Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models: Application to Diabrotica virgifera virgifera

Many distribution models developed to predict the presence/absence of invasive alien species need to be fitted to a training dataset before practical use. The training dataset is characterized by the number of recorded presences/absences and by their geographical locations. The aim of this paper is to study the effect of the training dataset characteristics on model performance and to compare the relative importance of three factors influencing model predictive capability; size of training dataset, stage of the biological invasion, and choice of input variables. Nine models were assessed for their ability to predict the distribution of the western corn rootworm, Diabrotica virgifera virgifera, a major pest of corn in North America that has recently invaded Europe. Twenty-six training datasets of various sizes (from 10 to 428 presence records) corresponding to two different stages of invasion (1955 and 1980) and three sets of input bioclimatic variables (19 variables, six variables selected using information on insect biology, and three linear combinations of 19 variables derived from Principal Component Analysis) were considered. The models were fitted to each training dataset in turn and their performance was assessed using independent data from North America and Europe. The models were ranked according to the area under the Receiver Operating Characteristic curve and the likelihood ratio. Model performance was highly sensitive to the geographical area used for calibration; most of the models performed poorly when fitted to a restricted area corresponding to an early stage of the invasion. Our results also showed that Principal Component Analysis was useful in reducing the number of model input variables for the models that performed poorly with 19 input variables. DOMAIN, Environmental Distance, MAXENT, and Envelope Score were the most accurate models but all the models tested in this study led to a substantial rate of mis-classification

Signaling pathway networks mined from human pituitary adenoma proteomics data

Abstract Background We obtained a series of pituitary adenoma proteomic expression data, including protein-mapping data (111 proteins), comparative proteomic data (56 differentially expressed proteins), and nitroproteomic data (17 nitroproteins). There is a pressing need to clarify the significant signaling pathway networks that derive from those proteins in order to clarify and to better understand the molecular basis of pituitary adenoma pathogenesis and to discover biomarkers. Here, we describe the significant signaling pathway networks that were mined from human pituitary adenoma proteomic data with the Ingenuity pathway analysis system. Methods The Ingenuity pathway analysis system was used to analyze signal pathway networks and canonical pathways from protein-mapping data, comparative proteomic data, adenoma nitroproteomic data, and control nitroproteomic data. A Fisher's exact test was used to test the statistical significance with a significance level of 0.05. Statistical significant results were rationalized within the pituitary adenoma biological system with literature-based bioinformatics analyses. Results For the protein-mapping data, the top pathway networks were related to cancer, cell death, and lipid metabolism; the top canonical toxicity pathways included acute-phase response, oxidative-stress response, oxidative stress, and cell-cycle G2/M transition regulation. For the comparative proteomic data, top pathway networks were related to cancer, endocrine system development and function, and lipid metabolism; the top canonical toxicity pathways included mitochondrial dysfunction, oxidative phosphorylation, oxidative-stress response, and ERK/MAPK signaling. The nitroproteomic data from a pituitary adenoma were related to cancer, cell death, lipid metabolism, and reproductive system disease, and the top canonical toxicity pathways mainly related to p38 MAPK signaling and cell-cycle G2/M transition regulation. Nitroproteins from a pituitary control related to gene expression and cellular development, and no canonical toxicity pathways were identified. Conclusions This pathway network analysis demonstrated that mitochondrial dysfunction, oxidative stress, cell-cycle dysregulation, and the MAPK-signaling abnormality are significantly associated with a pituitary adenoma. These pathway-network data provide new insights into the molecular mechanisms of human pituitary adenoma pathogenesis, and new clues for an in-depth investigation of pituitary adenoma and biomarker discovery.</p

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children &lt;18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p&lt;0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p&lt;0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p&lt;0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

T Cell Interactions in Mycobacterial Granulomas: Non-Specific T Cells Regulate Mycobacteria-Specific T Cells in Granulomatous Lesions

Infections with pathogenic mycobacteria are controlled by the formation of a unique structure known as a granuloma. The granuloma represents a host&ndash;pathogen interface where bacteria are killed and confined by the host response, but also where bacteria persist. Previous work has demonstrated that the T cell repertoire is heterogenous even at the single granuloma level. However, further work using pigeon cytochrome C (PCC) epitope-tagged BCG (PCC-BCG) and PCC-specific 5CC7 RAG&minus;/&minus; TCR transgenic (Tg) mice has demonstrated that a monoclonal T cell population is able to control infection. At the chronic stage of infection, granuloma-infiltrating T cells remain highly activated in wild-type mice, while T cells in the monoclonal T cell mice are anergic. We hypothesized that addition of an acutely activated non-specific T cell to the monoclonal T cell system could recapitulate the wild-type phenotype. Here we report that activated non-specific T cells have access to the granuloma and deliver a set of cytokines and chemokines to the lesions. Strikingly, non-specific T cells rescue BCG-specific T cells from anergy and enhance the function of BCG-specific T cells in the granuloma in the chronic phase of infection when bacterial antigen load is low. In addition, we find that these same non-specific T cells have an inhibitory effect on systemic BCG-specific T cells. Taken together, these data suggest that T cells non-specific for granuloma-inducing agents can alter the function of granuloma-specific T cells and have important roles in mycobacterial immunity and other granulomatous disorders

Smoking experience of Filipino adolescents and its impact on social life and self-concept

The study validates the proximal influences of initiation and maintenance of Filipino adolescent\u27s smoking behavior under social life and self concept proposed by comprehensive framework of Theory of Triadic Influence (TTI) as well as exploring the adolescent\u27s experience based their perception of social life and self concept. Using a qualitative thermatic analysis, 4 participants were interviewed (15-19 years old). All the themes were found in the existing literature. Most social life and self concept related factors contributed to influence the initiation and maintenance of the smoking behavior. Social life related factors influence more in initiation and self concept factors influence more in maintenance of smoking behavior. The research findings suggest that new methods may be added in future research in order to understand different degrees of influential factors in order to further understand the TTI on smoking behaviors. Moreover, bigger sample size may be necessary in order to further explore the factors that may influence adolescent\u27s smoking behavior