Machine learning application in personalised lung cancer recurrence and survivability prediction

Machine learning is an important artificial intelligence technique that is widely applied in cancer diagnosis and detection. More recently, with the rise of personalised and precision medicine, there is a growing trend towards machine learning applications for prognosis prediction. However, to date, building reliable prediction models of cancer outcomes in everyday clinical practice is still a hurdle. In this work, we integrate genomic, clinical and demographic data of lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) patients from The Cancer Genome Atlas (TCGA) and introduce copy number variation (CNV) and mutation information of 15 selected genes to generate predictive models for recurrence and survivability. We compare the accuracy and benefits of three well-established machine learning algorithms: decision tree methods, neural networks and support vector machines. Although the accuracy of predictive models using the decision tree method has no significant advantage, the tree models reveal the most important predictors among genomic information (e.g. KRAS, EGFR, TP53), clinical status (e.g. TNM stage and radiotherapy) and demographics (e.g. age and gender) and how they influence the prediction of recurrence and survivability for both early stage LUAD and LUSC. The machine learning models have the potential to help clinicians to make personalised decisions on aspects such as follow-up timeline and to assist with personalised planning of future social care needs

Finding needles in haystacks:Linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Reannotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi.The Intramural Research Programs of the National Center for Biotechnology Information, National Library of Medicine and the National Human Genome Research Institute, both at the National Institutes of Health.http://www.ncbi.nlm.nih.gov/bioproject/PRJNA177353am201

Finding needles in haystacks : linking scientific names, reference specimens and molecular data for Fungi

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Reannotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi.The Intramural Research Programs of the National Center for Biotechnology Information, National Library of Medicine and the National Human Genome Research Institute, both at the National Institutes of Health.http://www.ncbi.nlm.nih.gov/bioproject/PRJNA177353am201

Association analysis of FXYD5 with prognosis and immunological characteristics across pan-cancer

Background: The FXYD domain-containing ion transport regulator 5 (FXYD5) gene is a cancer promoter. However, evidence for an association between FXYD5 and various types of cancer is still lacking. Using multi-omics bioinformatics, our study aimed to reveal the expression distribution, prognostic value, immune infiltration correlation, and molecular functions of FXYD5. Methods: Using pan-cancer multi-omics data (including The Cancer Genome Atlas, PrognoScan, Gene Expression Profiling Interactive Analysis, cBioPortal, Gene Expression Omnibus, TIMER and scTIME Portal), we assessed the differences in the expression and prognostic value of FXYD5 in malignant tumors. Furthermore, at the single-cell level, we analyze the expression distribution of FXYD5 across different cell types within the tumor microenvironment, and its relationship with the immune microenvironment. Finally, focusing on ovarian cancer, we conducted preliminary validation of the above findings using cell and molecular biology techniques. Results: Our results indicated that FXYD5 was up-regulated in various tumor types and was positively associated with tumor progression. We also revealed that FXYD5 was ubiquitously expressed in microenvironmental cells at the single-cell level, and its upregulation was associated with enhanced immune infiltration, cancer-associated fibroblast infiltration, and dysfunction of tumor-infiltrating cytotoxic T lymphocyte. Additionally, its expression was positively correlated with immune checkpoint genes, DNA mismatch repair genes, MSI (microsatellite instability) and TMB (tumor mutational burden) across various cancers. Its higher expression in cytotoxic T lymphocytes attenuated its ability to predict patient survival with PD-L1 (programmed death-ligand 1) blockade therapy, and FXYD5 was found to be a potential regulator of tumor immune escape and resistance to cancer immunotherapies. Based on GSEA (gene set enrichment analysis) and experimental verification, FXYD5 activated TGF‐β/SMAD signaling and drove EMT (epithelial-mesenchymal transition) to promote ovarian cancer progression. Conclusion: In summary, our study revealed that FXYD5-TGFβ axis may coregulate the interaction between tumors, CAFs (carcinoma-associated fibroblasts) and immune cells to reshape the tumor immune microenvironment and promote tumorigenesis and tumor progression. Thus, FXYD5 could be used as an immune-related biomarker for diagnosing and predicting the prognosis of multiple cancer types. Therefore, our findings suggest that targeting FXYD5 in TME (tumor microenvironment) may be a promising therapeutic strategy

Effect of Salinity on the Zooplankton Community in the Pearl River Estuary

Understanding the relationship between the zooplankton distribution and salinity may provide key information to understand ecosystem function under the condition of a global mean sea level rise caused by global climate change. However, little is known about how increasing salinity level will affect the entire zooplankton community on a large scale. Here we completed 1 year of field investigations on the Pearl River Estuary and analyzed the distribution and structure of the zooplankton community. A total of 68 zooplankton species were identified during the survey. The number and diversity (richness, evenness, Shannon index, and Simpson's index) of the zooplankton species decreased as salinity increased from 0.10 to 21.26. Salinity negatively affected the abundances of rotifers, cladocerans, and total zooplankton, while it had little effect on copepod abundance. Some salt-tolerant species, such as Keratella tropica, Polyarthra vulgaris, and Paracalanus crassirostris, survived at high-salinity sites. A pattern was observed at all sites: the peak in copepod abundance always occurred when rotifers were abundant (sites S1 and S2) or after rotifer abundance reached a maximum level (sites S3, S4, and S5). In general, salinity was the most important environmental factor shaping zooplankton biodiversity and abundance. This study provides insight into potential biodiversity and structure of the zooplankton community in response to salinity change

KIF3C Promotes Proliferation, Migration, and Invasion of Glioma Cells by Activating the PI3K/AKT Pathway and Inducing EMT

Kinesin superfamily protein 3C (KIF3C), a motor protein of the kinesin superfamily, is expressed in the central nervous system (CNS). Recently, several studies have suggested that KIF3C may act as a potential therapeutic target in solid tumors. However, the exact function and possible mechanism of the motor protein KIF3C in glioma remain unclear. In this study, a variety of tests including CCK-8, migration, invasion, and flow cytometry assays, and western blot were conducted to explore the role of KIF3C in glioma cell lines (U87 and U251). We found that overexpression of KIF3C in glioma cell lines promoted cell proliferation, migration, and invasion and suppressed apoptosis, while silencing of KIF3C reversed these effects. Ectopic KIF3C also increased the expression of N-cadherin, vimentin, snail, and slug to promote the epithelial-mesenchymal transition (EMT). Mechanistically, overexpression of KIF3C increased the levels of phosphatidylinositol 3-kinase (PI3K) and phosphorylated protein kinase B (p-AKT). These responses were reversed by KIF3C downregulation or AKT inhibition. Our results indicate that KIF3C promotes proliferation, migration, and invasion and inhibits apoptosis in glioma cells, possibly by activating the PI3K/AKT pathway in vitro. KIF3C might act as a potential biomarker or therapeutic target for further basic research or clinical management of glioma

Study on External Power Receiving Planning of Receiving-end Grid in AC/DC Hybrid Background

Based on the practical experience of power grid planning, the general characteristics and main problems of the receiving-end grid are summarized, and the ideas and methods of external power receiving planning are put forward. Combined with the current situation, the pattern of power supply and demands of a typical recipient power network in China, this paper analysed the reasonable scale of power receiving, the proportion of AC/DC power transmitted and the infeed AC/DC terminal location for long-term development, and conducts comprehensive technical and economic comparisons among various feasible external power receiving schemes to form a recommended schem