AIMC Topic: Molecular Diagnostic Techniques

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Artificial intelligence-driven quantification of antibiotic-resistant Bacteria in food by color-encoded multiplex hydrogel digital LAMP.

Food chemistry
Antibiotic-resistant bacteria pose considerable risks to global health, particularly through transmission in the food chain. Herein, we developed the artificial intelligence-driven quantification of antibiotic-resistant bacteria in food using a color...

A novel machine-learning aided platform for rapid detection of urine ESBLs and carbapenemases: URECA-LAMP.

Journal of clinical microbiology
Pathogenic gram-negative bacteria frequently carry genes encoding extended-spectrum beta-lactamases (ESBL) and/or carbapenemases. Of great concern are carbapenem resistant , , and . Despite the need for rapid AMR diagnostics globally, current molecu...

Construction of a molecular diagnostic system for neurogenic rosacea by combining transcriptome sequencing and machine learning.

BMC medical genomics
Patients with neurogenic rosacea (NR) frequently demonstrate pronounced neurological manifestations, often unresponsive to conventional therapeutic approaches. A molecular-level understanding and diagnosis of this patient cohort could significantly g...

High-Throughput and Integrated CRISPR/Cas12a-Based Molecular Diagnosis Using a Deep Learning Enabled Microfluidic System.

ACS nano
CRISPR/Cas-based molecular diagnosis demonstrates potent potential for sensitive and rapid pathogen detection, notably in SARS-CoV-2 diagnosis and mutation tracking. Yet, a major hurdle hindering widespread practical use is its restricted throughput,...

No longer stuck in the past: new advances in artificial intelligence and molecular assays for parasitology screening and diagnosis.

Current opinion in infectious diseases
PURPOSE OF REVIEW: Emerging technologies are revolutionizing parasitology diagnostics and challenging traditional methods reliant on microscopic analysis or serological confirmation, which are known for their limitations in sensitivity and specificit...

Deep Learning Enabled Universal Multiplexed Fluorescence Detection for Point-of-Care Applications.

ACS sensors
There is a significant demand for multiplexed fluorescence sensing and detection across a range of applications. Yet, the development of portable and compact multiplexable systems remains a substantial challenge. This difficulty largely stems from th...

Enhanced detection of Listeria monocytogenes using tetraethylenepentamine-functionalized magnetic nanoparticles and LAMP-CRISPR/Cas12a-based biosensor.

Analytica chimica acta
BACKGROUND: Listeria monocytogenes is a pathogenic bacterium that can lead to severe illnesses, especially among vulnerable populations. Therefore, the development of rapid and sensitive detection methods is vital to prevent and manage foodborne dise...

Ferrobotic swarms enable accessible and adaptable automated viral testing.

Nature
Expanding our global testing capacity is critical to preventing and containing pandemics. Accordingly, accessible and adaptable automated platforms that in decentralized settings perform nucleic acid amplification tests resource-efficiently are requi...

A deep learning-driven low-power, accurate, and portable platform for rapid detection of COVID-19 using reverse-transcription loop-mediated isothermal amplification.

Scientific reports
This paper presents a deep learning-driven portable, accurate, low-cost, and easy-to-use device to perform Reverse-Transcription Loop-Mediated Isothermal Amplification (RT-LAMP) to facilitate rapid detection of COVID-19. The 3D-printed device-powered...

NGS and phenotypic ontology-based approaches increase the diagnostic yield in syndromic retinal diseases.

Human genetics
Syndromic retinal diseases (SRDs) are a group of complex inherited systemic disorders, with challenging molecular underpinnings and clinical management. Our main goal is to improve clinical and molecular SRDs diagnosis, by applying a structured pheno...