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As an intravenous anesthetic, propofol has been indicated to induce neurotoxicity in both animal and human brains. It is of great significance to better understand the potential mechanism of propofol-induced neurotoxicity to eliminate the side effects of propofol. Esketamine is a sedative that has been proven to have an antidepressant effect. However, its effect on propofol-induced neurotoxicity and the underlying mechanism remain unclear. Herein, we investigated the role of esketamine in propofol-induced brain injury. A rat model of propofol-induced brain injury was established with or without the treatment of esketamine. The results demonstrated that propofol-induced impairment in spatial learning and memory of rats and promoted oxidative stress, neuronal injury and apoptosis in rat hippocampal tissues. The effects caused by propofol were attenuated by esketamine. Esketamine activated the mature brain-derived neurotrophic factor/tropomyosin receptor kinase B/phosphatidylinositide 3-kinase (mBDNF/TrkB/PI3K) signaling pathway in propofol-administrated rats. Moreover, knocking down BDNF partially reversed esketamine-mediated activation of the mBDNF/TrkB/PI3K signaling pathway and inhibition of neuronal apoptosis in propofol-induced rats. Overall, esketamine mitigates propofol-induced cognitive dysfunction and brain injury in rats by activating mBDNF/TrkB/PI3K signaling.

Aims: The aim of this study was to report the incidence, prevalence, and disability‐adjusted life‐years (DALYs) of periodontal diseases during the period 1990–2019. Methods: Data on periodontal diseases were retrieved from the Global Burden of Diseases, Injuries, and Risk Factors study (GBD) 2019. The estimated annual percentage changes were calculated to evaluate the changing trend of age‐standardized incidence, prevalence, and DALY rates related to periodontal diseases. Results: Globally, there were 1,087,367,744.0 cases with 91,518,820.6 new incidence and 7,090,390.3 DALYs of periodontal diseases in 2019, almost twice as many as in 1990. Moreover, the pace of increase in age‐standardized incidence, age‐standardized prevalence, and age‐standardized DALY rates had accelerated during the 1990–2019 time period, with EAPC of 0.29 (95% CI, 0.22 to 0.35), 0.34 (95% CI, 0.26 to 0.43), and 0.35 (95% CI, 0.27 to 0.44) separately. The corresponding age‐standardized percentage changes were more pronounced in females, Southeast Asia, and low‐middle SDI regions. Western Sub‐Saharan Africa was the high‐risk area of standardized periodontal diseases burden in 2019, among which Gambia was the country with the heaviest burden. Conclusion: The globally incidence, prevalence, and DALYs of periodontal diseases are substantially increased from 1990 to 2019, which highlights the importance and urgency of periodontal care. [ABSTRACT FROM AUTHOR]

To observe the surgical procedure and outcome of percutaneous endoscopic lumbar discectomy for L5/S1 lumbar disc herniation (LDH) by the interlaminar and transforaminal approach. A total of 153 patients with L5/S1 LDH who were treated using percutaneous endoscopic transforaminal discectomy (PETD, n = 84) or percutaneous endoscopic interlaminar discectomy (PEID, n = 69) from January 2016 to January 2018 were enrolled in this retrospective study. The time of puncture, operation under the endoscope, total operation and number of fluoroscopy of the two groups were compared. All groups were followed up for two years by using the Oswestry disability index (ODI) and the Visual Analogue Scale (VAS). Additionally, the incidence of complications, reoperation and postoperative low back pain were compared between the two groups. There were no significant difference in general information between the two groups. Compared to the PEID group, the PETD group had a decreased operation time under the endoscope and an increased puncture time, total operation time, and the number of fluoroscopy (p < 0.05). The preoperative VAS and ODI scores of the PETD and PEID group were decreased at the last follow-up (p < 0.05). There were no difference in the preoperative or last follow-up VAS and ODI scores, as well as complications, reoperation between the two groups (p > 0.05). The incidence of postoperative low back pain in the PETD group was lower than that in the PEID group (p > 0.05). The two-year clinical outcome of PETD is equal to that of PEID for L5/S1 LDH. Compared to those with PETD, the puncture time, total operation time and radiation exposure are lower with PEID, but the incidence of postoperative low back pain is higher. [ABSTRACT FROM AUTHOR]

Sparse representation is an effective data classification algorithm that depends on the known training samples to categorise the test sample. It has been widely used in various image classification tasks. Sparseness in sparse representation means that only a few of instances selected from all training samples can effectively convey the essential class‐specific information of the test sample, which is very important for classification. For deformable images such as human faces, pixels at the same location of different images of the same subject usually have different intensities. Therefore, extracting features and correctly classifying such deformable objects is very hard. Moreover, the lighting, attitude and occlusion cause more difficulty. Considering the problems and challenges listed above, a novel image representation and classification algorithm is proposed. First, the authors' algorithm generates virtual samples by a non‐linear variation method. This method can effectively extract the low‐frequency information of space‐domain features of the original image, which is very useful for representing deformable objects. The combination of the original and virtual samples is more beneficial to improve the classification performance and robustness of the algorithm. Thereby, the authors' algorithm calculates the expression coefficients of the original and virtual samples separately using the sparse representation principle and obtains the final score by a designed efficient score fusion scheme. The weighting coefficients in the score fusion scheme are set entirely automatically. Finally, the algorithm classifies the samples based on the final scores. The experimental results show that our method performs better classification than conventional sparse representation algorithms. [ABSTRACT FROM AUTHOR]

Sparse representation plays an important role in the research of face recognition. As a deformable sample classification task, face recognition is often used to test the performance of classification algorithms. In face recognition, differences in expression, angle, posture, and lighting conditions have become key factors that affect recognition accuracy. Essentially, there may be significant differences between different image samples of the same face, which makes image classification very difficult. Therefore, how to build a robust virtual image representation becomes a vital issue. To solve the above problems, this paper proposes a novel image classification algorithm. First, to better retain the global features and contour information of the original sample, the algorithm uses an improved non‐linear image representation method to highlight the low‐intensity and high‐intensity pixels of the original training sample, thus generating a virtual sample. Second, by the principle of sparse representation, the linear expression coefficients of the original sample and the virtual sample can be calculated, respectively. After obtaining these two types of coefficients, calculate the distances between the original sample and the test sample and the distance between the virtual sample and the test sample. These two distances are converted into distance scores. Finally, a simple and effective weight fusion scheme is adopted to fuse the classification scores of the original image and the virtual image. The fused score will determine the final classification result. The experimental results show that the proposed method outperforms other typical sparse representation classification methods. [ABSTRACT FROM AUTHOR]