BAND: Biomedical Alert News Dataset

Infectious disease outbreaks continue to pose a significant threat to human health and well-being. To improve disease surveillance and understanding of disease spread, several surveillance systems have been developed to monitor daily news alerts and social media. However, existing systems lack thorough epidemiological analysis in relation to corresponding alerts or news, largely due to the scarcity of well-annotated reports data. To address this gap, we introduce the Biomedical Alert News Dataset (BAND), which includes 1,508 samples from existing reported news articles, open emails, and alerts, as well as 30 epidemiology-related questions. These questions necessitate the model's expert reasoning abilities, thereby offering valuable insights into the outbreak of the disease. The BAND dataset brings new challenges to the NLP world, requiring better disguise capability of the content and the ability to infer important information. We provide several benchmark tasks, including Named Entity Recognition (NER), Question Answering (QA), and Event Extraction (EE), to show how existing models are capable of handling these tasks in the epidemiology domain. To the best of our knowledge, the BAND corpus is the largest corpus of well-annotated biomedical outbreak alert news with elaborately designed questions, making it a valuable resource for epidemiologists and NLP researchers alike

Dietary exposure level of to perfluorinated compounds and its relationship with perinatal adverse events in pregnant women in Xuhui District of Shanghai

BackgroundPerfluorinated compounds (PFCs) are persistent organic pollutants. Dietary exposure to PFCs among pregnant women may lead to elevated risks of adverse events during pregnancy and postpartum depression. ObjectiveTo estimate potential risk of dietary exposure to PFCs among pregnant women in Xuhui District, Shanghai, and the relationship between dietary PFCs exposure and risks of adverse events during pregnancy and postpartum depression. MethodsThis study was a small cohort study which recruited women residing in Xuhui District from July 2017 to September 2018. All information was collected through questionnaires by trained investigators. Basic information and dietary information were collected at the time of inclusion, where the dietary information was obtained through the Food Frequency Questionnaire (FFQ). A follow-up visit was conducted within 42 d after delivery to collect the occurrence of adverse events during pregnancy and postpartum depression. According to the results of dietary survey, sampling and PFCs level testing were conducted on commercially available staple foods, poultry and livestock meat, aquatic products, vegetables, milk and dairy products, eggs, etc. The food sampling points covered all subdistricts in Xuhui District, including farmers' markets, supermarkets, convenience stores, and shops. Daily exposure level and hazard ratio (HR) of PFCs per capita were calculated according to the dietary survey and laboratory testing. Logistic regression was used to estimate the relationship between PFCs exposure and the risks of adverse events during pregnancy and postpartum depression. The levels of PFCs exposure were further divided into 4 groups according to interquartile range, and OR and Ptrend value were calculated respectively. ResultsA total of 345 pregnant women were recruited in this study, whose average age was (29.61±4.92) years. Among them, 26.37% subjects reported at least one adverse event during pregnancy, and 30.14% subjects reported an Edinburgh Postnatal Depression Scale (EPDS) score ≥12. A total of 132 food samples were collected and tested, and PFCs were positive mainly in milk and dairy products, poultry meat, livestock meat, eggs, fresh water products, and sea water products. The PFCs positive rate in fresh water products was the highest, reaching 100%. The average concentration of PFCs in the positive samples was 0.018-2.10 μg·kg−1. The HR of PFCs was 4.44. A higher risk of postpartum depression was found along with a higher perfluorooctane sulfonate (PFOS) exposure level (Ptrend=0.02). ConclusionDietary PFCs exposure may pose a health risk to pregnant women. The study findings suggest that decreasing the intake of freshwater products might help reduce the risk of PFCs exposure among pregnant women in Xuhui district, Shanghai

Critical role of c-Jun overexpression in liver metastasis of human breast cancer xenograft model

<p>Abstract</p> <p>Background</p> <p>c-Jun/AP-1 has been linked to invasive properties of aggressive breast cancer. Recently, it has been reported that overexpression of c-Jun in breast cancer cell line MCF-7 resulted in increased AP-1 activity, motility and invasiveness of the cells <it>in vitro </it>and tumor formation in nude mice. However, the role of c-Jun in metastasis of human breast cancer <it>in vivo </it>is currently unknown.</p> <p>Methods</p> <p>To further investigate the direct involvement of c-Jun in tumorigenesis and metastasis, in the present study, the effects of c-Jun overexpression were studied in both <it>in vitro </it>and in nude mice.</p> <p>Results</p> <p>Ectopic overexpression of c-Jun promoted the growth of MCF-7 cells and resulted in a significant increase in the percentage of cells in S phase and increased motility and invasiveness. Introduction of c-Jun gene alone into weakly invasive MCF-7 cells resulted in the transfected cells capable of metastasizing to the nude mouse liver following tail vein injection.</p> <p>Conclusion</p> <p>The present study confirms that overexpression of c-Jun contributes to a more invasive phenotype in MCF-7 cells. It indicates an interesting relationship between c-Jun expression and increased property of adhesion, migration and <it>in vivo </it>liver metastasis of MCF-7/c-Jun cells. The results provide further evidence that c-Jun is involved in the metastasis of breast cancer. The finding also opens an opportunity for development of anti-c-Jun strategies in breast cancer therapy.</p

Open-source genomic analysis of Shiga-toxin–producing E. coli O104:H4

An outbreak caused by Shiga-toxin–producing Escherichia coli O104:H4 occurred in Germany in May and June of 2011, with more than 3000 persons infected. Here, we report a cluster of cases associated with a single family and describe an open-source genomic analysis of an isolate from one member of the family. This analysis involved the use of rapid, bench-top DNA sequencing technology, open-source data release, and prompt crowd-sourced analyses. In less than a week, these studies revealed that the outbreak strain belonged to an enteroaggregative E. coli lineage that had acquired genes for Shiga toxin 2 and for antibiotic resistance

Fine root decomposition in forest ecosystems: an ecological perspective

Fine root decomposition is a physio-biochemical activity that is critical to the global carbon cycle (C) in forest ecosystems. It is crucial to investigate the mechanisms and factors that control fine root decomposition in forest ecosystems to understand their system-level carbon balance. This process can be influenced by several abiotic (e.g., mean annual temperature, mean annual precipitation, site elevation, stand age, salinity, soil pH) and biotic (e.g., microorganism, substrate quality) variables. Comparing decomposition rates within sites reveals positive impacts of nitrogen and phosphorus concentrations and negative effects of lignin concentration. Nevertheless, estimating the actual fine root breakdown is difficult due to inadequate methods, anthropogenic activities, and the impact of climate change. Herein, we propose that how fine root substrate and soil physiochemical characteristics interact with soil microorganisms to influence fine root decomposition. This review summarized the elements that influence this process, as well as the research methods used to investigate it. There is also need to study the influence of annual and seasonal changes affecting fine root decomposition. This cumulative evidence will provide information on temporal and spatial dynamics of forest ecosystems, and will determine how logging and reforestation affect fine root decomposition

Catecholamine up-regulates MMP-7 expression by activating AP-1 and STAT3 in gastric cancer

<p>Abstract</p> <p>Background</p> <p>Stress, anxiety and depression can cause complex physiological and neuroendocrine changes, resulting in increased level of stress related hormone catecholamine, which may constitute a primary mechanism by which physiological factors impact gene expression in tumors. In the present study, we investigated the effects of catecholamine stimulation on MMP-7 expression in gastric cancer cells and elucidated the molecular mechanisms of the up-regulation of MMP-7 level by catecholamine through an adrenergic signaling pathway.</p> <p>Results</p> <p>Increased MMP-7 expression was identified at both mRNA and protein levels in the gastric cancer cells in response to isoproterenol stimulation. β2-AR antigonist effectively abrogated isoproterenol-induced MMP-7 expression. The activation of STAT3 and AP-1 was prominently induced by isoproterenol stimulation and AP-1 displayed a greater efficacy than STAT3 in isoproterenol-induced MMP-7 expression. Mutagenesis of three STAT3 binding sites in MMP-7 promoter failed to repress the transactivation of MMP-7 promoter and silencing STAT3 expression was not effective in preventing isoproterenol-induced MMP-7 expression. However, isoproterenol-induced MMP-7 promoter activities were completely disappeared when the AP-1 site was mutated. STAT3 and c-Jun could physically interact and bind to the AP-1 site, implicating that the interplay of both transcriptional factors on the AP-1 site is responsible for isoproterenol-stimulated MMP-7 expression in gastric cancer cells. The expression of MMP-7 in gastric cancer tissues was found to be at the site where β2-AR was overexpressed and the levels of MMP-7 and β2-AR were the highest in the metastatic locus of gastric cancer.</p> <p>Conclusions</p> <p>Up-regulation of MMP-7 expression through β2-AR-mediated signaling pathway is involved in invasion and metastasis of gastric cancer.</p

Global Analysis of Gene Expression Profiles in Developing Physic Nut (Jatropha curcas L.) Seeds

Background: Physic nut (Jatropha curcas L.) is an oilseed plant species with high potential utility as a biofuel. Furthermore, following recent sequencing of its genome and the availability of expressed sequence tag (EST) libraries, it is a valuable model plant for studying carbon assimilation in endosperms of oilseed plants. There have been several transcriptomic analyses of developing physic nut seeds using ESTs, but they have provided limited information on the accumulation of stored resources in the seeds. Methodology/Principal Findings: We applied next-generation Illumina sequencing technology to analyze global gen