Performance Analysis of Extracted Rule-Base Multivariable Type-2 Self-Organizing Fuzzy Logic Controller Applied to Anesthesia

We compare type-1 and type-2 self-organizing fuzzy logic controller (SOFLC) using expert initialized and pretrained extracted rule-bases applied to automatic control of anaesthesia during surgery. We perform experimental simulations using a nonfixed patient model and signal noise to account for environmental and patient drug interaction uncertainties. The simulations evaluate the performance of the SOFLCs in their ability to control anesthetic delivery rates for maintaining desired physiological set points for muscle relaxation and blood pressure during a multistage surgical procedure. The performances of the SOFLCs are evaluated by measuring the steady state errors and control stabilities which indicate the accuracy and precision of control task. Two sets of comparisons based on using expert derived and extracted rule-bases are implemented as Wilcoxon signed-rank tests. Results indicate that type-2 SOFLCs outperform type-1 SOFLC while handling the various sources of uncertainties. SOFLCs using the extracted rules are also shown to outperform those using expert derived rules in terms of improved control stability

An Optimized Type-2 Self-Organizing Fuzzy Logic Controller Applied in Anesthesia for Propofol Dosing to Regulate BIS

During general anesthesia, anesthesiologists who provide anesthetic dosage traditionally play a fundamental role to regulate Bispectral Index (BIS). However, in this paper, an optimized type-2 Self-Organizing Fuzzy Logic Controller (SOFLC) is designed for Target Controlled Infusion (TCI) pump related to propofol dosing guided by BIS, to realize automatic control of general anesthesia. The type-2 SOFLC combines a type-2 fuzzy logic controller with a self-organizing (SO) mechanism to facilitate online training while able to contend with operational uncertainties. A novel data driven Surrogate Model (SM) and Genetic Programming (GP) based strategy is introduced for optimizing the type-2 SOFLC parameters offline to handle inter-patient variability. A pharmacological model is built for simulation in which different optimization strategies are tested and compared. Simulation results are presented to demonstrate the applicability of our approach and show that the proposed optimization strategy can achieve better control performance in terms of steady state error and robustness

Right ventricular exclusion for hepatocellular carcinoma metastatic to the heart

We used for the first time a right ventricular exclusion procedure for the treatment of hepatocellular carcinoma metastatic to the right ventricle. Our case report shows that this surgical option can be effective as rescue therapy for right ventricular outflow tract obstruction secondary to myocardial metastasis in critically ill patients. Most notably, this technique can prevent inadvertent dislodgement of tumor cells

Adaptive computation of multiscale entropy and its application in EEG signals for monitoring depth of anesthesia during surgery

Entropy as an estimate of complexity of the electroencephalogram is an effective parameter for monitoring the depth of anesthesia (DOA) during surgery. Multiscale entropy (MSE) is useful to evaluate the complexity of signals over different time scales. However, the limitation of the length of processed signal is a problem due to observing the variation of sample entropy (SE) on different scales. In this study, the adaptive resampling procedure is employed to replace the process of coarse-graining in MSE. According to the analysis of various signals and practical EEG signals, it is feasible to calculate the SE from the adaptive resampled signals, and it has the highly similar results with the original MSE at small scales. The distribution of the MSE of EEG during the whole surgery based on adaptive resampling process is able to show the detailed variation of SE in small scales and complexity of EEG, which could help anesthesiologists evaluate the status of patients.The Center for Dynamical Biomarkers and Translational Medicine, National Central University, Taiwan which is sponsored by National Science Council (Grant Number: NSC 100-2911-I-008-001). Also, it was supported by Chung-Shan Institute of Science & Technology in Taiwan (Grant Numbers: CSIST-095-V101 and CSIST-095-V102). Furthermore, it was supported by the National Science Foundation of China (No.50935005)

Changes in endotracheal tube cuff pressure during laparoscopic surgery in head-up or head-down position

BACKGROUND: The abdominal insufflation and surgical positioning in the laparoscopic surgery have been reported to result in an increase of airway pressure. However, associated effects on changes of endotracheal tube cuff pressure are not well established. METHODS: 70 patients undergoing elective laparoscopic colorectal tumor resection (head-down position, n = 38) and laparoscopic cholecystecomy (head-up position, n = 32) were enrolled and were compared to 15 patients undergoing elective open abdominal surgery. Changes of cuff and airway pressures before and after abdominal insufflation in supine position and after head-down or head-up positioning were analysed and compared. RESULTS: There was no significant cuff and airway pressure changes during the first fifteen minutes in open abdominal surgery. After insufflation, the cuff pressure increased from 26 ± 3 to 32 ± 6 and 27 ± 3 to 33 ± 5 cmH(2)O in patients receiving laparoscopic cholecystecomy and laparoscopic colorectal tumor resection respectively (both p < 0.001). The head-down tilt further increased cuff pressure from 33 ± 5 to 35 ± 5 cmH(2)O (p < 0.001). There six patients undergoing colorectal tumor resection (18.8%) and eight patients undergoing cholecystecomy (21.1%) had a total increase of cuff pressure more than 10 cm H(2)O (18.8%). There was no significant correlation between increase of cuff pressure and either the patient's body mass index or the common range of intra-abdominal pressure (10-15 mmHg) used in laparoscopic surgery. CONCLUSIONS: An increase of endotracheal tube cuff pressure may occur during laparoscopic surgery especially in the head-down position

Ludwigia octovalvis extract improves glycemic control and memory performance in diabetic mice

Ethnopharmacological relevance Ludwigia octovalvis (Jacq.) P.H. Raven (Onagraceae) extracts have historically been consumed as a healthful drink for treating various conditions, including edema, nephritis, hypotension and diabetes. Aim of the study We have previously shown that Ludwigia octovalvis extract (LOE) can significantly extend lifespan and improve age-related memory deficits in Drosophila melanogaster through activating AMP-activated protein kinase (AMPK). Since AMPK has become a critical target for treating diabetes, we herein investigate the anti-hyperglycemic potential of LOE. Materials and methods Differentiated C2C12 muscle cells, HepG2 hepatocellular cells, streptozotocin (STZ)-induced diabetic mice and high fat diet (HFD)-induced diabetic mice were used to investigate the anti-hyperglycemic potential of LOE. The open field test and novel object recognition test were used to evaluate spontaneous motor activity and memory performance of HFD-induced diabetic mice. Results In differentiated C2C12 muscle cells and HepG2 hepatocellular cells, treatments with LOE and its active component (β-sitosterol) induced significant AMPK phosphorylation. LOE also enhanced uptake of a fluorescent glucose derivative (2-NBDG) and inhibited glucose production in these cells. The beneficial effects of LOE were completely abolished when an AMPK inhibitor, dorsomorphin, was added to the culture system, suggesting that LOE requires AMPK activation for its action in vitro. In streptozotocin (STZ)-induced diabetic mice, we found that both LOE and β-sitosterol induced an anti-hyperglycemic effect comparable to that of metformin, a drug that is commonly prescribed to treat diabetes. Moreover, LOE also improved glycemic control and memory performance of mice fed a HFD. Conclusions These results indicate that LOE is a potent anti-diabetic intervention that may have potential for future clinical applications

Patient-controlled epidural Levobupicvacaine with or without Fentanyl for post-cesarean section pain relief

Purpose. The purpose of this study was to compare the analgesic properties of levobupivacaine with or without fentanyl for patient-controlled epidural analgesia after Cesarean section in a randomized, double-blinded study. Methods. We enrolled American Society of Anesthesiologists class I/II, full-term pregnant women at National Taiwan University Hospital who received patient-controlled epidural analgesia after Cesarean section between 2009 and 2010. Eighty women were randomly assigned into two groups. In group A, the 40 subjects received drug solutions made of 0.6 mg/ml levobupivacaine plus 2 mcg/ml fentanyl, and in group B the 40 subjects received 1 mg/ml levobupivacaine. Maintenance was self-administered boluses and a continuous background infusion. Results. There were no significant differences in the resting and dynamic pain scales and total volume of drug used between the two groups. Patient satisfaction was good in both groups. Conclusion. Our study showed that pure epidural levobupivacaine can provide comparative analgesic properties to the levobupivacaine-fentanyl combination after Cesarean section. Pure levobupivacaine may serve as an alternative pain control regimen to avoid opioid-related adverse events in parturients

Investigating Power Density and the Degree of Nonlinearity in Intrinsic Components of Anesthesia EEG by the Hilbert-Huang Transform: An Example Using Ketamine and Alfentanil

Empirical mode decomposition (EMD) is an adaptive filter bank for processing nonlinear and non-stationary signals, such as electroencephalographic (EEG) signals. EMD works well to decompose a time series into a set of intrinsic mode functions with specific frequency bands. An IMF therefore represents an intrinsic component on its correspondingly intrinsic frequency band. The word of ‘intrinsic’ means the frequency is totally adaptive to the nature of a signal. In this study, power density and nonlinearity are two critical parameters for characterizing the amplitude and frequency modulations in IMFs. In this study, a nonlinearity level is quantified using degree of waveform distortion (DWD), which represents the characteristic of waveform distortion as an assessment of the intra-wave modulation of an IMF. In the application of anesthesia EEG analysis, the assessments of power density and DWD for a set of IMFs represent dynamic responses in EEG caused by two different anesthesia agents, Ketamine and Alfentanil, on different frequency bands. Ketamine causes the increase of power density and the decrease of nonlinearity on γ-band neuronal oscillation, which cannot be found EEG responses of group B using Alfentanil. Both agents cause an increase of power density and a decrease of nonlinearity on β-band neuronal oscillation accompany with a loss of consciousness. Moreover, anesthesia agents cause the decreases of power density and nonlinearity (i.e. DWD) for the low-frequency IMFs

Instantaneous 3D EEG Signal Analysis Based on Empirical Mode Decomposition and the Hilbert–Huang Transform Applied to Depth of Anaesthesia

Depth of anaesthesia (DoA) is an important measure for assessing the degree to which the central nervous system of a patient is depressed by a general anaesthetic agent, depending on the potency and concentration with which anaesthesia is administered during surgery. We can monitor the DoA by observing the patient’s electroencephalography (EEG) signals during the surgical procedure. Typically high frequency EEG signals indicates the patient is conscious, while low frequency signals mean the patient is in a general anaesthetic state. If the anaesthetist is able to observe the instantaneous frequency changes of the patient’s EEG signals during surgery this can help to better regulate and monitor DoA, reducing surgical and post-operative risks. This paper describes an approach towards the development of a 3D real-time visualization application which can show the instantaneous frequency and instantaneous amplitude of EEG simultaneously by using empirical mode decomposition (EMD) and the Hilbert–Huang transform (HHT). HHT uses the EMD method to decompose a signal into so-called intrinsic mode functions (IMFs). The Hilbert spectral analysis method is then used to obtain instantaneous frequency data. The HHT provides a new method of analyzing non-stationary and nonlinear time series data. We investigate this approach by analyzing EEG data collected from patients undergoing surgical procedures. The results show that the EEG differences between three distinct surgical stages computed by using sample entropy (SampEn) are consistent with the expected differences between these stages based on the bispectral index (BIS), which has been shown to be quantifiable measure of the effect of anaesthetics on the central nervous system. Also, the proposed filtering approach is more effective compared to the standard filtering method in filtering out signal noise resulting in more consistent results than those provided by the BIS. The proposed approach is therefore able to distinguish between key operational stages related to DoA, which is consistent with the clinical observations. SampEn can also be viewed as a useful index for evaluating and monitoring the DoA of a patient when used in combination with this approach

Serotonin receptor HTR6-mediated mTORC1 signaling regulates dietary restriction-induced memory enhancement

Dietary restriction (DR; sometimes called calorie restriction) has profound beneficial effects on physiological, psychological, and behavioral outcomes in animals and in humans. We have explored the molecular mechanism of DR-induced memory enhancement and demonstrate that dietary tryptophan-a precursor amino acid for serotonin biosynthesis in the brain-and serotonin receptor 5-hydroxytryptamine receptor 6 (HTR6) are crucial in mediating this process. We show that HTR6 inactivation diminishes DR-induced neurological alterations, including reduced dendritic complexity, increased spine density, and enhanced long-term potentiation (LTP) in hippocampal neurons. Moreover, we find that HTR6-mediated mechanistic target of rapamycin complex 1 (mTORC1) signaling is involved in DR-induced memory improvement. Our results suggest that the HTR6-mediated mTORC1 pathway may function as a nutrient sensor in hippocampal neurons to couple memory performance to dietary intake