Self-calibrating dual-sensing electrochemical sensors for accurate detection of carbon dioxide in blood.

A paper-based electrochemical dual-function biosensor capable of determining pH and TCO2 was synthesized for the first time using an iridium oxide pH electrode and an all-solid-state ion electrode (ASIE). In the study, to obtain highly reliable results, the biosensor was equipped with a real-time pH correction function before TCO2 measurements. Compared to traditional liquid-filling carbon dioxide detection sensors, the utilization of ferrocene endows our novel sensor with abundant positive sites, and thus greatly improves its performance. Conversely, the introduction of MXene with conductivity close to that of metals reduces electrode resistance, which is beneficial for accelerating the electrochemical reaction of the sensor and reducing LOD. After optimization, the detection range of TCO2 is 0.095 nM-0.66 M, with a detection limit of as low as 0.023 nM. In addition, the sensor was used in real serum sample-spiked recovery experiments and comparison experiments with existing clinical blood gas analyzers, which confirmed the effectiveness of its clinical application. This study provides a method for the rational design of paper-based electrochemical biosensors and a new approach for the clinical detection of blood carbon dioxide.

Noninvasive real-time detection of cerebral blood perfusion in hemorrhagic shock rabbits based on whole-brain magnetic induction phase shift: an experimental study.

OBJECTIVE: This study aimed to perform experiments to investigate the change trend in brain magnetic induction phase shift (MIPS) during hemorrhagic shock of different degrees of severity and to find the correlation between brain MIPS value and commonly used physiological indicators for detecting shock so as to explore a noninvasive method suitable for prehospital real-time detection of cerebral blood perfusion in hemorrhagic shock. APPROACH: The self-developed MIPS detection system was used to monitor the brain MIPS value in the whole process of hemorrhagic shock models of rabbits with different degrees of severity (control, mild, moderate, and severe) of shock in real time. Meanwhile, common physiological parameters, including arterial blood lactate (ABL), mean arterial pressure (MAP), heart rate (HR),core body temperature (CBT), regional cerebral blood flow (rCBF), and electroencephalogram (EEG), were also evaluated. MAIN RESULTS: The findings suggested that the brain MIPS value showed a downward trend in the shock process, and the decline degree of the MIPS value positively correlated with the severity of shock. Moreover, it showed a good detection and resolution ability in time/process and severity (P < 0.05). The MIPS values significantly correlated with ABL (P < 0.01), CBT (P < 0.01), and EEG (P < 0.05) at all four shock levels; with MAP (P < 0.05) and rCBF (P < 0.05) in the control, moderate, and severe groups; and with HR (P < 0.01) only in the severe group. SIGNIFICANCE: The results demonstrated that the brain MIPS value has the capability of detecting hemorrhagic shock. The MIPS technique is a noninvasive method suitable for prehospital real-time detection of cerebral blood perfusion in hemorrhagic shock.

[The research on cardiac volume-time relationship based on retrospective electrocardiograph four-dimension computer tomography data collection and structured sparse algorithm].

This paper explores the relationship between the cardiac volume and time, which is applied to control dynamic heart phantom. We selected 50 patients to collect their cardiac computed tomography angiography (CTA) images, which have 20 points in time series CTA images using retrospective electrocardiograph gating, and measure the volume of four chamber in 20-time points with cardiac function analysis software. Then we grouped patients by gender, age, weight, height, heartbeat, and utilize repeated measurement design to conduct statistical analyses. We proposed structured sparse learning to estimate the mathematic expression of cardiac volume variation. The research indicates that all patients' groups are statistically significant in time factor ( P = 0.000); there are interactive effects between time and gender groups in left ventricle ( F = 8.597, P = 0.006) while no interactive effects in other chambers with the remaining groups; and the different weight groups' volume is statistically significant in right ventricle ( F = 9.004, P = 0.005) while no statistical significance in other chambers with remaining groups. The accuracy of cardiac volume and time relationship utilizing structured sparse learning is close to the least square method, but the former's expression is more concise and more robust. The number of nonzero basic function of the structured sparse model is just 2.2 percent of that of least square model. Hence, the work provides more the accurate and concise expression of the cardiac for cardiac motion simulation.

[Experimental Detection Study on Cerebral Hemorrhage in Rabbits Based on Magnetic Induction Phase Shift Spectroscopy Under the Feature Band].

This study was aimed to improve the sensitivity of magnetic induction phase shift detection system for cerebral hemorrhage. In the study, a cerebral hemorrhage model with 13 rabbits was established by injection of autologous blood and the cerebral hemorrhage was detected by utilizing magnetic induction phase shift spectroscopy (MIPSS) detection method under the feature band. Sixty five groups of phase shift spectroscopy data were obtained. According to the characteristics of cerebral hemorrhage phase shift spectroscopy under the feature hand, an effective method, B-F distribution, to diagnose the severity of cerebral hemorrhage was designed. The results showed that using MIPSS detection method under feature band, the phase shift obviously growed with increase of injection volume of autologous blood, and the phase shift induced by a 3-mL injection reached -7.750 3 degrees ± 1.420 4 degrees. B-F distribution could effectively diagnose the severity of cerebral hemorrhage. It can be concluded that the sensitivity of the cerebral hemorrhage magnetic induction detection system is improved by one order of magnitude with the MIPSS detection method under the feature band.

[Constitution of a Real-time Monitoring System of Cerebral Hemorrhage with Magnetic Induction].

The real-time monitoring of cerebral hemorrhage can reduce its disability and fatality rates greatly. On the basis of magnetic induction phase shift, we in this study used filter and amplifier hardware module, NI-PXI data-acquisition system and LabVIEW software to set up an experiment system. We used Band-pass sample method and correlation phase demodulation algorithm in the system. In order to test and evaluate the performance of the system, we carried out saline simulation experiments of brain hemorrhage. We also carried out rabbit cerebral hemorrhage experiments. The results of both saline simulation and animal experiments suggested that our monitoring system had a high phase detection precision, and it needed only about 0.030 4s to finish a single phase shift measurement, and the change of phase shift was directly proportional to the volume of saline or blood. The experimental results were consistent with theory. As a result, this system has the ability of real-time monitoring the progression of cerebral hemorrhage precisely, with many distinguished features, such as low cost, high phase detection precision, high sensitivity of response so that it has showed a good application prospect.

Detection of cerebral hemorrhage in rabbits by time-difference magnetic inductive phase shift spectroscopy.

Cerebral hemorrhage, a difficult issue in clinical practice, is often detected and studied with computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). However, these expensive devices are not readily available in economically underdeveloped regions, and hence are unable to provide bedside and emergency on-site monitoring. The magnetic inductive phase shift (MIPS) is an emerging technology that may become a new tool to detect cerebral hemorrhage and to serve as an inexpensive partial substitute to medical imaging. In order to study a wider band of cerebral hemorrhage MIPS and to provide more useful information for measuring cerebral hemorrhage, we established a cerebral hemorrhage magnetic induction phase shift spectroscopy (MIPSS) detection system. Thirteen rabbits with five cerebral hemorrhage states were studied using a single coil-coil within a 1 MHz-200 MHz frequency range in linear sweep. A feature band (FB) with the highest detection sensitivity and the greatest stability was selected for further analysis and processing. In addition, a maximum conductivity cerebrospinal fluid (CSF) MRI was performed to verify and interpret the MIPSS result. The average phase shift change induced by a 3 ml injection of autologous blood under FB was -7.7503° ± 1.4204°, which was considerably larger than our previous work. Data analysis with a non-parametric statistical Friedman M test showed that in the FB, MIPSS could distinguish the five states of cerebral hemorrhage in rabbits, with a statistical significance of p<0.05. A B-F distribution profile was designed according to the MIPSS under FB that can provide instantaneous diagnostic information about the cerebral hemorrhage severity from a single set of measurements. The results illustrate that the MIPSS detection method is able to provide a new possibility for real-time monitoring and diagnosis of the severity of cerebral hemorrhage.

A special phase detector for magnetic inductive measurement of cerebral hemorrhage.

Cerebral hemorrhage is an important clinical problem that is often monitored and studied with expensive techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). These devices are not readily available in economically underdeveloped regions of the world and in emergency departments and emergency zones. The magnetic inductive method is an emerging technology that may become a new tool to detect cerebral hemorrhage. In this study, a special phase detector (PD) was developed and used for cerebral hemorrhage detection with the magnetic inductive method. The performance indicated that the PD can achieve phase noise as low as 6 m° and a 4-hour phase drift as low as 30 m° at 21.4 MHz. The noise and drift decreased as the frequency decreased. The performance at 10.7 MHz was slightly better than that of other recently developed phase detection systems. To test the practicality of the system, the PD was used to detect the volume change in a self-made physical model of the brain. The measured phase shift was approximately proportional to the volume change of physiological saline inside the model. The change of the phase shift increased as the volume change and frequency increased. The results are in agreement with those from previous reports. To verify the feasibility of in vivo detection, an autologous blood injection model was established in rabbit brain. The results from the injection group showed a similar trend of increasing phase shift change with increasing injection volume. The average phase shift change induced by a 3-ml injection of blood was 0.502°±0.119°, which was much larger than that of the control group. The measurement system can distinguish a minimal cerebral hemorrhage volume of approximately 0.5 ml. All of the results demonstrated that the PD used with this method can detect cerebral hemorrhage.