fMRI Brain Decoding and Its Applications in Brain-Computer Interface: A Survey.

Brain neural activity decoding is an important branch of neuroscience research and a key technology for the brain-computer interface (BCI). Researchers initially developed simple linear models and machine learning algorithms to classify and recognize brain activities. With the great success of deep learning on image recognition and generation, deep neural networks (DNN) have been engaged in reconstructing visual stimuli from human brain activity via functional magnetic resonance imaging (fMRI). In this paper, we reviewed the brain activity decoding models based on machine learning and deep learning algorithms. Specifically, we focused on current brain activity decoding models with high attention: variational auto-encoder (VAE), generative confrontation network (GAN), and the graph convolutional network (GCN). Furthermore, brain neural-activity-decoding-enabled fMRI-based BCI applications in mental and psychological disease treatment are presented to illustrate the positive correlation between brain decoding and BCI. Finally, existing challenges and future research directions are addressed.

The Cell-Isolation Capsules with Rod-Like Channels Ensure the Survival and Response of Cancer Cells to Their Microenvironment.

Current macrocapsules with semipermeable but immunoprotective polymeric membranes are attractive devices to achieve the purpose of immunoisolation, however, their ability to allow diffusion of essential nutrients and oxygen is limited, which leads to a low survival rate of encapsulated cells. Here, a novel method is reported by taking advantage of thermotropic liquid crystals, sodium laurylsulfonate (SDS) liquid crystals (LCs), and rod-like crystal fragments (LCFs) to develop engineered alginate hydrogels with rod-like channels. This cell-isolation capsule with an engineered alginate hydrogel-wall allows small molecules, large molecules, and bacteria to diffuse out from the capsules freely but immobilizes the encapsulated cells inside and prevents cells in the microenvironment from moving in. The encapsulated cells show a high survival rate with isolation of host immune cells and long-term growth with adequate nutrients and oxygen supply. In addition, by sharing and responding to the normal molecular and vesicular microenvironment (NMV microenvironment), encapsulated cancer cells display a transition from tumorous phenotypes to ductal features of normal epithelial cells. Thus, this device will be potentially useful for clinical application in cell therapy by secreting molecules and for establishment of patient-derived xenograft (PDX) models that are often difficult to achieve for certain types of tumors, such as prostate cancer.

Single-cell RNA sequencing reveals the epithelial cell heterogeneity and invasive subpopulation in human bladder cancer.

Bladder cancer represents a highly heterogeneous disease characterized by distinct histological, molecular and clinical phenotypes, and a detailed analysis of tumor cell invasion and crosstalks within bladder tumor cells has not been determined. Here, we applied droplet-based single-cell RNA sequencing (scRNA-seq) to acquire transcriptional profiles of 36 619 single cells isolated from seven patients. Single cell transcriptional profiles matched well with the pathological basal/luminal subtypes. Notably, in T1 tumors diagnosed as luminal subtype, basal cells displayed characteristics of epithelial-mesenchymal transition (EMT) and mainly located at the tumor-stromal interface as well as micrometastases in the lamina propria. In one T3 tumor, muscle-invasive tumor showed significantly higher expression of cancer stem cell markers SOX9 and SOX2 than the primary tumor. We additionally analyzed communications between tumor cells and demonstrated its relevance to basal/luminal phenotypes. Overall, our single-cell study provides a deeper insight into the tumor cell heterogeneity associated with bladder cancer progression.

Single-cell spatial transcriptomic analysis reveals common and divergent features of developing postnatal granule cerebellar cells and medulloblastoma.

BACKGROUND: Cerebellar neurogenesis involves the generation of large numbers of cerebellar granule neurons (GNs) throughout development of the cerebellum, a process that involves tight regulation of proliferation and differentiation of granule neuron progenitors (GNPs). A number of transcriptional regulators, including Math1, and the signaling molecules Wnt and Shh have been shown to have important roles in GNP proliferation and differentiation, and deregulation of granule cell development has been reported to be associated with the pathogenesis of medulloblastoma. While the progenitor/differentiation states of cerebellar granule cells have been broadly investigated, a more detailed association between developmental differentiation programs and spatial gene expression patterns, and how these lead to differential generation of distinct types of medulloblastoma remains poorly understood. Here, we provide a comparative single-cell spatial transcriptomics analysis to better understand the similarities and differences between developing granule and medulloblastoma cells. RESULTS: To acquire an enhanced understanding of the precise cellular states of developing cerebellar granule cells, we performed single-cell RNA sequencing of 24,919 murine cerebellar cells from granule neuron-specific reporter mice (Math1-GFP; Dcx-DsRed mice). Our single-cell analysis revealed that there are four major states of developing cerebellar granule cells, including two subsets of granule progenitors and two subsets of differentiating/differentiated granule neurons. Further spatial transcriptomics technology enabled visualization of their spatial locations in cerebellum. In addition, we performed single-cell RNA sequencing of 18,372 cells from Patched+/- mutant mice and found that the transformed granule cells in medulloblastoma closely resembled developing granule neurons of varying differentiation states. However, transformed granule neuron progenitors in medulloblastoma exhibit noticeably less tendency to differentiate compared with cells in normal development. CONCLUSION: In sum, our study revealed the cellular and spatial organization of the detailed states of cerebellar granule cells and provided direct evidence for the similarities and discrepancies between normal cerebellar development and tumorigenesis.

Single-cell analysis reveals urothelial cell heterogeneity and regenerative cues following cyclophosphamide-induced bladder injury.

Cyclophosphamide is a commonly used chemotherapeutic drug to treat cancer with side effects that trigger bladder injury and hemorrhagic cystitis. Although previous studies have demonstrated that certain cell subsets and communications are activated to drive the repair and regeneration of bladder, it is not well understood how distinct bladder cell subsets function synergistically in this process. Here, we used droplet-based single-cell RNA sequencing (scRNA-seq) to profile the cell types within the murine bladder mucous layer under normal and injured conditions. Our analysis showed that superficial cells are directly repaired by cycling intermediate cells. We further identified two resident mesenchymal lineages (Acta2+ myofibroblasts and Cd34+ fibroblasts). The delineation of cell-cell communications revealed that Acta2+ myofibroblasts upregulated Fgf7 expression during acute injury, which activated Fgfr signaling in progenitor cells within the basal/intermediate layers to promote urothelial cell growth and repair. Overall, our study contributes to a more comprehensive understanding of the cellular dynamics during cyclophosphamide-induced bladder injury and may help identify important niche factors contributing to the regeneration of injured bladders.

Single-cell analysis supports a luminal-neuroendocrine transdifferentiation in human prostate cancer.

Neuroendocrine prostate cancer is one of the most aggressive subtypes of prostate tumor. Although much progress has been made in understanding the development of neuroendocrine prostate cancer, the cellular architecture associated with neuroendocrine differentiation in human prostate cancer remain incompletely understood. Here, we use single-cell RNA sequencing to profile the transcriptomes of 21,292 cells from needle biopsies of 6 castration-resistant prostate cancers. Our analyses reveal that all neuroendocrine tumor cells display a luminal-like epithelial phenotype. In particular, lineage trajectory analysis suggests that focal neuroendocrine differentiation exclusively originate from luminal-like malignant cells rather than basal compartment. Further tissue microarray analysis validates the generality of the luminal phenotype of neuroendocrine cells. Moreover, we uncover neuroendocrine differentiation-associated gene signatures that may help us to further explore other intrinsic molecular mechanisms deriving neuroendocrine prostate cancer. In summary, our single-cell study provides direct evidence into the cellular states underlying neuroendocrine transdifferentiation in human prostate cancer.

Single-Cell Characterization of Malignant Phenotypes and Developmental Trajectories of Adrenal Neuroblastoma.

Neuroblastoma (NB), which is a subtype of neural-crest-derived malignancy, is the most common extracranial solid tumor occurring in childhood. Despite extensive research, the underlying developmental origin of NB remains unclear. Using single-cell RNA sequencing, we generate transcriptomes of adrenal NB from 160,910 cells of 16 patients and transcriptomes of putative developmental cells of origin of NB from 12,103 cells of early human embryos and fetal adrenal glands at relatively late development stages. We find that most adrenal NB tumor cells transcriptionally mirror noradrenergic chromaffin cells. Malignant states also recapitulate the proliferation/differentiation status of chromaffin cells in the process of normal development. Our findings provide insight into developmental trajectories and cellular states underlying human initiation and progression of NB.

An ultrasensitive system for measuring the USPs and OTULIN activity using Nanoluc as a reporter.

The deubiquitinating enzymes (DUBs) are a family of isopeptidases responsible for removing the ubiquitin from the ubiquitinated proteins. Identification of inhibitors for DUBs is emerging as an efficient way for discovering potential medicines for disease treatment. However, the high throughput screening (HTS) assay is still not available for all USPs, especially OTULIN. Here, we described a novel steadily quantifiable DUBs assay platform using Nanoluc (Nluc) as reporter. We further demonstrated that the Ub-Nluc assay could be used for HTS of DUBs inhibitors. Moreover, we generated a sensitive system for OTULIN inhibitors screening using Nluc as a reporter. In summary, our data indicate that Ub-Nluc and the improved Ub-Ub-GS-Nluc assay are efficient systems for measuring activities and screening inhibitors of USPs and OTULIN.