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Abstract Background Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. While many patients survive, a portion of PTC cases display high aggressiveness and even develop into refractory differentiated thyroid carcinoma. This may be alleviated by developing a novel model to predict the risk of recurrence. Ferroptosis is an iron-dependent form of regulated cell death (RCD) driven by lethal accumulation of lipid peroxides, is regulated by a set of genes and shows a variety of metabolic changes. To elucidate whether ferroptosis occurs in PTC, we analyse the gene expression profiles of the disease and established a new model for the correlation. Methods The thyroid carcinoma (THCA) datasets were downloaded from The Cancer Genome Atlas (TCGA), UCSC Xena and MisgDB, and included 502 tumour samples and 56 normal samples. A total of 60 ferroptosis related genes were summarised from MisgDB database. Gene set enrichment analysis (GSEA) and Gene set variation analysis (GSVA) were used to analyse pathways potentially involving PTC subtypes. Single sample GSEA (ssGSEA) algorithm was used to analyse the proportion of 28 types of immune cells in the tumour immune infiltration microenvironment in THCA and the hclust algorithm was used to conduct immune typing according to the proportion of immune cells. Spearman correlation analysis was performed on the ferroptosis gene expression and the correlation between immune infiltrating cells proportion. We established the WGCNA to identify genes modules that are highly correlated with the microenvironment of immune invasion. DEseq2 algorithm was further used for differential analysis of sequencing data to analyse the functions and pathways potentially involving hub genes. GO and KEGG enrichment analysis was performed using Clusterprofiler to explore the clinical efficacy of hub genes. Univariate Cox analysis was performed for hub genes combined with clinical prognostic data, and the results was included for lasso regression and constructed the risk regression model. ROC curve and survival curve were used for evaluating the model. Univariate Cox analysis and multivariate Cox analysis were performed in combination with the clinical data of THCA and the risk score value, the clinical efficacy of the model was further evaluated. Results We identify two subtypes in PTC based on the expression of ferroptosis related genes, with the proportion of cluster 1 significantly higher than cluster 2 in ferroptosis signature genes that are positively associated. The mutations of Braf and Nras are detected as the major mutations of cluster 1 and 2, respectively. Subsequent analyses of TME immune cells infiltration indicated cluster 1 is remarkably richer than cluster 2. The risk score of THCA is in good performance evaluated by ROC curve and survival curve, in conjunction with univariate Cox analysis and multivariate Cox analysis results based on the clinical data shows that the risk score of the proposed model could be used as an independent prognostic indicator to predict the prognosis of patients with papillary thyroid cancer. Conclusions Our study finds seven crucial genes, including Ac008063.2, Apoe, Bcl3, Acap3, Alox5ap, Atxn2l and B2m, and regulation of apoptosis by parathyroid hormone-related proteins significantly associated with ferroptosis and immune cells in PTC, and we construct the risk score model which can be used as an independent prognostic index to predict the prognosis of patients with PTC.

Background: Snails belong to the molluscan class Gastropoda, which inhabit land, freshwater and marine environments. Several land snail species, including Theba pisana, are crop pests of major concern, causing extensive damage to agriculture and horticulture. A deeper understanding of their molecular biology is necessary in order to develop methods to manipulate land snail populations. Results: The present study used in silico gene data mining of T. pisana tissue transcriptomes to predict 24,920 central nervous system (CNS) proteins, 37,661 foot muscle proteins and 40,766 hepatopancreas proteins, which together have 5,236 unique protein functional domains. Neuropeptides, metabolic enzymes and epiphragmin genes dominated expression within the CNS, hepatopancreas and muscle, respectively. Further investigation of the CNS transcriptome demonstrated that it might contain as many as 5,504 genes that encode for proteins destined for extracellular secretion. Neuropeptides form an important class of cell-cell messengers that control or influence various complex metabolic events. A total of 35 full-length neuropeptide genes were abundantly expressed within T. pisana CNS, encoding precursors that release molluscan-type bioactive neuropeptide products. These included achatin, allototropin, conopressin, elevenin, FMRFamide, LFRFamide, LRFNVamide, myomodulins, neurokinin Y, PKYMDT, PXFVamide, sCAPamides and several insulin-like peptides. Liquid chromatography-mass spectrometry of neural ganglia confirmed the presence of many of these neuropeptides. Conclusions: Our results provide the most comprehensive picture of the molecular genes and proteins associated with land snail functioning, including the repertoire of neuropeptides that likely play significant roles in neuroendocrine signalling. This information has the potential to expedite the study of molluscan metabolism and potentially stimulate advances in the biological control of land snail pest species. [ABSTRACT FROM AUTHOR]

Background: Oysters impart significant socio-ecological benefits from primary production of food supply, to estuarine ecosystems via reduction of water column nutrients, plankton and seston biomass. Little though is known at the molecular level of what genes are responsible for how oysters reproduce, filter nutrients, survive stressful physiological events and form reef communities. Neuropeptides represent a diverse class of chemical messengers, instrumental in orchestrating these complex physiological events in other species. Results: By a combination of in silico data mining and peptide analysis of ganglia, 74 putative neuropeptide genes were identified from genome and transcriptome databases of the Akoya pearl oyster, Pinctata fucata and the Pacific oyster, Crassostrea gigas, encoding precursors for over 300 predicted bioactive peptide products, including three newly identified neuropeptide precursors PFGx8amide, RxIamide and Wx3Yamide. Our findings also include a gene for the gonadotropin-releasing hormone (GnRH) and two egg-laying hormones (ELH) which were identified from both oysters. Multiple sequence alignments and phylogenetic analysis supports similar global organization of these mature peptides. Computer-based peptide modeling of the molecular tertiary structures of ELH highlights the structural homologies within ELH family, which may facilitate ELH activity leading to the release of gametes. Conclusion: Our analysis demonstrates that oysters possess conserved molluscan neuropeptide domains and overall precursor organization whilst highlighting many previously unrecognized bivalve idiosyncrasies. This genomic analysis provides a solid foundation from which further studies aimed at the functional characterization of these molluscan neuropeptides can be conducted to further stimulate advances in understanding the ecology and cultivation of oysters. [ABSTRACT FROM AUTHOR]