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In this study, a multi-scale high-density convolutional neural network (MHCNN) classification method for spatial cognitive ability assessment was proposed, aiming at achieving the binary classification of task-state EEG signals before and after spatial cognitive training. Besides, the multi-dimensional conditional mutual information method was used to extract the frequency band features of the EEG data. And the coupling features under the combination of multi-frequency bands were transformed into multi-spectral images. At the same time, the idea of Densenet was introduced to improve the multi-scale convolutional neural network. Firstly, according to the discreteness of multispectral EEG image features, two-scale convolution kernels were used to calculate and learn useful channel and frequency band feature information in multispectral image data. Secondly, to enhance feature propagation and reduce the number of parameters, the dense network was connected after the multi-scale convolutional network, and the learning rate change function of the stochastic gradient descent algorithm was optimized to objectively evaluate the training effect. The experimental results showed that compared with the classical convolution neural network (CNN) and multi-scale convolution neural network, the proposed MHCNN had better classification performance in the six frequency band combinations with the highest accuracy of 98%: Theta-Alpha2-Gamma, Alpha2-Beta2-Gamma, Beta1-Beta2-Gamma, Theta-Beta2-Gamma, Theta- Alpha1-Gamma, and Alpha1-Alpha2-Gamma. By comparing the classification results of six frequency band combinations, it was found that the combination of the Theta-Beta2-Gamma band had the best classification effect. The MHCNN classification method proposed in this research could be used as an effective biological indicator of spatial cognitive training effect and could be extended to other brain function evaluations.

Abstract Background Traditional medial malleolar osteotomy combined with autologous osteochondral transplantation (AOT) is mostly used in the treatment of osteochondral lesions of the talus (OLTs), but with high osteotomy and donor site complications. We hypothesis a new triplane medial malleolar osteotomy combined with AOT from non-weight-bearing area of the talus could be a promising choice for OLTs. Methods We reviewed all the symptomatic OLTs patients who received AOT with triplane osteotomy of the medial malleolus between September 2015 and December 2017 in our department. According to the inclusion and exclusion criteria, 23 patients (23 ankles), including 14 males and 9 females, were included in the study. The mean age was 35.6 years. The mean size of the lesion area was 141.5 mm2. According Ferkel’s classification, including 5 type I, 11 typeIIa and 7 typeIIb. The visual analog scale (VAS) for pain during walking and the American Orthopaedic Foot and Ankle Society (AOFAS) ankle-hindfoot score were used for the pre- and postoperative evaluations. In addition, the incorporation of the grafts was assessed by computed tomography (CT). Results All patients had a minimum follow-up of 22 months, with an average of 37.1 months. The mean time from osteotomy to full weight-bearing activity was 8.1 ± 2.3 weeks (range, 5–12 weeks). The mean VAS score improved from 5.6 ± 0.7 preoperatively to 0.7 ± 1.0 postoperatively (P

Reversing the thermal induced sintering phenomenon and forming high temperature stable fine dispersed metallic centers is one of the ever-lasting targets in heterogeneous catalysis. Here the authors report the dispersion of metallic Ni particles into under-coordinated two-dimensional Ni clusters over γ-Mo2N.

Exosomes have attracted increasing attention in the early diagnosis of tumors due to their participation in physiological and pathological processes. Herein, a novel label-free aptasensor based on the CuNi bimetallic metal–organic frameworks (MOFs) that was decorated with MXene quantum dots (MQDs) was fabricated for exosome sensing. The CuNi-MOFs functionalized with dual specific aptamers, CD63 and MUC1, served as an ideal nanocarrier and catalyst for efficient recognition and capture of target exosomes. Meanwhile, the MQDs with excellent electron transfer can promote the electrochemical catalytic performance of this designed aptasensor. It is noteworthy that the large specific surface area of 2D bimetallic CuNi-MOF nanosheets can offer plenty of exposed active sites and facilitate the connection of aptamers, thereby achieving the goal of specific capture and detection of exosomes. The as-prepared electrochemical aptasensor possesses a wide linear range of 1 × 101 to 1 × 106 particles μL−1 for exosome detection and a low detection limit of 5 particles μL−1 (S/N = 3). Besides, the as-prepared aptasensor exhibited satisfactory electrochemical stability for the detection of exosomes, which can provide new ideas for clinical detection and tumor diagnosis. [ABSTRACT FROM AUTHOR]

This document provides a list of references to scientific articles and papers related to topics such as Alzheimer's disease, cognitive decline, virtual reality, and machine learning. The articles cover a range of subjects including biomarkers for Alzheimer's disease diagnosis, cognitive training interventions, the use of virtual reality in assessing cognitive impairment, and the application of machine learning in healthcare. These references can be helpful for library patrons conducting research on these specific topics. [Extracted from the article]

This collection of articles explores the use of virtual reality (VR) technology in assessing and improving cognitive function, specifically executive functions. The articles cover a variety of topics, including the assessment of attention profiles in children with brain injuries, cognitive training for older adults using VR-based exergaming, and the development of virtual environments for assessing everyday cognitive function. The articles also discuss the use of EEG and other neuroimaging techniques in combination with VR for measuring cognitive load and identifying psychiatric disorders. These articles offer valuable insights into the potential advantages of VR in cognitive assessment and rehabilitation. [Extracted from the article]