Epstein-Barr virus: clinical and epidemiological revisits and genetic basis of oncogenesis

Epstein-Barr virus (EBV) is classified as a member in the order herpesvirales, family herpesviridae, subfamily gammaherpesvirinae and the genus lymphocytovirus. The virus is an exclusively human pathogen and thus also termed as human herpesvirus 4 (HHV4). It was the first oncogenic virus recognized and has been incriminated in the causation of tumors of both lymphatic and epithelial nature. It was reported in some previous studies that 95% of the population worldwide are serologically positive to the virus. Clinically, EBV primary infection is almost silent, persisting as a life-long asymptomatic latent infection in B cells although it may be responsible for a transient clinical syndrome called infectious mononucleosis. Following reactivation of the virus from latency due to immunocompromised status, EBV was found to be associated with several tumors. EBV linked to oncogenesis as detected in lymphoid tumors such as Burkitt's lymphoma (BL), Hodgkin's disease (HD), post-transplant lymphoproliferative disorders (PTLD) and T-cell lymphomas (e.g. Peripheral T-cell lymphomas; PTCL and Anaplastic large cell lymphomas; ALCL). It is also linked to epithelial tumors such as nasopharyngeal carcinoma (NPC), gastric carcinomas and oral hairy leukoplakia (OHL). In vitro, EBV many studies have demonstrated its ability to transform B cells into lymphoblastoid cell lines (LCLs). Despite these malignancies showing different clinical and epidemiological patterns when studied, genetic studies have suggested that these EBV- associated transformations were characterized generally by low level of virus gene expression with only the latent virus proteins (LVPs) upregulated in both tumors and LCLs. In this review, we summarize some clinical and epidemiological features of EBV- associated tumors. We also discuss how EBV latent genes may lead to oncogenesis in the different clinical malignancie

Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance

Published in Handbook of financial time series, 2008, https://doi.org/10.1007/978-3-540-71297-8_22</p

Maximum likelihood and Gaussian estimation of continuous time models in finance

Ministry of Education, Singapore under its Academic Research Funding Tier

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

What are Research Expectations? A Comparative Study of Different Academic Disciplines

This paper is intended to assist professors, administrators, librarians and other members of university level committees that must consider research expectations and research quality in academic fields that they lack. While this is not a problem for field experts, it is a difficulty when people are asked to make decisions in areas of study other than their own. This is commonly the case for senior university professors, librarians and administrators in regards to university wide decisions. The paper investigates this gap, through a study of 27 academic fields in 348 highly regarded universities. We find that there are almost always statistically significant differences in activity between academic fields, regardless of the metric one considers. However, it is possible to understand these differences by comparing the distribution of a known academic field to that of a field that one is not familiar with. Tables and information are provided to assist in the comparison of different fields of study on metrics such as: departmental publications and researcher level metrics of publications, citations, H-index, and total number of co-authors. The information can also be used to support decisions associated with promotion to senior posts such as endowed chairs and professorships. Information regarding specific universities and researchers are included in the data supplement

Managing highly flexible facilities: an essential complementary asset at risk

Purpose: Twenty first century problems are increasingly being addressed by multi technology solutions developed by regional entrepreneurial and intreprepreneurial innovators. However, they require an expensive new type of fabrication facility. Multiple technology production facilities (MTPF) have become the essential incubators for these innovations. This paper aims to focus on the issues. Design/methodology/approach: The authors address the lack of managerial understanding of how to express the value and operationally manage MTPF centers through the use of investigative case study methods for multiple firms in the study. Findings: Owing to the MTPF centers' novelty and outward similarity to high volume semiconductor fabrication (HVF) facilities, they are laden with ineffective operation and strategic management practices. Metrics are the standard for both operational and strategic management of HVF facilities, yet their application to this new type of center is proving ineffectual. Research limitations/implications: These new types of regional economic resources may be at risk. A new approach is needed. Practical implications: The authors develop an operational and strategic metrics management approach for MTPFs that are based on these facilities' unique nature and leverages both the HVF and R&D metrics knowledge base. Social implications: Innovations at the interface of micro technology, nanotechnology and semiconductor micro fabrication are poised to solve many of these problems and become a basis for job creation and prosperity. If a new management technique is not developed, then these harbingers of regional economic development will be closed. Originality/value: While there is an abundance of research on metrics for HVF, this is the first attempt to develop metrics for MTPF

Lifetime reproductive output in a hermaphrodite cestode when reproducing alone or in pairs : a time cost of pairing

The cestode Schistocephalus solidus is a facultatively self-fertilising simultaneous hermaphrodite. Here we test for di€erences in the starting point, the rate, and the magnitude of egg production between individuals allowed to reproduce alone (only self-fertilisation possible) or in pairs (both self- and cross-fertilisation possible). Specifically, we want to distinguish between alternative processes responsible for the lower egg production in paired individuals observed in an earlier study (Wedekind et al., 1998). We designed an improved in vitro system, replacing the bird final host that allows us to measure, with high temporal resolution, the timing and magnitude of lifetime egg production of worms in these two social situations. We found that the experimental groups did not di€er significantly in the starting point of egg production. However, the temporal pattern in egg production di€ered between them, in that paired individuals had a lower rate of egg production. This, however, did not lead to a significant reduction in lifetime egg production, as pairs compensated for the lower rate by producing eggs longer than single individuals. We argue that the lower rate of egg production may nevertheless lead to a time cost of pairing in the study species, and that this cost is likely to represent a cost of outcrossing due to sexual selection