Lupus

Discovery of quinolone derivatives as antimycobacterial agents.

Tuberculosis (TB), an infectious disease caused by (), is an important public health issue. Current...

Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort.

Drug-drug interactions account for up to 30% of adverse drug reactions. Increasing prevalence of ele...

Orthogonal quantification of soluble inducible T-cell costimulator (ICOS) in healthy and diseased human serum.

Inducible T-cell costimulator (ICOS), a homodimeric protein expressed on the surface of activated T-...

Clinical decision support algorithm based on machine learning to assess the clinical response to anti-programmed death-1 therapy in patients with non-small-cell lung cancer.

OBJECTIVE: Anti-programmed death (PD)-1 therapy confers sustainable clinical benefits for patients w...

Self-assembly of diclofenac prodrug into nanomicelles for enhancing the anti-inflammatory activity.

Non-steroidal anti-inflammatory drugs (NSAIDs) are widely prescribed for the treatment of various ty...

Development of a fluorescent immunochromatographic assay based on quantum dots for the detection of fleroxacin.

Fleroxacin (FLE) is a broad-spectrum fluoroquinolone antibiotic widely used in animal husbandry, vet...

One-step-immunoassay of procalcitonin enables rapid and accurate diagnosis of bacterial infection.

Procalcitonin (PCT) ( a precursor of calcitonin) attracts much attention as a reliable biomarker of ...

Cisplatin and paclitaxel co-delivery nanosystem for ovarian cancer chemotherapy.

We have designed and developed an effective drug delivery system using biocompatible polymer of poly...

Development and validation of consensus machine learning-based models for the prediction of novel small molecules as potential anti-tubercular agents.

Tuberculosis (TB) is an infectious disease and the leading cause of death globally. The rapidly emer...

Immunomodulatory and antimicrobial non-mulberry silk fibroin accelerates fibroblast repair and regeneration by protecting oxidative stress.

The antimicrobial nature of silk-fibroin (SF) is reported but antioxidant potential and the immunom...

5FU encapsulated polyglycerol sebacate nanoparticles as anti-cancer drug carriers.

The majority of anti-cancer drugs fail to reach clinical trials due to their low water solubility. A...

Efficient extraction of bioactive flavonoids from leaves using deep eutectic solvent as green media.

In recent years, deep eutectic solvent (DES) has attracted comprehensive attention on the extraction...

Anti-transfer learning for task invariance in convolutional neural networks for speech processing.

We introduce the novel concept of anti-transfer learning for speech processing with convolutional ne...

Texture analysis of muscle MRI: machine learning-based classifications in idiopathic inflammatory myopathies.

To develop a machine learning (ML) model that predicts disease groups or autoantibodies in patients ...

Finite-time control of delay switched systems via input anti-bump switching.

This article devotes to the finite-time (FT) input anti-bump switching control (SC) issue for a kind...

A Zwitterionic-Aromatic Motif-Based ionic skin for highly biocompatible and Glucose-Responsive sensor.

Electronic skins that can sense external stimuli have been of great significance in artificial intel...

A computational method for drug sensitivity prediction of cancer cell lines based on various molecular information.

Determining sensitive drugs for a patient is one of the most critical problems in precision medicine...

Artificial Intelligence-Assisted Amphiregulin and Epiregulin IHC Predicts Panitumumab Benefit in Wild-Type Metastatic Colorectal Cancer.

PURPOSE: High tumor mRNA levels of the EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are as...

Response to "Reply to 'A deep learning-based smartphone platform for cutaneous lupus erythematosus classification assistance: Simplifying the diagnosis of complicated diseases.' Has the complicated disease been simplified too much?" Artificial intelligence system is helpful for diagnosis of cutaneous lupus erythematosus.

Reply to "A deep learning-based smartphone platform for cutaneous lupus erythematosus classification assistance - simplifying the diagnosis of complicated diseases": Machine learning evaluations need to consider the true clinical context.

Application of deep learning and molecular modeling to identify small drug-like compounds as potential HIV-1 entry inhibitors.

A generative adversarial autoencoder for the rational design of potential HIV-1 entry inhibitors abl...