Rheumatoid Arthritis

Reliable prediction of cannabinoid receptor 2 ligand by machine learning based on combined fingerprints.

Cannabinoid receptors, as part of the family of the G protein-coupled receptors (GPCRs), are involved in various physiological functions. Its subtype cannabinoid receptor subtype 2 (CB2), mainly distributed in the periphery, is a crucial therapeutic target for anti-epileptic, anti-inflammation, anti-fibrosis, and bone metabolism regulation, and it regulates these physiological functions without ps...

Compact artificial neuron based on anti-ferroelectric transistor.

Neuromorphic machines are intriguing for building energy-efficient intelligent systems, where spiking neurons are pivotal components. Recently, memristive neurons with promising bio-plausibility have been developed, but with limited reliability, bulky capacitors or additional reset circuits. Here, we propose an anti-ferroelectric field-effect transistor neuron based on the inherent polarization an...

Continuous Estimation of Human Joint Angles From sEMG Using a Multi-Feature Temporal Convolutional Attention-Based Network.

Intention recognition based on surface electromyography (sEMG) signals is pivotal in human-machine interaction (HMI), where continuous motion estimati...

Microfluidics guided by deep learning for cancer immunotherapy screening.

Immunocyte infiltration and cytotoxicity play critical roles in both inflammation and immunotherapy. However, current cancer immunotherapy screening m...

Complementary Memtransistor-Based Multilayer Neural Networks for Online Supervised Learning Through (Anti-)Spike-Timing-Dependent Plasticity.

We propose a complete hardware-based architecture of multilayer neural networks (MNNs), including electronic synapses, neurons, and periphery circuitr...

De novo design of anti-tuberculosis agents using a structure-based deep learning method.

Mycobacterium tuberculosis (Mtb) is a pathogen of major concern due to its ability to withstand both first- and second-line antibiotics, leading to dr...

Shared subspace-based radial basis function neural network for identifying ncRNAs subcellular localization.

Non-coding RNAs (ncRNAs) play an important role in revealing the mechanism of human disease for anti-tumor and anti-virus substances. Detecting subcel...

Design and implementation of an adaptive fuzzy sliding mode controller for drug delivery in treatment of vascular cancer tumours and its optimisation using genetic algorithm tool.

In this paper, the side effects of drug therapy in the process of cancer treatment are reduced by designing two optimal non-linear controllers. The re...

A systematic review of robot-assisted anti-reflux surgery to examine reporting standards.

Robot-assisted anti-reflux surgery (RA-ARS) is increasingly being used to treat refractory gastro-oesophageal reflux disease. The IDEAL (Idea, Develop...

Prediction of the Lotus Effect on Solid Surfaces by Machine Learning.

Superhydrophobic surfaces with the "lotus effect" have wide applications in daily life and industry, such as self-cleaning, anti-freezing, and anti-co...

Robotic single port anti-reflux surgery: Initial worldwide experience of two cases with a novel surgical approach to treat gastroesophageal reflux disease.

INTRODUCTION: To date, no anti-reflux operations have been reported with the new da Vinci Single-Port (single port (SP)) robotic platform. We aimed to...

Development of GBRT Model as a Novel and Robust Mathematical Model to Predict and Optimize the Solubility of Decitabine as an Anti-Cancer Drug.

The efficient production of solid-dosage oral formulations using eco-friendly supercritical solvents is known as a breakthrough technology towards dev...

Anti-Colorectal Cancer Effects of (Bull.: Fr.) P. Karst. Spore Powder through Regulation of Gut Microbiota-Mediated JAK/STAT Signaling.

(Bull.: Fr.) P. Karst. spore powder (IHS) contains polyphenols and triterpenoids with pharmacological effects. Here, we analyzed its composition, and...

Simultaneous regression and classification for drug sensitivity prediction using an advanced random forest method.

Machine learning methods trained on cancer cell line panels are intensively studied for the prediction of optimal anti-cancer therapies. While classif...

Revisiting Light Field Rendering With Deep Anti-Aliasing Neural Network.

The light field (LF) reconstruction is mainly confronted with two challenges, large disparity and the non-Lambertian effect. Typical approaches either...

Prediction of Anti-proliferation Effect of [1,2,3]Triazolo[4,5-d]pyrimidine Derivatives by Random Forest and Mix-Kernel Function SVM with PSO.

In order to predict the anti-gastric cancer effect of [1,2,3]triazolo[4,5-d]pyrimidine derivatives (1,2,3-TPD), quantitative structure-activity relati...

The involvement of gut microbiota in the anti-tumor effect of carnosic acid via IL-17 suppression in colorectal cancer.

Colorectal cancer (CRC) is a malignant tumor that threatens human health worldwide. Disturbance of the gut microbiota caused by various external facto...

Design of predictive model to optimize the solubility of Oxaprozin as nonsteroidal anti-inflammatory drug.

These days, many efforts have been made to increase and develop the solubility and bioavailability of novel therapeutic medicines. One of the most bel...

Deep Learning-Based Image Analysis for the Quantification of Tumor-Induced Angiogenesis in the 3D In Vivo Tumor Model-Establishment and Addition to Laser Speckle Contrast Imaging (LSCI).

(1) Background: angiogenesis plays an important role in the growth and metastasis of tumors. We established the CAM assay application, an image analys...

Deep learning for de-convolution of Smad2 versus Smad3 binding sites.

BACKGROUND: The transforming growth factor beta-1 (TGF β-1) cytokine exerts both pro-tumor and anti-tumor effects in carcinogenesis. An increasing bod...