The Effects of Different Brain Regions on fNIRS-based Task-state Detection in Speech Imagery.

Brain-computer interface (BCI) based on speech imagery can decode users' verbal intent and help people with motor disabilities communicate naturally. Functional near-infrared spectroscopy (fNIRS) is a commonly used brain signal acquisition method. Asynchronous BCI can response to control commands at any time, which provides great convenience for users. Task state detection, defined as identifying whether user starts or continues covertly articulating, plays an important role in speech imagery BCIs. To better distinguish task state from idle state during speech imagery, this work used fNIRS signals from different brain regions to study the effects of different brain regions on task state detection accuracy. The imagined tonal syllables included four lexical tones and four vowels in Mandarin Chinese. The brain regions that were measured included Broca's area, Wernicke's area, Superior temporal cortex and Motor cortex. Task state detection accuracies of imagining tonal monosyllables with four different tones were analyzed. The average accuracy of four speech imagery tasks based on the whole brain was 0.67 and it was close to 0.69, which was the average accuracy based on Broca's area. The accuracies of Broca's area and the whole brain were significantly higher than those of other brain regions. The findings of this work demonstrated that using a few channels of Broca's area could result in a similar task state detection accuracy to that using all the channels of the brain. Moreover, it was discovered that speech imagery with tone 2/3 tasks yielded higher task state detection accuracy than speech imagery with other tones.

From materials to clinical use: advances in 3D-printed scaffolds for cartilage tissue engineering.

Osteoarthritis caused by articular cartilage defects is a particularly common orthopedic disease that can involve the entire joint, causing great pain to its sufferers. A global patient population of approximately 250 million people has an increasing demand for new therapies with excellent results, and tissue engineering scaffolds have been proposed as a potential strategy for the repair and reconstruction of cartilage defects. The precise control and high flexibility of 3D printing provide a platform for subversive innovation. In this perspective, cartilage tissue engineering (CTE) scaffolds manufactured using different biomaterials are summarized from the perspective of 3D printing strategies, the bionic structure strategies and special functional designs are classified and discussed, and the advantages and limitations of these CTE scaffold preparation strategies are analyzed in detail. Finally, the application prospect and challenges of 3D printed CTE scaffolds are discussed, providing enlightening insights for their current research.

Extraction of total wheat (Triticum aestivum) protein fractions and cross-reactivity of wheat allergens with other cereals.

A one-step mild extraction of total wheat protein fractions was developed in this study, and the allergic cross-reactivity among dietary cereals were assessed by SDS-PAGE, western blotting, indirect ELISA, and inhibition ELISA using sera from 12 wheat allergic patients. The fractions of albumin, globulin, gliadin and glutenins in wheat flour can be obtained by a one-step extraction with Na2CO3-NaHCO3 (20 mM, pH 9.6, 0.5 M NaCl, 40% ethanol, 1 mM PMSF) in comparison to sequential extractions. Results showed high cross-reactivity in wheat, barley and rye due to close resemblance and high sequence identity (>50%), whereas nearly negligible cross-reactivity among rice, buckwheat, and quinoa was observed. Our research findings suggest that people with wheat allergy should rely primarily on the use of rice, quinoa and non-grain buckwheat, which is an effective substitute for wheat, while those with hypersensitivity should avoid the use of barley and rye in their diet.