Application of a low-cost, specific, and sensitive loop-mediated isothermal amplification (LAMP) assay to detect Plasmodium falciparum imported from Africa.

BACKGROUND: Chinese citizens traveling abroad bring back imported malaria cases to China. Current malaria diagnostic tests, including microscopy and antigen-detecting rapid tests, cannot reliably detect low-density infections. To complement existing diagnostic methods, we aimed to develop a new loop-mediated isothermal amplification (LAMP) assay to detect and identify Plasmodium falciparum in Chinese travelers returning from Africa. METHODS: We developed a miniaturized LAMP assay to amplify the actin I gene of P. falciparum. Each reaction consumed only 25% of the reagents used in a conventional LAMP assay and the same amount of DNA templates used in nested PCR. We evaluated this LAMP assay's performance and compared it to microscopy and a nested PCR assay using 466 suspected malaria cases imported from Africa. We assessed the sensitivity of the new LAMP assay using cultured P. falciparum, clinical samples, and a plasmid construct, allowing unprecedented precision when quantifying the limit of detection. RESULTS: The new LAMP assay was highly sensitive and detected two more malaria cases than nested PCR. Compared to nested PCR, the sensitivity and specificity of the novel LAMP assay were 100% [95% confidence interval (CI) 98.5-100%] and 99.1% (95% CI 96.7-99.9%), respectively. When evaluated using serial dilutions of the plasmid construct, the detection limit of the new LAMP was as low as 102 copies/µL, 10-fold lower than PCR. The LAMP assay detected 0.01 parasites/µL of blood (equal to 0.04 parasites/µL of DNA) using cultured P. falciparum and 1-7 parasites/µL of blood (4-28 parasites/µL of DNA) in clinical samples, which is as good as or better than previously reported and commercially licensed assays. CONCLUSION: The novel LAMP assay based on the P. falciparum actin I gene was specific, sensitive, and cost-effective, as it consumes 1/4 of the reagents in a typical LAMP reaction.

The Quantitative Assessment of Using Multiparametric MRI for Prediction of Extraprostatic Extension in Patients Undergoing Radical Prostatectomy: A Systematic Review and Meta-Analysis.

PURPOSE: To investigate the diagnostic performance of using quantitative assessment with multiparametric MRI (mpMRI) for prediction of extraprostatic extension (EPE) in patients with prostate cancer (PCa). METHODS: We performed a computerized search of MEDLINE, Embase, Cochrane Library, Web of Science, and Google Scholar from inception until July 31, 2021. Summary estimates of sensitivity and specificity were pooled with the bivariate model, and quality assessment of included studies was performed with the Quality Assessment of Diagnostic Accuracy Studies-2. We plotted forest plots to graphically present the results. Multiple subgroup analyses and meta-regression were performed to explore the variate clinical settings and heterogeneity. RESULTS: A total of 23 studies with 3,931 participants were included. The pooled sensitivity and specificity for length of capsular contact (LCC) were 0.79 (95% CI 0.75-0.83) and 0.77 (95% CI 0.73-0.80), for apparent diffusion coefficient (ADC) were 0.71 (95% CI 0.50-0.86) and 0.71 (95% CI 059-0.81), for tumor size were 0.62 (95% CI 0.57-0.67) and 0.75 (95% CI 0.67-0.82), and for tumor volume were 0.77 (95% CI 0.68-0.84) and 0.72 (95% CI 0.56-0.83), respectively. Substantial heterogeneity was presented among included studies, and meta-regression showed that publication year (≤2017 vs. >2017) was the significant factor in studies using LCC as the quantitative assessment (P=0.02). CONCLUSION: Four quantitative assessments of LCC, ADC, tumor size, and tumor volume showed moderate to high diagnostic performance of predicting EPE. However, the optimal cutoff threshold varied widely among studies and needs further investigation to establish.

DnsID in MyCompoundID for rapid identification of dansylated amine- and phenol-containing metabolites in LC-MS-based metabolomics.

High-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) is an enabling technology based on rational design of labeling reagents to target a class of metabolites sharing the same functional group (e.g., all the amine-containing metabolites or the amine submetabolome) to provide concomitant improvements in metabolite separation, detection, and quantification. However, identification of labeled metabolites remains to be an analytical challenge. In this work, we describe a library of labeled standards and a search method for metabolite identification in CIL LC-MS. The current library consists of 273 unique metabolites, mainly amines and phenols that are individually labeled by dansylation (Dns). Some of them produced more than one Dns-derivative (isomers or multiple labeled products), resulting in a total of 315 dansyl compounds in the library. These metabolites cover 42 metabolic pathways, allowing the possibility of probing their changes in metabolomics studies. Each labeled metabolite contains three searchable parameters: molecular ion mass, MS/MS spectrum, and retention time (RT). To overcome RT variations caused by experimental conditions used, we have developed a calibration method to normalize RTs of labeled metabolites using a mixture of RT calibrants. A search program, DnsID, has been developed in www.MyCompoundID.org for automated identification of dansyl labeled metabolites in a sample based on matching one or more of the three parameters with those of the library standards. Using human urine as an example, we illustrate the workflow and analytical performance of this method for metabolite identification. This freely accessible resource is expandable by adding more amine and phenol standards in the future. In addition, the same strategy should be applicable for developing other labeled standards libraries to cover different classes of metabolites for comprehensive metabolomics using CIL LC-MS.