The Ethical, Legal, and Social Issues Impacted by Modern Assisted Reproductive Technologies

Background. While assisted reproductive technology (ART), including in vitro fertilization has given hope to millions of couples suffering from infertility, it has also introduced countless ethical, legal, and social challenges. The objective of this paper is to identify the aspects of ART that are most relevant to present-day society and discuss the multiple ethical, legal, and social challenges inherent to this technology. Scope of Review. This paper evaluates some of the most visible and challenging topics in the field of ART and outlines the ethical, legal, and social challenges they introduce. Major Conclusions. ART has resulted in a tectonic shift in the way physicians and the general population perceive infertility and ethics. In the coming years, advancing technology is likely to exacerbate ethical, legal, and social concerns associated with ART. ART is directly challenging society to reevaluate the way in which human life, social justice and equality, and claims to genetic offspring are viewed. Furthermore, these issues will force legal systems to modify existing laws to accommodate the unique challenges created by ART. Society has a responsibility to ensure that the advances achieved through ART are implemented in a socially responsible manner

Acid loading during treatment with sevelamer hydrochloride: Mechanisms and clinical implications

Acid loading during treatment with sevelamer hydrochloride: Mechanisms and clinical implications. Short-term and long-term studies indicate that patients treated with sevelamer hydrochloride have lower serum bicarbonate levels than patients treated with calcium-containing phosphate binders. This observation has previously been attributed to withdrawal of a source of base with discontinuation of calcium carbonate or calcium acetate. However, understanding of the chemistry of sevelamer hydrochloride suggests at least three potential mechanisms whereby it might induce a dietary acid load. Moreover, preliminary results from an animal model demonstrate that treatment with sevelamer hydrochloride results in a fall in urine pH, as well as an increase in urinary ammonium and calcium excretion consistent with an increase in net acid excretion. Chronic metabolic acidosis in maintenance dialysis patients is associated with major systemic effects. It is independently associated with an increased risk of death in dialysis patients. Metabolic acidosis has both catabolic and antianabolic effects that may lead to a net negative nitrogen balance and total body protein balance. Metabolic acidosis also leads to physiochemical dissolution of bone and promotes cell-mediated bone resorption due to enhanced osteoclast activity and reduced osteoblast activity. It may also exacerbate secondary hyperparathyroidism and renal osteodystrophy. Given the long-term risks of chronic metabolic acidosis in maintenance dialysis patients, Kidney/Dialysis Outcome Quality Initiative (K/DOQI) guidelines have recently recommended maintaining predialysis serum levels of CO2 above 22 mmol/L in order to improve bone histology, and to ameliorate excess protein catabolism

Predicting Adaptive Behavior in the Environment from Central Nervous System Dynamics

To generate adaptive behavior, the nervous system is coupled to the environment. The coupling constrains the dynamical properties that the nervous system and the environment must have relative to each other if adaptive behavior is to be produced. In previous computational studies, such constraints have been used to evolve controllers or artificial agents to perform a behavioral task in a given environment. Often, however, we already know the controller, the real nervous system, and its dynamics. Here we propose that the constraints can also be used to solve the inverse problem—to predict from the dynamics of the nervous system the environment to which they are adapted, and so reconstruct the production of the adaptive behavior by the entire coupled system. We illustrate how this can be done in the feeding system of the sea slug Aplysia. At the core of this system is a central pattern generator (CPG) that, with dynamics on both fast and slow time scales, integrates incoming sensory stimuli to produce ingestive and egestive motor programs. We run models embodying these CPG dynamics—in effect, autonomous Aplysia agents—in various feeding environments and analyze the performance of the entire system in a realistic feeding task. We find that the dynamics of the system are tuned for optimal performance in a narrow range of environments that correspond well to those that Aplysia encounter in the wild. In these environments, the slow CPG dynamics implement efficient ingestion of edible seaweed strips with minimal sensory information about them. The fast dynamics then implement a switch to a different behavioral mode in which the system ignores the sensory information completely and follows an internal “goal,” emergent from the dynamics, to egest again a strip that proves to be inedible. Key predictions of this reconstruction are confirmed in real feeding animals

Parallel Algebraic Multigrids for Structural mechanics

This paper presents the results of a comparison of three parallel algebraic multigrid (AMG) preconditioners for structural mechanics applications. In particular, they are interested in investigating both the scalability and robustness of the preconditioners. Numerical results are given for a range of structural mechanics problems with various degrees of difficulty

The impact of luteal phase support on endometrial estrogen and progesterone receptor expression: a randomized control trial

<p>Abstract</p> <p>Background</p> <p>To assess the impact of luteal phase support on the expression of estrogen receptor (ER) alpha and progesterone receptors B (PR-B) on the endometrium of oocyte donors undergoing controlled ovarian hyperstimulation (COH).</p> <p>Methods</p> <p>A prospective, randomized study was conducted in women undergoing controlled ovarian hyperstimulation for oocyte donation. Participants were randomized to receive no luteal support, vaginal progesterone alone, or vaginal progesterone plus orally administered 17 Beta estradiol. Endometrial biopsies were obtained at 4 time points in the luteal phase and evaluated by tissue microarray for expression of ER alpha and PR-B.</p> <p>Results</p> <p>One-hundred and eight endometrial tissue samples were obtained from 12 patients. No differences were found in expression of ER alpha and PR-B among all the specimens with the exception of one sample value.</p> <p>Conclusions</p> <p>The administration of progesterone during the luteal phase of COH for oocyte donor cycles, either with or without estrogen, does not significantly affect the endometrial expression of ER alpha and PR.</p

First-line high-dose therapy and autologous blood stem cell transplantation in patients with primary central nervous system non-Hodgkin lymphomas-a single-centre experience in 61 patients

Primary central nervous system non-Hodgkin lymphomas (PCNS-NHLs) are extranodal B-cell lymphomas with poor prognosis. The role of high-dose therapy (HDT) followed by autologous blood stem cell transplantation (ASCT) as first-line therapy is still not clear. We retrospectively collected long-term follow up data of 61 consecutive patients with PCNS-NHL at the University Hospital Düsseldorf from January 2004 to December 2016. Thirty-six patients were treated with conventional chemoimmunotherapy (cCIT) only (CT-group). Seventeen patients received an induction cCIT followed by HDT and ASCT. In the CT-group, the overall response rate (ORR) was 61% (CR 47%, PR 14%), and there were 8% treatment-related deaths (TRD). Progression-free survival (PFS) was 31.8 months, and overall survival (OS) was 57.3 months. In the HDT-group, the ORR was 88% (59% CR, 29% PR), and there were 6% TRD. Median PFS and OS were not reached at 5 years. The 5-year PFS and OS were 64.7%. After a median follow up of 71 months, 10 patients (59%) were still alive in CR/PR following HDT and ASCT, one patient was treated for progressive disease (PD), and 7 had died (41%, 6 PD, 1 TRD). All patients achieving CR prior to HDT achieved durable CR. In the CT-group, 8 patients (22%) were alive in CR/PR after a median follow-up of 100 months. Twenty-eight patients died (78%, 24 PD, 2 TRD, 2 deaths in remission). In the univariate analysis, the HDT-group patients had significantly better PFS (not reached vs 31.8 months, p = 0.004) and OS (not reached vs 57.3 months, p = 0.021). The multivariate analysis showed HDT was not predictive for survival. Treatment with HDT + ASCT is feasible and offers the chance for long-term survival with low treatment-related mortality in younger patients. In this analysis, ORR, PFS and OS were better with HDT than with conventional cCIT alone. This result was not confirmed in the multivariate analysis, and further studies need to be done to examine the role of HDT in PCNSL

Adaptive Algebraic Multigrid Methods

Our ability to simulate physical processes numerically is constrained by our ability to solve the resulting linear systems, prompting substantial research into the development of multiscale iterative methods capable of solving these linear systems with an optimal amount of effort. Overcoming the limitations of geometric multigrid methods to simple geometries and differential equations, algebraic multigrid methods construct the multigrid hierarchy based only on the given matrix. While this allows for efficient black-box solution of the linear systems associated with discretizations of many elliptic differential equations, it also results in a lack of robustness due to assumptions made on the near-null spaces of these matrices. This paper introduces an extension to algebraic multigrid methods that removes the need to make such assumptions by utilizing an adaptive process. The principles which guide the adaptivity are highlighted, as well as their application to algebraic multigrid solution of certain symmetric positive-definite linear systems

Large rivers and orogens: the evolution of the Yarlung Tsangpo–Irrawaddy system and the eastern Himalayan syntaxis

The eastern Himalayan syntaxis has experienced some of the highest rates of deformation and erosion in the orogen during the Late Cenozoic, and the Yarlung Tsangpo, Brahmaputra, Irrawaddy, Salween, and Mekong rivers are the key erosional systems in that region. The Yarlung Tsangpo drains southern Tibet and the deep Siang River gorge through the eastern Himalayan syntaxis before joining the Brahmaputra in northeastern India. It has been proposed that the Yarlung Tsangpo drained into other large rivers of southern Asia, such as the Irrawaddy, Salween and Red River. We have used uranium/lead dating and hafnium measurements of detrital zircons from Cenozoic sedimentary deposits in Central Myanmar to demonstrate that the Yarlung Tsangpo formerly drained into the Irrawaddy River in Myanmar through the eastern syntaxis, and that this ancient river system was established by (at least) the Middle–Late Eocene. The Yarlung Tsangpo–Irrawaddy river disconnected in the Early Miocene driven by increased deformation in the eastern syntaxis and headward erosion by tributaries of the Brahmaputra. Our results highlight the significance of the sedimentary record of large orogen-parallel rivers and provide key chronological constraints on landscape evolution during the Early Miocene phase of the Himalayan orogeny

Beyond element-wise interactions: identifying complex interactions in biological processes

Background: Biological processes typically involve the interactions of a number of elements (genes, cells) acting on each others. Such processes are often modelled as networks whose nodes are the elements in question and edges pairwise relations between them (transcription, inhibition). But more often than not, elements actually work cooperatively or competitively to achieve a task. Or an element can act on the interaction between two others, as in the case of an enzyme controlling a reaction rate. We call “complex” these types of interaction and propose ways to identify them from time-series observations. Methodology: We use Granger Causality, a measure of the interaction between two signals, to characterize the influence of an enzyme on a reaction rate. We extend its traditional formulation to the case of multi-dimensional signals in order to capture group interactions, and not only element interactions. Our method is extensively tested on simulated data and applied to three biological datasets: microarray data of the Saccharomyces cerevisiae yeast, local field potential recordings of two brain areas and a metabolic reaction. Conclusions: Our results demonstrate that complex Granger causality can reveal new types of relation between signals and is particularly suited to biological data. Our approach raises some fundamental issues of the systems biology approach since finding all complex causalities (interactions) is an NP hard problem

Extending the applicability of multigrid methods

Multigrid methods are ideal for solving the increasingly large-scale problems that arise in numerical simulations of physical phenomena because of their potential for computational costs and memory requirements that scale linearly with the degrees of freedom. Unfortunately, they have been historically limited by their applicability to elliptic-type problems and the need for special handling in their implementation. In this paper, we present an overview of several recent theoretical and algorithmic advances made by the TOPS multigrid partners and their collaborators in extending applicability of multigrid methods. Specific examples that are presented include quantum chromodynamics, radiation transport, and electromagnetics