Development of an effective vaccine is critically needed for the prevention of malaria. One of the key antigens for malaria vaccines is the apical membrane antigen 1 (AMA-1) of the human malaria parasite Plasmodium falciparum, the surface protein for erythrocyte invasion of the parasite. The gene encoding AMA-1 has been sequenced from populations of P. falciparum worldwide, but the haplotype diversity of the gene in P. falciparum populations in the Greater Mekong Subregion (GMS), including Thailand, remains to be characterized. In the present study, the AMA-1 gene was PCR amplified and sequenced from the genomic DNA of 65 P. falciparum isolates from 5 endemic areas in Thailand. The nearly full-length 1,848 nucleotide sequence of AMA-1 was subjected to molecular analyses, including nucleotide sequence diversity, haplotype diversity and deduced amino acid sequence diversity and neutrality tests. Phylogenetic analysis and pairwise population differentiation (Fst indices) were performed to infer the population structure. The analyses identified 60 single nucleotide polymorphic loci, predominately located in domain I of AMA-1. A total of 31 unique AMA-1 haplotypes were identified, which included 11 novel ones. The phylogenetic tree of the AMA-1 haplotypes revealed multiple clades of AMA-1, each of which contained parasites of multiple geographical origins, consistent with the Fst indices indicating genetic homogeneity or gene flow among geographically distinct populations of P. falciparum in Thailand’s borders with Myanmar, Laos and Cambodia. In summary, the study revealed novel haplotypes and population structure needed for the further advancement of AMA-1-based malaria vaccines in the GMS.
Beta-lactam (BL) antibiotics are among the drugs commonly related to hypersensitivity reactions. Several candidate gene studies and genome-wide association studies have reported associations of genetic variants and hypersensitivity reactions induced by BL antibiotics. However, the results were inconclusive. This protocol details a comprehensive systematic review of genetic factors associated with BL-induced hypersensitivity. A systematic search of literature related to genetic associations of BL-induced hypersensitivity will be performed through PubMed, Medline, Scopus, EMBASE, Web of Science, CINAHL, and the Cochrane central register of Controlled Trials (CENTRAL) from their inception dates with no language restrictions. Two reviewers will independently screen, extract, and appraise the risk of bias. Frequencies of genetic variants that comply with Hardy–Weinberg equilibrium will be extracted and pooled. Genetic models will be applied to variant effect calculation as per allele and genotype analysis. Based on statistical heterogeneity among studies, common effect estimation (odds ratio) and its corresponding 95% confidence interval will be analyzed. Sensitivity and subgroup analyses will be performed to determine the robustness of eligible studies. This systematic review and meta-analysis will provide comprehensive evidence of genetic effects regarding BL-induced hypersensitivity. The findings will enlighten the determination of disease-related genotypes that would potentially reveal allergy profiling in patients.
ST-elevated acute coronary syndrome (STEACS) is a serious condition requiring timely treatment. Reperfusion with primary percutaneous coronary intervention (pPCI) is recommended and preferred over fibrinolysis. Despite its efficacy, lethal complications, such as life-threatening arrhythmia (LTA), are common in post-PCI patients. Although various risk assessment tools were developed, only a few focus on LTA prediction. This study aimed to develop a risk score to predict LTA events after pPCI. A risk score was developed using a retrospective cohort of consecutive patients with STEACS who underwent pPCI at Chiangrai Prachanukroh Hospital from January 2012 to December 2016. LTA is defined as the occurrence of malignant arrhythmia that requires advanced cardiovascular life support (ACLS) within 72 h after pPCI. Logistic regression was used for model derivation. Among 273 patients, 43 (15.8%) developed LTA events. Seven independent predictors were identified: female sex, hemoglobin <12 gm/dL, pre-and intra- procedural events (i.e., respiratory failure and pulseless arrest), IABP insertion, intervention duration >60 min, and desaturation after pPCI. The LTA score showed an AuROC of 0.93 (95%CI 0.90, 0.97). The score was categorized into three risk categories: low (<2.5), moderate (2.5–4), and high risk (>4) for LTA events. The LTA score demonstrated high predictive performance and potential clinical utility for predicting LTA events after pPCI.
A diagnostic model to differentiate multiple myeloma (MM) from bone metastasis (BM) in patients with destructive bone lesions (MM-BM DDx) was developed to promote timely and appropriate referral of patients with MM to hematologists. External validation has never been conducted. This study aims to externally validate the performance of the MM-BM DDx model. Patients and Methods: This multi-center external validation study was conducted using retrospective data of patients over 45 years old diagnosed with MM or BM at six university-affiliated hospitals in Thailand from 2016 to 2022. The MM-BM DDx development dataset, including patients from 2012 to 2015, was utilized during external validation. Diagnostic indicators for MM included in the MM-BM DDx model are serum creatinine, serum globulin, and serum alkaline phosphatase (ALP). MM and BM diagnosis was based on the documented International Classification of Diseases 10th Revision codes. Model performance was evaluated in terms of discrimination, calibration, and accuracy.Results: A total of 3018 patients were included in the validation dataset (586 with MM and 2432 with BM). Clinical characteristics were similar between the validation and development datasets. The MM-BM DDx model's predictions showed an AUC of 0.89 (95% CI, 0.87, 0.90). The predicted probabilities of MM from the model increased concordantly with the observed proportion of MM within the validation dataset. The estimated sensitivity, specificity, and LR for each odds class in the validation dataset were similar to those of the development dataset. Conclusion:The discriminative ability and calibration of the MM-BM DDx model were found to be preserved during external validation. These findings provide support for the practical use of the MM-BM DDx model to assist clinicians in identifying patients with destructive bone lesions who are likely to have MM and enable them to arrange timely referrals for further evaluation by hematologists.
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