AIMC Topic: Erythrocytes

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Cell-Like Micromotors.

Accounts of chemical research
In the past decade, versatile micro- and nanosized machines have emerged as active agents for large-scale detoxification, sensing, microfabrication, and many other promising applications. Micromachines have also been envisioned as the next advancemen...

Catechin rich butanol fraction extracted from Acacia catechu L. (a thirst quencher) exhibits immunostimulatory potential.

Journal of food and drug analysis
Acacia catechu L., (Fabaceae) named as "catechu" is a plant, the decoction of heartwood of which is daily consumed as thirst quencher by a good percentage of the population in South India. The plant is mainly distributed in India and other Asian coun...

Machine learning-based in-line holographic sensing of unstained malaria-infected red blood cells.

Journal of biophotonics
Accurate and immediate diagnosis of malaria is important for medication of the infectious disease. Conventional methods for diagnosing malaria are time consuming and rely on the skill of experts. Therefore, an automatic and simple diagnostic modality...

Machine learning prioritizes synthesis of primaquine ureidoamides with high antimalarial activity and attenuated cytotoxicity.

European journal of medicinal chemistry
Primaquine (PQ) is a commonly used drug that can prevent the transmission of Plasmodium falciparum malaria, however toxicity limits its use. We prepared five groups of PQ derivatives: amides 1a-k, ureas 2a-k, semicarbazides 3a,b, acylsemicarbazides 4...

Calli Essential Oils Synergize with Lawsone against Multidrug Resistant Pathogens.

Molecules (Basel, Switzerland)
The fast development of multi-drug resistant (MDR) organisms increasingly threatens global health and well-being. Plant natural products have been known for centuries as alternative medicines that can possess pharmacological characteristics, includin...

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

Biosensors & bioelectronics
Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate eryt...

A deep convolutional neural network for classification of red blood cells in sickle cell anemia.

PLoS computational biology
Sickle cell disease (SCD) is a hematological disorder leading to blood vessel occlusion accompanied by painful episodes and even death. Red blood cells (RBCs) of SCD patients have diverse shapes that reveal important biomechanical and bio-rheological...

Very Deep Convolutional Neural Networks for Morphologic Classification of Erythrocytes.

Clinical chemistry
BACKGROUND: Morphologic profiling of the erythrocyte population is a widely used and clinically valuable diagnostic modality, but one that relies on a slow manual process associated with significant labor cost and limited reproducibility. Automated p...