Blood pressure lowering enhances cerebrospinal fluid efflux to the systemic circulation primarily via the lymphatic vasculature.

BACKGROUND: Inside the incompressible cranium, the volume of cerebrospinal fluid is directly linked to blood volume: a change in either will induce a compensatory change in the other. Vasodilatory lowering of blood pressure has been shown to result in an increase of intracranial pressure, which, in normal circumstances should return to equilibrium by increased fluid efflux. In this study, we investigated the effect of blood pressure lowering on fluorescent cerebrospinal fluid tracer absorption into the systemic blood circulation. METHODS: Blood pressure lowering was performed by an i.v. administration of nitric oxide donor (sodium nitroprusside, 5 µg kg-1 min-1) or the Ca2+-channel blocker (nicardipine hydrochloride, 0.5 µg kg-1 min-1) for 10, and 15 to 40 min, respectively. The effect of blood pressure lowering on cerebrospinal fluid clearance was investigated by measuring the efflux of fluorescent tracers (40 kDa FITC-dextran, 45 kDa Texas Red-conjugated ovalbumin) into blood and deep cervical lymph nodes. The effect of nicardipine on cerebral hemodynamics was investigated by near-infrared spectroscopy. The distribution of cerebrospinal fluid tracers (40 kDa horse radish peroxidase,160 kDa nanogold-conjugated IgG) in exit pathways was also analyzed at an ultrastructural level using electron microscopy. RESULTS: Nicardipine and sodium nitroprusside reduced blood pressure by 32.0 ± 19.6% and 24.0 ± 13.3%, while temporarily elevating intracranial pressure by 14.0 ± 7.0% and 18.2 ± 15.0%, respectively. Blood pressure lowering significantly increased tracer accumulation into dorsal dura, deep cervical lymph nodes and systemic circulation, but reduced perivascular inflow along penetrating arteries in the brain. The enhanced tracer efflux by blood pressure lowering into the systemic circulation was markedly reduced (- 66.7%) by ligation of lymphatic vessels draining into deep cervical lymph nodes. CONCLUSIONS: This is the first study showing that cerebrospinal fluid clearance can be improved with acute hypotensive treatment and that the effect of the treatment is reduced by ligation of a lymphatic drainage pathway. Enhanced cerebrospinal fluid clearance by blood pressure lowering may have therapeutic potential in diseases with dysregulated cerebrospinal fluid  flow.

Altered cerebrovascular-CSF coupling in Alzheimer's Disease measured by functional near-infrared spectroscopy.

In-vivo microscopical studies indicate that brain cerebrospinal fluid (CSF) transport driven by blood vessel pulsations is reduced in the early stages of Alzheimer's disease (AD). We hypothesized that the coupling pattern between cerebrovascular pulsations and CSF is altered in AD, and this can be measured using multi-wavelength functional near-infrared spectroscopy (fNIRS). To study this, we quantified simultaneously cerebral hemo- and CSF hydrodynamics in early AD patients and age-matched healthy controls. Physiological pulsations were analysed in the vasomotor very low frequency (VLF 0.008-0.1 Hz), respiratory (Resp. 0.1-0.6 Hz), and cardiac (Card. 0.6-5 Hz) bands. A sliding time window cross-correlation approach was used to estimate the temporal stability of the cerebrovascular-CSF coupling. We investigated how the lag time series variation of the coupling differs between AD patients and control. The couplings involving deoxyhemoglobin (HbR) and CSF water, along with their first derivative, in the cardiac band demonstrated significant difference between AD patients and controls. Furthermore, the lag time series variation of HbR-CSF in the cardiac band provided a significant relationship, p-value = 0.04 and r2 = 0.16, with the mini-mental state exam (MMSE) score. In conclusion, the coupling pattern between hemodynamics and CSF is reduced in AD and it correlates with MMSE score.

Cerebral tissue oxygenation response to brain irradiation measured during clinical radiotherapy.

Significance: Cancer therapy treatments produce extensive changes in the physiological and morphological properties of tissues, which are also individual dependent. Currently, a key challenge involves developing more tailored cancer therapy, and consequently, individual biological response measurement during therapy, such as tumor hypoxia, is of high interest. This is the first time human cerebral haemodynamics and cerebral tissue oxygenation index (TOI) changes were measured during the irradiation in clinical radiotherapy and functional near-infrared spectroscopy (fNIRS) technique was demonstrated as a feasible technique for clinical use in radiotherapy, based on 34 online patient measurements. Aim: Our aim is to develop predictive biomarkers and noninvasive real-time methods to establish the effect of radiotherapy during treatment as well as to optimize radiotherapy dose planning for individual patients. In particular, fNIRS-based technique could offer an effective and clinically feasible online technique for continuous monitoring of brain tissue hypoxia and responses to chemo- and radiotherapy, which involves modulating tumor oxygenation to increase or decrease tumor hypoxia. We aim to show that fNIRS is feasible for repeatability measuring in patient radiotherapy, the temporal alterations of tissue oxygenation induced by radiation. Approach: Fiber optics setup using multiwavelength fNIRS was built and combined with a medical linear accelerator to measure cerebral tissue oxygenation changes during the whole-brain radiotherapy treatment, where the radiation dose is given in whole brain area only preventing dosage to eyes. Correlation of temporal alterations in cerebral haemodynamics and TOI response to brain irradiation was quantified. Results: Online fNIRS patient measurement of cerebral haemodynamics during clinical brain radiotherapy is feasible in clinical environment, and results based on 34 patient measurements show strong temporal alterations in cerebral haemodynamics and decrease in TOI during brain irradiation and confirmed the repeatability. Our proof-of-concept study shows evidently that irradiation causes characteristic immediate changes in brain tissue oxygenation. Conclusions: In particular, TOI seems to be a sensitive parameter to observe the tissue effects of radiotherapy. Monitoring the real-time interactions between the subjected radiation dose and corresponding haemodynamic effects may provide important tool for the researchers and clinicians in the field of radiotherapy. Eventually, presented fNIRS technique could be used for improving dose planning and safety control for individual patients.

Blood pressure wave propagation-a multisensor setup for cerebral autoregulation studies.

Objective.Cerebral autoregulation is critically important to maintain proper brain perfusion and supply the brain with oxygenated blood. Non-invasive measures of blood pressure (BP) are critical in assessing cerebral autoregulation. Wave propagation velocity may be a useful technique to estimate BP but the effect of the location of the sensors on the readings has not been thoroughly examined. In this paper, we were interested in studying whether the propagation velocity of a pressure wave in the direction from the heart to the brain may differ compared with propagation from the heart to the periphery, as well as across different physiological tasks and/or health conditions. Using non-invasive sensors simultaneously placed at different locations of the human body allows for the study of how the propagation velocity of the pressure wave, based on pulse transit time (PTT), varies across different directions.Approach.We present a multi-sensor BP wave propagation measurement setup intended for cerebral autoregulation studies. The presented sensor setup consists of three sensors, one placed on each of the neck, chest and finger, allowing simultaneous measurement of changes in BP propagation velocity towards the brain and to the periphery. We show how commonly tested physiological tasks affect the relative changes of PTT and correlations with BP.Main results.We observed that during maximal blow, valsalva and breath hold breathing tasks, the relative changes of PTT were higher when PTT was measured in the direction from the heart to the brain than from the heart to the peripherals. In contrast, during a deep breathing task, the relative change in PTT from the heart to the brain was lower. In addition, we present a short literature review of the PTT methods used in brain research.Significance.These preliminary data suggest that the physiological task and direction of PTT measurement may affect relative PTT changes. The presented three-sensor setup provides an easy and neuroimaging compatible method for cerebral autoregulation studies by allowing measurement of BP wave propagation velocity towards the brain versus towards the periphery.

A Video-Based DT-SVM School Violence Detecting Algorithm.

School bullying is a serious problem among teenagers. School violence is one type of school bullying and considered to be the most harmful. As AI (Artificial Intelligence) techniques develop, there are now new methods to detect school violence. This paper proposes a video-based school violence detecting algorithm. This algorithm first detects foreground moving targets via the KNN (K-Nearest Neighbor) method and then preprocesses the detected targets via morphological processing methods. Then, this paper proposes a circumscribed rectangular frame integrating method to optimize the circumscribed rectangular frame of moving targets. Rectangular frame features and optical-flow features were extracted to describe the differences between school violence and daily-life activities. We used the Relief-F and Wrapper algorithms to reduce the feature dimension. SVM (Support Vector Machine) was applied as the classifier, and 5-fold cross validation was performed. The accuracy was 89.6%, and the precision was 94.4%. To further improve the recognition performance, we developed a DT-SVM (Decision Tree-SVM) two-layer classifier. We used boxplots to determine some features of the DT layer that are able to distinguish between typical physical violence and daily-life activities and between typical daily-life activities and physical violence. For the remainder of activities, the SVM layer performed a classification. For this DT-SVM classifier, the accuracy reached 97.6%, and the precision reached 97.2%, thus showing a significant improvement.

Photoplethysmography signal analysis to assess obesity, age group and hypertension.

Photoplethysmography (PPG) provides a simple, convenient and noninvasive method to assess pulse oximetry. Several attempts have been made to use PPG also to estimate blood pressure and arterial stiffness. This paper attempts to assess obesity classes, age group, and hypertension classes using PPG measured from the finger. One set of features was derived from the normalized pulse width of PPG and the other from original PPG. The features were calculated based on the pulse decomposition analysis using five lognormal functions and the up-slope of the PPG pulse. Using kNN and SVM as classifiers, the results were validated using leave-one-out validation. Performances of both features sets have no significant difference, and the kNN outperformed the SVM. The best accuracies are 93%, 88%, and 92% for obesity (5 classes), age group (7 classes), and hypertension (4 classes) respectively. These three assessment targets have a strong relationship with arterial stiffness, therefore it also leads to a study about arterial stiffness using PPG. Width normalization to 1 second might affect some features points based on pulse decomposition analysis. This study also found that the up-slope analysis might give good indices when width normalization was employed. However, these findings still require more experiments to gain conclusions that are more comprehensive.

Bivariate empirical mode decomposition for ECG-based biometric identification with emotional data.

Emotions modulate ECG signals such that they might affect ECG-based biometric identification in real life application. It motivated in finding good feature extraction methods where the emotional state of the subjects has minimum impacts. This paper evaluates feature extraction based on bivariate empirical mode decomposition (BEMD) for biometric identification when emotion is considered. Using the ECG signal from the Mahnob-HCI database for affect recognition, the features were statistical distributions of dominant frequency after applying BEMD analysis to ECG signals. The achieved accuracy was 99.5% with high consistency using kNN classifier in 10-fold cross validation to identify 26 subjects when the emotional states of the subjects were ignored. When the emotional states of the subject were considered, the proposed method also delivered high accuracy, around 99.4%. We concluded that the proposed method offers emotion-independent features for ECG-based biometric identification. The proposed method needs more evaluation related to testing with other classifier and variation in ECG signals, e.g. normal ECG vs. ECG with arrhythmias, ECG from various ages, and ECG from other affective databases.