Efficacy of tranexamic acid in reducing blood loss in posterior lumbar spine surgery for degenerative spinal stenosis with instability: a retrospective case control study

<p>Abstract</p> <p>Background</p> <p>Degenerative spinal stenosis and instability requiring multilevel spine surgery has been associated with large blood losses. Factors that affect perioperative blood loss include time of surgery, surgical procedure, patient height, combined anterior/posterior approaches, number of levels fused, blood salvage techniques, and the use of anti-fibrinolytic medications. This study was done to evaluate the efficacy of tranexamic acid in reducing blood loss in spine surgery.</p> <p>Methods</p> <p>This retrospective case control study includes 97 patients who had to undergo surgery because of degenerative lumbar spinal stenosis and instability. All operations included spinal decompression, interbody fusion and posterior instrumentation (4-5 segments). Forty-six patients received 1 g tranexamic acid intravenous, preoperative and six hours and twelve hours postoperative; 51 patients without tranexamic acid administration were evaluated as a control group. Based on the records, the intra- and postoperative blood losses were measured by evaluating the drainage and cell saver systems 6, 12 and 24 hours post operation. Additionally, hemoglobin concentration and platelet concentration were reviewed. Furthermore, the number of red cell transfusions given and complications associated with tranexamic acid were assessed.</p> <p>Results</p> <p>The postoperative hemoglobin concentration demonstrated a statistically significant difference with a p value of 0.0130 showing superiority for tranexamic acid use (tranexamic acid group: 11.08 g/dl, SD: 1.68; control group: 10.29 g/dl, SD: 1.39). The intraoperative cell saver volume and drainage volume after 24 h demonstrated a significant difference as well, which indicates a less blood loss in the tranexamic acid group than the control group. The postoperative drainage volume at12 hours showed no significant differences; nor did the platelet concentration Allogenic blood transfusion (two red cell units) was needed for eight patients in the tranexamic acid group and nine in the control group because of postoperative anemia. Complications associated with the administration of tranexamic acid, e.g. renal failure, deep vein thrombosis or pulmonary embolism did not occur.</p> <p>Conclusions</p> <p>This study suggests a less blood loss when administering tranexamic acid in posterior lumbar spine surgery as demonstrated by the higher postoperative hemoglobin concentration and the less blood loss. But given the relatively small volume of blood loss in the patients of this study it is underpowered to show a difference in transfusion rates.</p

The interplay of intrinsic and extrinsic bounded noises in genetic networks

After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a genetic network. The influence of intrinsic and extrinsic noises on genetic networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: $(i)$ the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, $(ii)$ a model of enzymatic futile cycle and $(iii)$ a genetic toggle switch. In $(ii)$ and $(iii)$ we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possibile functional role of bounded noises

Bridging Time Scales in Cellular Decision Making with a Stochastic Bistable Switch

Cellular transformations which involve a significant phenotypical change of the cell's state use bistable biochemical switches as underlying decision systems. In this work, we aim at linking cellular decisions taking place on a time scale of years to decades with the biochemical dynamics in signal transduction and gene regulation, occuring on a time scale of minutes to hours. We show that a stochastic bistable switch forms a viable biochemical mechanism to implement decision processes on long time scales. As a case study, the mechanism is applied to model the initiation of follicle growth in mammalian ovaries, where the physiological time scale of follicle pool depletion is on the order of the organism's lifespan. We construct a simple mathematical model for this process based on experimental evidence for the involved genetic mechanisms. Despite the underlying stochasticity, the proposed mechanism turns out to yield reliable behavior in large populations of cells subject to the considered decision process. Our model explains how the physiological time constant may emerge from the intrinsic stochasticity of the underlying gene regulatory network. Apart from ovarian follicles, the proposed mechanism may also be of relevance for other physiological systems where cells take binary decisions over a long time scale.Comment: 14 pages, 4 figure

Chronic NMDA administration to rats increases brain pro-apoptotic factors while decreasing anti-Apoptotic factors and causes cell death

<p>Abstract</p> <p>Background</p> <p>Chronic <it>N</it>-Methyl-d-aspartate (NMDA) administration to rats is reported to increase arachidonic acid signaling and upregulate neuroinflammatory markers in rat brain. These changes may damage brain cells. In this study, we determined if chronic NMDA administration (25 mg/kg i.p., 21 days) to rats would alter expression of pro- and anti-apoptotic factors in frontal cortex, compared with vehicle control.</p> <p>Results</p> <p>Using real time RT-PCR and Western blotting, chronic NMDA administration was shown to decrease mRNA and protein levels of anti-apoptotic markers Bcl-2 and BDNF, and of their transcription factor phospho-CREB in the cortex. Expression of pro-apoptotic Bax, Bad, and 14-3-3ζ was increased, as well as Fluoro-Jade B (FJB) staining, a marker of neuronal loss.</p> <p>Conclusion</p> <p>This alteration in the balance between pro- and anti-apoptotic factors by chronic NMDA receptor activation in this animal model may contribute to neuronal loss, and further suggests that the model can be used to examine multiple processes involved in excitotoxicity.</p

A Dominated Coupling From The Past algorithm for the stochastic simulation of networks of biochemical reactions

<p>Abstract</p> <p>Background</p> <p>In recent years, stochastic descriptions of biochemical reactions based on the Master Equation (ME) have become widespread. These are especially relevant for models involving gene regulation. Gillespie’s Stochastic Simulation Algorithm (SSA) is the most widely used method for the numerical evaluation of these models. The SSA produces exact samples from the distribution of the ME for finite times. However, if the stationary distribution is of interest, the SSA provides no information about convergence or how long the algorithm needs to be run to sample from the stationary distribution with given accuracy. </p> <p>Results</p> <p>We present a proof and numerical characterization of a Perfect Sampling algorithm for the ME of networks of biochemical reactions prevalent in gene regulation and enzymatic catalysis. Our algorithm combines the SSA with Dominated Coupling From The Past (DCFTP) techniques to provide guaranteed sampling from the stationary distribution. The resulting DCFTP-SSA is applicable to networks of reactions with uni-molecular stoichiometries and sub-linear, (anti-) monotone propensity functions. We showcase its applicability studying steady-state properties of stochastic regulatory networks of relevance in synthetic and systems biology.</p> <p>Conclusion</p> <p>The DCFTP-SSA provides an extension to Gillespie’s SSA with guaranteed sampling from the stationary solution of the ME for a broad class of stochastic biochemical networks.</p

Linear mapping approximation of gene regulatory networks with stochastic dynamics

The intractability of most stochastic models of gene regulatory networks (GRNs) limits their utility. Here, the authors present a linear-mapping approximation mapping models onto simpler ones, giving approximate but accurate analytic or semi- analytic solutions for a wide range of model GRNs

Analysis of Stochastic Strategies in Bacterial Competence: A Master Equation Approach

Competence is a transiently differentiated state that certain bacterial cells reach when faced with a stressful environment. Entrance into competence can be attributed to the excitability of the dynamics governing the genetic circuit that regulates this cellular behavior. Like many biological behaviors, entrance into competence is a stochastic event. In this case cellular noise is responsible for driving the cell from a vegetative state into competence and back. In this work we present a novel numerical method for the analysis of stochastic biochemical events and use it to study the excitable dynamics responsible for competence in Bacillus subtilis. Starting with a Finite State Projection (FSP) solution of the chemical master equation (CME), we develop efficient numerical tools for accurately computing competence probability. Additionally, we propose a new approach for the sensitivity analysis of stochastic events and utilize it to elucidate the robustness properties of the competence regulatory genetic circuit. We also propose and implement a numerical method to calculate the expected time it takes a cell to return from competence. Although this study is focused on an example of cell-differentiation in Bacillus subtilis, our approach can be applied to a wide range of stochastic phenomena in biological systems

Naturally Occurring Genetic Variants in Human Chromogranin A (CHGA) Associated with Hypertension as well as Hypertensive Renal Disease

Chromogranin A (CHGA) plays a fundamental role in the biogenesis of catecholamine secretory granules. Changes in storage and release of CHGA in clinical and experimental hypertension prompted us to study whether genetic variation at the CHGA locus might contribute to alterations in autonomic function, and hence hypertension and its target organ consequences such as hypertensive renal disease (nephrosclerosis). Systematic polymorphism discovery across the human CHGA locus revealed both common and unusual variants in both the open reading frame and such regulatory regions as the proximal promoter and 3′-UTR. In chromaffin cell-transfected CHGA 3′-UTR and promoter/luciferase reporter plasmids, the functional consequences of the regulatory/non-coding allelic variants were documented. Variants in both the proximal promoter and the 3′-UTR displayed statistical associations with hypertension. Genetic variation in the proximal CHGA promoter predicted glomerular filtration rate in healthy twins. However, for hypertensive renal damage, both end-stage renal disease and rate of progression of earlier disease were best predicted by variants in the 3′-UTR. Finally, mechanistic studies were undertaken initiated by the clue that CHGA promoter variation predicted circulating endothelin-1. In cultured endothelial cells, CHGA triggered co-release of not only the vasoconstrictor and pro-fibrotic endothelin-1, but also the pro-coagulant von Willebrand Factor and the pro-angiogenic angiopoietin-2. These findings, coupled with stimulation of endothelin-1 release from glomerular capillary endothelial cells by CHGA, suggest a plausible mechanism whereby genetic variation at the CHGA locus eventuates in alterations in human renal function. These results document the consequences of genetic variation at the CHGA locus for cardiorenal disease and suggest mechanisms whereby such variation achieves functional effects

A new multicompartmental reaction-diffusion modeling method links transient membrane attachment of E. coli MinE to E-ring formation

Many important cellular processes are regulated by reaction-diffusion (RD) of molecules that takes place both in the cytoplasm and on the membrane. To model and analyze such multicompartmental processes, we developed a lattice-based Monte Carlo method, Spatiocyte that supports RD in volume and surface compartments at single molecule resolution. Stochasticity in RD and the excluded volume effect brought by intracellular molecular crowding, both of which can significantly affect RD and thus, cellular processes, are also supported. We verified the method by comparing simulation results of diffusion, irreversible and reversible reactions with the predicted analytical and best available numerical solutions. Moreover, to directly compare the localization patterns of molecules in fluorescence microscopy images with simulation, we devised a visualization method that mimics the microphotography process by showing the trajectory of simulated molecules averaged according to the camera exposure time. In the rod-shaped bacterium _Escherichia coli_, the division site is suppressed at the cell poles by periodic pole-to-pole oscillations of the Min proteins (MinC, MinD and MinE) arising from carefully orchestrated RD in both cytoplasm and membrane compartments. Using Spatiocyte we could model and reproduce the _in vivo_ MinDE localization dynamics by accounting for the established properties of MinE. Our results suggest that the MinE ring, which is essential in preventing polar septation, is largely composed of MinE that is transiently attached to the membrane independently after recruited by MinD. Overall, Spatiocyte allows simulation and visualization of complex spatial and reaction-diffusion mediated cellular processes in volumes and surfaces. As we showed, it can potentially provide mechanistic insights otherwise difficult to obtain experimentally

Multi-Scale Stochastic Simulation of Diffusion-Coupled Agents and Its Application to Cell Culture Simulation

Many biological systems consist of multiple cells that interact by secretion and binding of diffusing molecules, thus coordinating responses across cells. Techniques for simulating systems coupling extracellular and intracellular processes are very limited. Here we present an efficient method to stochastically simulate diffusion processes, which at the same time allows synchronization between internal and external cellular conditions through a modification of Gillespie's chemical reaction algorithm. Individual cells are simulated as independent agents, and each cell accurately reacts to changes in its local environment affected by diffusing molecules. Such a simulation provides time-scale separation between the intra-cellular and extra-cellular processes. We use our methodology to study how human monocyte-derived dendritic cells alert neighboring cells about viral infection using diffusing interferon molecules. A subpopulation of the infected cells reacts early to the infection and secretes interferon into the extra-cellular medium, which helps activate other cells. Findings predicted by our simulation and confirmed by experimental results suggest that the early activation is largely independent of the fraction of infected cells and is thus both sensitive and robust. The concordance with the experimental results supports the value of our method for overcoming the challenges of accurately simulating multiscale biological signaling systems