Diverse tumorigenic consequences of human papillomavirus integration in primary oropharyngeal cancers

Human papillomavirus (HPV) causes 5% of all cancers and frequently integrates into host chromosomes. The HPV oncoproteins E6 and E7 are necessary but insufficient for cancer formation, indicating that additional secondary genetic events are required. Here, we investigate potential oncogenic impacts of virus integration. Analysis of 105 HPV-positive oropharyngeal cancers by whole-genome sequencing detects virus integration in 77%, revealing five statistically significant sites of recurrent integration near genes that regulate epithelial stem cell maintenance (i.e., SOX2, TP63, FGFR, MYC) and immune evasion (i.e., CD274). Genomic copy number hyperamplification is enriched 16-fold near HPV integrants, and the extent of focal host genomic instability increases with their local density. The frequency of genes expressed at extreme outlier levels is increased 86-fold within ±150 kb of integrants. Across 95% of tumors with integration, host gene transcription is disrupted via intragenic integrants, chimeric transcription, outlier expression, gene breaking, and/or de novo expression of noncoding or imprinted genes. We conclude that virus integration can contribute to carcinogenesis in a large majority of HPV-positive oropharyngeal cancers by inducing extensive disruption of host genome structure and gene expression.

Diverse tumorigenic consequences of human papillomavirus integration in primary oropharyngeal cancers

Human papillomavirus (HPV) causes 5% of all cancers and frequently integrates into host chromosomes, but the impacts of integration in tumorigenesis remain unclear. Analysis of 105 HPV-positive oropharyngeal cancers by whole genome sequencing detects viral integration in 77%, revealing five statistically significant integration hotspots near genes that regulate epithelial stem cell maintenance (i.e. SOX2, TP63, FGFR, MYC) and immune evasion (i.e. CD274). Somatic hyperamplification is enriched 16-fold near HPV integrants, and the extent of focal host genomic instability increases with local density of HPV integrants. Genes expressed at extreme outlier levels are increased 86-fold within +/- 150 kb of integrants. Across 95% of tumors with integration, host gene transcription is disrupted via intragenic integrants, chimeric transcription, outlier expression, gene breaking and/or de novo expression of noncoding or imprinted genes. We conclude that HPV integration contributes substantively to cancer development by causing extensive disruption of host genome structure and gene expression.

Concept of Outlier Study: The Management of Outlier Handling with Significance in Inclusive Education Setting

Collection of data and to check its suitability is the first step in any statistical data analysis. In such analyses, the presence of outliers appears as an unavoidable important problem. Outliers are unexpected random values in dataset, and they can alter the statistical conclusion and also affect their assumptions. Thus, in order to manage the data properly, outliers must be defined and treated. So all statisticians have to confront the analysis and forced to take a decision. There is only being one of the two extreme choices left for the researcher or statistician during the analysis of outliers. First, either to reject the outlier with the risk of loss of genuine information and the second one is to include them with the risk of error in drawing conclusion. The study therefore summarize the various potential causes of extreme scores in a data set (e.g., data recording or entry errors, sampling errors, and legitimate sampling), how to detect them, and whether they should be removed or not. Another objective of this study was to explore how significantly a small proportion of outliers can affect even simple analyses. The study was explored with citing suitable examples including outlier value and also excluding the outlier data. The examples show a strong beneficial effect of repetition of the study based on extreme of scores. One way ANOVA test was performed and the significance of extreme outlier was described.

Potential Community and Campus Covid-19 Outcomes Under University and College Reopening Scenarios

Background: Significant uncertainty exists in many countries about the safety of, and best strategies for, reopening college and university campuses until the Covid-19 pandemic is better controlled. Little also is known about the effects on-campus students may have on local higher-risk communities. We aimed to estimate potential community and campus Covid-19 exposures, infections, and mortality due to various university reopening and precaution plans under current ranges of assumptions and uncertainties. Methods: We developed and calibrated campus-only, community-only, and campus-x-community epidemic differential equation and agent-based models. Input parameters for campus and surrounding communities were estimated via published and grey literature, scenario development, expert opinion, accuracy optimization algorithms, and Monte Carlo simulation; models were cross-validated against each other using February-June 2020 data from heterogeneous U.S. counties and states. Campus opening plans (spanning various fully open, hybrid, and fully virtual approaches) were identified from websites and publications. All scenarios were simulated assuming 16-week semesters and estimated ranges for Covid-19 prevalence among community residents and arriving students, precaution compliance, contact frequency, virus attack rates, and tracing and isolation effectiveness. Additional student and community exposures, infections, and mortality were estimated under each scenario, with 10% trimmed medians, standard deviations, and probability intervals computed to omit extreme outlier scenarios. Factorial analyses were conducted to identify intervention inputs with largest and smallest effects. Results: As a base case with no precautions (or no compliance), predicted 16-week student infections and mortality under normal operations ranged significantly from 471 to 9,495 (median: 2,286, SD: 2,627) and 0 to 123 (median: 9, SD: 14) per 10,000 students, respectively. The maximum active exposures across a semester was 15.76% of all students warranting tracing. Total additional community exposures, infections, and mortality ranged from 1 to 187, 13 to 820, and 1 to 21 per 10,000 residents, respectively. 1% and 5% of on-campus students were infected after a mean (SD) of 11 (3) and 76 (17) days, respectively; >10% students infected by the end of a semester in 34.8% of scenarios, with the greatest increase (first inflection point) occurring on aver-age on day 84 (SD: 10.2 days). Common reopening precautions reduced infections by 24% to 26% and mortality by 36% to 50% in both populations. Uncertainties in many factors, however, produced tremendous variability in all results, ranging from medians by -67% to +342%. Conclusions: Consequences on community and student Covid-19 exposures, infections, and mortality of reopening physical campuses are very highly unpredictable, depending on a combination of random chance, controllable (e.g. physical layouts), and uncontrollable (e.g. human behavior) factors. Implications include needs for criteria to adapt campus operations mid-semester, methods to detect when necessary, and contingency plans for doing so.

Fiscal Policy and Institutions in Imperial China

Up until the final four decades of the Qing Dynasty, fiscal extraction in imperial China was primarily a matter of taxing agricultural production, generally in the form of an annual property tax assessed on the basis of landholding, and collected in either grain or cash. All major dynasties prior to the Qing wielded this fiscal instrument somewhat flexibly, with large-scale reforms, usually leading to significantly higher taxes, occurring around mid-dynasty, but the Qing broke this trend: the absolute volume of agricultural taxes remained locked in place for the great majority of its 278-year life span, despite a near tripling of both the population and the economy. This eventually rendered the Qing fiscal state an extreme outlier in both horizontal and vertical comparisons: relative to the economy it governed, not only was it much smaller than its major early modern competitors, ranging from Japan to Western European states to other central Asian empires, but it was also probably the smallest post-Qin dynastic state by far. Preexisting scholarship has largely failed to identify, let alone explain, this sudden and dramatic shift in fiscal policy towards the end of China’s imperial history. There are a number of possible explanations for it, some of which have appeared in the extant literature, but the most promising one—which has not appeared—seems to be that the extraordinary circumstances of the Ming–Qing transition served as the catalyst for a decisive conservative turn in Chinese fiscal thought, pushing the Qing state into a fundamentally different political and institutional equilibrium than its predecessors.

Runs of homozygosity in killer whale genomes provide a global record of demographic histories

SUMMARYRuns of homozygosity (ROH) occur when offspring receive the same ancestral haplotype from both parents, and, accordingly, reduce individual heterozygosity. Their distribution throughout the genome contains information on the probability of inbreeding mediated by mating system and population demography. Here, we investigate variation in killer whale demographic history as reflected in genome-wide heterozygosity, using a global dataset of 26 genomes. We find an overall pattern of lower heterozygosity in genomes sampled at high latitudes, with hundreds of short ROH (< 1Mbp) reflecting high background relatedness due to coalescence of haplotypes during bottlenecks associated with founder events during post-glacial range expansions. Across most of the species’ range, intermediate length ROH (1-10Mb) revealed long-term inbreeding in 22 of the 26 sampled killer whale genomes, consistent with the high social philopatry observed in all populations studied to date. Inbreeding coefficients (FROH) were comparable to those reported in other taxa with long-term low population size, such as bonobos and the Native American Karitiana of the Brazilian Amazon. The extreme outlier in this dataset, a Scottish killer whale, was homozygous over one-third of the autosomes (41.6%) with a distinct distribution of ROH length, indicating generations of inbreeding. This exceeds autozygosity in emblematic examples of long-term inbreeding, such as the Altai Neanderthal, and eastern lowland and mountain gorillas. The fate of this Scottish killer whale population, in which no calves have been born in over two decades, may be inextricably linked to its demographic history and consequential inbreeding depression.

An interim screening limit of detection for naproxen in equine plasma: a review and analysis

Starting in August 2015 Thoroughbred racing in Charles Town, West Virginia experienced a sequence of intermittent low concentration Naproxen identifications from 6.3 to 161 ng/ml of plasma (27.3 to 699 nM). These identifications were ongoing, indicating the horsemen were unaware of their origins. Naproxen is administered orally to horses at substantial doses and is chemically stable in the environment. These identifications are therefore most likely associated with exposure of these horses to environmental traces of Naproxen. Given the low concentrations of these identifications, we were asked to identify a Screening Limit of Detection (SLOD) below which these trace level Naproxen identifications would not be reported. Review of the data set suggested an SLOD of 200 ng/ml, while outlier analysis suggested an ‘extreme’ outlier level at 247 ng/ml, which figure was rounded up to 250 ng/ml Naproxen or 1.09 uM. This proposed SLOD is in good agreement with other US regulatory thresholds for therapeutic medications and this Interim Screening Limit of Detection was presented for review.