Polysaccharide extracted from the Sargassum fusiforme induces cell cycle arrest and apoptosis of B16F10 melanoma cells through the PI3K/AKT pathway.

BACKGROUND: SARGASSUM FUSIFORME: (S. fusiforme) is a brown alga that has been utilized as a medicine for a long time. Polysaccharides extracted from S. fusiforme demonstrate antitumor activities. METHODS: The impact of S. fusiforme polysaccharides (SFPS 191,212) on the proliferation, apoptosis, and cell cycle kinetics of B16F10 murine melanoma cells were thoroughly investigated in this work. The anticancer activities of the SFPS 191,212 compounds were assayed in the B16F10 cells at both transcriptional and translational levels. RESULTS: The compound exhibited concentration-dependent effects. Moreover, SPFS 191,212 increased the numbers of apoptotic cells and arrested the cell cycle in the S phase of the quantitative real-time PCR. From western blotting, it was verified that the SFPS 191,212 treatment improved the expression of Bax, Caspase-9, and Caspase-3 genes and proteins, while it reduced phosphatidylinositol 3 kinase and Bcl-2 genes and proteins, suggesting the involvement of mitochondria. CONCLUSION: Overall, SFPS 191,212 can be further explored as a potential functional food or adjuvant agent for the prevention or treatment of melanoma.

An improved transformer network for skin cancer classification.

BACKGROUND: Use of artificial intelligence to identify dermoscopic images has brought major breakthroughs in recent years to the early diagnosis and early treatment of skin cancer, the incidence of which is increasing year by year worldwide and poses a great threat to human health. Achievements have been made in the research of skin cancer image classification by using the deep backbone of the convolutional neural network (CNN). This approach, however, only extracts the features of small objects in the image, and cannot locate the important parts. OBJECTIVES: As a result, researchers of the paper turn to vision transformers (VIT) which has demonstrated powerful performance in traditional classification tasks. The self-attention is to improve the value of important features and suppress the features that cause noise. Specifically, an improved transformer network named SkinTrans is proposed. INNOVATIONS: To verify its efficiency, a three step procedure is followed. Firstly, a VIT network is established to verify the effectiveness of SkinTrans in skin cancer classification. Then multi-scale and overlapping sliding windows are used to serialize the image and multi-scale patch embedding is carried out which pay more attention to multi-scale features. Finally, contrastive learning is used which makes the similar data of skin cancer encode similarly so that the encoding results of different data are as different as possible. MAIN RESULTS: The experiment is carried out based on two datasets, namely (1) HAM10000: a large dataset of multi-source dermatoscopic images of common skin cancers; (2)A clinical dataset of skin cancer collected by dermoscopy. The model proposed has achieved 94.3% accuracy on HAM10000 and 94.1% accuracy on our datasets, which verifies the efficiency of SkinTrans. CONCLUSIONS: The transformer network has not only achieved good results in natural language but also achieved ideal results in the field of vision, which also lays a good foundation for skin cancer classification based on multimodal data. This paper is convinced that it will be of interest to dermatologists, clinical researchers, computer scientists and researchers in other related fields, and provide greater convenience for patients.

Extracellular vesicles derived from glioblastoma promote proliferation and migration of neural progenitor cells via PI3K-Akt pathway.

BACKGROUND: Glioblastomas are lethal brain tumors under the current combinatorial therapeutic strategy that includes surgery, chemo- and radio-therapies. Extensive changes in the tumor microenvironment is a key reason for resistance to chemo- or radio-therapy and frequent tumor recurrences. Understanding the tumor-nontumor cell interaction in TME is critical for developing new therapy. Glioblastomas are known to recruit normal cells in their environs to sustain growth and encroachment into other regions. Neural progenitor cells (NPCs) have been noted to migrate towards the site of glioblastomas, however, the detailed mechanisms underlying glioblastoma-mediated NPCs' alteration remain unkown. METHODS: We collected EVs in the culture medium of three classic glioblastoma cell lines, U87 and A172 (male cell lines), and LN229 (female cell line). U87, A172, and LN229 were co-cultured with their corresponding EVs, respectively. Mouse NPCs (mNPCs) were co-cultured with glioblastoma-derived EVs. The proliferation and migration of tumor cells and mNPCs after EVs treatment were examined. Proteomic analysis and western blotting were utilized to identify the underlying mechanisms of glioblastoma-derived EVs-induced alterations in mNPCs. RESULTS: We first show that glioblastoma cell lines U87-, A172-, and LN229-derived EVs were essential for glioblastoma cell prolifeartion and migration. We then demonstrated that glioblastoma-derived EVs dramatically promoted NPC proliferation and migration. Mechanistic studies identify that glioblastoma-derived EVs achieve their functions via activating PI3K-Akt-mTOR pathway in mNPCs. Inhibiting PI3K-Akt pathway reversed the elevated prolfieration and migration of glioblastoma-derived EVs-treated mNPCs. CONCLUSION: Our findings demonstrate that EVs play a key role in intercellular communication in tumor microenvironment. Inhibition of the tumorgenic EVs-mediated PI3K-Akt-mTOR pathway activation might be a novel strategy to shed light on glioblastoma therapy. Video Abstract.

Reprogrammed astrocytes display higher neurogenic competence, migration ability and cell death resistance than reprogrammed fibroblasts.

The direct reprogramming of somatic cells into induced neural progenitor cells (iNPCs) has been envisioned as a promising approach to overcome ethical and clinical issues of pluripotent stem cell transplantation. We previously reported that astrocyte-derived induced pluripotent stem cells (iPSCs) have more tendencies for neuronal differentiation than fibroblast-derived iPSCs. However, the differences of neurogenic potential between astrocyte-derived iNPCs (AiNPCs) and iNPCs from non-neural origins, such as fibroblast-derived iNPCs (FiNPCs), and the underlying mechanisms remain unclear. Our results suggested that AiNPCs exhibited higher differentiation efficiency, mobility and survival capacities, compared to FiNPCs. The whole transcriptome analysis revealed higher activities of TGFß signaling in AiNPCs, versus FiNPCs, following a similar trend between astrocytes and fibroblasts. The higher neurogenic competence, migration ability, and cell death resistance of AiNPCs could be abrogated using TGFß signaling inhibitor LY2157299. Hence, our study demonstrates the difference between iNPCs generated from neural and non-neural cells, together with the underlying mechanisms, which, provides valuable information for donor cell selection in the reprogramming approach.

Direct conversion of mouse astrocytes into neural progenitor cells and specific lineages of neurons.

BACKGROUND: Cell replacement therapy has been envisioned as a promising treatment for neurodegenerative diseases. Due to the ethical concerns of ESCs-derived neural progenitor cells (NPCs) and tumorigenic potential of iPSCs, reprogramming of somatic cells directly into multipotent NPCs has emerged as a preferred approach for cell transplantation. METHODS: Mouse astrocytes were reprogrammed into NPCs by the overexpression of transcription factors (TFs) Foxg1, Sox2, and Brn2. The generation of subtypes of neurons was directed by the force expression of cell-type specific TFs Lhx8 or Foxa2/Lmx1a. RESULTS: Astrocyte-derived induced NPCs (AiNPCs) share high similarities, including the expression of NPC-specific genes, DNA methylation patterns, the ability to proliferate and differentiate, with the wild type NPCs. The AiNPCs are committed to the forebrain identity and predominantly differentiated into glutamatergic and GABAergic neuronal subtypes. Interestingly, additional overexpression of TFs Lhx8 and Foxa2/Lmx1a in AiNPCs promoted cholinergic and dopaminergic neuronal differentiation, respectively. CONCLUSIONS: Our studies suggest that astrocytes can be converted into AiNPCs and lineage-committed AiNPCs can acquire differentiation potential of other lineages through forced expression of specific TFs. Understanding the impact of the TF sets on the reprogramming and differentiation into specific lineages of neurons will provide valuable strategies for astrocyte-based cell therapy in neurodegenerative diseases.