New molecular signatures are needed to improve the diagnosis of thyroid cancer (TC) and avoid unnecessary surgeries. In this study, we aimed to develop a robust and individualized diagnostic signature in TC. Gene expression profiles of tumor and nontumor samples were from 13 microarray datasets of Gene Expression Omnibus (GEO) database and one RNA‐sequencing dataset of The Cancer Genome Atlas (TCGA). A total of 1246 samples were divided into a training set (N = 435), a test set (N = 247), and one independent validation set (N = 564). In the training set, 115 most frequent differentially expressed genes (DEGs) among the included datasets were used to construct 6555 gene pairs, and 19 significant pairs were detected to further construct the diagnostic signature by a penalized generalized linear model. The signature showed a good diagnostic ability for TC in the training set (area under receiver operating characteristic curve (AUC) = 0.976), test set (AUC = 0.960), and TCGA dataset (AUC = 0.979). Subgroup analyses showed consistent results when considering the type of nontumor samples and microarray platforms. When compared with two existing molecular signatures in the diagnosis of thyroid nodules, the signature (AUC = 0.933) also showed a higher diagnostic ability (AUC = 0.886 for a 7‐gene signature and AUC = 0.892 for a 10‐gene signature). In conclusion, our study developed and validated an individualized diagnostic signature in TC. Large‐scale prospective studies were needed to further validate its diagnostic ability.

Using a number of fast-track and damage control surgical techniques, we have successfully established a stable model of gastric bypass in diabetic rats.

The study aimed to dissect the molecular mechanism of pancreatic cancer by a range of bioinformatics approaches. Three microarray datasets (GSE32676, GSE21654, and GSE14245) were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) with logarithm of fold change (|logFC|) >0.585 and p value <0.05 were identified between pancreatic cancer samples and normal controls. Transcription factors (TFs) were selected from the DEGs based on TRASFAC database. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed for the DEGs using The Database for Annotation, Visualization and Integrated Discovery (p value <0.05), followed by construction of protein-protein interaction (PPI) network using Search Tool for the Retrieval of Interacting Genes software. Latent pathway identification analysis was applied to analyze the DEGs-related pathways crosstalk and the pathways with high weight value were included in the pathway crosstalk network using Cytoscape. Sixty-five DEGs were screened out. CCAAT/enhancer-binding protein delta (CEBPD), FBJ osteosarcoma oncogene B (FOSB), Stratifin (SFN), Krüppel-like factor 5 (KLF5), Pentraxin 3 (PTX3), and nuclear receptor subfamily 4, group A, member 3 (NR4A3) were important TFs. Interleukin-6 (IL-6) was the hub node of the PPI network. DEGs were significantly enriched in NOD-like receptor signaling pathway which was primarily interacted with inflammation and immune related pathways (cytosolic DNA-sensing, hematopoietic cell lineage, intestinal immune network for IgA production and chemokine pathways). The study suggested CEBPD, FOSB, SFN, KLF5, PTX3, NR4A3, IL-6, and NOD-like receptor pathways were involved in pancreatic cancer.

Current evidence is inconsistent regarding the impact of metabolic syndrome (MetS) on sex hormones and reproductive function, and this meta-analysis aimed to illuminate the association. A literature search was conducted in public databases to identify all relevant studies, and study-specific standardized mean differences (SMD) and 95% confidence intervals (CI) were pooled using a random-effects model. Finally, 21 studies were identified with a total of 2923 MetS cases and 14062 controls. In males, MetS cases had a lower level of testosterone, inhibin B, total sperm count, sperm concentration, sperm normal morphology, sperm total motility, sperm progressive motility and sperm vitality, and a higher level of DNA fragmentation and mitochondrial membrane potential. In females, MetS cases had a higher level of testosterone. No significant difference was detected for follicle-stimulating hormone, luteinizing hormone, oestradiol, prolactin, anti-Müllerian hormone and semen volume in males, and for oestradiol, follicle-stimulating hormone, luteinizing hormone and progesterone in females. In conclusion, this meta-analysis indicated the impact of MetS on sex hormones and reproductive function, and MetS cases had a potential risk of infertility.

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