Objectives To assess the associations between occupational exposure to biocides and pesticides and risk of thyroid cancer. Methods Using data from a population-based case-control study involving 462 incident thyroid cancer cases and 498 controls in Connecticut collected in 2010–2011, we examined the association with occupational exposure to biocides and pesticides through a job-exposure matrix. We used unconditional logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (95% CI), adjusting for potential confounders. Results Individuals who were occupationally ever exposed to biocides had an increased risk of thyroid cancer (OR=1.65, 95% CI: 1.16, 2.35), and the highest risk was observed for the high cumulative probability of exposure (OR=2.18, 95%CI: 1.28–3.73). The observed associations were similar when we restricted to papillary thyroid cancer and well-differentiated thyroid cancer. Stronger associations were observed for thyroid microcarcinomas (tumor size ≤1cm). No significant association was observed for occupational exposure to pesticides. Conclusions Our study provides the first evidence linking occupational exposure to biocides and risk of thyroid cancer. The results warrant further investigation.

Among gynecological cancers, cervical cancer is a common malignancy and remains the leading cause of cancer-related death for women. However, the exact molecular pathogenesis of cervical cancer is not known. Hence, understanding the molecular mechanisms underlying cervical cancer pathogenesis will aid in the development of effective treatment modalities. In this research, we attempted to discern candidate biomarkers for cervical cancer by using multiple bioinformatics approaches. First, we performed differential expression analysis based on cervical squamous cell carcinoma and endocervical adenocarcinoma data from The Cancer Genome Atlas database, then used differentially expressed genes for weighted gene co-expression network construction to find the most relevant gene module for cervical cancer. Next, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on the module genes, followed by using protein–protein interaction network analysis and Cytoscape to find the key gene. Finally, we validated the key gene by using multiple online sites and experimental methods. Through weighted gene co-expression network analysis, we found the turquoise module was the highest correlated module with cervical cancer diagnosis. The biological process of the module genes focused on cell proliferation, cell adhesion, and protein binding processes, while the Kyoto Encyclopedia of Genes and Genomes pathway of the module significantly enriched pathways related to cancer and cell circle. Among the module genes, SOX9 was identified as the hub gene, and its expression was associated with cervical cancer prognosis. We found the expression of SOX9 correlates with cancer-associated fibroblast immune infiltration in immune cells by Timer2.0. Furthermore, cancer-associated fibroblast infiltration is linked to cervical cancer patients’ prognosis. Compared to those in normal adjacent, immunohistochemical and real-time quantitative polymerase chain reaction (qPCR) showed that the protein and mRNA expression of SOX9 in cervical cancer were higher. Therefore, the SOX9 gene acts as an oncogene in cervical cancer, interactive with immune infiltration of cancer-associated fibroblasts, thereby affecting the prognosis of patients with cervical cancer.

Background: Mutations in genes associated with deafness differ between ethnic groups and regions in China. In this study, we investigated the genes associated with deafness in pregnant women to analyze the distribution of mutations leading to deafness in Zhuzhou, China.Methods: A total of 10,684 pregnant women were enrolled in this study. DNA samples were collected to detect the 14 common mutations in deafness genes (at 108 sites). Results: Prevalence of mutations in deafness genes in pregnant women with normal hearing in Zhuzhou was 4.92% (526/10,684). Among these 526 pregnant women with deafness gene mutations, the frequencies of mutated GJB2, GJB3, SLC26A4, and mtDNA 12S rRNA were 40.11, 7.22, 40.68, and 11.98%, respectively. The hotspots for mutations in the deafness genes were: c.235delC in GJB2 (31.18%), c.919-2A > G in SLC26A4 (18.44%), c.299_300delAT in GJB2(5.70%), m.7444G > A in mtDNA 12S rRNA (5.70%), c.1229C > T in SLC26A4 (5.51%), m.1555A > G in mtDNA 12S rRNA (5.32%), accounting for 71.85%. Moreover, husbands of the 526 pregnant women who carried the deafness gene mutations were also included in the analysis to detect deafness gene mutations. Among the 526 husbands, 23 husbands carried mutations in deafness genes, accounting for 4.37%. The deafness gene mutations of the husbands and pregnant wives were not the same. In addition, the results of the neonatal follow-up hearing tests were all normal. Conclusion:Our study identified the prevalence of mutations in GJB2, SLC26A4, mtDNA 12S rRNA, and GJB3 genes in pregnant women from Zhuzhou, China.

This study set out to determine the key metabolite changes underlying the pathophysiology of severe preeclampsia (PE) using metabolic analysis. We collected sera from 10 patients with severe PE and from 10 healthy pregnant women of the same trimester and analyzed them using liquid chromatography mass spectrometry. A total of 3,138 differential metabolites were screened, resulting in the identification of 124 differential metabolites. Kyoto encyclopedia of genes and genomes pathway analysis revealed that they were mainly enriched in the following metabolic pathways: central carbon metabolism in cancer; protein digestion and absorption; aminoacyl-transfer RNA biosynthesis; mineral absorption; alanine, aspartate, and glutamate metabolism; and prostate cancer. After analysis of 124 differential metabolites, 2-hydroxybutyric acid was found to be the most critical differential metabolite, and its use allowed the differentiation of women with severe PE from healthy pregnant women. In summary, our analysis revealed that 2-hydroxybutyric acid is a potential key metabolite for distinguishing severe PE from healthy controls and is also a marker for the early diagnosis of severe PE, thus allowing early intervention.