Role of Sector Vulnerability in the Temperature, Wildlife Tourism Sector Performance Relationship in Maasai Mara Ecosystem, Kenya

Abstract This study sought to investigate the effect of sector vulnerability in the relationship between temperature and wildlife tourism performance. The study adapted a pragmatic research design that advocates for mixed methods which allows for the use of both qualitative and quantitative research methods to study phenomena. Qualitative data collected was analyzed by use of content analysis while quantitative data collected was analyzed by use of SPSS for exploratory factor analysis and AMOS for confirmatory factor analysis and structural equation modeling. The results of the study were that vulnerability mediated the relationship between temperature and wildlife tourism ? = - 0.121, t = -4.583, P <.00, the results of this study are useful to wildlife tourism stakeholders because it forms a basis that can be used by industry players to develop appropriate adaptations since climate change is the new norm globally.  Key words: wildlife tourism, vulnerability, climate chang

Generation of orthotopic patient-derived xenografts from gastrointestinal stromal tumor.

BackgroundGastrointestinal stromal tumor (GIST) is the most common sarcoma and its treatment with imatinib has served as the paradigm for developing targeted anti-cancer therapies. Despite this success, imatinib-resistance has emerged as a major problem and therefore, the clinical efficacy of other drugs has been investigated. Unfortunately, most clinical trials have failed to identify efficacious drugs despite promising in vitro data and pathological responses in subcutaneous xenografts. We hypothesized that it was feasible to develop orthotopic patient-derived xenografts (PDXs) from resected GIST that could recapitulate the genetic heterogeneity and biology of the human disease.MethodsFresh tumor tissue from three patients with pathologically confirmed GISTs was obtained immediately following tumor resection. Tumor fragments (4.2-mm3) were surgically xenografted into the liver, gastric wall, renal capsule, and pancreas of immunodeficient mice. Tumor growth was serially assessed with ultrasonography (US) every 3-4 weeks. Tumors were also evaluated with positron emission tomography (PET). Animals were sacrificed when they became moribund or their tumors reached a threshold size of 2500-mm3. Tumors were subsequently passaged, as well as immunohistochemically and histologically analyzed.ResultsHerein, we describe the first model for generating orthotopic GIST PDXs. We have successfully xenografted three unique KIT-mutated tumors into a total of 25 mice with an overall success rate of 84% (21/25). We serially followed tumor growth with US to describe the natural history of PDX growth. Successful PDXs resulted in 12 primary xenografts in NOD-scid gamma or NOD-scid mice while subsequent successful passages resulted in 9 tumors. At a median of 7.9 weeks (range 2.9-33.1 weeks), tumor size averaged 473 ± 695-mm³ (median 199-mm3, range 12.6-2682.5-mm³) by US. Furthermore, tumor size on US within 14 days of death correlated with gross tumor size on necropsy. We also demonstrated that these tumors are FDG-avid on PET imaging, while immunohistochemically and histologically the PDXs resembled the primary tumors.ConclusionsWe report the first orthotopic model of human GIST using patient-derived tumor tissue. This novel, reproducible in vivo model of human GIST may enhance the study of GIST biology, biomarkers, personalized cancer treatments, and provide a preclinical platform to evaluate new therapeutic agents for GIST

Combined linkage and association mapping of putative QTLs controlling black tea quality and drought tolerance traits

The advancements in genotyping have opened new approaches for identification and precise mapping of quantitative trait loci (QTLs) in plants, particularly by combining linkage and association mapping (AM) analysis. In this study, a combination of linkage and the AM approach was used to identify and authenticate putative QTLs associated with black tea quality traits and percent relative water content (%RWC). The population structure analysis clustered two parents and their respective 261 F1 progenies from the two reciprocal crosses into two clusters with 141 tea accessions in cluster one and 122 tea accessions in cluster two. The two clusters were of mixed origin with tea accessions in population TRFK St. 504 clustering together with tea accessions in population TRFK St. 524. A total of 71 putative QTLs linked to black tea quality traits and %RWC were detected in interval mapping (IM) method and were used as cofactors in multiple QTL model (MQM) mapping where 46 putative QTLs were detected. The phenotypic variance for each QTL ranged from 2.8 to 23.3% in IM and 4.1 to 23% in MQM mapping. Using Q-model and Q + K-model in AM, a total of 49 DArTseq markers were associated with 16 phenotypic traits. Significant marker-trait association in AM were similar to those obtained in IM, and MQM mapping except for six more putative QTLs detected in AM which are involved in biosynthesis of secondary metabolites, carbon fixation and abiotic stress. The combined linkage and AM approach appears to have great potential to improve the selection of desirable traits in tea breeding.James Finlay (Kenya) Ltd., George Williamson (Kenya) Ltd., Sotik Tea Company (Kenya) Ltd., Mcleod Russell (Uganda) Ltd., the TRI of Kenya and Southern African Biochemistry and Informatics for Natural Products (SABINA) as well as the Technology and Human Resources for Industry Programme (THRIP), an initiative of the Department of Trade and Industries of South Africa (dti), the National Research Foundation (NRF) of South Africa, and the University of Pretoria (South Africa).https://www.springer.com/journal/106812020-09-11hj2020BiochemistryGeneticsMicrobiology and Plant Patholog

Functional annotation of putative QTL associated with black tea quality and drought tolerance traits

The understanding of black tea quality and percent relative water content (%RWC) traits in tea (Camellia sinensis) by a quantitative trait loci (QTL) approach can be useful in elucidation and identification of candidate genes underlying the QTL which has remained to be difficult. The objective of the study was to identify putative QTL controlling black tea quality and percent relative water traits in two tea populations and their F1 progeny. A total of 1,421 DArTseq markers derived from the linkage map identified 53 DArTseq markers to be linked to black tea quality and %RWC. All 53 DArTseq markers with unique best hits were identified in the tea genome. A total of 5,592 unigenes were assigned gene ontology (GO) terms, 56% comprised biological processes, cellular component (29%) and molecular functions (15%), respectively. A total of 84 unigenes in 15 LGs were assigned to 25 different Kyoto Encyclopedia of Genes and Genomes (KEGG) database pathways based on categories of secondary metabolite biosynthesis. The three major enzymes identified were transferases (38.9%), hydrolases (29%) and oxidoreductases (18.3%). The putative candidate proteins identified were involved in flavonoid biosynthesis, alkaloid biosynthesis, ATPase family proteins related to abiotic/biotic stress response. The functional annotation of putative QTL identified in this current study will shed more light on the proteins associated with caffeine and catechins biosynthesis and % RWC. This study may help breeders in selection of parents with desirable DArTseq markers for development of new tea cultivars with desirable traits.http://www.nature.com/sreppm2020BiochemistryGeneticsMicrobiology and Plant Patholog

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH -Mutant Molecular Profiles

Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahepatic CCA cases and propose a molecular classification scheme. We identified an IDH mutant-enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance