409 research outputs found
Smoke gets in your eyes:what is sociological about cigarettes?
Contemporary public health approaches increasingly draw attention to the unequal social distribution of cigarette smoking. In contrast, critical accounts emphasize the importance of smokers’ situated agency, the relevance of embodiment and how public health measures against smoking potentially play upon and exacerbate social divisions and inequality. Nevertheless, if the social context of cigarettes is worthy of such attention, and sociology lays a distinct claim to understanding the social, we need to articulate a distinct, positive and systematic claim for smoking as an object of sociological enquiry. This article attempts to address this by situating smoking across three main dimensions of sociological thinking: history and social change; individual agency and experience; and social structures and power. It locates the emergence and development of cigarettes in everyday life within the project of modernity of the nineteenth and twentieth centuries. It goes on to assess the habituated, temporal and experiential aspects of individual smoking practices in everyday lifeworlds. Finally, it argues that smoking, while distributed in important ways by social class, also works relationally to render and inscribe it
Climate Policies with Burden Sharing: The Economics of Climate Financing
The maintenance of a favorable climate accounts for the most challenging contemporary global governance predicament that seems to pit today’s generation against future world inhabitants. In a trade-off of economic growth versus sustainability, a broad-based international coalition could establish climate justice. As a novel angle towards climate justice, the following paper proposes (1) a well-balanced climate mitigation and adaptation public policy mix guided by micro- and macroeconomic analysis results, and (2) a new way of funding climate change mitigation and adaptation policies through carbon tax and broad-based climate bonds that also involve future generations. Contemporary climate financing strategies (e.g., Sachs Model) are thereby added into Integrated Assessment Models of the Nordhaus Type. Overall, the paper strives to delve deeper into a discussion of how market economies can be brought to a path consistent with prosperity and sustainability. Finding innovative ways how to finance climate abatement over time coupled with future risk prevention as well as adaptation to higher temperatures appears as an innovative and easily-implementable solution to nudge overlapping generations towards climate justice in the sustainability domain
A framework for orthology assignment from gene rearrangement data
Abstract. Gene rearrangements have successfully been used in phylogenetic reconstruction and comparative genomics, but usually under the assumption that all genomes have the same gene content and that no gene is duplicated. While these assumptions allow one to work with organellar genomes, they are too restrictive when comparing nuclear genomes. The main challenge is how to deal with gene families, specifically, how to identify orthologs. While searching for orthologies is a common task in computational biology, it is usually done using sequence data. We approach that problem using gene rearrangement data, provide an optimization framework in which to phrase the problem, and present some preliminary theoretical results.
Recipient screening in IVF: First data from women undergoing anonymous oocyte donation in Dublin
BACKGROUND:
Guidelines for safe gamete donation have emphasised donor screening, although none exist specifically for testing oocyte recipients. Pre-treatment assessment of anonymous donor oocyte IVF treatment in Ireland must comply with the European Union Tissues and Cells Directive (Directive 2004/23/EC). To determine the effectiveness of this Directive when applied to anonymous oocyte recipients in IVF, we reviewed data derived from selected screening tests performed in this clinical setting.
METHODS:
Data from tests conducted at baseline for all women enrolling as recipients (n = 225) in the anonymous oocyte donor IVF programme at an urban IVF referral centre during a 24-month period were analysed. Patient age at programme entry and clinical pregnancy rate were also tabulated. All recipients had at least one prior negative test for HIV, Hepatitis B/C, chlamydia, gonorrhoea and syphilis performed by her GP or other primary care provider before reproductive endocrinology consultation.
RESULTS:
Mean (±SD) age for donor egg IVF recipients was 40.7 ± 4.2 yrs. No baseline positive chlamydia, gonorrhoea or syphilis screening results were identified among recipients for anonymous oocyte donation IVF during the assessment interval. Mean pregnancy rate (per embryo transfer) in this group was 50.5%.
CONCLUSION:
When tests for HIV, Hepatitis B/C, chlamydia, gonorrhoea and syphilis already have been confirmed to be negative before starting the anonymous donor oocyte IVF sequence, additional (repeat) testing on the recipient contributes no new clinical information that would influence treatment in this setting. Patient safety does not appear to be enhanced by application of Directive 2004/23/EC to recipients of anonymous donor oocyte IVF treatment. Given the absence of evidence to quantify risk, this practice is difficult to justify when applied to this low-risk population
Contingent Kernel Density Estimation
Kernel density estimation is a widely used method for estimating a distribution based on a sample of points drawn from that distribution. Generally, in practice some form of error contaminates the sample of observed points. Such error can be the result of imprecise measurements or observation bias. Often this error is negligible and may be disregarded in analysis. In cases where the error is non-negligible, estimation methods should be adjusted to reduce resulting bias. Several modifications of kernel density estimation have been developed to address specific forms of errors. One form of error that has not yet been addressed is the case where observations are nominally placed at the centers of areas from which the points are assumed to have been drawn, where these areas are of varying sizes. In this scenario, the bias arises because the size of the error can vary among points and some subset of points can be known to have smaller error than another subset or the form of the error may change among points. This paper proposes a “contingent kernel density estimation” technique to address this form of error. This new technique adjusts the standard kernel on a point-by-point basis in an adaptive response to changing structure and magnitude of error. In this paper, equations for our contingent kernel technique are derived, the technique is validated using numerical simulations, and an example using the geographic locations of social networking users is worked to demonstrate the utility of the method
A Six-Gene Signature Predicts Survival of Patients with Localized Pancreatic Ductal Adenocarcinoma
Jen Jen Yeh and colleagues developed and validated a six-gene signature in patients with pancreatic ductal adenocarcinoma that may be used to better stage the disease in these patients and assist in treatment decisions
Age related endocrine patterns observed in polycystic ovary syndrome patients vs. ovulatory controls: descriptive data from a university based infertility center
Subependymal giant cell astrocytomas are characterized by mTORC1 hyperactivation, a very low somatic mutation rate, and a unique gene expression profile
Subependymal giant-cell astrocytomas (SEGAs) are slow-growing brain tumors that are a hallmark feature seen in 5–10% of patients with Tuberous Sclerosis Complex (TSC). Though histologically benign, they can cause serious neurologic symptoms, leading to death if untreated. SEGAs consistently show biallelic loss of TSC1 or TSC2. Herein, we aimed to define other somatic events beyond TSC1/TSC2 loss and identify potential transcriptional drivers that contribute to SEGA formation. Paired tumor-normal whole-exome sequencing was performed on 21 resected SEGAs from 20 TSC patients. Pathogenic variants in TSC1/TSC2 were identified in 19/21 (90%) SEGAs. Copy neutral loss of heterozygosity (size range: 2.2–46 Mb) was seen in 76% (16/21) of SEGAs (44% chr9q and 56% chr16p). An average of 1.4 other somatic variants (range 0–7) per tumor were identified, unlikely of pathogenic significance. Whole transcriptome RNA-sequencing analyses revealed 190 common differentially expressed genes in SEGA (n = 16, 13 from a prior study) in pairwise comparison to each of: low grade diffuse gliomas (n = 530) and glioblastoma (n = 171) from The Cancer Genome Atlas (TCGA) consortium, ganglioglioma (n = 10), TSC cortical tubers (n = 15), and multiple normal tissues. Among these, homeobox transcription factors (TFs) HMX3, HMX2, VAX1, SIX3; and TFs IRF6 and EOMES were all expressed >12-fold higher in SEGAs (FDR/q-value < 0.05). Immunohistochemistry supported the specificity of IRF6, VAX1, SIX3 for SEGAs in comparison to other tumor entities and normal brain. We conclude that SEGAs have an extremely low somatic mutation rate, suggesting that TSC1/TSC2 loss is sufficient to drive tumor growth. The unique and highly expressed SEGA-specific TFs likely reflect the neuroepithelial cell of origin, and may also contribute to the transcriptional and epigenetic state that enables SEGA growth following two-hit loss of TSC1 or TSC2 and mTORC1 activation
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