Deciphering ligand-receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data.

Background: Cell-cell communication in a tumor microenvironment is vital to tumorigenesis, tumor progression and therapy. Intercellular communication inference helps understand molecular mechanisms of tumor growth, progression and metastasis.

Methods: Focusing on ligand-receptor co-expressions, in this study, we developed an ensemble deep learning framework, CellComNet, to decipher ligand-receptor-mediated cell-cell communication from single-cell transcriptomic data.

CellEnBoost: A Boosting-Based Ligand-Receptor Interaction Identification Model for Cell-to-Cell Communication Inference.

Cell-to-cell communication (CCC) plays important roles in multicellular organisms. The identification of communication between cancer cells themselves and one between cancer cells and normal cells in tumor microenvironment helps understand cancer genesis, development and metastasis. CCC is usually mediated by Ligand-Receptor Interactions (LRIs).

Cell-cell communication inference and analysis in the tumour microenvironments from single-cell transcriptomics: data resources and computational strategies.

Carcinomas are complex ecosystems composed of cancer, stromal and immune cells. Communication between these cells and their microenvironments induces cancer progression and causes therapy resistance. In order to improve the treatment of cancers, it is essential to quantify crosstalk between and within various cell types in a tumour microenvironment.

EnANNDeep: An Ensemble-based lncRNA-protein Interaction Prediction Framework with Adaptive k-Nearest Neighbor Classifier and Deep Models.

lncRNA-protein interactions (LPIs) prediction can deepen the understanding of many important biological processes. Artificial intelligence methods have reported many possible LPIs. However, most computational techniques were evaluated mainly on one dataset, which may produce prediction bias.

Synthesis and Application of AS1411-Functionalized Gold Nanoparticles for Targeted Therapy of Gastric Cancer.

Gastric cancer therapy is still a big challenge, and nanomedicines bring much more hope. It is essential to develop multifunctional nanoparticles, especially those with high targeted capacity and antitumor effects, to improve gastric cancer therapy. In this study, we constructed AS1411 aptamer-based gold nanoparticles with appropriate size facilitating endocytosis and actively targeted drug delivery for gastric cancer cells via the specific AS1411-nucleolin interaction.

Laser-triggered collaborative chemophotothermal effect of gold nanoparticles for targeted colon cancer therapy.

Nanotechnology has shown advantages for cancer treatment. Multimodal nanoparticles (NPs) combining chemotherapy and photothermal therapy are promising and elicit synergetic benefit. However, there were still less multifunctional nanomaterials with good targeting and anti-tumor property applied as the colon cancer therapeutic strategy.

A stable filamentous coaxial microelectrode for Li-ion batteries: a case of olivine LiFePO.

By using a facile spray drying method, we fabricated a stable filamentous coaxial microelectrode of olivine LiFePO4, which delivers an excellent electrochemical performance in Li-ion batteries. Due to its simple structure, the microelectrode is a perfect model to study electrochemical reactions, even through in situ electrochemical measurements.

A variant of TNFR2-Fc fusion protein exhibits improved efficacy in treating experimental rheumatoid arthritis.

Etanercept, a TNF receptor 2-Fc fusion protein, is currently being used for the treatment of rheumatoid arthritis (RA). However, 25% to 38% of patients show no response which is suspected to be partially due to insufficient affinity of this protein to TNFalpha. By using computational protein design, we found that residue W89 and E92 of TNFR2 were critical for ligand binding.

Platinums sensitize human epithelial tumor cells to lymphotoxin alpha by inhibiting NFkappaB-dependent transcription.

Lymphotoxin alpha (LTalpha) was first identified as a direct anti-tumor factor, whereas increasing evidence has recently shown that in most cases the growth inhibition mediated by LTalpha requires the synergistic action of other factors, such as RNA transcription or protein synthesis inhibitor. In this study, we evaluated the combined effects of LTalpha and ten chemotherapeutic drugs on cell growth in a panel of human epithelial tumor cells, and explored the molecular mechanism of their mutual action. The results showed that platinums (cisplatin, carboplatin, oxaliplatin) are more universally effective than other chemotherapeutic drugs (doxorubicin, epi-doxorubicin, 5-flourouracil, mitomycin, cyclophosphamide, vincristine and vinorelbine) to enhance the response of six human epithelial tumor cell lines (A375, Bcap37, NCI-H157, SW480, BGC-823 and HeLa) to LTalpha.

Indomethacin enhances the cytotoxicity of recombinant human lymphotoxin alpha on tumor cells by suppressing NFkappaB signaling.

Indomethacin is widely used to treat inflammatory and prevent adverse events which frequently accrue in biotherapy. In phase I clinical trial of recombinant human lymphotoxin alpha (rhLTalpha), indomethacin was premedicated to alleviate chill and fever. However, it is unknown whether indomethacin influences the therapeutic efficacy of rhLTalpha.

[Construction of combined site-directed random mutation libraries of recombinant human lymphotoxin].

To construct the combined site-directed random mutation library of recombinant human Lymphotoxin (rhLT) for in vitro molecular evolution study, and to study the structure and function relationship. The random point mutations at the sites of 46,106 and 130 were individually generated by overlap PCR amplification with the random nucleotide primers. The three point mutations were combined and cloned into pMD-18T vector to construct the combined mutation library.