N6-methyladenosine-modified circCDK14 promotes ossification of the ligamentum flavum via epigenetic modulation by targeting AFF4.

Background: The ligamentum flavum (LF) is an important anatomical structure of the spine. Ossification of the LF (OLF) has become the leading cause of thoracic spinal stenosis. Circular RNAs (circRNAs) and N6-methyladenosine (m6A) modification are reported to be associated with several human diseases.

HTRA1 from OVX rat osteoclasts causes detrimental effects on endplate chondrocytes through NF-κB.

Endplate osteochondritis is considered one of the major causes of intervertebral disc degeneration (IVDD) and low back pain. Menopausal women have a higher rate of endplate cartilage degeneration than similarly aged men, but the related mechanisms are still unclear. Subchondral bone changes, mainly mediated by osteoblasts and osteoclasts, are considered an important reason for the degeneration of cartilage.

Associations of Homocysteine, Folate, and Vitamin B12 with Osteoarthritis: A Mendelian Randomization Study.

Homocysteine, inversely related to folate and vitamin B12, is an independent risk factor for several age-related disorders. However, little is known about the association of homocysteine and related vitamins with osteoarthritis (OA). This study aimed to elucidate the potential causal effects of homocysteine, folate, and vitamin B12 on site- and gender-specific OA by applying the two-sample Mendelian randomization (MR) approach.

Enhancement of motor imagery training efficiency by an online adaptive training paradigm integrated with error related potential.

. Motor imagery (MI) is a process of autonomously modulating the motor area to rehearse action mentally without actual execution. Based on the neuroplasticity of the cerebral cortex, MI can promote the functional rehabilitation of the injured cerebral cortex motor area.

Data Augmentation for Motor Imagery Signal Classification Based on a Hybrid Neural Network.

As an important paradigm of spontaneous brain-computer interfaces (BCIs), motor imagery (MI) has been widely used in the fields of neurological rehabilitation and robot control. Recently, researchers have proposed various methods for feature extraction and classification based on MI signals. The decoding model based on deep neural networks (DNNs) has attracted significant attention in the field of MI signal processing.

Steady-State Motion Visual Evoked Potential (SSMVEP) Enhancement Method Based on Time-Frequency Image Fusion.

The steady-state motion visual evoked potential (SSMVEP) collected from the scalp suffers from strong noise and is contaminated by artifacts such as the electrooculogram (EOG) and the electromyogram (EMG). Spatial filtering methods can fuse the information of different brain regions, which is beneficial for the enhancement of the active components of the SSMVEP. Traditional spatial filtering methods fuse electroencephalogram (EEG) in the time domain.

Human action recognition based on kinematic similarity in real time.

Human action recognition using 3D pose data has gained a growing interest in the field of computer robotic interfaces and pattern recognition since the availability of hardware to capture human pose. In this paper, we propose a fast, simple, and powerful method of human action recognition based on human kinematic similarity. The key to this method is that the action descriptor consists of joints position, angular velocity and angular acceleration, which can meet the different individual sizes and eliminate the complex normalization.

Measuring cervical vertebra movements using kinect sensor.

The incidence of cervical vertebra spondylosis is increasing with the pace of life while there is no high-efficient measurement method. This study proposed a non-contact, high-efficient, and high-precisionmethod measuring the cervical vertebra activities which obtains the cervical vertebra activities by combining the function of skeletal tracking and face tracking. A comparison study between the proposed and traditional methods has been conducted here.