Four-Pyroptosis Gene-Based Nomogram as a Novel Strategy for Predicting the Effect of Immunotherapy in Hepatocellular Carcinoma.

Background: Immunotherapy has been considered as a promising cancer treatment for hepatocellular carcinoma (HCC). However, due to the particular immune environment of the liver, identifying patients who could benefit from immunotherapy is critical in clinical practice. Methods: The pyroptosis gene expression database of 54 candidates from The Cancer Genome Atlas (TCGA) were collected to discover the critical prognostic-related pyroptosis genes. A novel pyroptosis gene model was established to calculate the risk score. Kaplan-Meier analysis and receiver operating characteristic curve (ROC) were used to verify its predictive ability. The International Cancer Genome Consortium (ICGC) data was collected as external validation data to verify the model's accuracy. We employed multiple bioinformatics tools and algorithms to evaluate the tumor immune microenvironment (TIME) and the response to immunotherapy. Results: Our study found that most pyroptosis genes were expressed differently in normal and tumor tissues and that their expression was associated with the prognosis. Then, a precise four-pyroptosis gene model was generated. The one-year area under the curves (AUCs) among the training, internal, and external validation patients were 0.901, 0.727, and 0.671, respectively. An analysis of survival data revealed that individuals had a worse prognosis than patients with low risk. The analysis of TIME revealed that the low-risk group had more antitumor cells, fewer immunosuppressive cells, stronger immune function, less immune checkpoint gene expression, and better immunotherapy response than the high-risk group. Immunophenoscore (IPS) analysis also demonstrated that the low-risk score was related to superior immune checkpoint inhibitors therapy. Conclusion: A nomogram based on the four-pyroptosis gene signature was a novel tool to predict the effectiveness of immunotherapy for HCC. Therefore, individualized treatment targeting the pyroptosis genes may influence TIME and play an essential role in improving the prognosis in HCC patients.

Rutaecarpine Ameliorated High Sucrose-Induced Alzheimer's Disease Like Pathological and Cognitive Impairments in Mice.

High sucrose can induce tau hyperphosphorylation and cognitive dysfunction/memory impairment as observed in Alzheimer's disease (AD). Rutaecarpine, a specific (transient receptor potential vanilloid 1 [TRPV1]) agonist, is neuroprotective against high sucrose diet-induced impairment, but detailed mechanisms are still elusive. In this study, we investigated whether rutaecarpine mitigates high sucrose diet-induced pathological alterations and cognitive in AD-like mice. Mice were administered fodder containing 0.01% rutaecarpine and 20% sucrose solution. Our results showed that rutaecarpine significantly attenuated high sucrose diet-induced spatial memory impairment and enhanced synaptic plasticity; rutaecarpine prevented high sucrose diet-induced tau hyperphosphorylation by decreasing glycogen synthase kinase-3ß (GSK-3ß) activity; activation of GSK-3ß reversed the protective effect of rutaecarpine on learning and memory deficits, synaptic plasticity, and tau hyperphosphorylation induced by high-glucose diet significantly, suggesting that GSK-3ß activation is required for high glucose-induced tau hyperphosphorylation. These results demonstrated that rutaecarpine can mitigate high sucrose diet-induced hyperphosphorylation of AD-associated tau protein and cognitive impairment by inhibiting GSK-3ß, which supported that dietary rutaecarpine might have a promising use for therapeutic intervention of AD.

3D printing collagen/chitosan scaffold ameliorated axon regeneration and neurological recovery after spinal cord injury.

Spinal cord injury (SCI) is a disaster that can cause severe motor, sensory, and functional disorders. Implanting biomaterials have been regarded as hopeful strategies to restore neurological function. However, no optimized scaffold has been available. In this study, a novel 3D printing technology was used to fabricate the scaffold with designed structure. The composite biomaterials of collagen and chitosan were also adopted to balance both compatibility and strength. Female Sprague-Dawley rats were subjected to a T8 complete-transection SCI model. Scaffolds of C/C (collagen/chitosan scaffold with freeze-drying technology) or 3D-C/C (collagen/chitosan scaffold with 3D printing technology) were implanted into the lesion. Compared with SCI or C/C group, 3D-C/C implants significantly promoted locomotor function with the elevation in Basso-Beattie-Bresnahan (BBB) score and angle of inclined plane. Decreased latency and increased amplitude were observed both in motor-evoked potential and somatosensory-evoked potential in 3D-C/C group compared with SCI or C/C group, which further demonstrated the improvement of neurological recovery. Fiber tracking of diffusion tensor imaging (DTI) showed the most fibers traversing the lesion in 3D-C/C group. Meanwhile, we observed that the correlations between the locomotor (BBB score or angle of inclined plane) and the DTI parameters (fractional anisotropy values) were positive. Although C/C implants markedly enhanced biotin dextran amine (BDA)-positive neural profiles compared with SCI group, rats implanted with 3D-C/C scaffold displayed the largest degree of BDA profiles regeneration. Collectively, our 3D-C/C scaffolds demonstrated significant therapeutic effects on rat complete-transected spinal cord model, which provides a promising and innovative therapeutic approach for SCI. © 2019 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 107A: 1898-1908, 2019.

Solving the EEG inverse problem based on space-time-frequency structured sparsity constraints.

We introduce STOUT (spatio-temporal unifying tomography), a novel method for the source analysis of electroencephalograpic (EEG) recordings, which is based on a physiologically-motivated source representation. Our method assumes that only a small number of brain sources are active throughout a measurement, where each of the sources exhibits focal (smooth but localized) characteristics in space, time and frequency. This structure is enforced through an expansion of the source current density into appropriate spatio-temporal basis functions in combination with sparsity constraints. This approach combines the main strengths of two existing methods, namely Sparse Basis Field Expansions (Haufe et al., 2011) and Time-Frequency Mixed-Norm Estimates (Gramfort et al., 2013). By adjusting the ratio between two regularization terms, STOUT is capable of trading temporal for spatial reconstruction accuracy and vice versa, depending on the requirements of specific analyses and the provided data. Due to allowing for non-stationary source activations, STOUT is particularly suited for the localization of event-related potentials (ERP) and other evoked brain activity. We demonstrate its performance on simulated ERP data for varying signal-to-noise ratios and numbers of active sources. Our analysis of the generators of visual and auditory evoked N200 potentials reveals that the most active sources originate in the temporal and occipital lobes, in line with the literature on sensory processing.