Krupal P. Jethava
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View article: Impact Induces Phagocytic Defect in Reactive Microglia
Impact Induces Phagocytic Defect in Reactive Microglia Open
Summary We have developed traumatic brain injury (TBI)-on-a-chip in vitro models using primary microglia and neuronal networks and recorded the molecular and cellular changes following impact to represent impact injury. Using a pH-responsi…
View article: Amyloid β Induces Lipid Droplet-Mediated Microglial Dysfunction in Alzheimer’s Disease
Amyloid β Induces Lipid Droplet-Mediated Microglial Dysfunction in Alzheimer’s Disease Open
Summary Several microglia-expressed genes have emerged as top risk variants for Alzheimer’s disease (AD). Impaired microglial phagocytosis is one of the main proposed outcomes by which these AD-risk genes may contribute to neurodegeneratio…
View article: Graph Neural Networks Bootstrapped for Synthetic Selection and Validation of Small Molecule Immunomodulators
Graph Neural Networks Bootstrapped for Synthetic Selection and Validation of Small Molecule Immunomodulators Open
The Programmed Cell Death Protein 1/Programmed Death-Ligand 1 (PD-1/PD-L1) interaction is an immune checkpoint utilized by cancer cells to enhance immune suppression. There is a huge need to develop small molecule drugs that are fast actin…
View article: Graph Neural Networks Bootstrapped for Synthetic Selection and Validation of Small Molecule Immunomodulators
Graph Neural Networks Bootstrapped for Synthetic Selection and Validation of Small Molecule Immunomodulators Open
The Programmed Cell Death Protein 1/Programmed Death-Ligand 1 (PD-1/PD-L1) interaction is an immune checkpoint utilized by cancer cells to enhance immune suppression. There is a huge need to develop small molecule drugs that are fast actin…
View article: One Scaffold, Different Organelle Sensors: pH‐Activable Fluorescent Probes for Targeting Live Microglial Cell Organelles**
One Scaffold, Different Organelle Sensors: pH‐Activable Fluorescent Probes for Targeting Live Microglial Cell Organelles** Open
Targeting live cell organelles is essential for imaging, understanding, and controlling specific biochemical processes. Typically, fluorescent probes with distinct structural scaffolds are used to target specific cell organelles. Here, we …
View article: One Scaffold – Different Organelles Sensors: pH-Activable Fluorescent Probes for Targeting Live Primary Microglial Cell Organelles
One Scaffold – Different Organelles Sensors: pH-Activable Fluorescent Probes for Targeting Live Primary Microglial Cell Organelles Open
Targeting live cell organelles is important for imaging and to understand and control specific biochemical processes. Typically, fluorescent probes with distinct structural scaffolds have been used for targeting specific cell organelle. He…
View article: Monitoring phagocytic uptake of amyloid β into glial cell lysosomes in real time
Monitoring phagocytic uptake of amyloid β into glial cell lysosomes in real time Open
Glial cell phagocytosis of pH-dependent amyloid-β, Aβ pH , in live and fixed cultures, brain tissue sections, retina, cortex and in live animals useful for studying function in health and disease.
View article: Accelerated Reactivity Mechanism and Interpretable Machine Learning Model of N-Sulfonylimines Towards Fast Multicomponent Reactions
Accelerated Reactivity Mechanism and Interpretable Machine Learning Model of N-Sulfonylimines Towards Fast Multicomponent Reactions Open
Predicting the outcome of chemical reactions using machine learning models has emerged as a promising research area in chemical science. However, the use of such models to prospectively test new reactions by interpreting chemical reactivit…
View article: Accelerated Reactivity Mechanism and Interpretable Machine Learning Model of N-Sulfonylimines Towards Fast Multicomponent Reactions
Accelerated Reactivity Mechanism and Interpretable Machine Learning Model of N-Sulfonylimines Towards Fast Multicomponent Reactions Open
Predicting the outcome of chemical reactions using machine learning models has emerged as a promising research area in chemical science. However, the use of such models to prospectively test new reactions by interpreting chemical reactivit…
View article: Combined Molecular Graph Neural Network and Structural Docking Selects Potent Programmable Cell Death Protein 1/Programmable Death-Ligand 1 (PD-1/PD-L1) Small Molecule Inhibitors
Combined Molecular Graph Neural Network and Structural Docking Selects Potent Programmable Cell Death Protein 1/Programmable Death-Ligand 1 (PD-1/PD-L1) Small Molecule Inhibitors Open
The Programmable Cell Death Protein 1/Programmable Death-Ligand 1 (PD-1/PD-L1) interaction is an immune checkpoint utilized by cancer cells to enhance immune suppression. There exists a huge need to develop small molecules drugs that are f…
View article: Combined Molecular Graph Neural Network and Structural Docking Selects Potent Programmable Cell Death Protein 1/Programmable Death-Ligand 1 (PD-1/PD-L1) Small Molecule Inhibitors
Combined Molecular Graph Neural Network and Structural Docking Selects Potent Programmable Cell Death Protein 1/Programmable Death-Ligand 1 (PD-1/PD-L1) Small Molecule Inhibitors Open
The Programmable Cell Death Protein 1/Programmable Death-Ligand 1 (PD-1/PD-L1) interaction is an immune checkpoint utilized by cancer cells to enhance immune suppression. There exists a huge need to develop small molecules drugs that are f…
View article: Monitoring phagocytic uptake of amyloid β into glial cell lysosomes in real time
Monitoring phagocytic uptake of amyloid β into glial cell lysosomes in real time Open
Phagocytosis by glial cells is essential to regulate brain function during development and disease. Given recent interest in using amyloid β (Aβ)-targeted antibodies as a therapy for patients with Alzheimer’s disease, removal of Aβ by phag…
View article: Spectral Deep Learning for Prediction and Prospective Validation of Functional Groups
Spectral Deep Learning for Prediction and Prospective Validation of Functional Groups Open
State-of-the-art identification of the functional groups present in an unknown chemical entity requires expertise of a skilled spectroscopist to analyse and interpret Fourier Transform Infra-Red (FTIR), Mass Spectroscopy (MS) and/or Nuclea…
View article: Spectral deep learning for prediction and prospective validation of functional groups
Spectral deep learning for prediction and prospective validation of functional groups Open
A new multi-label deep neural network architecture is used to combine Infrared and mass spectra, trained on single compounds to predict functional groups, and experimentally validated on complex mixtures.
View article: Rapid, Refined, and Robust Method for Expression, Purification, and Characterization of Recombinant Human Amyloid beta 1-42
Rapid, Refined, and Robust Method for Expression, Purification, and Characterization of Recombinant Human Amyloid beta 1-42 Open
Amyloid plaques found in the brains of Alzheimer’s disease patients primarily consists of amyloid beta 1-42 (Aβ42). Commercially, Aβ42 is synthesized using high-throughput peptide synthesizers resulting in the presence of impurities and th…
View article: Spectral Deep Learning for Prediction and Prospective Validation of Functional Groups
Spectral Deep Learning for Prediction and Prospective Validation of Functional Groups Open
State-of-the-art identification of the functional groups present in an unknown chemical entity requires expertise of a skilled spectroscopist to analyse and interpret Fourier Transform Infra-Red (FTIR), Mass Spectroscopy (MS) and/or Nuclea…
View article: Rapid, Refined, and Robust Method for Expression, Purification, and Characterization of Recombinant Human Amyloid-beta M1-42
Rapid, Refined, and Robust Method for Expression, Purification, and Characterization of Recombinant Human Amyloid-beta M1-42 Open
Amyloid plaques found in the brains of Alzheimer’s disease (AD) patients primarily consists of amyloid beta 1-42 (Ab42). Commercially, Ab42 is synthetized using peptide synthesizers. We describe a robust methodology for expression of recom…
View article: Rapid, Refined, and Robust Method for Expression, Purification, and Characterization of Recombinant Human Amyloid-beta M1-42
Rapid, Refined, and Robust Method for Expression, Purification, and Characterization of Recombinant Human Amyloid-beta M1-42 Open
Amyloid plaques found in the brains of Alzheimer’s disease (AD) patients primarily consists of amyloid beta 1-42 (Ab42). Commercially, Ab42 is synthetized using peptide synthesizers. We describe a robust methodology for expression of recom…