Astragalus polysaccharide (APS) exerts protective effect against acute ischemic stroke (AIS) through enhancing M2 micoglia polarization by regulating adenosine triphosphate (ATP)/ purinergic receptor (P2X7R) axis.

Clinically, the effective treatment for patients with acute ischemic stroke (AIS) is very limited. Therefore, this paper aims to investigate the mechanism how astragalus polysaccharide (APS) exerts protective effect against AIS and provide a new method for the treatment of AIS. Cell surface antigen flow cytometry and immunofluorescence were used to identify M1 and M2 microglia. Western blot was used to evaluate the expression of associated protein. Oxygen-glucose deprivation (OGD) was used to simulate the effect of AIS on rat microglia. The middle cerebral artery occlusion (MCAO) model was established to simulate the effect of AIS in vivo. Evans blue dye (EBD) was used to evaluate the permeability of blood-brain barrier (BBB). Western blot and cell surface antigen flow cytometry results showed that APS promoted the M2 polarization of rat microglia by inhibiting the expression of purinergic receptor (P2X7R). APS reversed the effect of OGD on the polarization of rat microglia M1/ M2 by regulating P2X7R. APS reversed the effect of MCAO on the polarization of rat microglia M1/ M2 in vivo. Furthermore, APS inhibited the expression of P2X7R by promoting the degradation of adenosine triphosphate (ATP) in the cerebral cortex of MCAO rats. In addition, APS contributed to maintain the integrity of BBB. Summarily, APS can reduce brain injury by promoting the degradation of ATP in microglia and inhibiting the expression of P2X7R after AIS.

Multi-resolution modulation-filtered cochleagram feature for LSTM-based dimensional emotion recognition from speech.

Continuous dimensional emotion recognition from speech helps robots or virtual agents capture the temporal dynamics of a speaker's emotional state in natural human-robot interactions. Temporal modulation cues obtained directly from the time-domain model of auditory perception can better reflect temporal dynamics than the acoustic features usually processed in the frequency domain. Feature extraction, which can reflect temporal dynamics of emotion from temporal modulation cues, is challenging because of the complexity and diversity of the auditory perception model. A recent neuroscientific study suggests that human brains derive multi-resolution representations through temporal modulation analysis. This study investigates multi-resolution representations of an auditory perception model and proposes a novel feature called multi-resolution modulation-filtered cochleagram (MMCG) for predicting valence and arousal values of emotional primitives. The MMCG is constructed by combining four modulation-filtered cochleagrams at different resolutions to capture various temporal and contextual modulation information. In addition, to model the multi-temporal dependencies of the MMCG, we designed a parallel long short-term memory (LSTM) architecture. The results of extensive experiments on the RECOLA and SEWA datasets demonstrate that MMCG provides the best recognition performance in both datasets among all evaluated features. The results also show that the parallel LSTM can build multi-temporal dependencies from the MMCG features, and the performance on valence and arousal prediction is better than that of a plain LSTM method.

Modified Huang-Lian-Jie-Du Decoction Ameliorates Aß Synaptotoxicity in a Murine Model of Alzheimer's Disease.

Alzheimer's disease (AD) is a common neurodegenerative disease, characterized by cognitive dysfunction; however, the therapeutic strategies are not fully understood. Huang-Lian-Jie-Du-Decoction (HLJDD) is a famous traditional Chinese herbal formula that has been widely used clinically to treat dementia. Recently, according to previous study and our clinical practice, we generate a new modification of HLJDD (named modified-HLJDD). In this study, we indicated that modified-HLJDD attenuated learning and memory deficiencies in Aß 1-42 oligomer-induced AD model, and we confirmed the exact metabolites in modified-HLJDD solution, as compared with HLJDD by UHPLC-Q-TOF-MS. Using GC-Q-TOF/MS-based metabolomics, we identified adenosine as the potential significant metabolite, responsible for modified-HLJDD regulating energy metabolism and synaptic plasticity in AD model. We also revealed that the potential underlying mechanism of modified-HLJDD in AD model may involve NMDA receptor-mediated glutamatergic transmission and adenosine/ATPase/AMPK cascade. Moreover, we also indicated the differential gut microbiota which mainly involved Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria at the phylum level upon modified-HLJDD treatment in AD model. Based on the correlation of metabolomic analysis with microbiome analysis, we clarified that Dorea is the most affected microbiota with adenosine upon modified-HLJDD treatment in AD model. Thus, our study suggests that modified-HLJDD may serve as a potential therapeutic drug in treating AD.