Moderate hyperventilation during intravenous anesthesia increases net cerebral lactate efflux

BACKGROUND:: Hyperventilation is known to decrease cerebral blood flow (CBF) and to impair cerebral metabolism, but the threshold in patients undergoing intravenous anesthesia is unknown. The authors hypothesized that reduced CBF associated with moderate hyperventilation might impair cerebral aerobic metabolism in patients undergoing intravenous anesthesia. METHODS:: Thirty male patients scheduled for coronary surgery were included in a prospective, controlled crossover trial. Measurements were performed under fentanyl-midazolam anesthesia in a randomized sequence aiming at partial pressures of carbon dioxide of 30 and 50 mmHg. Endpoints were CBF, blood flow velocity in the middle cerebral artery, and cerebral metabolic rates for oxygen, glucose, and lactate. Global CBF was measured using a modified Kety-Schmidt technique with argon as inert gas tracer. CBF velocity of the middle cerebral artery was recorded by transcranial Doppler sonography. Data were presented as mean (SD). Two-sided paired t tests and one-way ANOVA for repeated measures were used for statistical analysis. RESULTS:: Moderate hyperventilation significantly decreased CBF by 60%, blood flow velocity by 41%, cerebral oxygen delivery by 58%, and partial pressure of oxygen of the jugular venous bulb by 45%. Cerebral metabolic rates for oxygen and glucose remained unchanged; however, net cerebral lactate efflux significantly increased from -0.38 (2.18) to -2.41(2.43) μmol min 100 g. CONCLUSIONS:: Moderate hyperventilation, when compared with moderate hypoventilation, in patients with cardiovascular disease undergoing intravenous anesthesia increased net cerebral lactate efflux and markedly reduced CBF and partial pressure of oxygen of the jugular venous bulb, suggesting partial impairment of cerebral aerobic metabolism at clinically relevant levels of hypocapnia. Copyrigh

FSH prevents depletion of the resting follicle pool by promoting follicular number and morphology in fresh and cryopreserved primate ovarian tissues following xenografting

Background: Cryopreservation and transplantation of ovarian tissue is one option for re-establishing ovarian function, but optimal conditions for graft sustainment and follicular survival are still considered experimental. The present study aims to analyze the effect of FSH treatment on the resting follicle pool in fresh and cryopreserved primate ovarian tissues following xenografting. Methods: Ovarian tissues from adult marmosets were grafted freshly or following cryopreservation to ovarectomized nude mice treated with FSH 25 IU twice daily post transplantation or left untreated as controls. Grafts were retrieved 2 or 4 weeks after transplantation to evaluate the number and morphological appearance of follicles. Results: Early start of FSH treatment within 1 week following transplantation partly prevents primordial follicle loss in fresh and frozen-thawed tissues, whereas after a 3 weeks time interval this effect is present only in fresh tissues. A similar positive effect of early, but not later FSH treatment on primary follicles is seen in fresh tissues compared to only marginal effects in frozen-thawed tissues. The percentage of morphologically normal follicles is generally increased in FSH treated tissues, whereas the percentage of primary follicles over all primordial and primary follicles is increased by FSH only in freshly-grafted tissues. Conclusions: FSH treatment alleviates depletion of the resting follicle pool and promotes normal follicular morphology both in freshly and frozen-thawed grafted tissues. In previously cryopreserved tissues, applying to most of the tissues intended for clinical use in fertility preservation attempts, its positive effect on primordial follicle numbers and potential graft sustainment is dependent on an early start of treatment within one week of transplantation

Measuring Behavior in the Home Cage : Study Design, Applications, Challenges, and Perspectives

FUNDING This research was supported by NIH grants R00AG056662, P20GM125528, AG057424 to WS and SLPeer reviewedPublisher PD

A rule-based model of insulin signalling pathway

\u3cp\u3eBackground: The insulin signalling pathway (ISP) is an important biochemical pathway, which regulates some fundamental biological functions such as glucose and lipid metabolism, protein synthesis, cell proliferation, cell differentiation and apoptosis. In the last years, different mathematical models based on ordinary differential equations have been proposed in the literature to describe specific features of the ISP, thus providing a description of the behaviour of the system and its emerging properties. However, protein-protein interactions potentially generate a multiplicity of distinct chemical species, an issue referred to as combinatorial complexity , which results in defining a high number of state variables equal to the number of possible protein modifications. This often leads to complex, error prone and difficult to handle model definitions. Results: In this work, we present a comprehensive model of the ISP, which integrates three models previously available in the literature by using the rule-based modelling (RBM) approach. RBM allows for a simple description of a number of signalling pathway characteristics, such as the phosphorylation of signalling proteins at multiple sites with different effects, the simultaneous interaction of many molecules of the signalling pathways with several binding partners, and the information about subcellular localization where reactions take place. Thanks to its modularity, it also allows an easy integration of different pathways. After RBM specification, we simulated the dynamic behaviour of the ISP model and validated it using experimental data. We the examined the predicted profiles of all the active species and clustered them in four clusters according to their dynamic behaviour. Finally, we used parametric sensitivity analysis to show the role of negative feedback loops in controlling the robustness of the system. Conclusions: The presented ISP model is a powerful tool for data simulation and can be used in combination with experimental approaches to guide the experimental design. The model is available at http://sysbiobig.dei.unipd.it/was submitted to Biomodels Database ( https://www.ebi.ac.uk/biomodels-main/ # MODEL 1604100005).\u3c/p\u3