Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Advanced Clinical Diagnosis of Malaria Using a Simple Red-Emissive Smart Fluorescent Probe

Domaine:

healthcare

Type de record:

paper
Créateur:
Yi ShiGenZon
Hôte:avatar
Malaria, a potentially life-threatening disease caused by the mosquito-borne parasitic infection of human red blood cells, still accounts for over half a million deaths worldwide every year. Accurate early-stage diagnosis of malaria is indispensable for quick medical intervention and the avoidance of any potential complications leading to fatality. In this regard, DNA-specific fluorescent probes coupled with flow cytometry techniques emerged as a promising cost-effective diagnostic platform for highly sensitive rapid detection of malaria. However, ideal DNA-specific fluorescent probes that can be efficiently employed for both fluorescence microscopic studies as well as flow cytometric analysis to enable precise, high-quality clinical diagnosis of malaria are inadequate. In this context, we have reported a rationally designed hemicyanine dye MR-1 with blue absorption and red emission that can exhibit a turn-on fluorescence response upon effective binding with the AT-rich segments of dsDNA. The rationale behind designing the fluorescent probe MR-1 was well explained with the help of control compounds MR-2 and MR-3. The DNA-specific fluorescent probe MR-1 revealed excellent cell permeability and localized in the cellular nucleus of both live and fixed cells. A marked enhancement in fluorescence intensity was observed when malaria parasite-infected red blood cells were incubated with MR-1, and the detection limit was found to be ∼20/μL. Further, the flow cytometric analysis of clinical malaria parasite-infected red blood cells incubated with MR-1 not only demonstrated precise detection and classification of various malaria parasites but also smartly enabled the differentiation of malaria from Babesia-parasite infection with similar clinical symptoms.

Visit

figshare.com

Tags

MedicineMicrobiologyCell BiologyBiotechnologyImmunologyCancerPhysical Sciences not elsewhere classifiedthreatening disease causedsimilar clinical symptomsrationale behind designing+38

Licenses

CC BY-NC 4.0

Similaires

The financial and clinical implications of adult malaria diagnosis using microscopy in Kenya.Field evaluation of a quantitative, and rapid malaria diagnostic system using a fluorescent Blue-ray optical deviceInference and dynamic simulation of malaria using a simple climate-driven entomological model of malaria transmissionDiagnosis of red cell G6PD deficiency in rural Burkina Faso. Comparison of a rapid fluorescent enzyme test on filter paper with polymerase chain reaction based genotypingMALARIA DIAGNOSIS BY TRANSFER LEARNING ANALYSIS OF PARASITIZED AND UNINFECTED RED BLOOD CELL IMAGES USING VGG16, DENSENET201, VGG21, AND VGG19Ensemble Machine Learning for Malaria Diagnosis in Resource-Limited Settings Using Clinical and Demographic Features

The financial and clinical implications of adult malaria diagnosis using microscopy in Kenya.

OBJECTIVE: A recent observational study undertaken at 17 health facilities with microscopy in Kenya

Field evaluation of a quantitative, and rapid malaria diagnostic system using a fluorescent Blue-ray optical device

Abstract We improved a previously developed quantitative malari

Inference and dynamic simulation of malaria using a simple climate-driven entomological model of malaria transmission

Given the crucial role of climate in malaria transmission, many mechanistic models of malaria repres

Diagnosis of red cell G6PD deficiency in rural Burkina Faso. Comparison of a rapid fluorescent enzyme test on filter paper with polymerase chain reaction based genotyping

Summary Glucose‐6‐phosphate dehydrogenase (G6PD) deficient individuals are at increased risk of dev

MALARIA DIAGNOSIS BY TRANSFER LEARNING ANALYSIS OF PARASITIZED AND UNINFECTED RED BLOOD CELL IMAGES USING VGG16, DENSENET201, VGG21, AND VGG19

Malaria is still a major worldwide health concern, and effective treatment depends on early discover

Ensemble Machine Learning for Malaria Diagnosis in Resource-Limited Settings Using Clinical and Demographic Features

Abstract Background Sub-Saharan Africa con