TDLNet: Transfer Data Learning Network for Cross-Subject Classification Based on Multiclass Upper Limb Motor Imagery EEG.

The limited number of brain-computer interface based on motor imagery (MI-BCI) instruction sets for different movements of single limbs makes it difficult to meet practical application requirements. Therefore, designing a single-limb, multi-category motor imagery (MI) paradigm and effectively decoding it is one of the important research directions in the future development of MI-BCI. Furthermore, one of the major challenges in MI-BCI is the difficulty of classifying brain activity across different individuals. In this article, the transfer data learning network (TDLNet) is proposed to achieve the cross-subject intention recognition for multiclass upper limb motor imagery. In TDLNet, the Transfer Data Module (TDM) is used to process cross-subject electroencephalogram (EEG) signals in groups and then fuse cross-subject channel features through two one-dimensional convolutions. The Residual Attention Mechanism Module (RAMM) assigns weights to each EEG signal channel and dynamically focuses on the EEG signal channels most relevant to a specific task. Additionally, a feature visualization algorithm based on occlusion signal frequency is proposed to qualitatively analyze the proposed TDLNet. The experimental results show that TDLNet achieves the best classification results on two datasets compared to CNN-based reference methods and transfer learning method. In the 6-class scenario, TDLNet obtained an accuracy of 65%±0.05 on the UML6 dataset and 63%±0.06 on the GRAZ dataset. The visualization results demonstrate that the proposed framework can produce distinct classifier patterns for multiple categories of upper limb motor imagery through signals of different frequencies. The ULM6 dataset is available at https://dx.doi.org/10.21227/8qw6-f578.

TSPNet: a time-spatial parallel network for classification of EEG-based multiclass upper limb motor imagery BCI.

The classification of electroencephalogram (EEG) motor imagery signals has emerged as a prominent research focus within the realm of brain-computer interfaces. Nevertheless, the conventional, limited categories (typically just two or four) offered by brain-computer interfaces fail to provide an extensive array of control modes. To address this challenge, we propose the Time-Spatial Parallel Network (TSPNet) for recognizing six distinct categories of upper limb motor imagery. Within TSPNet, temporal and spatial features are extracted separately, with the time dimension feature extractor and spatial dimension feature extractor performing their respective functions. Following this, the Time-Spatial Parallel Feature Extractor is employed to decouple the connection between temporal and spatial features, thus diminishing feature redundancy. The Time-Spatial Parallel Feature Extractor deploys a gating mechanism to optimize weight distribution and parallelize time-spatial features. Additionally, we introduce a feature visualization algorithm based on signal occlusion frequency to facilitate a qualitative analysis of TSPNet. In a six-category scenario, TSPNet achieved an accuracy of 49.1% ± 0.043 on our dataset and 49.7% ± 0.029 on a public dataset. Experimental results conclusively establish that TSPNet outperforms other deep learning methods in classifying data from these two datasets. Moreover, visualization results vividly illustrate that our proposed framework can generate distinctive classifier patterns for multiple categories of upper limb motor imagery, discerned through signals of varying frequencies. These findings underscore that, in comparison to other deep learning methods, TSPNet excels in intention recognition, which bears immense significance for non-invasive brain-computer interfaces.

Entecavir plus Biejia-Ruangan compound reduces the risk of hepatocellular carcinoma in Chinese patients with chronic hepatitis B.

BACKGROUND & AIMS: Chronic hepatitis B (CHB) and liver fibrosis are associated with a high risk of hepatocellular carcinoma (HCC) development. We assessed whether entecavir (ETV) plus Biejia-Ruangan compound (BRC), an anti-fibrotic traditional Chinese medicine, can further reduce the risk of HCC in treatment-naïve Chinese patients with CHB and an Ishak fibrosis score of ≥3 points derived from our parent double-blind randomized placebo-controlled trial. METHODS: After a 72-week comparison between ETV+BRC and ETV+placebo treatment, participants were eligible to enter an open-label treatment phase and were followed up every 6 months. The primary [secondary] endpoints were the incidence of HCC [liver-related deaths, non-HCC events, and non-liver-related deaths]. Modified intention-to-treat (mITT), intention-to-treat (ITT), and per-protocol (PP) populations were defined for the time-to-event analysis. RESULTS: A total of 1,000 patients were recruited; the median age was 42.0 years; 69.9% were male and 58.3% were HBeAg positive. In the mITT population, the 7-year cumulative incidence of HCC [liver-related deaths] was 4.7% [0.2%] for ETV+BRC, which was significantly lower than 9.3% [2.2%] for ETV monotherapy (p = 0.008 [p = 0.030]). Notably, ETV+BRC treatment yielded a lower incidence of HCC in those who did not achieve regression of fibrosis at week 72 than ETV monotherapy (p = 0.018). There were no differences in the other 2 secondary endpoints or safety profiles between the groups. Multivariable Cox proportional regression analysis, including the treatment allocation as a parameter, also demonstrated that ETV+BRC treatment was associated with a reduced incidence of HCC. The ITT and PP analyses showed consistent results. CONCLUSIONS: ETV plus BRC combination treatment could further reduce the risk of HCC and liver-related deaths in patients with CHB and advanced fibrosis or cirrhosis, which may have important clinical implications for HCC prevention. LAY SUMMARY: Patients with chronic hepatitis B virus infection are at an increased risk of developing liver cancer (specifically hepatocellular carcinoma [HCC]). While there are effective antiviral treatments that can suppress the virus in chronically infected patients, the risk of HCC remains. Herein, we show that adding a traditional Chinese medicine called Biejia-Ruangan compound to an antiviral reduced the risk of HCC in patients with chronic hepatitis B.

Synergistic Effect of Biejia-Ruangan on Fibrosis Regression in Patients With Chronic Hepatitis B Treated With Entecavir: A Multicenter, Randomized, Double-Blind, Placebo-Controlled Trial.

BACKGROUND: Long-term nucleos(t)ide analogue (NA) treatment can reverse liver fibrosis in chronic hepatitis B (CHB), but its effect on fibrosis regression remains limited. Biejia-Ruangan (BR) has been approved in China as an antifibrotic traditional Chinese medicine drug in patients with chronic liver diseases. A multicenter randomized controlled trial aims to evaluate the effect of BR on fibrosis regression in CHB patients treated with NAs. METHODS: CHB patients with histologically confirmed advanced fibrosis or cirrhosis were randomly assigned to receive entecavir (ETV) (0.5 mg per day) plus BR (2 g 3 times a day) or placebo for 72 weeks. Liver fibrosis regression was defined as a reduction of ≥ 1 point by the Ishak fibrosis stage (IFS). RESULTS: Overall, 500 patients were enrolled in each group as the intention-to-treat population. The rate of fibrosis regression after 72 weeks of treatment was significantly higher in the ETV + BR group (40% vs 31.8%; P = .0069). Among 388 patients with cirrhosis (ie, IFS ≥ 5) at baseline, the rate of cirrhosis reversal (ie, IFS ≤ 4) was significantly higher in the ETV + BR group (41.5% vs 30.7%; P = .0103). CONCLUSIONS: Addition of BR to the current standard treatment with NAs in CHB patients with advanced fibrosis or cirrhosis can improve liver fibrosis regression. CLINICAL TRIALS REGISTRATION: NCT01965418.

Exploring an Integrative Therapy for Treating COVID-19: A Randomized Controlled Trial.

OBJECTIVES: To develop a new Chinese medicine (CM)-based drug and to evaluate its safety and effect for suppressing acute respiratory distress syndrome (ARDS) in COVID-19 patients. METHODS: A putative ARDS-suppressing drug Keguan-1 was first developed and then evaluated by a randomized, controlled two-arm trial. The two arms of the trial consist of a control therapy (alpha interferon inhalation, 50 µg twice daily; and lopinavir/ritonavir, 400 and 100 mg twice daily, respectively) and a testing therapy (control therapy plus Keguan-1 19.4 g twice daily) by random number table at 1:1 ratio with 24 cases each group. After 2-week treatment, adverse events, time to fever resolution, ARDS development, and lung injury on newly diagnosed COVID-19 patients were assessed. RESULTS: An analysis of the data from the first 30 participants showed that the control arm and the testing arm did not exhibit any significant differences in terms of adverse events. Based on this result, the study was expanded to include a total of 48 participants (24 cases each arm). The results show that compared with the control arm, the testing arm exhibited a significant improvement in time to fever resolution (P=0.035), and a significant reduction in the development of ARDS (P=0.048). CONCLUSIONS: Keguan-1-based integrative therapy was safe and superior to the standard therapy in suppressing the development of ARDS in COVID-19 patients. (Trial registration No. NCT04251871 at www.clinicaltrials.gov ).

In silico identification of EP400 and TIA1 as critical transcription factors involved in human hepatocellular carcinoma relapse.

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-associated mortality worldwide. Transcription factors (TFs) are crucial proteins that regulate gene expression during cancer progression; however, the roles of TFs in HCC relapse remain unclear. To identify the TFs that drive HCC relapse, the present study constructed co-expression network and identified the Tan module the most relevant to HCC relapse. Numerous hub TFs (highly connected) were subsequently obtained from the Tan module according to the intra-module connectivity and the protein-protein interaction network connectivity. Next, E1A-binding protein p400 (EP400) and TIA1 cytotoxic granule associated RNA binding protein (TIA1) were identified as hub TFs differentially connected between the relapsed and non-relapsed subnetworks. In addition, zinc finger protein 143 (ZNF143) and Yin Yang 1 (YY1) were also identified by using the plugin iRegulon in Cytoscape as master upstream regulatory elements, which could potentially regulate expression of the genes and TFs of the Tan module, respectively. The Kaplan-Meier (KM) curves obtained from KMplot and Gene Expression Profiling Interactive Analysis tools confirmed that the high expression of EP400 and TIA1 were significantly associated with shorter relapse-free survival and disease-free survival of patients with HCC. Furthermore, the KM curves from the UALCAN database demonstrated that high EP400 expression significantly reduced the overall survival of patients with HCC. EP400 and TIA1 may therefore serve as potential prognostic and therapeutic biomarkers.

Bupleurum chinense polysaccharide inhibit adhesion of human melanoma cells via blocking ß1 integrin function.

Adhesive interaction contributes toward tumor metastasis and the transmembrane glycoprotein receptor, integrin has been recognized to mediate the adhesion to extracellular matrix thus upregulating tumor metastasis. In the current study, we evaluated the anti-adhesive mechanisms of a water-soluble polysaccharide (BCP) extracted from Bupleurum chinense. BCP inhibited integrin-mediated adhesion of human melanoma A375 cells to fibronectin but had no effects on nonspecific adhesion to poly-l-lysine. BCP also reduced ß1 integrin ligand affinity for GST-FNIII9-10 proteins. The adhesion-dependent formation of F-actin stress fiber and focal adhesion (FA) was also inhibited by BCP treatment. The inhibition of BCP on integrin-mediated signaling is probably through inhibiting phosphorylation of focal adhesion kinase (FAK) and paxillin. Collectively, our current findings indicated that BCP may be a potential therapy for melanoma metastasis due to its inhibitory effects on integrin function.