High-quality lung fixation by controlled closed loop perfusion for stereological analysis in a large animal model

Stereology is an essential method for quantitative analysis of lung structure. Adequate fixation is a prerequisite for stereological analysis to avoid bias in pulmonary tissue, dimensions and structural details. We present a technique for in situ fixation of large animal lungs for stereological analysis, based on closed loop perfusion fixation.

Closed-loop control of mean arterial blood pressure during surgery with alfentanil: clinical evaluation of a novel model-based predictive controller

BACKGROUND: In contrast to hypnosis, there is no surrogate parameter for analgesia in anesthetized patients. Opioids are titrated to suppress blood pressure response to noxious stimulation. The authors evaluated a novel model predictive controller for closed-loop administration of alfentanil using mean arterial blood pressure and predicted plasma alfentanil concentration (Cp Alf) as input parameters. METHODS: The authors studied 13 healthy patients scheduled to undergo minor lumbar and cervical spine surgery. After induction with propofol, alfentanil, and mivacurium and tracheal intubation, isoflurane was titrated to maintain the Bispectral Index at 55 (+/- 5), and the alfentanil administration was switched from manual to closed-loop control. The controller adjusted the alfentanil infusion rate to maintain the mean arterial blood pressure near the set-point (70 mmHg) while minimizing the Cp Alf toward the set-point plasma alfentanil concentration (Cp Alfref) (100 ng/ml). RESULTS: Two patients were excluded because of loss of arterial pressure signal and protocol violation. The alfentanil infusion was closed-loop controlled for a mean (SD) of 98.9 (1.5)% of presurgery time and 95.5 (4.3)% of surgery time. The mean (SD) end-tidal isoflurane concentrations were 0.78 (0.1) and 0.86 (0.1) vol%, the Cp Alf values were 122 (35) and 181 (58) ng/ml, and the Bispectral Index values were 51 (9) and 52 (4) before surgery and during surgery, respectively. The mean (SD) absolute deviations of mean arterial blood pressure were 7.6 (2.6) and 10.0 (4.2) mmHg (P = 0.262), and the median performance error, median absolute performance error, and wobble were 4.2 (6.2) and 8.8 (9.4)% (P = 0.002), 7.9 (3.8) and 11.8 (6.3)% (P = 0.129), and 14.5 (8.4) and 5.7 (1.2)% (P = 0.002) before surgery and during surgery, respectively. A post hoc simulation showed that the Cp Alfref decreased the predicted Cp Alf compared with mean arterial blood pressure alone. CONCLUSION: The authors' controller has a similar set-point precision as previous hypnotic controllers and provides adequate alfentanil dosing during surgery. It may help to standardize opioid dosing in research and may be a further step toward a multiple input-multiple output controller.

Real-time closed-loop electrophysiology: towards new frontiers in in vitro investigations in the neurosciences

Reflected at any level of organization of the central nervous system, most of the processes ranging from ion channels to neuronal networks occur in a closed loop, where the input to the system depends on its output. In contrast, most in vitro preparations and experimental protocols operate autonomously, and do not depend on the output of the studied system. Thanks to the progress in digital signal processing and real-time computing, it is now possible to artificially close the loop and investigate biophysical processes and mechanisms under increased realism. In this contribution, we review some of the most relevant examples of a new trend in in vitro electrophysiology, ranging from the use of dynamic-clamp to multi-electrode distributed feedback stimulation. We are convinced these represents the beginning of new frontiers for the in vitro investigation of the brain, promising to open the still existing borders between theoretical and experimental approaches while taking advantage of cutting edge technologies.

Use of a computerized closed-loop sodium nitroprusside titration system for antihypertensive treatment after open heart surgery

This study evaluates the clinical applicability of administering sodium nitroprusside by a closed-loop titration system compared with a manually adjusted system. The mean arterial pressure (MAP) was registered every 10 and 30 sec during the first 150 min after open heart surgery in 20 patients (group 1: computer regulation) and in ten patients (group 2: manual regulation). The results (16,343 and 2,912 data points in groups 1 and 2, respectively), were then analyzed in four time frames and five pressure ranges to indicate clinical efficacy. Sixty percent of the measured MAP in both groups was within the desired +/- 10% during the first 10 min. Thereafter until the end of observation, the MAP was maintained within +/- 10% of the desired set-point 90% of the time in group 1 vs. 60% of the time in group 2. One percent and 11% of data points were +/- 20% from the set-point in groups 1 and 2, respectively (p less than .05, chi-square test). The computer-assisted therapy provided better control of MAP, was safe to use, and helped to reduce nursing demands.

Spike-based decision learning of nash equilibria in two-player games

Humans and animals face decision tasks in an uncertain multi-agent environment where an agent's strategy may change in time due to the co-adaptation of others strategies. The neuronal substrate and the computational algorithms underlying such adaptive decision making, however, is largely unknown. We propose a population coding model of spiking neurons with a policy gradient procedure that successfully acquires optimal strategies for classical game-theoretical tasks. The suggested population reinforcement learning reproduces data from human behavioral experiments for the blackjack and the inspector game. It performs optimally according to a pure (deterministic) and mixed (stochastic) Nash equilibrium, respectively. In contrast, temporal-difference(TD)-learning, covariance-learning, and basic reinforcement learning fail to perform optimally for the stochastic strategy. Spike-based population reinforcement learning, shown to follow the stochastic reward gradient, is therefore a viable candidate to explain automated decision learning of a Nash equilibrium in two-player games.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior. But behavioral decision making is likely to involve the integration of many synaptic events in space and time. So in using a single reinforcement signal to modulate synaptic plasticity a twofold problem arises. Different synapses will have contributed differently to the behavioral decision and, even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward but by a population feedback signal as well. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second one involves an action sequence which is itself extended in time and reward is only delivered at the last action, as is the case in any type of board-game. The third is the inspection game that has been studied in neuroeconomics. It only has a mixed Nash equilibrium and exemplifies that the model also copes with stochastic reward delivery and the learning of mixed strategies.

An Actor-Critic based controller for glucose regulation in type 1 diabetes

A novel adaptive approach for glucose control in individuals with type 1 diabetes under sensor-augmented pump therapy is proposed. The controller, is based on Actor-Critic (AC) learning and is inspired by the principles of reinforcement learning and optimal control theory. The main characteristics of the proposed controller are (i) simultaneous adjustment of both the insulin basal rate and the bolus dose, (ii) initialization based on clinical procedures, and (iii) real-time personalization. The effectiveness of the proposed algorithm in terms of glycemic control has been investigated in silico in adults, adolescents and children under open-loop and closed-loop approaches, using announced meals with uncertainties in the order of ±25% in the estimation of carbohydrates. The results show that glucose regulation is efficient in all three groups of patients, even with uncertainties in the level of carbohydrates in the meal. The percentages in the A+B zones of the Control Variability Grid Analysis (CVGA) were 100% for adults, and 93% for both adolescents and children. The AC based controller seems to be a promising approach for the automatic adjustment of insulin infusion in order to improve glycemic control. After optimization of the algorithm, the controller will be tested in a clinical trial.

Control of muscle relaxation during anesthesia: a novel approach for clinical routine

During general anesthesia drugs are administered to provide hypnosis, ensure analgesia, and skeletal muscle relaxation. In this paper, the main components of a newly developed controller for skeletal muscle relaxation are described. Muscle relaxation is controlled by administration of neuromuscular blocking agents. The degree of relaxation is assessed by supramaximal train-of-four stimulation of the ulnar nerve and measuring the electromyogram response of the adductor pollicis muscle. For closed-loop control purposes, a physiologically based pharmacokinetic and pharmacodynamic model of the neuromuscular blocking agent mivacurium is derived. The model is used to design an observer-based state feedback controller. Contrary to similar automatic systems described in the literature this controller makes use of two different measures obtained in the train-of-four measurement to maintain the desired level of relaxation. The controller is validated in a clinical study comparing the performance of the controller to the performance of the anesthesiologist. As presented, the controller was able to maintain a preselected degree of muscle relaxation with excellent precision while minimizing drug administration. The controller performed at least equally well as the anesthesiologist.

Model-based control of neuromuscular block using mivacurium: design and clinical verification

BACKGROUND: Short-acting agents for neuromuscular block (NMB) require frequent dosing adjustments for individual patient's needs. In this study, we verified a new closed-loop controller for mivacurium dosing in clinical trials. METHODS: Fifteen patients were studied. T1% measured with electromyography was used as input signal for the model-based controller. After induction of propofol/opiate anaesthesia, stabilization of baseline electromyography signal was awaited and a bolus of 0.3 mg kg-1 mivacurium was then administered to facilitate endotracheal intubation. Closed-loop infusion was started thereafter, targeting a neuromuscular block of 90%. Setpoint deviation, the number of manual interventions and surgeon's complaints were recorded. Drug use and its variability between and within patients were evaluated. RESULTS: Median time of closed-loop control for the 11 patients included in the data processing was 135 [89-336] min (median [range]). Four patients had to be excluded because of sensor problems. Mean absolute deviation from setpoint was 1.8 +/- 0.9 T1%. Neither manual interventions nor complaints from the surgeons were recorded. Mean necessary mivacurium infusion rate was 7.0 +/- 2.2 microg kg-1 min-1. Intrapatient variability of mean infusion rates over 30-min interval showed high differences up to a factor of 1.8 between highest and lowest requirement in the same patient. CONCLUSIONS: Neuromuscular block can precisely be controlled with mivacurium using our model-based controller. The amount of mivacurium needed to maintain T1% at defined constant levels differed largely between and within patients. Closed-loop control seems therefore advantageous to automatically maintain neuromuscular block at constant levels.

Clinical validation of electromyography and acceleromyography as sensors for muscle relaxation

BACKGROUND AND OBJECTIVE: The aim of this study was to determine which of two clinically applied methods, electromyography or acceleromyography, was less affected by external disturbances, had a higher sensitivity and which would provide the better input signal for closed loop control of muscle relaxation. METHODS: In 14 adult patients, anaesthesia was induced with intravenous opioids and propofol. The response of the thumb to ulnar nerve stimulation was recorded on the same arm. Mivacurium was used for neuromuscular blockade. Under stable conditions of relaxation, the infusion-rate was decreased and the effects of turning the hand were investigated. RESULTS: Electromyography and acceleromyography both reflected the change of the infusion rate (P = 0.015 and P < 0.001, respectively). Electromyography was significantly less affected by the hand-turn (P = 0.008) than acceleromyography. While zero counts were detected with acceleromyography, electromyography could still detect at least one count in 51.1%. CONCLUSIONS: Electromyography is more reliable for use in daily practice as it is less influenced by external disturbances than acceleromyography.

eIF4E-bound mRNPs are substrates for nonsense-mediated mRNA decay in mammalian cells

Eukaryotic mRNAs with premature translation-termination codons (PTCs) are recognized and degraded by a process referred to as nonsense-mediated mRNA decay (NMD). The evolutionary conservation of the core NMD factors UPF1, UPF2 and UPF3 would imply a similar basic mechanism of PTC recognition in all eukaryotes. However, unlike NMD in yeast, which targets PTC-containing mRNAs irrespectively of whether their 5' cap is bound by the cap-binding complex (CBC) or by the eukaryotic initiation factor 4E (eIF4E), mammalian NMD has been claimed to be restricted to CBC-bound mRNAs during the pioneer round of translation. In our recent study we compared decay kinetics of two NMD reporter systems in mRNA fractions bound to either CBC or eIF4E in human cells. Our findings reveal that NMD destabilizes eIF4E bound transcripts as efficiently as those associated with CBC. These results corroborate an emerging unified model for NMD substrate recognition, according to which NMD can ensue at every aberrant translation termination event. Additionally, our results indicate that the closed loop structure of mRNA forms only after the replacement of CBC with eIF4E at the 5' cap.

eIF4E‐bound mRNPs are substrates for nonsense‐mediated mRNA decay in mammalian cells

Eukaryotic mRNAs with premature translation-termination codons (PTCs) are recognized and degraded by a process referred to as nonsense-mediated mRNA decay (NMD). The evolutionary conservation of the core NMD factors UPF1, UPF2 and UPF3 would imply a similar basic mechanism of PTC recognition in all eukaryotes. However, unlike NMD in yeast, which targets PTC-containing mRNAs irrespectively of whether their 5' cap is bound by the cap-binding complex (CBC) or by the eukaryotic initiation factor 4E (eIF4E), mammalian NMD has been claimed to be restricted to CBC-bound mRNAs during the pioneer round of translation. In our recent study we compared decay kinetics of two NMD reporter systems in mRNA fractions bound to either CBC or eIF4E in human cells. Our findings reveal that NMD destabilizes eIF4E bound transcripts as efficiently as those associated with CBC. These results corroborate an emerging unified model for NMD substrate recognition, according to which NMD can ensue at every aberrant translation termination event. Additionally, our results indicate that the closed loop structure of mRNA forms only after the replacement of CBC with eIF4E at the 5' cap.

eIF4E-bound mRNPs are substrates for nonsense-mediated mRNA decay in mammalian cells

Eukaryotic mRNAs with premature translation-termination codons (PTCs) are recognized and degraded by a process referred to as nonsense-mediated mRNA decay (NMD). The evolutionary conservation of the core NMD factors UPF1, UPF2 and UPF3 would imply a similar basic mechanism of PTC recognition in all eukaryotes. However, unlike NMD in yeast, which targets PTC-containing mRNAs irrespectively of whether their 5' cap is bound by the cap-binding complex (CBC) or by the eukaryotic initiation factor 4E (eIF4E), mammalian NMD has been claimed to be restricted to CBC-bound mRNAs during the pioneer round of translation. In our recent study we compared decay kinetics of two NMD reporter systems in mRNA fractions bound to either CBC or eIF4E in human cells. Our findings reveal that NMD destabilizes eIF4E bound transcripts as efficiently as those associated with CBC. These results corroborate an emerging unified model for NMD substrate recognition, according to which NMD can ensue at every aberrant translation termination event. Additionally, our results indicate that the closed loop structure of mRNA forms only after the replacement of CBC with eIF4E at the 5' cap.

eIF4E‐bound mRNPs are substrates for nonsense‐mediated mRNA decay in mammalian cells

Eukaryotic mRNAs with premature translation-termination codons (PTCs) are recognized and degraded by a process referred to as nonsense-mediated mRNA decay (NMD). The evolutionary conservation of the core NMD factors UPF1, UPF2 and UPF3 would imply a similar basic mechanism of PTC recognition in all eukaryotes. However, unlike NMD in yeast, which targets PTC-containing mRNAs irrespectively of whether their 5' cap is bound by the cap-binding complex (CBC) or by the eukaryotic initiation factor 4E (eIF4E), mammalian NMD has been claimed to be restricted to CBC-bound mRNAs during the pioneer round of translation. In our recent study we compared decay kinetics of two NMD reporter systems in mRNA fractions bound to either CBC or eIF4E in human cells. Our findings reveal that NMD destabilizes eIF4E bound transcripts as efficiently as those associated with CBC. These results corroborate an emerging unified model for NMD substrate recognition, according to which NMD can ensue at every aberrant translation termination event. Additionally, our results indicate that the closed loop structure of mRNA forms only after the replacement of CBC with eIF4E at the 5' cap.