Classification of Three Anesthesia Stages Based on Near-Infrared Spectroscopy Signals.

Proper monitoring of anesthesia stages can guarantee the safe performance of clinical surgeries. In this study, different anesthesia stages were classified using near-infrared spectroscopy (NIRS) signals with machine learning. The cerebral hemodynamic variables of right proximal oxyhemoglobin (HbO2) in maintenance (MNT), emergence (EM) and the consciousness (CON) stage were collected and then the differences between the three stages were compared by phase-amplitude coupling (PAC). Then combined with time-domain including linear (mean, standard deviation, max, min and range), nonlinear (sample entropy) and power in frequency-domain signal features, feature selection was performed and finally classification was performed by support vector machine (SVM) classifier. The results show that the PAC of the NIRS signal was gradually enhanced with the deepening of anesthesia level. A good three-classification accuracy of 69.27% was obtained, which exceeded the result of classification of any single category feature. These results indicate the fesibility of NIRS signals in performing three or even more anesthesia stage classifications, providing insight into the development of new anesthesia monitoring modalities.

Monitoring the Depth of Anesthesia Based on Phase-Amplitude Coupling of Near-Infrared Spectroscopy Signals.

Accurate monitoring of the depth of anesthesia (DOA) is essential to ensure the safety of the operation. In this study, a new index using near-infrared spectroscopy (NIRS) signal was proposed to assess the relationship between the DOA and cerebral hemodynamic variables. METHODS: Four cerebral hemodynamic variables of 15 patients were collected, including left, right, proximal, distal, oxygenated (HbO 2) and deoxygenated (Hb) hemoglobin concentration changes. The Phase-Amplitude coupling (PAC), an adaptation of cross-frequency coupling to reflect the modulation of the amplitude of high-frequency signals by the phase of low-frequency signals, was measured and the modulation index (MI) was obtained to monitor the DOA afterwards. Meanwhile, the BIS value based on electroencephalogram is also measured and compared. RESULTS: Compared with awake period, in anesthesia maintenance period, the PAC was strengthened. The analysis of receiver operating characteristic (ROC) curve showed that the MI, especially the MI of rp-HbO2, could effectively discriminate these two periods. Additionally, during the whole anesthesia process, the BIS value was statistically consistent with the MI of cerebral hemodynamic variables, and cerebral hemodynamic variables were immune from interference by clinical electric devices. CONCLUSION: The MI of cerebral hemodynamic variables was appropriate to be used as a new index to monitor the DOA. SIGNIFICANCE: This study is of great significance to the development of new modes of anesthesia monitoring and new decoding methods, and is expected to develop a high-performance anesthesia monitoring system.

Hemolymph Node - An Immunomorphlogical Organ: Modeling the Hemolymph Node by Allografting Renal Tissue in the Rat.

There is no authoritative characterization of the attributes of the hemolymph node (HLN) since Gibbes' first description in 1884. Early reports showed that HLN are found near the kidney in human and animals with the feature of numerous erythrocytes in sinuses. Subsequent studies mainly focused on anatomy and histology, such as the source, distribution, and quantity of erythrocytes in sinuses. Recent articles mentioned that the emergence of HLN was related to immunity, but there was no strong evidence to support this hypothesis. Therefore, it is still uncertain whether the HLN is an organ of anatomy, histology, or immunology. It has been found that the development of HLN could be elicited in the parathymic area by stimuli such as Escherichia coli, allogeneic breast cancer cells, and renal tissue that were injected/transplanted into the tail of rats in our pilot studies. In this study, the model of the HLN was established by transferring allogeneic renal tissue in the rat. Intrasinusoidal erythrocytes of the node were the component for producing a red macroscopic appearance, while macrophage-erythrocyte-lymphocyte rosettes were the major immunomorphological changes, reflecting the immune activity against the invasion of the allogeneic tissue within the node. Therefore, the HLN is an immunomorphological organ.

Brain connectivity changes of propofol-induced altered states of consciousness using High-Density EEG Source Estimation.

Through source estimation, high-density electroencephalogram (EEG) signals at scalp level can be converted into signals at cerebral cortex level, which helps to measure cortical activity during anesthesia induced changes in consciousness level to explore the mechanism. In this research, the high-density EEG of propofol-induced consciousness states alterations in 20 healthy adults were converted into cortical signals of 68 regions of interest (ROI), after alpha bandpass filtering, the pairwise orthogonal power envelope connectivity (PEC) was calculated. Then, due to the number of PECs was huge, the least absolute shrinkage and selection operator (LASSO) was used to select as few PECs as possible as the indicators to distinguish baseline (BS) and moderate sedation (MD) states. The results show that most PECs that can be used as indicators are related to ROI related to default mode network (DMN). At the same time, changes of thalamocortical connectivity and frontal-parietal connectivity could be observed, similar to the neuroimaging method of directly measuring cerebral cortical activity. By extracting the PEC as a classifier to classify the BS and MD States, the accuracy could reach more than 70%. Therefore, this method can not only reflect the mechanism of cortical activity alterations induced by anesthetics, but also provide a new idea for monitoring the depth of anesthesia in the future. Clinical Relevance - This shows that the high-density EEG of scalp level can be converted into cortical signals by source estimation, which is similar to the neuroimaging method of directly measuring cortical activity.

Characteristics of EEG Microstate Sequences During Propofol-Induced Alterations of Brain Consciousness States.

Monitoring the consciousness states of patients and ensuring the appropriate depth of anesthesia (DOA) is critical for the safe implementation of surgery. In this study, a high-density electroencephalogram (EEG) combined with blood drug concentration and behavioral response indicators was used to monitor propofol-induced sedation and evaluate the alterations in consciousness states. Microstate analysis, which can reflect the semi-stable state of the sub-second activation of the brain functional network, can be used to assess the brain's consciousness states. In this research, the EEG microstate sequences were constructed to compare the characteristics of corresponding sequences. Compared with the baseline (BS) state, the microstate sequences in the moderate sedation (MD) state exhibited higher complexity indexes of the multiscale sample entropy. With respect to the transition probability (TP) of microstates, most microstates tended to be converted into microstate C in the BS state. In contrast, they tended to be converted into microstate F in the MD state. The significant difference between the expected TP and observed TP could lead to the conclusion that hidden layers were present when there were changes in the consciousness states. According to the hidden Markov model, the accuracy of distinguishing the BS and MD states was 80.16%. The characteristics of microstate sequence revealed the variations in the brain states caused by alterations in consciousness states during anesthesia from a new perspective and presented a new idea for monitoring the DOA.

Diagnostic Value of Multimodal Intraoperative Neuromonitoring by Combining Somatosensory-With Motor-Evoked Potential in Posterior Decompression Surgery for Thoracic Spinal Stenosis.

Background: Intraoperative neuromonitoring (IONM) has become an increasingly essential technique in spinal surgery. However, data on the diagnostic value of IONM in predicting impending postoperative neurological deficits (PONDs) for patients who underwent posterior decompression surgery for thoracic spinal stenosis (TSS) are limited. Furthermore, patients who are at the highest risk of waveform changes during the surgery remain unknown. Our purpose was to (1) assess the diagnostic accuracy of IONM by combining somatosensory-evoked potential (SSEP) with motor-evoked potential (MEP) in predicting PONDs for patients who underwent the surgery and (2) identify the independent risk factors correlated with IONM changes in our study population. Methods: A total of 326 consecutive patients who underwent the surgery were identified and analyzed. We collected the following data: (1) demographic and clinical data; (2) IONM data; and (3) outcome data such as details of PONDs, and recovery status (complete, partial, or no recovery) at the 12-month follow-up visit. Results: In total, 27 patients developed PONDs. However, 15, 6, and 6 patients achieved complete recovery, partial recovery, and no recovery, respectively, at the 12-month follow-up. SSEP or MEP change monitoring yielded better diagnostic efficacy in predicting PONDs as indicated by the increased sensitivity (96.30%) and area under the receiver operating characteristic (ROC) curve (AUC) value (0.91). Only one neurological deficit occurred without waveform changes. On multiple logistic regression analysis, the independent risk factors associated with waveform changes were as follows: preoperative moderate or severe neurological deficits (p = 0.002), operating in the upper- or middle-thoracic spinal level (p = 0.003), estimated blood loss (EBL) ≥ 400 ml (p < 0.001), duration of symptoms ≥ 3 months (p < 0.001), and impairment of gait (p = 0.001). Conclusion: Somatosensory-evoked potential or MEP change is a highly sensitive and moderately specific indicator for predicting PONDs in posterior decompression surgery for TSS. The independent risks for IONM change were as follows: operated in upper- or middle-thoracic spinal level, presented with gait impairment, had massive blood loss, moderate or severe neurological deficits preoperatively, and had a longer duration of symptoms. Clinical Trial Registration: [http://www.chictr.org.cn]; identifier [ChiCTR 200003 2155].

A Loading Dose of Dexmedetomidine With Constant Infusion Inhibits Intraoperative Neuromonitoring During Thoracic Spinal Decompression Surgery: A Randomized Prospective Study.

Background: The effect of a bolus dose of dexmedetomidine on intraoperative neuromonitoring (IONM) parameters during spinal surgeries has been variably reported and remains a debated topic. Methods: A randomized, double-blinded, placebo-controlled study was performed to assess the effect of dexmedetomidine (1 µg/kg in 10 min) followed by a constant infusion rate on IONM during thoracic spinal decompression surgery (TSDS). A total of 165 patients were enrolled and randomized into three groups. One group received propofol- and remifentanil-based total intravenous anesthesia (TIVA) (T group), one group received TIVA combined with dexmedetomidine at a constant infusion rate (0.5 µg kg-1 h-1) (D1 group), and one group received TIVA combined with dexmedetomidine delivered in a loading dose (1 µg kg-1 in 10 min) followed by a constant infusion rate (0.5 µg kg-1 h-1) (D2 group). The IONM data recorded before test drug administration was defined as the baseline value. We aimed at comparing the parameters of IONM. Results: In the D2 group, within-group analysis showed suppressive effects on IONM parameters compared with baseline value after a bolus dose of dexmedetomidine. Furthermore, the D2 group also showed inhibitory effects on IONM recordings compared with both the D1 group and the T group, including a statistically significant decrease in SSEP amplitude and MEP amplitude, and an increase in SSEP latency. No significance was found in IONM parameters between the T group and the D1 group. Conclusion: Dexmedetomidine delivered in a loading dose can significantly inhibit IONM parameters in TSDS. Special attention should be paid to the timing of a bolus dose of dexmedetomidine under IONM. However, dexmedetomidine delivered at a constant speed does not exert inhibitory effects on IONM data.

The Prognostic Value of Intraoperative Neuromonitoring by Combining Somatosensory- and Motor-Evoked Potentials for Thoracic Spinal Decompression Surgery in Patients with Neurological Deficit.

STUDY DESIGN: Retrospective study. OBJECTIVE: To explore a relation between somatosensory- and motor-evoked potential (SEPs, MEPs) and corresponding thoracic cord function for thoracic spinal decompression surgery (TSDS) in patients with neurological deficit. SUMMARY OF BACKGROUND DATA: Although SEPs and MEPs monitoring has been developed as an essential technique in spinal surgery. There are limited data on the reliability of using SEPs and MEPs for TSDS and its prognosis. METHODS: One hundred twenty patients underwent TSDS in our hospital, 91 patients completed the trial. All the patients were divided into three subgroups according to the changes of MEPs and SEPs: neither SEPs nor MEP deteriorated -. Simply MEP deteriorated and both SEPs and MEP deteriorated -. Bispectral (BIS) was used to monitor the depth of sedation, which ranged from 40 to 60 by varying the infusion speed of anesthetics. The pre- and postoperative spinal function was assessed by muscle strength and Japanese Orthopaedic Association (JOA) score at three time points:1) before surgery; 2) immediately after general anesthesia recovery; 3) after 3-month follow-up. RESULTS: Sixty-nine cases showed neither SEPs nor MEP deteriorated -, 10 cases showed only MEP deteriorated, and 12 cases showed both SEPs and MEP deteriorated -. The patients in the group where neither SEPs nor MEP deteriorated had the best recovery of the extremity muscle strength, the shortest recovery time (8.10 ±â€Š1.60, P < 0.05), and toe movement time (8.50 ±â€Š1.60, P < 0.05). There is a strong correlation between SEPs variability ratio at T4 time point and JOA recovery ratio (JOA RR) in the 3-month follow-up. CONCLUSION: Combined SEPs and MEPs monitoring are important for TSDS in patients with neurological deficit and it is helpful for evaluating postoperative prognosis. It is more accurate to record SEPs at T4 time point to predict the patients' prognosis.Level of Evidence: 3.

Occurrence of hypertension during third-line anlotinib is associated with progression-free survival in patients with squamous cell lung cancer (SCC): A post hoc analysis of the ALTER0303 trial.

BACKGROUND: There is a lack of targeted therapeutic options for squamous cell lung cancer (SCC). Accelerated hypertension is an issue with many targeted therapies for lung cancer. This study aimed to analyze the efficacy of anlotinib, based on progression-free survival (PFS) and overall survival (OS) in patients with SCC, stratified by hypertension and Eastern Cooperative Oncology Group (ECOG) score. METHODS: This was a post hoc analysis of a multicenter, double-blind, phase III ALTER0303 randomized controlled trial. Only patients with SCC were included. The occurrence of hypertension during the study period was defined according to CTCAE 4.03. OS and PFS were the primary and secondary endpoints, respectively. The patients were stratified according to hypertension and ECOG score, respectively. RESULTS: The median PFS in the patients who developed hypertension was longer than in those who did not (7.2 (95% CI: 3.5-11.0) versus 3.2 (95% CI: 1.2-5.3) months, p = 0.001; HR (95% CI), 0.4 (0.2-0.8)). In the ECOG 0 patients, the median PFS in the patients who developed hypertension versus those who did not was 5.6 vs. 1.8 months, respectively (Figure 2(d)). In the ECOG 1 patients, the median PFS in the patients who developed hypertension versus those who did not was 7.0 (95% CI: 3.0-11.0) vs. 4.8 (95% CI: 1.2-8.5) months (p = 0.043). No statistically significant differences were found in OS in the stratified analyses. CONCLUSIONS: The occurrence of hypertension might be a clinical indicator predicting the efficacy of third-line anlotinib treatment in patients with SCC.

Improvement in EEG Source Imaging Accuracy by Means of Wavelet Packet Transform and Subspace Component Selection.

The electroencephalograph (EEG) source imaging (ESI) method is a non-invasive method that provides high temporal resolution imaging of brain electrical activity on the cortex. However, because the accuracy of EEG source imaging is often affected by unwanted signals such as noise or other source-irrelevant signals, the results of ESI are often incongruous with the real sources of brain activities. This study presents a novel ESI method (WPESI) that is based on wavelet packet transform (WPT) and subspace component selection to image the cerebral activities of EEG signals on the cortex. First, the original EEG signals are decomposed into several subspace components by WPT. Second, the subspaces associated with brain sources are selected and the relevant signals are reconstructed by WPT. Finally, the current density distribution in the cerebral cortex is obtained by establishing a boundary element model (BEM) from head MRI and applying the appropriate inverse calculation. In this study, the localization results obtained by this proposed approach were better than those of the original sLORETA approach (OESI) in the computer simulations and visual evoked potential (VEP) experiments. For epilepsy patients, the activity sources estimated by this proposed algorithm conformed to the seizure onset zones. The WPESI approach is easy to implement achieved favorable accuracy in terms of EEG source imaging. This demonstrates the potential for use of the WPESI algorithm to localize epileptogenic foci from scalp EEG signals.

Reliability of EEG microstate analysis at different electrode densities during propofol-induced transitions of brain states.

Electroencephalogram (EEG) microstate analysis is a promising and effective spatio-temporal method that can segment signals into several quasi-stable classes, providing a great opportunity to investigate short-range and long-range neural dynamics. However, there are still many controversies in terms of reproducibility and reliability when selecting different parameters or datatypes. In this study, five electrode configurations (91, 64, 32, 19, and 8 channels) were used to measure the reliability of microstate analysis at different electrode densities during propofol-induced sedation. First, the microstate topography and parameters at five different electrode densities were compared in the baseline (BS) condition and the moderate sedation (MD) condition, respectively. The intraclass correlation coefficient (ICC) and coefficient of variation (CV) were introduced to quantify the consistency of the microstate parameters. Second, statistical analysis and classification between BS and MD were performed to determine whether the microstate differences between different conditions remained stable at different electrode densities, and ICC was also calculated between the different conditions to measure the consistency of the results in a single condition. The results showed that in both the BS or MD condition, respectively, there were few significant differences in the microstate parameters among the 91-, 64-, and 32-channel configurations, with most of the differences observed between the 19- or 8-channel configurations and the other configurations. The ICC and CV data also showed that the consistency among the 91-, 64-, and 32-channel configurations was better than that among all five electrode configurations after including the 19- and 8-channel configurations. Furthermore, the significant differences between the conditions in the 91-channel configuration remained stable at the 64- and 32-channel resolutions, but disappeared at the 19- and 8-channel resolutions. In addition, the classification and ICC results showed that the microstate analysis became unreliable with fewer than 20 electrodes. The findings of this study support the hypothesis that microstate analysis of different brain states is more reliable with higher electrode densities; the use of a small number of channels is not recommended.

Trpv4 regulates Nlrp3 inflammasome via SIRT1/PGC-1α pathway in a cuprizone-induced mouse model of demyelination.

Increasing evidence has demonstrated that the Nod-like receptor pyrin domain containing 3 (Nlrp3) inflammasome overactivated during demyelinating disorders. It has been implicated that transient receptor potential type 4 (Trpv4) is regarded as a polymodal ionotropic receptor that plays an important role in a multitude of pathological conditions, including inflammation. The aim of this study was to investigate whether the Trpv4 channel regulates Nlrp3 inflammasome in the corpus callosum of mice with demyelination. Our results showed that CPZ treatment significantly increased the expression of Trpv4, activated Nlrp3 inflammasome, reduced peroxisome proliferator-activated receptor gamma coactivator 1α (PGC-1α) and decreased mitochondrial function. siRNA-mediated Nlrp3 knockdown inhibited glial activation and alleviated demyelination. Whereas knockdown of Trpv4 by siRNA markedly ameliorated Nlrp3 inflammasome activation and restored mitochondrial function as well as reducing the level of reactive oxygen species (ROS). Meanwhile, glial activation, demyelination and behavioral impairment induced by CPZ were also alleviated by siRNA-mediated Trpv4 knockdown. Furthermore, immunoprecipitation and use of a lysine acetylation assay showed that Sirtuin1 (SIRT1) mediated the PGC-1α deacetylation, which is involved in Nlrp3 inflammasome activation. These findings suggest that Trpv4 regulates mitochondrial function through the SIRT1/PGC-1α pathway, which further trigger Nlrp3 inflammasome activation in the CPZ-induced demyelination in mice.

Effective Brain State Estimation During Propofol-Induced Sedation Using Advanced EEG Microstate Spectral Analysis.

Brain states are patterns of neuronal synchrony, and the electroencephalogram (EEG) microstate provides a promising tool to characterize and analyze the synchronous neural firing. However, the topographical spectral information for each predominate microstate is still unclear during the switch of consciousness, such as sedation, and the practical usage of the EEG microstate is worth probing. Also, the mechanism behind the anesthetic-induced alternations of brain states remains poorly understood. In this study, an advanced EEG microstate spectral analysis was utilized using multivariate empirical mode decomposition in Hilbert-Huang transform. The practicability was further investigated in scalp EEG recordings during the propofol-induced transition of consciousness. The process of transition from the awake baseline to moderate sedation was accompanied by apparent increases in microstate (A, B, and F) energy, especially in the whole-brain delta band, frontal alpha band and beta band. In comparison to other effective EEG-based parameters that commonly used to measure anesthetic depth, using the selected spectral features reached better performance (80% sensitivity, 90% accuracy) to estimate the brain states during sedation. The changes in microstate energy also exhibited high correlations with individual behavioral data during sedation. In a nutshell, the EEG microstate spectral analysis is an effective method to estimate brain states during propofol-induced sedation, giving great insights into the underlying mechanism. The generated spectral features can be promising markers to dynamically assess the consciousness level.

Correction to: Troxerutin protects against DHT-induced polycystic ovary syndrome in rats.

An amendment to this paper has been published and can be accessed via the original article.

Seizure Prediction Using Directed Transfer Function and Convolution Neural Network on Intracranial EEG.

Automatic seizure prediction promotes the development of closed-loop treatment system on intractable epilepsy. In this study, by considering the specific information exchange between EEG channels from the perspective of whole brain activities, the convolution neural network (CNN) and the directed transfer function (DTF) were merged to present a novel method for patient-specific seizure prediction. Firstly, the intracranial electroencephalogram (iEEG) signals were segmented and the information flow features of iEEG signals were calculated by using the DTF algorithm. Then, these features were reconstructed as the channel-frequency maps according to channel pairs and the frequency of information flow. Finally, these maps were fed into the CNN model and the outputs were post-processed by the moving average approach to predict the epileptic seizures. By the evaluation of cross-validation method, the proposed algorithm achieved the averaged sensitivity of 90.8%, the averaged false prediction rate of 0.08 per hour. Compared to the random predictor and other existing algorithms tested on the Freiburg EEG dataset, our proposed method achieved better performance for seizure prediction in all patients. These results demonstrated that the proposed algorithm could provide an robust seizure prediction solution by using deep learning to capture the brain network changes of iEEG signals from epileptic patients.

Troxerutin protects against DHT-induced polycystic ovary syndrome in rats.

The exact pathogenesis of polycystic ovary syndrome (PCOS), the most common neuroendocrine disorder in women of reproductive age, has not been fully elucidated. Recent studies suggested that chronic inflammation and neurotransmitter disorder involved in the progress of PCOS. Troxerutin, a natural flavonoid, was reported to possess neuroprotective effect in several disease models by inhibiting inflammation or enhancing neurotrophic factor. In this study, we investigated the possible protective effect and mechanism of troxerutin in a dihydrotestosterone (DHT)-induced rat model of PCOS. The PCOS rat models were treated with troxerutin at a dose of 150 mg/kg or 300 mg/kg for up to 4 weeks. Results showed that 300 mg/kg troxerutin significantly decreased the body weight gain and improved the pathological changes of ovary induced by DHT. Meanwhile, the elevated gonadotrophin-releasing hormone (GnRH), gonadotrophin and testosterone in the serum of PCOS rats were reduced with the treatment of troxerutin. The expression of kisspeptin and NKB in arcuate nucleus and their receptors kiss1r and NK3r in GnRH positive neurons of median eminence were markedly decreased in troxerutin-treated rats. Of note, the GnRH inhibitory regulator GABA and stimulatory regulator glutamate were also restored to the normal level by troxerutin. The present study indicated that troxerutin may exhibit a protective effect in PCOS rat model via regulating neurotransmitter release.

Non-Canonical Microstate Becomes Salient in High Density EEG During Propofol-Induced Altered States of Consciousness.

Dynamically assessing the level of consciousness is still challenging during anesthesia. With the help of Electroencephalography (EEG), the human brain electric activity can be noninvasively measured at high temporal resolution. Several typical quasi-stable states are introduced to represent the oscillation of the global scalp electric field. These so-called microstates reflect spatiotemporal dynamics of coherent neural activities and capture the switch of brain states within the millisecond range. In this study, the microstates of high-density EEG were extracted and investigated during propofol-induced transition of consciousness. To analyze microstates on the frequency domain, a novel microstate-wise spectral analysis was proposed by the means of multivariate empirical mode decomposition and Hilbert-Huang transform. During the transition of consciousness, a map with a posterior central maximum denoted as microstate F appeared and became salient. The current results indicated that the coverage, occurrence, and power of microstate F significantly increased in moderate sedation. The results also demonstrated that the transition of brain state from rest to sedation was accompanied by significant increase in mean energy of all frequency bands in microstate F. Combined with studies on the possible cortical sources of microstates, the findings reveal that non-canonical microstate F is highly associated with propofol-induced altered states of consciousness. The results may also support the inference that this distinct topography can be derived from canonical microstate C (anterior-posterior orientation). Finally, this study further develops pertinent methodology and extends possible applications of the EEG microstate during propofol-induced anesthesia.

Monitoring the Depth of Anesthesia Through the Use of Cerebral Hemodynamic Measurements Based on Sample Entropy Algorithm.

OBJECTIVE: The aim of this study is to explore the relationship between the depth of anesthesia and the cerebral hemodynamic variables during the complete anesthesia process. METHODS: In this study, near-infrared spectroscopy signals were used to record eight kinds of cerebral hemodynamic variables, including left, right, proximal, distal deoxygenated (Hb) and oxygenated (HbO2) hemoglobin concentration changes. Then, by measuring the complexity information of cerebral hemodynamic variables, the sample entropy was calculated as a new index of monitoring the depth of anesthesia. RESULTS: By means of receiver operating characteristic curve analysis, the sample entropy approach was proved to effectively discriminate anesthesia maintenance and waking phases. The discriminatory ability of HbO2 signals was stronger than that of Hb signals and the distal signals had weaker discrimination capability when compared with the proximal signals. In addition, there was statistical consistency between the bispectral index and sample entropy of cerebral hemodynamic variables during the complete anesthesia process. Moreover, the cerebral hemodynamic signals could not be interfered by clinical electrical devices. CONCLUSION: The sample entropy of cerebral hemodynamic variables could be suitable as a new index for monitoring the depth of anesthesia. SIGNIFICANCE: This study is very meaningful for developing new modality and decoding methods in perspective of anesthesia surveillance and may result in the anesthesia monitoring system with high performance.

Deep lymphatic anatomy of the upper limb: An anatomical study and clinical implications.

BACKGROUND: The deep and perforating lymphatic anatomy of the upper limb still remains the least described in medical literature. MATERIALS AND METHODS: Six upper limbs with the axillary tissue were harvested from three unembalmed human cadavers amputated at the shoulder joint. A small amount of 6% hydrogen peroxide was employed to detect the lymphatic vessels around the deep palmar arch, radial and ulnar neurovascular bundles. A 30-gauge needle was inserted into the vessels and they were injected with a barium sulphate compound. Each specimen was dissected, photographed and radiographed to demonstrate deep lymphatic distribution of the upper limb. RESULTS: Continuing from the deep lymph vessels of the hand, single or multiple deep collecting lymph vessels have been found along the radial, ulnar, anterior and posterior interosseous neurovascular bundles in the forearm, brachial and deep branchial neurovascular bundles in the upper arm. During their courses, lymph nodes were found setting in the trunk of the radial, ulnar and brachial lymph vessels near or in the cubital fossa, and in the axillar. Perforating lymph vessels have been found near the wrist and in the cubital fossa, which linked the superficial and deep lymph vessels. The direction of lymphatic drainage was from the deep to superficial or superficial to deep vessels. CONCLUSION: The deep lymphatic anatomy of the upper limb has been described. The results will provide an anatomical basis for clinical management, educational reference and scientific research.

Inhibition of LPS-induced brain injury by NR2B antagonists through reducing assembly of NR2B-CaMKII-PSD95 signal module.

Background: Accumulating evidence suggests that inflammation is a contributor to the cause and progression of neurodegenerative disease, such as Alzheimer's disease (AD) and Parkinson disease (PD). However, the exact mechanisms of neuroinflammation are still unclear. Here, we discussed the potential mechanisms of lipopolysaccharide (LPS)-induced brain injury via NR2B antagonists (Ro25-6981) treatment in mice. Methods: Neuroinflammation was induced in mice by virtue of LPS (1 mg/kg) by intraperitoneal injection. Immunoprecipitation was performed to measure the assembly of NR2B-calmodulin dependent protein kinase II (CaMKII)-Postsynaptic density protein 95 (PSD95) signal module in the hippocampus and frontal cortex. Nissl's staining was employed to access neuron injury in the brain. Results: Data demonstrated that LPS could induce neuron damage, and promote the assembly of NR2B-CaMKII-PSD95 signal module and increase the expression of phosphorylated CaMKII and c-Jun N-terminal kinase (JNK) in the frontal cortex and hippocampus. However, NR2B antagonists could protect neuron injury against LPS-induced inflammation, inhibit the assembly of NR2B-CaMKII-PSD95 signal module and decrease the level of phosphorylated CaMKII and JNKs in mice. Conclusions: These findings indicated that the assembly of NR2B-CaMKII-PSD95 signal module is related to LPS-induced neuroinflammation, NR2B plays a key role in the assembly of NR2B-CaMKII-PSD95 signal module and NR2B antagonists could alleviate LPS-related inflammation through the reduced assembly of NR2B-CaMKII-PSD95 signal module in frontal cortex and hippocampus.