Coexistence between Javan Slow Lorises (Nycticebus javanicus) and humans in a dynamic agroforestry landscape in West Java, Indonesia

In a world increasingly dominated by human demand for agricultural products, we need to understand wildlife’s ability to survive in agricultural environments. We studied the interaction between humans and Javan slow lorises (Nycticebus javanicus) in Cipaganti, Java, Indonesia. After its introduction in 2013, chayote (Sechium edule), a gourd grown on bamboo lattice frames, became an important cash crop. To evaluate people’s use of this crop and to measure the effect of this increase on slow loris behavior, home ranges, and sleep sites, we conducted interviews with local farmers and analysed the above variables in relation to chayote expansion between 2011 and 2015. Interviews with farmers in 2011, 2013, and 2015 confirm the importance of chayote and of bamboo and slow lorises in their agricultural practices. In 2015 chayote frames covered 12% of land in Cipaganti, occupying 4% of slow loris home ranges, which marginally yet insignificantly increased in size with the increase in chayote. Slow lorises are arboreal and the bamboo frames increased connectivity within their ranges. Of the sleep sites we monitored from 2013 to 2016, 24 had disappeared, and 201 continued to be used by the slow lorises and processed by local people. The fast growth rate of bamboo, and the recognition of the value of bamboo by farmers, allow persistence of slow loris sleep sites. Overall introduction of chayote did not result in conflict between farmers and slow lorises, and once constructed the chayote bamboo frames proved to be beneficial for slow lorises

Suffering in long-term cancer survivors: An evaluation of the PRISM-R2 in a population-based cohort

The Pictorial Representation of Illness and Self Measure-Revised 2 (PRISM-R2) has been developed as generic measure to assess suffering. The aim of this study was to evaluate the ability of this instrument to identify long-term cancer survivors with high levels of suffering who may need additional support. 1299 cancer survivors completed the PRISM-R2, the Short Form Health Survey (SF-36), and the Quality of Life-Cancer Survivors questionnaire (QoL-CS). The PRISM-R2 distinguishes between the Self-Illness Separation (SIS) and Illness Perception Measure (IPM), both measuring aspects of suffering. 112 (9%) cancer survivors reported high suffering according to IPM. This group had a higher cancer stage at diagnosis, more cancer recurrences, more comorbidities, and were lower educated compared to people reporting less suffering. The PRISM-R2 could explain substantial amounts of variance (10-14%) in the psychological aspects of the SF-36 and QoL-CS. The IPM also discriminated statistically and clinically significant between high- and low-health status. The PRISM-R2 proved to be able to discriminate between individuals with good and deteriorated levels of QoL. Further evaluation of its validity and screening potential is recommended

A chemical biology toolbox to study protein methyltransferases and epigenetic signaling

© 2019, The Author(s). Protein methyltransferases (PMTs) comprise a major class of epigenetic regulatory enzymes with therapeutic relevance. Here we present a collection of chemical probes and associated reagents and data to elucidate the function of human and murine PMTs in cellular studies. Our collection provides inhibitors and antagonists that together modulate most of the key regulatory methylation marks on histones H3 and H4, providing an important resource for modulating cellular epigenomes. We describe a comprehensive and comparative characterization of the probe collection with respect to their potency, selectivity, and mode of inhibition. We demonstrate the utility of this collection in CD4 + T cell differentiation assays revealing the potential of individual probes to alter multiple T cell subpopulations which may have implications for T cell-mediated processes such as inflammation and immuno-oncology. In particular, we demonstrate a role for DOT1L in limiting Th1 cell differentiation and maintaining lineage integrity. This chemical probe collection and associated data form a resource for the study of methylation-mediated signaling in epigenetics, inflammation and beyond

Multiple Cellular Responses to Serotonin Contribute to Epithelial Homeostasis

Epithelial homeostasis incorporates the paradoxical concept of internal change (epithelial turnover) enabling the maintenance of anatomical status quo. Epithelial cell differentiation and cell loss (cell shedding and apoptosis) form important components of epithelial turnover. Although the mechanisms of cell loss are being uncovered the crucial triggers that modulate epithelial turnover through regulation of cell loss remain undetermined. Serotonin is emerging as a common autocrine-paracine regulator in epithelia of multiple organs, including the breast. Here we address whether serotonin affects epithelial turnover. Specifically, serotonin's roles in regulating cell shedding, apoptosis and barrier function of the epithelium. Using in vivo studies in mouse and a robust model of differentiated human mammary duct epithelium (MCF10A), we show that serotonin induces mammary epithelial cell shedding and disrupts tight junctions in a reversible manner. However, upon sustained exposure, serotonin induces apoptosis in the replenishing cell population, causing irreversible changes to the epithelial membrane. The staggered nature of these events induced by serotonin slowly shifts the balance in the epithelium from reversible to irreversible. These finding have very important implications towards our ability to control epithelial regeneration and thus address pathologies of aberrant epithelial turnover, which range from degenerative disorders (e.g.; pancreatitis and thyrioditis) to proliferative disorders (e.g.; mastitis, ductal ectasia, cholangiopathies and epithelial cancers)

CyclinPred: A SVM-Based Method for Predicting Cyclin Protein Sequences

Functional annotation of protein sequences with low similarity to well characterized protein sequences is a major challenge of computational biology in the post genomic era. The cyclin protein family is once such important family of proteins which consists of sequences with low sequence similarity making discovery of novel cyclins and establishing orthologous relationships amongst the cyclins, a difficult task. The currently identified cyclin motifs and cyclin associated domains do not represent all of the identified and characterized cyclin sequences. We describe a Support Vector Machine (SVM) based classifier, CyclinPred, which can predict cyclin sequences with high efficiency. The SVM classifier was trained with features of selected cyclin and non cyclin protein sequences. The training features of the protein sequences include amino acid composition, dipeptide composition, secondary structure composition and PSI-BLAST generated Position Specific Scoring Matrix (PSSM) profiles. Results obtained from Leave-One-Out cross validation or jackknife test, self consistency and holdout tests prove that the SVM classifier trained with features of PSSM profile was more accurate than the classifiers based on either of the other features alone or hybrids of these features. A cyclin prediction server- CyclinPred has been setup based on SVM model trained with PSSM profiles. CyclinPred prediction results prove that the method may be used as a cyclin prediction tool, complementing conventional cyclin prediction methods

Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated

PURPOSE: Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for individual patients is of pivotal importance. However, only biomarkers for highly aggressive tumors are established (CDKN2A/B and TERT), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma. METHODS: DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 multicenter cases. RESULTS: Both CNV- and methylation family-based subgrouping independently resulted in increased prediction accuracy of risk of recurrence compared with the WHO classification (c-indexes WHO 2016, CNV, and methylation family 0.699, 0.706, and 0.721, respectively). Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference P = .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively). CONCLUSION: Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction

LMTK3 confers chemo-resistance in breast cancer

Lemur tyrosine kinase 3 (LMTK3) is an oncogenic kinase that is involved in different types of cancer (breast, lung, gastric, colorectal) and biological processes including proliferation, invasion, migration, chromatin remodeling as well as innate and acquired endocrine resistance. However, the role of LMTK3 in response to cytotoxic chemotherapy has not been investigated thus far. Using both 2D and 3D tissue culture models, we found that overexpression of LMTK3 decreased the sensitivity of breast cancer cell lines to cytotoxic (doxorubicin) treatment. In a mouse model we showed that ectopic overexpression of LMTK3 decreases the efficacy of doxorubicin in reducing tumor growth. Interestingly, breast cancer cells overexpressing LMTK3 delayed the generation of double strand breaks (DSBs) after exposure to doxorubicin, as measured by the formation of γH2AX foci. This effect was at least partly mediated by decreased activity of ataxia-telangiectasia mutated kinase (ATM) as indicated by its reduced phosphorylation levels. In addition, our RNA-seq analyses showed that doxorubicin differentially regulated the expression of over 700 genes depending on LMTK3 protein expression levels. Furthermore, these genes were found to promote DNA repair, cell viability and tumorigenesis processes / pathways in LMTK3-overexpressing MCF7 cells. In human cancers, immunohistochemistry staining of LMTK3 in pre- and postchemotherapy breast tumor pairs from four separate clinical cohorts revealed a significant increase of LMTK3 following both doxorubicin and docetaxel based chemotherapy. In aggregate, our findings show for the first time a contribution of LMTK3 in cytotoxic drug resistance in breast cancer

A systematic review on integration mechanisms in human and animal health surveillance systems with a view to addressing global health security threats

Lymphatic filariasis and onchocerciasis are neglected tropical diseases (NTDs) targeted for elimination by mass (antifilarial) drug administration. These drugs are predominantly active against the microfilarial progeny of adult worms. New drugs or combinations are needed to improve patient therapy and to enhance the effectiveness of interventions in persistent hotspots of transmission. Several therapies and regimens are currently in (pre-)clinical testing. Clinical trial simulators (CTSs) project patient outcomes to inform the design of clinical trials but have not been widely applied to NTDs, where their resource-saving payoffs could be highly beneficial. We demonstrate the utility of CTSs using our individual-based onchocerciasis transmission model (EPIONCHO-IBM) that projects trial outcomes of a hypothetical macrofilaricidal drug. We identify key design decisions that influence the power of clinical trials, including participant eligibility criteria and post-treatment follow-up times for measuring infection indicators. We discuss how CTSs help to inform target product profiles

Mapping the Relationship Among Political Ideology, CSR Mindset, and CSR Strategy: A Contingency Perspective Applied to Chinese Managers

The literature on antecedents of corporate social responsibility (CSR) strategies of firms has been predominately content driven. Informed by the managerial sense-making process perspective, we develop a contingency theoretical framework explaining how political ideology of managers affects the choice of CSR strategy for their firms through their CSR mindset. We also explain to what extent the outcome of this process is shaped by the firm’s internal institutional arrangements and external factors impacting on the firm. We develop and test several hypotheses using data collected from 129 Chinese managers. The results show that managers with a stronger socialist ideology are likely to develop a mindset favouring CSR, which induces the adoption of a proactive CSR strategy. The CSR mindset mediates the link between socialist ideology and CSR strategy. The strength of the relationship between the CSR mindset and the choice of CSR strategy is moderated by customer response to CSR, industry competition, the role of government, and CSR-related managerial incentives