Minimally invasive surgery when treating endometriosis has a positive effect on health and on quality of work life of affected women

STUDY QUESTION What is the effect of the minimally invasive surgical treatment of endometriosis on health and on quality of work life (e.g. working performance) of affected women? SUMMARY ANSWER Absence from work, performance loss and the general negative impact of endometriosis on the job are reduced significantly by the laparoscopic surgery. WHAT IS KNOWN ALREADY The benefits of surgery overall and of the laparoscopic method in particular for treating endometriosis have been described before. However, previous studies focus on medical benchmarks without including the patient's perspective in a quantitative manner. STUDY DESIGN, SIZE, DURATION A retrospective questionnaire-based survey covering 211 women with endometriosis and a history of specific laparoscopic surgery in a Swiss university hospital, tertiary care center. Data were returned anonymously and were collected from the beginning of 2012 until March 2013. PARTICIPANTS/MATERIALS, SETTING, METHODS Women diagnosed with endometriosis and with at least one specific laparoscopic surgery in the past were enrolled in the study. The study investigated the effect of the minimally invasive surgery on health and on quality of work life of affected women. Questions used were obtained from the World Endometriosis Research Foundation (WERF) Global Study on Women's Health (GSWH) instrument. The questionnaire was shortened and adapted for the purpose of the present study. MAIN RESULTS AND THE ROLE OF CHANCE Of the 587 women invited to participate in the study, 232 (232/587 = 40%) returned the questionnaires. Twenty-one questionnaires were excluded due to incomplete data and 211 sets (211/587 = 36%) were included in the study. Our data show that 62% (n = 130) of the study population declared endometriosis as influencing the job during the period prior to surgery, compared with 28% after surgery (P < 0.001). The mean (maximal) absence from work due to endometriosis was reduced from 2.0 (4.9) to 0.5 (1.4) hours per week (P < 0.001). The mean (maximal) loss in working performance after the surgery averaged out at 5.7% (12.6%) compared with 17.5% (30.5%) before this treatment (P < 0.001). LIMITATIONS, REASONS FOR CAUTION The mediocre response rate of the study weakens the representativeness of the investigated population. Considering the anonymous setting a non-responder investigation was not performed. A bias due to selection, information and negativity effects within a retrospective survey cannot be excluded, although study-sensitive questions were provided in multiple ways. The absence of a control group (sham group; e.g. patients undergoing specific diagnostic laparoscopy without treatment) is a further limitation of the study. WIDER IMPLICATIONS OF THE FINDINGS Our study shows that indicated minimally invasive surgery has a clear positive effect on the wellbeing and working performance of women suffering from moderate to severe endometriosis. Furthermore, national net savings in indirect costs with the present number of surgeries is estimated to be €10.7 million per year. In an idealized setting (i.e. without any diagnosis delay) this figure could be more than doubled. STUDY FUNDING/COMPETING INTEREST(S) The study was performed on behalf of the University Hospital of Bern (Inselspital) as one of the leading Swiss tertiary care centers. The authors do not declare any competing interest

Building Oblivious Transfer on Channel Delays

In the information-theoretic setting, where adversaries have unlimited computational power, the fundamental cryptographic primitive Oblivious Transfer (OT) cannot be securely achieved if the parties are communicating over a clear channel. To preserve secrecy and security, the players have to rely on noise in the communication. Noisy channels are therefore a useful tool to model noise behavior and build protocols implementing OT. This paper explores a source of errors that is inherently present in practically any transmission medium, but has been scarcely studied in this context: delays in the communication. In order to have a model for the delays that is both general and comparable to the channels usually used for OT – such as the Binary Symmetric Channel (BSC) – we introduce a new noisy channel, the Binary Discrete-time Delaying Channel (BDDC). We show that such a channel realistically reproduces real-life communication scenarios where delays are hard to predict and we propose a protocol for achieving oblivious transfer over the BDDC. We analyze the security of our construction in the semi-honest setting, showing that our realization of OT substantially decreases the protocol sensitivity to the user’s knowledge of the channel compared to solutions relying on other channel properties, and is very efficient for wide ranges of delay probabilities. The flexibility and generality of the model opens the way for future implementation in media where delays are a fundamental characteristic

Unconditionally Secure Oblivious Transfer from Real Network Behavior

Secure multi-party computation (MPC) deals with the problem of shared computation between parties that do not trust each other: they are interested in performing a joint task, but they also want to keep their respective inputs private. In a world where an ever-increasing amount of computation is outsourced, for example to the cloud, MPC is a subject of crucial importance. However, unconditionally secure MPC protocols have never found practical application: the lack of realistic noisy channel models, that are required to achieve security against computationally unbounded adversaries, prevents implementation over real-world, standard communication protocols. In this paper we show for the first time that the inherent noise of wireless communication can be used to build multi-party protocols that are secure in the information-theoretic setting. In order to do so, we propose a new noisy channel, the Delaying-Erasing Channel (DEC), that models network communication in both wired and wireless contexts. This channel integrates erasures and delays as sources of noise, and models reordered, lost and corrupt packets. We provide a protocol that uses the properties of the DEC to achieve Oblivious Transfer (OT), a fundamental primitive in cryptography that implies any secure computation. In order to show that the DEC reflects the behavior of wireless communication, we run an experiment over a 802.11n wireless link, and gather extensive experimental evidence supporting our claim. We also analyze the collected data in order to estimate the level of security that such a network can provide in our model. We show the flexibility of our construction by choosing for our implementation of OT a standard communication protocol, the Real-time Transport Protocol (RTP). Since the RTP is used in a number of multimedia streaming and teleconference applications, we can imagine a wide variety of practical uses and application settings for our construction

Entanglement and non-locality are different resources

Bell's theorem states that, to simulate the correlations created by measurement on pure entangled quantum states, shared randomness is not enough: some "non-local" resources are required. It has been demonstrated recently that all projective measurements on the maximally entangled state of two qubits can be simulated with a single use of a "non-local machine". We prove that a strictly larger amount of this non-local resource is required for the simulation of pure non-maximally entangled states of two qubits $\ket{\psi(\alpha)}= \cos\alpha\ket{00}+\sin\alpha\ket{11}$ with $0<\alpha\lesssim\frac{\pi}{7.8}$.Comment: 8 pages, 3 figure

Sphagnum physiology in the context of changing climate: emergent influences of genomics, modelling and host-microbiome interactions on understanding ecosystem function.

Peatlands harbour more than one-third of terrestrial carbon leading to the argument that the bryophytes, as major components of peatland ecosystems, store more organic carbon in soils than any other collective plant taxa. Plants of the genus Sphagnum are important components of peatland ecosystems and are potentially vulnerable to changing climatic conditions. However, the response of Sphagnum to rising temperatures, elevated CO2 and shifts in local hydrology have yet to be fully characterized. In this review, we examine Sphagnum biology and ecology and explore the role of this group of keystone species and its associated microbiome in carbon and nitrogen cycling using literature review and model simulations. Several issues are highlighted including the consequences of a variable environment on plant-microbiome interactions, uncertainty associated with CO2 diffusion resistances and the relationship between fixed N and that partitioned to the photosynthetic apparatus. We note that the Sphagnum fallax genome is currently being sequenced and outline potential applications of population-level genomics and corresponding plant photosynthesis and microbial metabolic modelling techniques. We highlight Sphagnum as a model organism to explore ecosystem response to a changing climate and to define the role that Sphagnum can play at the intersection of physiology, genetics and functional genomics

Evaluation of mTOR-regulated mRNA translation.

mTOR, the mammalian target of rapamycin, regulates protein synthesis (mRNA translation) by affecting the phosphorylation or activity of several translation factors. Here, we describe methods for studying the impact of mTOR signalling on protein synthesis, using inhibitors of mTOR such as rapamycin (which impairs some of its functions) or mTOR kinase inhibitors (which probably block all functions).To assess effects of mTOR inhibition on general protein synthesis in cells, the incorporation of radiolabelled amino acids into protein is measured. This does not yield information on the effects of mTOR on the synthesis of specific proteins. To do this, two methods are described. In one, stable-isotope labelled amino acids are used, and their incorporation into new proteins is determined using mass spectrometric methods. The proportions of labelled vs. unlabeled versions of each peptide from a given protein provide quantitative information about the rate of that protein's synthesis under different conditions. Actively translated mRNAs are associated with ribosomes in polyribosomes (polysomes); thus, examining which mRNAs are found in polysomes under different conditions provides information on the translation of specific mRNAs under different conditions. A method for the separation of polysomes from non-polysomal mRNAs is describe

Local randomness in Hardy's correlations: Implications from information causality principle

Study of nonlocal correlations in term of Hardy's argument has been quite popular in quantum mechanics. Recently Hardy's argument of non-locality has been studied in the context of generalized non-signaling theory as well as theory respecting information causality. Information causality condition significantly reduces the success probability for Hardy's argument when compared to the result based on non-signaling condition. Here motivated by the fact that maximally entangled state in quantum mechanics does not exhibit Hardy's non-local correlation, we do a qualitative study of the property of local randomness of measured observable on each side reproducing Hardy's non-locality correlation,in the context of information causality condition. On applying the necessary condition for respecting the principle of information causality, we find that there are severe restrictions on the local randomness of measured observable in contrast to results obtained from no-signaling condition.Still, there are some restrictions imposed by quantum mechanics that are not obtained from information causality condition.Comment: 6 pages, 2 tables, new references adde

Toward a Mechanistic Modeling of Nitrogen Limitation on Vegetation Dynamics

Nitrogen is a dominant regulator of vegetation dynamics, net primary production, and terrestrial carbon cycles; however, most ecosystem models use a rather simplistic relationship between leaf nitrogen content and photosynthetic capacity. Such an approach does not consider how patterns of nitrogen allocation may change with differences in light intensity, growing-season temperature and CO2 concentration. To account for this known variability in nitrogen-photosynthesis relationships, we develop a mechanistic nitrogen allocation model based on a trade-off of nitrogen allocated between growth and storage, and an optimization of nitrogen allocated among light capture, electron transport, carboxylation, and respiration. The developed model is able to predict the acclimation of photosynthetic capacity to changes in CO2 concentration, temperature, and radiation when evaluated against published data of Vc,max (maximum carboxylation rate) and Jmax (maximum electron transport rate). A sensitivity analysis of the model for herbaceous plants, deciduous and evergreen trees implies that elevated CO2 concentrations lead to lower allocation of nitrogen to carboxylation but higher allocation to storage. Higher growing-season temperatures cause lower allocation of nitrogen to carboxylation, due to higher nitrogen requirements for light capture pigments and for storage. Lower levels of radiation have a much stronger effect on allocation of nitrogen to carboxylation for herbaceous plants than for trees, resulting from higher nitrogen requirements for light capture for herbaceous plants. As far as we know, this is the first model of complete nitrogen allocation that simultaneously considers nitrogen allocation to light capture, electron transport, carboxylation, respiration and storage, and the responses of each to altered environmental conditions. We expect this model could potentially improve our confidence in simulations of carbon-nitrogen interactions and the vegetation feedbacks to climate in Earth system models

Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM-Microbe Model

Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2&nbsp;+&nbsp;H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape

Oak forest carbon and water simulations:Model intercomparisons and evaluations against independent data

Models represent our primary method for integration of small-scale, process-level phenomena into a comprehensive description of forest-stand or ecosystem function. They also represent a key method for testing hypotheses about the response of forest ecosystems to multiple changing environmental conditions. This paper describes the evaluation of 13 stand-level models varying in their spatial, mechanistic, and temporal complexity for their ability to capture intra- and interannual components of the water and carbon cycle for an upland, oak-dominated forest of eastern Tennessee. Comparisons between model simulations and observations were conducted for hourly, daily, and annual time steps. Data for the comparisons were obtained from a wide range of methods including: eddy covariance, sapflow, chamber-based soil respiration, biometric estimates of stand-level net primary production and growth, and soil water content by time or frequency domain reflectometry. Response surfaces of carbon and water flux as a function of environmental drivers, and a variety of goodness-of-fit statistics (bias, absolute bias, and model efficiency) were used to judge model performance. A single model did not consistently perform the best at all time steps or for all variables considered. Intermodel comparisons showed good agreement for water cycle fluxes, but considerable disagreement among models for predicted carbon fluxes. The mean of all model outputs, however, was nearly always the best fit to the observations. Not surprisingly, models missing key forest components or processes, such as roots or modeled soil water content, were unable to provide accurate predictions of ecosystem responses to short-term drought phenomenon. Nevertheless, an inability to correctly capture short-term physiological processes under drought was not necessarily an indicator of poor annual water and carbon budget simulations. This is possible because droughts in the subject ecosystem were of short duration and therefore had a small cumulative impact. Models using hourly time steps and detailed mechanistic processes, and having a realistic spatial representation of the forest ecosystem provided the best predictions of observed data. Predictive ability of all models deteriorated under drought conditions, suggesting that further work is needed to evaluate and improve ecosystem model performance under unusual conditions, such as drought, that are a common focus of environmental change discussions