Automatic classification of nerve discharge rhythms based on sparse auto-encoder and time series feature.

BACKGROUND: Nerve discharge is the carrier of information transmission, which can reveal the basic rules of various nerve activities. Recognition of the nerve discharge rhythm is the key to correctly understand the dynamic behavior of the nervous system. The previous methods for the nerve discharge recognition almost depended on the traditional statistical features, and the nonlinear dynamical features of the discharge activity. The artificial extraction and the empirical judgment of the features were required for the recognition. Thus, these methods suffered from subjective factors and were not conducive to the identification of a large number of discharge rhythms. RESULTS: The ability of automatic feature extraction along with the development of the neural network has been greatly improved. In this paper, an effective discharge rhythm classification model based on sparse auto-encoder was proposed. The sparse auto-encoder was used to construct the feature learning network. The simulated discharge data from the Chay model and its variants were taken as the input of the network, and the fused features, including the network learning features, covariance and approximate entropy of nerve discharge, were classified by Softmax. The results showed that the accuracy of the classification on the testing data was 87.5%, which could provide more accurate classification results. Compared with other methods for the identification of nerve discharge types, this method could extract the characteristics of nerve discharge rhythm automatically without artificial design, and show a higher accuracy. CONCLUSIONS: The sparse auto-encoder, even neural network has not been used to classify the basic nerve discharge from neither biological experiment data nor model simulation data. The automatic classification method of nerve discharge rhythm based on the sparse auto-encoder in this paper reduced the subjectivity and misjudgment of the artificial feature extraction, saved the time for the comparison with the traditional method, and improved the intelligence of the classification of discharge types. It could further help us to recognize and identify the nerve discharge activities in a new way.

Treatment outcomes of posterior pilon fractures using a simple single lateral approach via stretching fibular fracture line.

Purpose: The aim of this study was to explore the treatment outcomes of a novel single lateral approach via fibular fracture line for patients with posterior pilon fractures. Patients and methods: From January 2020 to December 2021, a total of 41 patients with posterior pilon fractures who received surgical treatment in our hospital were retrospectively reviewed. Twenty patients (Group A) were treated with open reduction and internal fixation (ORIF) via posterolateral approach. Twenty-one patients (Group B) were treated with ORIF using a simple single lateral approach via stretching fibular fracture line. Clinical assessments, including operation time, intraoperative blood loss, the American Orthopaedic Foot and Ankle Society (AOFAS) ankle-hindfoot score, visual analogue scale (VAS), and the active range of motion (ROM) of the ankle at the final follow-up visit after surgery, were performed in all patients. Radiographic outcome was evaluated by using the criteria proposed by Burwell and Charnley. Results: The mean follow-up time was 21 months (range 12-35). The average operation time and intraoperative blood loss in the Group B were significantly less than those in the Group A. Moreover, the AOFAS score and ankle ROM in the Group B were significantly higher than those in the Group A at the final follow-up visit. Eighteen cases (90%) in Group A and 19 cases (90.5%) in Group B achieved anatomical reduction of the fracture. Conclusion: The single lateral approach via stretching fibular fracture line is a simple and effective technique for reduction and fixation of posterior pilon fractures.

Repair of deep deltoid ligament ruptures near the medial malleolar attachment or midsubstance rupture by using suture anchors into the talus combined with the transosseous suture in the medial malleolar.

Purpose: For deep deltoid ligament ruptures near the medial malleolar attachment, anchors were usually placed at the posterior colliculus and intercollicular groove. However, this procedure usually requires a prolonged surgical incision to fully expose the deep deltoid ligament, causing more trauma. In order to reduce surgical trauma, we explored the treatment outcomes of suture anchor into the talus combined with transosseous suture in the medial malleolar for the treatment of deep deltoid ligament ruptures near the medial malleolar attachment or midsubstance rupture. Patients and methods: This is a retrospective study of patients who received suture anchor into the talus combined with transosseous suture in the medial malleolar for repairing deltoid ligament ruptures near the medial malleolar attachment or midsubstance rupture. The outcome measures include the American Orthopaedic Foot and Ankle Society (AOFAS) ankle-hindfoot score, visual analogue scale (VAS), and the active range of motion (ROM) of the ankle at the final follow-up visit after surgery. Medial malleolus gap was evaluated by radiographic examination. Results: This study included 64 patients. The mean follow-up time was 36.3 ± 15.2 months. There were 43 patients with injuries on the medial malleolar side, and 21 cases on the midsubstance. The average AOFAS and VAS were 87.5 ± 4.9 and 0.7 ± 0.5, respectively. No significance in medial malleolus gap between the contralateral side and affected side was observed. Conclusion: For deltoid ligament ruptures near the medial malleolar attachment or midsubstance rupture, suture anchor into the talus combined with transosseous suture in the medial malleolar yields good clinical effect and outcome, is an optimal management of ankle syndesmosis injuries.

Effect of potassium channel noise on nerve discharge based on the Chay model.

BACKGROUND: The nervous system senses and transmits information through the firing behavior of neurons, and this process is affected by various noises. However, in the previous study of the influence of noise on nerve discharge, the channel of some noise effects is not clear, and the difference from other noises was not examined. OBJECTIVE: To construct ion channel noise which is more biologically significant, and to clarify the basic characteristics of the random firing rhythm of neurons generated by different types of noise acting on ion channels. METHOD: Based on the dynamics of the ion channel, we constructed ion channel noise. We simulated the nerve discharge based on the Chay model of potassium ion channel noise, and used the nonlinear time series analysis method to measure the certainty and randomness of nerve discharge. RESULTS: In the Chay model with potassium ion noise, the chaotic rhythm defined by the original model could be effectively unified with the random rhythm simulated by the previous random Chay model into a periodic bifurcation process. CONCLUSION: This method clarified the influence of ion channel noise on nerve discharge, better understood the randomness of nerve discharge and provided a more reasonable explanation for the mechanism of nerve discharge.

Predicting subcellular localization of multisite proteins using differently weighted multi-label k-nearest neighbors sets.

BACKGROUND: For a protein to execute its function, ensuring its correct subcellular localization is essential. In addition to biological experiments, bioinformatics is widely used to predict and determine the subcellular localization of proteins. However, single-feature extraction methods cannot effectively handle the huge amount of data and multisite localization of proteins. Thus, we developed a pseudo amino acid composition (PseAAC) method and an entropy density technique to extract feature fusion information from subcellular multisite proteins. OBJECTIVE: Predicting multiplex protein subcellular localization and achieve high prediction accuracy. METHOD: To improve the efficiency of predicting multiplex protein subcellular localization, we used the multi-label k-nearest neighbors algorithm and assigned different weights to various attributes. The method was evaluated using several performance metrics with a dataset consisting of protein sequences with single-site and multisite subcellular localizations. RESULTS: Evaluation experiments showed that the proposed method significantly improves the optimal overall accuracy rate of multiplex protein subcellular localization. CONCLUSION: This method can help to more comprehensively predict protein subcellular localization toward better understanding protein function, thereby bridging the gap between theory and application toward improved identification and monitoring of drug targets.