best outcomes in the management of paediatric cancers. Compared to the adult population, treatment adherence in the paediatric population is a more complex subject which involves unique dimensions. In this study, we aimed to systematically review the literature to identify factors associated with treatment adherence in the paediatric oncology population. METHODS: A literature search was carried out using related keywords on electronic databases. RESULTS AND DISCUSSION: A total of 1036 articles were reviewed, and 39 articles were found to be relevant. A comprehensive review of these articles identified 17 factors that influence adherence. These factors were classified into five major categories: patient-/caregiver-related factors; therapy-related factors; condition-related factors; health system-related factors; and social/economic factors. A baby bear model was proposed to better visualize these five categories that affect treatment adherence, and a framework of questions was designed to help clinicians identify those at risk of non-adherence for early intervention. WHAT IS NEW AND CONCLUSION: Seventeen factors reviewed were categorized into five main categories, namely patient-/caregiver-related factors, therapy-related factors, condition-related factors, health system factors and social/economic factors, as causes for poor medication adherence in the paediatric oncology population. Clinicians need to be aware that these factors can interact to influence treatment adherence and that some factors may be more relevant in specific contexts (e.g. third world countries, minority groups). The baby bear model is presented to help understand the issues affecting adherence in the paediatric oncology population, and a framework of questions is proposed to help clinicians identify patients at risk of non-adherence.
