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Background Depression is a common mood disorder that seriously affects the recovery of various functions in patients after stroke. Antidepressant drug therapy alone could not achieve satisfactory treatment responses. Objective To investigate the effects of rational emotive behavior therapy (REBT) on sleep and mood in patients with post-stroke depression. Methods Seventy-one patients with post-stroke depression were selected from Department of Neurological Rehabilitation, the Second Affiliated Hospital of Zhengzhou University from June 2019 to June 2020, and according to random number table, they were divided into the control group (n=35) or combined treatment group (n=36) . The control group received four consecutive weeks of treatment with oral sertraline hydrochloride tablets (25 mg per day within the first week, and 50 mg per day within other three weeks) . The combined treatment group received four consecutive weeks of treatment with REBT (three times per week, the treatment duration for each time lasting for 30 minutes) plus the same treatment for the control group. Pittsburgh Sleep Quality Index (PSQI) , Insomnia Severity Index (ISI) , 17-item Hamilton Depression Rating Scale (HAMD-17) , Hamilton Anxiety Rating Scale (HAMA) , and Modified Barthel Index (MBI) were used to assess pre- and post-treatment sleep quality, insomnia severity, depression prevalence, anxiety prevalence and ability to engage in basic activities of daily living, respectively. Results The mean scores of PSQI, ISI, HAMD-17, and HAMA showed a significant decrease and the mean score of MBI demonstrated a significant increase in both groups after treatment (P0.05) . The combined treatment group had lower mean post-treatment scores of ISI and HAMD-17 and higher mean post-treatment score of MBI than the control group (P

Background: Applying convolutional neural networks to a large number of EEG signal samples is computationally expensive because the computational complexity is linearly proportional to the number of dimensions of the EEG signal. We propose a new Gated Recurrent Unit (GRU) network model based on reinforcement learning, which considers the implementation of attention mechanisms in Electroencephalogram (EEG) signal processing scenarios as a reinforcement learning problem. Methods: The model can adaptively select target regions or position sequences from inputs and effectively extract information from EEG signals of different resolutions at multiple scales. Just as convolutional neural networks benefit from translation invariance, our proposed network also has a certain degree of translation invariance, making its computational complexity independent of the EEG signal dimension, thus maintaining a lower learning cost. Although the introduction of reinforcement learning makes the model non differentiable, we use policy gradient methods to achieve end-to-end learning of the model. Results: We evaluated our proposed model on publicly available EEG dataset (BCI Competition IV-2a). The proposed model outperforms the current state-of-the-art techniques in the BCI Competition IV- 2a dataset with an accuracy of 86.78 and 71.54% for the subject-dependent and subject-independent modes, respectively. Conclusion: In the field of EEG signal processing, attention models that combine reinforcement learning principles can focus on key features, automatically filter out noise and redundant data, and improve the accuracy of signal decoding. [ABSTRACT FROM AUTHOR]

A diastereoselective and enantioselective formal [4+1] ylide annulation of chiral sulfonium salts with various substituted Morita‐Baylis‐Hillman (MBH) adducts leading to optically active isoxazoline N‐oxides with three chiral carbon centers has been explored. The salient features of this methodology include a high diastereo‐ and enantioselective transformation, easily accessible starting materials, and mild reaction conditions. In addition, the isoxazoline N‐oxides products can be conveniently transformed into functionalized compounds. [ABSTRACT FROM AUTHOR]

Iodine is a nuclide of crucial concern in radioactive waste management. Nanomaterials selectively adsorb iodine from water; however, the efficient application of nanomaterials in engineering still needs to be developed for radioactive wastewater deiodination. Artemia egg shells possess large surface groups and connecting pores, providing a new biomaterial to remove contaminants. Based on the Artemia egg shell-derived biochar (AES biochar) and in situ precipitation and reduction of cuprous, we synthesized a novel nanocomposite, namely porous biochar-confined nano-Cu2O/Cu0 (C-Cu). The characterization of C-Cu confirmed that the nano-Cu2O/Cu0 was dispersed in the pores of AES biochar, serving in the efficient and selective adsorption of iodide and iodate ions from water. The iodide ion removal by C-Cu when equilibrated for 40 min exhibited high removal efficiency over the wide pH range of 4 to 10. Remarkable selectivity towards both iodide and iodate ions of C-Cu was permitted against competing anions (Cl−/NO3−/SO42−) at high concentrations. The applicability of C-Cu was demonstrated by a packed column test with treated effluents of 1279 BV. The rapid and selective removal of iodide and iodate ions from water is attributed to nanoparticles confined on the AES biochar and pore-facilitated mass transfer. Combining the advantages of the porous biochar and nano-Cu2O/Cu0, the use of C-Cu offers a promising method of iodine removal from water in engineering applications. [ABSTRACT FROM AUTHOR]

Ischemia reperfusion (I/R)‐induced acute kidney injury (AKI) is a common and serious condition. Irisin, an exercise‐induced hormone, improves mitochondrial function and reduces reactive oxygen species (ROS) production. Glutathione peroxidase 4 (GPX4) is a key regulator of ferroptosis and its inactivation aggravates renal I/R injury by inducing ROS production. However, the effect of irisin on GPX4 and I/R‐induced AKI is still unknown. To study this, male adult mice were subjected to renal I/R by occluding bilateral renal hilum for 30 min, which was followed by 24 hr reperfusion. Our results showed serum irisin levels were decreased in renal I/R mice. Irisin (250 μg/kg) treatment alleviated renal injury, downregulated inflammatory response, improved mitochondrial function, and reduced ER stress and oxidative stress after renal I/R, which were associated with upregulation of GPX4. Treated with RSL3 (a GPX4 inhibitor) abolished irisin's protective effect. Thus, irisin attenuates I/R‐induced AKI through upregulating GPX4. [ABSTRACT FROM AUTHOR]

Disruption of the gut barrier results in severe clinical outcomes with no specific treatment. Metabolic disorders and destruction of enterocytes play key roles in gut barrier dysfunction. Irisin is a newly identified exercise hormone that regulates energy metabolism. However, the effect of irisin on gut barrier function remains unknown. The therapeutic effect of irisin on gut barrier dysfunction was evaluated in gut ischemia reperfusion (IR). The direct effect of irisin on gut barrier function was studied in Caco‐2 cells. Here, we discovered that serum and gut irisin levels were decreased during gut IR and that treatment with exogenous irisin restored gut barrier function after gut IR in mice. Meanwhile, irisin decreased oxidative stress, calcium influx and endoplasmic reticulum (ER) stress after gut IR. Moreover, irisin protected mitochondrial function and reduced enterocyte apoptosis. The neutralizing antibody against irisin significantly aggravated gut injury, oxidative stress and enterocyte apoptosis after gut IR. Further studies revealed that irisin activated the AMPK‐UCP 2 pathway via binding to the integrin αVβ5 receptor. Inhibition of integrin αVβ5, AMPK or UCP 2 abolished the protective role of irisin in gut barrier function. In conclusion, exogenous irisin restores gut barrier function after gut IR via the integrin αVβ5‐AMPK‐UCP 2 pathway. [ABSTRACT FROM AUTHOR]