BACKGROUND: Mirror therapy has been gradually adopted for lower limb rehabilitation, but its efficacy and neural mechanism are not well understood. OBJECTIVE: This study aims to investigate the effect and neural mechanism of mirror therapy on lower limb rehabilitation after ischemic stroke by using resting state functional magnetic resonance imaging (rs-fMRI). METHODS: A single-blind and randomized controlled pilot study was conducted. 32 patients with ischemic stroke were included in this study and randomly divided into two groups – the control group (CT, n = 16) and the mirror therapy group (MT, n = 16). Both the CT and MT groups received medication and routine rehabilitation training. In addition, mirror therapy was added to the MT group 5 times a week for 30 minutes each time over a period of 3 weeks. Patients’ motor functions, functional connectivity (FC), regional homogeneity (ReHo), and fractional amplitude of low-frequency fluctuations (fALFF) were analyzed both before and immediately after the treatment. RESULTS: Patients’ motor functions showed significant improvement in both groups compared to those before treatment (p <  0.01). Moreover, the MT group showed significantly better improvement than the CT group after the treatment (p <  0.05). FC, ReHo and fALFF indicated enhanced neuronal activities in motor function-related brain regions in the MT group compared to the CT group. CONCLUSION: Mirror therapy promotes the recovery of lower limb motor functions in patients with ischemic stroke. Through the comparative rs-fMRI analysis, it is found that the mirror therapy promotes the functional reorganization of the injured brain.

AimsGut dysbiosis appears rapidly after acute stroke and may affect the prognosis, whereas changes in gut microbiota with gradual recovery from stroke are unknown and rarely studied. The purpose of this study is to explore the characteristics of gut microbiota changes over time after stroke.MethodsStroke patients and healthy subjects were selected to compare the clinical data and gut microbiota of the patient group in two phases with that of healthy subjects and 16S rRNA gene sequencing was used to search the differences of gut microbiota in subjects.ResultsCompared with the healthy subjects, the subacute patients mainly decreased the abundance of some gut microbial communities, while the decreased communities reduced and more communities increased the abundance in the convalescent patients. The abundance of Lactobacillaceae increased in both phases in patient group, while Butyricimona, Peptostreptococaceae and Romboutsia decreased in both phases. Correlation analysis found that the MMSE scores of patients in the two phases had the greatest correlation with the gut microbiota.ConclusionGut dysbiosis still existed in patients in the subacute phase and convalescent phase, and gradually improved with the recovery of stroke. Gut microbiota may affect the prognosis of stroke by affecting BMI and/or related indicators, and there is a strong correlation between gut microbiota and cognitive function after stroke.

Radio frequency (RF) fingerprint identification is a nonpassword authentication method based on the physical layer of communication devices. Deep learning methods have thrown new light on RF fingerprint identification. In this paper, a conventional neural network- (CNN-) based RF identification model is proposed. The CNN models are designed to be lightweight. Raw data that reflects the characteristics of the I channel, the Q channel, and the 2-dimensional I + Q data is successively fed into a CNN model. Therefore, three submodels are generated. The final predictive labels are determined by the results of the three submodels through a voting scheme. Experimental results have demonstrated that in the SNR setting at 5 dB, the final recognition accuracy of four transmit devices could achieve as high as 97.25%, while the identification accuracies based on the I channel data, Q channel data, and I + Q channel data are 94.5%, 95%, and 94.5%, respectively. The training time for the 4 devices is around 30 seconds.

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Background: To evaluate the efficacy of multiple acupoint combinations for the treatment of post-stroke cognitive impairment (PSCI) using a network meta-analysis method. Methods: Searches for clinical randomized controlled trials (RCTs) of various types of acupuncture treatments for post-stroke cognitive dysfunction were conducted, data were extracted from studies selected according to the inclusion criteria, and the RCTs included in the analysis were assessed separately for risk of literature bias. Network meta-analysis was performed using Stata 14.0. Results: Sixteen RCTs involving 1257 patients were included, which involved 9 groups of acupoint treatment plans. The best treatment plan for improving the mini-mental state examination score of PSCI was a cephalic plexus spur (99.7%). The best treatment option for improving the montreal cognitive assessment score for PSCI was Zishen Yisui acupuncture therapy (ZSYSA) (77.3%). The best option for improving the barthel index score of PSCI was ZSYSA (99.2%). In terms of improving the overall clinical outcomes of PSCI, the best treatment option for improving the overall clinical effectiveness of PSCI is ZSYSA Therapy (92.2%). Conclusion: The analysis of all results shows that ZSYSA can significantly improve PSCI compared to other acupuncture therapies. Strengths and limitations of this study: This is the 1 st study on the treatment of PSCI with different acupoint combinations based on a network meta-analysis method, which provides a reference for clinical rehabilitation workers; all included studies were randomized controlled trials, which increased the reliability of this study. Limitations; The number of relevant clinical studies retrieved was too small, and all included clinical trials were located in China; therefore, there is a great possibility of publication bias; Most of the included studies did not clearly explain the random distribution mode, follow-up, distribution concealment, or other experimental conditions. Therefore, selection and reporting biases cannot be excluded, suggesting that the quality of the literature is not high; Because of the strict inclusion criteria, the number of studies was limited, and subgroup analysis could not be performed according to the time of onset and the length of the disease course.