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PredAPP: Predicting Anti-Parasitic Peptides with Undersampling and Ensemble Approaches.

Anti-parasitic peptides (APPs) have been regarded as promising therapeutic candidate drugs against parasitic diseases. Due to the fact that the experimental techniques for identifying APPs are expensive and time-consuming, there is an urgent need to develop a computational approach to predict APPs on a large scale. In this study, we provided a computational method, termed PredAPP (Prediction of An...

Long-term effect of tocilizumab on left ventricular hypertrophy and systolic dysfunction in AA amyloidosis with rheumatoid arthritis.

Because cardiac involvement of amyloid A (AA) is not frequent, little is known about the effects of tocilizumab (TCZ; a humanized monoclonal anti-interleukin-6 receptor antibody). We present the case of a 77-year-old man with cardiac AA amyloidosis due to rheumatoid arthritis (RA). He was admitted to our hospital because of gastrointestinal bleeding. Upon admission, chest radiography and electroca...

Machine learning risk prediction model for acute coronary syndrome and death from use of non-steroidal anti-inflammatory drugs in administrative data.

Our aim was to investigate the usefulness of machine learning approaches on linked administrative health data at the population level in predicting ol...

Repurposing non-oncology small-molecule drugs to improve cancer therapy: Current situation and future directions.

Drug repurposing or repositioning has been well-known to refer to the therapeutic applications of a drug for another indication other than it was orig...

Development of a gold-nanorod-based lateral flow immunoassay for a fast and dual-modal detection of C-reactive protein in clinical plasma samples.

Fast and simple detection of C-reactive protein (CRP) is highly significant for the diagnosis and prognosis of inflammatory or infectious diseases. La...

Syringaresinol derived from berry attenuates oxidative stress-induced skin aging via autophagy.

BACKGROUND: In aged skin, reactive oxygen species (ROS) induces degradation of the extracellular matrix (ECM), leading to visible aging signs. Collage...

A Novel Anti-Noise Fault Diagnosis Approach for Rolling Bearings Based on Convolutional Neural Network Fusing Frequency Domain Feature Matching Algorithm.

The development of deep learning provides a new research method for fault diagnosis. However, in the industrial field, the labeled samples are insuffi...

The Role of Deep Learning-Based Echocardiography in the Diagnosis and Evaluation of the Effects of Routine Anti-Heart-Failure Western Medicines in Elderly Patients with Acute Left Heart Failure.

OBJECTIVE: The role of deep learning-based echocardiography in the diagnosis and evaluation of the effects of routine anti-heart-failure Western medic...

Deep learning based joint segmentation and characterization of multi-class retinal fluid lesions on OCT scans for clinical use in anti-VEGF therapy.

BACKGROUND: In anti-vascular endothelial growth factor (anti-VEGF) therapy, an accurate estimation of multi-class retinal fluid (MRF) is required for ...

Design, synthesis and mechanistic study of new benzenesulfonamide derivatives as anticancer and antimicrobial agents carbonic anhydrase IX inhibition.

Changes in gene expression cause uncontrolled cell proliferation and consequently tumor hypoxia. The tumor cells shift their metabolism to anaerobic g...

A computational model of familiarity detection for natural pictures, abstract images, and random patterns: Combination of deep learning and anti-Hebbian training.

We present a neural network model for familiarity recognition of different types of images in the perirhinal cortex (the FaRe model). The model is des...

Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade.

Anti-PD-1 immunotherapy has recently shown tremendous success for the treatment of several aggressive cancers. However, variability and unpredictabili...

Future minds and a new challenge to anti-natalism.

Some futurists and philosophers have urged that recent developments in biotechnology promise advancements that challenge standard accepted views of hu...

Seasonal dynamics of the phenolic constituents of the cones and leaves of oriental ( L.) reveal their anti-inflammatory biomarkers.

In this study, the seasonal dynamics of the flavonoids in the cones and leaves of oriental ( L. Franco) as well as the anti-inflammatory activity of...

Antimicrobial behavior and mechanism of clove oil nanoemulsion.

Clove oil has many functions such as antibacterial, anti-inflammatory, anti-oxidation. In this experiment, a self-emulsification method was used to pr...

Discovery of quinolone derivatives as antimycobacterial agents.

Tuberculosis (TB), an infectious disease caused by (), is an important public health issue. Current first-line drugs administered to TB patients have...

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 electronic health records (EHRs) offers a unique oppo...

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-cells, is being investigated as a potential therap...

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 with non-small-cell lung cancer (NSCLC), but only s...

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 types of inflammatory conditions. Diclofenac is a ve...