Impact of epilepsy surgery on developmental trajectories of children under 3 years of age.

AIM: To investigate the developmental effects of epilepsy surgery in young children. METHOD: This study retrospectively reviewed 315 consecutive children under 3 years of age, and ultimately included 89 children (48 males, 41 females) with pre- and postsurgery developmental evaluations. RESULTS: The mean general quotient before surgery was 46.7 (SD 24.7). Before surgery, the general quotient decreased in 77.6% of patients, while after surgery it increased in 55.1%. Furthermore, 70% of those 20 patients whose presurgical general quotient decreased by more than 10 points experienced positive changes. General quotient scores decreased in 15 out of the 22 patients classified in the normal/marginal presurgical category. Children who underwent surgery before the age of 12 months had a median gain in general quotient score by 7.6. Short-term general quotient scores were highly correlated with long-term scores (r = 0.909, p < 0.001). INTERPRETATION: Surgical intervention was more inclined to positively impact developmental trajectories within a short postsurgical period, particularly among those affected by severe epileptic activity. However, in children with relatively typical development, certain developmental setbacks may arise. Postsurgical short-term developmental outcomes could predict longer-term outcomes.

Use of recurrent neural networks considering maintenance to predict urban road performance in Beijing, China.

A correct understanding of the pavement performance change law forms the premise of the scientific formulation of maintenance decisions. This paper aims to develop a predictive model taking into account the costs of different types of maintenance works that reflects the continuous true usage performance of the pavement. The model proposed in this study was trained on a dataset containing five-year maintenance work data on urban roads in Beijing with pavement performance indicators for the corresponding years. The same roads were matched and combined to obtain a set of sequences of pavement performance changes with the features of the current year; with the recurrent-neural-network-based long short-term memory (LSTM) network and gate recurrent unit (GRU) network, the prediction accuracy of highway pavement performance on the test set was significantly increased. The prediction result indicates that the generalization ability of the improved recurrent neural network model is satisfactory, with the R2 achieving 0.936, and of the two models the GRU model is more efficient, with an accuracy that reaches almost the same level as LSTM but with the training convergence time reduced to 25 s. This study demonstrates that data generated by the work of maintenance units can be used effectively in the prediction of pavement performance. This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.

Solution-Processed CsPbBr3 Perovskite Photodetectors for Cost-Efficient Underwater Wireless Optical Communication System.

Underwater wireless optical communication (UWOC) has attracted increasing attention due to its advantages in bandwidth, latency, interference resistance, and security. Photodetectors, as a crucial part of receivers, have been continuously developed with the great progress that has been made in advanced materials. Metal halide perovskites emerging as promising optoelectronic materials in the past decade have been used to fabricate various high-performance photodetectors. In this work, high-performance CsPbBr3 perovskite PDs were realized via solution process, with low noise, a high responsivity, and a fast response. Based on these perovskite PDs, a cost-efficient UWOC system was successfully demonstrated on an FPGA platform, achieving a data rate of 6.25 Mbps with a low bit error rate of 0.36%. Due to lower background noise under environment illumination, perovskite PDs exhibit better communication stability before reaching a data rate threshold; however, the BER increases rapidly due to the long fall time, resulting in difficulty in distinguishing switching signals. Reducing the fall time of perovskite PDs and using advanced coding techniques can help to further improve the performance of the UWOC system based on perovskite PDs. This work not only demonstrates the potential of perovskite PDs in the application of UWOC, but also improves the development of a cost-effective UWOC system based on FPGAs.

Increased expression of PSME2 is associated with clear cell renal cell carcinoma invasion by regulating BNIP3­mediated autophagy.

Previous studies have showed that proteasome activator complex subunit 2 (PSME2) may play a role in some types of cancer. However, the involvement of PSME2 in clear cell renal cell carcinoma (ccRCC) remains unknown. The aim of the present study was to assess the poorly understood function of PSME2 expression in renal carcinoma. Using bioinformatics analysis, PSME2 mRNA expression profiles were investigated, along with its potential prognostic value and its functional enrichment. Signaling pathways and putative hub genes associated with PSME2 in ccRCC were identified. Based on the bioinformatics analysis results, immunohistochemistry of human ccRCC samples and renal carcinoma cell lines (CAKI­1 and 786­O) transfected with short interfering RNA targeting PSME2 were analyzed using western blot analysis, reverse transcription­quantitative PCR, immunofluorescence, and Cell Counting Kit­8, Transwell and transmission electron microscope assays. The results showed that when PSME2 expression was knocked down, the invasive abilities of the tumor cell lines were reduced, while autophagy was enhanced. The present study demonstrated that PSME2 was associated with the invasion ability of ccRCC cell lines by inhibiting BNIP3­mediated autophagy. In summary, PSME2 could be used as a prognostic factor and a promising therapeutic target in ccRCC.