Ruptured abdominal aortic aneurysms: Factors influencing postoperative mortality and long-term survival

Objective:To update mortality rates and long-term survival of patients admitted to the hospital with ruptured abdominal aortic aneurysm (AAA) and to study prognostic factors associated with mortality.Design:Retrospective follow-up.Materials:309 patients (274 men, 35 women, average age 71) admitted to the hospital between January 1980 and January 1994 who were surgically treated for ruptured AAA were studied.Methods:To identify the preoperative (9), intraoperative (23) and postoperative (49) variables associated with mortality logistic regression analysis (mortality within 48 h) and Cox regression analysis (mortality between 48 h and 30 days) were performed.Results:Hospital mortality improved from 1980 to 1994. Compared with the normal population adjusted for age and sex the long-term mortality rate was increased (standardised mortality ratio 2.1; 95% confidence interval 1.7–2.5). Increased age, peroperative hypotension and need for a bifurcated graft were associated with significantly increased mortality. Co-morbidity was not a predictive variable. Overall hospital mortality was 25%.Conclusion:Surgical repair of ruptured AAA should be considered even in patients with co-morbidity. Elderly patients with severe preoperative hypotension have a very high mortality rate and surgery may not be justified in these cases. Long-term survival is also worse in older patients

The geographic scaling of biotic interactions

A central tenet of ecology and biogeography is that the broad outlines of species ranges are determined by climate, whereas the effects of biotic interactions are manifested at local scales. While the first proposition is supported by ample evidence, the second is still a matter of controversy. To address this question, we develop a mathematical model that predicts the spatial overlap, i.e. co-occurrence, between pairs of species subject to all possible types of interactions. We then identify the scale of resolution in which predicted range overlaps are lost. We found that co-occurrence arising from positive interactions, such as mutualism (+/+) and commensalism (+/0), are manifested across scales. Negative interactions, such as competition (-/-) and amensalism (-/0), generate checkerboard patterns of co-occurrence that are discernible at finer resolutions but that are lost and increasing scales of resolution. Scale dependence in consumer-resource interactions (+/-) depends on the strength of positive dependencies between species. If the net positive effect is greater than the net negative effect, then interactions scale up similarly to positive interactions. Our results challenge the widely held view that climate alone is sufficient to characterize species distributions at broad scales, but also demonstrate that the spatial signature of competition is unlikely to be discernible beyond local and regional scales. © 2013 The Authors.Peer Reviewe

Automated extraction of potential migraine biomarkers using a semantic graph

Problem Biomedical literature and databases contain important clues for the identification of potential disease biomarkers. However, searching these enormous knowledge reservoirs and integrating findings across heterogeneous sources is costly and difficult. Here we demonstrate how semantically integrated knowledge, extracted from biomedical literature and structured databases, can be used to automatically identify potential migraine biomarkers. Method We used a knowledge graph containing more than 3.5 million biomedical concepts and 68.4 million relationships. Biochemical compound concepts were filtered and ranked by their potential as biomarkers based on their connections to a subgraph of migraine-related concepts. The ranked results were evaluated against the results of a systematic literature review that was performed manually by migraine researchers. Weight points were assigned to these reference compounds to indicate their relative importance. Results Ranked results automatically generated by the knowledge graph were highly consistent with results from the manual literature review. Out of 222 reference compounds, 163 (73%) ranked in the top 2000, with 547 out of the 644 (85%) weight points assigned to the reference compounds. For reference compounds that were not in the top of the list, an extensive error analysis has been performed. When evaluating the overall performance, we obtained a ROC-AUC of 0.974. Discussion Semantic knowledge graphs composed of information integrated from multiple and varying sources can assist researchers in identifying potential disease biomarkers

An efficient conjugation approach for coupling drugs to native antibodies via the PtII linker Lx for improved manufacturability of antibody–drug conjugates

The Pt-II linker [ethylenediamineplatinum(II)](2+), coined Lx, has emerged as a novel non-conventional approach to antibody-drug conjugates (ADCs) and has shown its potential in preclinical in vitro and in vivo benchmark studies. A crucial improvement of the Lx conjugation reaction from initially <15 % to ca. 75-90 % conjugation efficiency is described, resulting from a systematic screening of all relevant reaction parameters. NaI, a strikingly simple inorganic salt additive, greatly improves the conjugation efficiency as well as the conjugation selectivity simply by exchanging the leaving chloride ligand on Cl-Lx-drug complexes (which are direct precursors for Lx-ADCs) for iodide, thus generating I-Lx-drug complexes as more reactive species. Using this iodide effect, we developed a general and highly practical conjugation procedure that is scalable: our lead Lx-ADC was produced on a 5 g scale with an outstanding conjugation efficiency of 89 %.Metals in Catalysis, Biomimetics & Inorganic Material

Antiferromagnetism in the Exact Ground State of the Half Filled Hubbard Model on the Complete-Bipartite Graph

As a prototype model of antiferromagnetism, we propose a repulsive Hubbard Hamiltonian defined on a graph \L={\cal A}\cup{\cal B} with ${\cal A}\cap {\cal B}=\emptyset$ and bonds connecting any element of ${\cal A}$ with all the elements of ${\cal B}$. Since all the hopping matrix elements associated with each bond are equal, the model is invariant under an arbitrary permutation of the ${\cal A}$-sites and/or of the ${\cal B}$-sites. This is the Hubbard model defined on the so called $(N_{A},N_{B})$-complete-bipartite graph, $N_{A}$ ($N_{B}$) being the number of elements in ${\cal A}$ (${\cal B}$). In this paper we analytically find the {\it exact} ground state for $N_{A}=N_{B}=N$ at half filling for any $N$; the repulsion has a maximum at a critical $N$-dependent value of the on-site Hubbard $U$. The wave function and the energy of the unique, singlet ground state assume a particularly elegant form for N \ra \inf. We also calculate the spin-spin correlation function and show that the ground state exhibits an antiferromagnetic order for any non-zero $U$ even in the thermodynamic limit. We are aware of no previous explicit analytic example of an antiferromagnetic ground state in a Hubbard-like model of itinerant electrons. The kinetic term induces non-trivial correlations among the particles and an antiparallel spin configuration in the two sublattices comes to be energetically favoured at zero Temperature. On the other hand, if the thermodynamic limit is taken and then zero Temperature is approached, a paramagnetic behavior results. The thermodynamic limit does not commute with the zero-Temperature limit, and this fact can be made explicit by the analytic solutions.Comment: 19 pages, 5 figures .ep

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2 total), and the proportion of heritability captured by known metabolite loci (h2 Metabolite-hits) for 309 lipids and

Effects of sleep deprivation on neural functioning: an integrative review

Sleep deprivation has a broad variety of effects on human performance and neural functioning that manifest themselves at different levels of description. On a macroscopic level, sleep deprivation mainly affects executive functions, especially in novel tasks. Macroscopic and mesoscopic effects of sleep deprivation on brain activity include reduced cortical responsiveness to incoming stimuli, reflecting reduced attention. On a microscopic level, sleep deprivation is associated with increased levels of adenosine, a neuromodulator that has a general inhibitory effect on neural activity. The inhibition of cholinergic nuclei appears particularly relevant, as the associated decrease in cortical acetylcholine seems to cause effects of sleep deprivation on macroscopic brain activity. In general, however, the relationships between the neural effects of sleep deprivation across observation scales are poorly understood and uncovering these relationships should be a primary target in future research