Highly Robust and Strain-Resilient Thin Film Conductors Featuring Brittle Materials.

Stretchable conductors with stable electrical conductivity under various deformations are essential for wearable electronics, soft robots, and biointegrated devices. However, brittle film-based conductors on elastomeric substrates often suffer from unexpected electrical disconnection due to the obvious mechanical incompatibility between stiff films and soft substrates. We proposed a novel out-of-plane crack control strategy to achieve the strain-insensitive electrical performance of thin-film-based conductors, featuring conductive brittle materials, including nanocrystalline metals (Cu, Ag, Mo) and transparent oxides (ITO). Our metal film-based conductors exhibit an ultrahigh initial conductivity (1.3 × 105 S cm-1) and negligible resistance change (R/R0 = 1.5) over wide strain range from 0 to 130%, enabled by film-induced substrate cracking and liquid metal-induced electrical self-repairing. They could function well under multimodal deformations (stretching, bending, and twisting) and severe mechanical damage (cutting and puncturing). We demonstrated the strain-resilient electrical functionality of metal film-based conductors in a flexible light-emitting diode display that shows high mechanical compliance.

Fast Iterative Shrinkage-Thresholding Algorithm with Continuation for Brain Injury Monitoring Imaging Based on Electrical Impedance Tomography.

Electrical impedance tomography (EIT) is low-cost and noninvasive and has the potential for real-time imaging and bedside monitoring of brain injury. However, brain injury monitoring by EIT imaging suffers from image noise (IN) and resolution problems, causing blurred reconstructions. To address these problems, a least absolute shrinkage and selection operator model is built, and a fast iterative shrinkage-thresholding algorithm with continuation (FISTA-C) is proposed. Results of numerical simulations and head phantom experiments indicate that FISTA-C reduces IN by 63.2%, 47.2%, and 29.9% and 54.4%, 44.7%, and 22.7%, respectively, when compared with the damped least-squares algorithm, the split Bergman, and the FISTA algorithms. When the signal-to-noise ratio of the measurements is 80-50 dB, FISTA-C can reduce IN by 83.3%, 72.3%, and 68.7% on average when compared with the three algorithms, respectively. Both simulation and phantom experiments suggest that FISTA-C produces the best image resolution and can identify the two closest targets. Moreover, FISTA-C is more practical for clinical application because it does not require excessive parameter adjustments. This technology can provide better reconstruction performance and significantly outperforms the traditional algorithms in terms of IN and resolution and is expected to offer a general algorithm for brain injury monitoring imaging via EIT.

Osteopontin in autoimmune disorders: current knowledge and future perspective.

Osteopontin (OPN) is a multifunctional cytokine and adhesion molecule, as well as an unusual regulator for both innate and adaptive immune responses. Several immune cells can produce OPN, including dendritic cells (DCs), macrophages, and T lymphocytes. OPN expression is reported to be increased in a wide range of disorders, including autoimmunity, cancer, and allergy. The overexpression of OPN in several autoimmune disorders, such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), multiple sclerosis (MS), Type 1 diabetes (T1D), inflammatory bowel disease (IBD), Sjögren's, and myasthenia gravis, have been shown to be correlated with disease severity. Regarding the important regulatory roles of OPN in the immune system, this study aimed to review the role of this molecule in autoimmune disorders and to provide a complete view of the current knowledge in this field.

LncRNA LINC00324 is upregulated in intervertebral disk degeneration and upregulates FasL in nucleus pulposus cells.

BACKGROUND: It has been reported that long intergenic non-protein-coding RNA 324 (LINC00324) promotes liver cancer by upregulating Fas ligand (FasL), which is a major player in intervertebral disk degeneration (IDD), indicating the involvement of LINC00324 in IDD. This study was carried out to investigate the interaction between LINC00324 and FasL in IDD. METHODS: Plasma samples were collected from both IDD (n = 60) and healthy controls (n = 60). The expression of LINC00324 and FasL in plasma was determined by RT-qPCR. The interactions between LINC00324 and FasL in nucleus pulposus (NP) cells were analyzed by overexpression experiments. RESULTS: LINC00324 and FasL were upregulated in IDD patients, and they were positively correlated. After treatment, the expression levels of FasL and LINC00324 were significantly decreased. In NP cells, overexpression of LINC00324 increased the expression of FasL at both mRNA and protein levels, while overexpression of FasL did not affect the expression of LINC00324. CONCLUSION: LINC00324 may upregulate FasL in IDD to promote disease progression.

Scientific Productivity in Rheumatoid Arthritis: A Global Survey of Research Activity.

OBJECTIVES: Assessment of scientific productivity provides a macroscopic view of research activity in a specific field. However, no analyses of rheumatoid arthritis (RA) have been published to date. Thus, this study aimed to investigate the characteristics of studies published on RA worldwide. METHODS: The Web of Science database was searched for articles on RA published between 2017 and 2019. Analysis parameters included the number of articles, number of times each publication was cited, country, journal, and research output adjusted by population and gross domestic product. RESULTS: Overall, 16,936 publications were identified. The United States was the largest contributor (17.71%), followed by China (17.17%), Japan (6.37%), the United Kingdom (5.82%), and Italy (4.76%). High-income economies (69.98%) ranked first in productivity, followed by middle- (30%) and low-income economies (0.02%). Significant correlations were found between research productivity and population (r = 0.461, p = 0.000), as well as gross domestic product (r = 0.786, p = 0.000). Publications from the United States received the highest number of total citations (21,669), followed by China (10,952) and the United Kingdom (7846). Austria had the highest average citations (16.18), followed by Norway (8.19) and the United Kingdom (7.98). When normalized by population, the leading country was Denmark, followed by the Netherlands and Sweden. When adjusted by gross domestic product, Denmark ranked first in publications on RA, followed by the Netherlands and Greece. CONCLUSION: The United States emerged as the largest contributor to the field of RA research. Countries with large populations and economies tended to have higher research productivity. Multiple countries in Europe performed better in research output when normalized by population and economy sizes.

[A multifrequency time-difference electrical impedance tomography algorithm using spectral constraints].

This study aims to propose a multifrequency time-difference algorithm using spectral constraints. Based on the knowledge of tissue spectrum in the imaging domain, the fraction model was used in conjunction with the finite element method (FEM) to approximate a conductivity distribution. Then a frequency independent parameter (volume or area fraction change) was reconstructed which made it possible to simultaneously employ multifrequency time-difference boundary voltage data and then reduce the degrees of freedom of the reconstruction problem. Furthermore, this will alleviate the illness of the EIT inverse problem and lead to a better reconstruction result. The numerical validation results suggested that the proposed time-difference fraction reconstruction algorithm behaved better than traditional damped least squares algorithm (DLS) especially in the noise suppression capability. Moreover, under the condition of low signal-to-noise ratio, the proposed algorithm had a more obvious advantage in reconstructions of targets shape and position. This algorithm provides an efficient way to simultaneously utilize multifrequency measurement data for time-difference EIT, and leads to a more accurate reconstruction result. It may show us a new direction for the development of time-difference EIT algorithms in the case that the tissue spectrums are known.

Lifetime super-resolution optical fluctuation imaging.

In this paper, we propose a promising super-resolution imaging scheme in fluorescence lifetime domain (lifetime super-resolution optical fluctuation imaging, ltSOFI). ltSOFI has the potential to obtain super-resolution images by taking advantage of fluorescence lifetime blinking under wide-field lifetime detection. The proof-of-concept for ltSOFI was demonstrated through numerical simulation of high-order cumulant analysis on fluorescence lifetime blinking emitters. As a tentative experimental demonstration, we obtained super-resolution lifetime imaging from time-lapse FLIM recording of HeLa cells expressing a cAMP sensor using ltSOFI method. ltSOFI is expected to initiate a new dimension in the lifetime domain for blinking-based super-resolution microscopy. LAY DESCRIPTION: We report on a promising super-resolution imaging scheme in fluorescence lifetime domain (lifetime super-resolution optical fluctuation imaging, ltSOFI). ltSOFI has the potential to obtain super-resolution images by taking advantage of fluorescence lifetime blinking under wide-field lifetime detection. Past advances in super-resolution fluorescence microscopy primarily rely on the spatiotemporal modulation of the fluorescence intensity. Although the applications of the Q-dot blinking have been discussed in the literature, most of the discussions have focused on the blinking of fluorescence intensity. Few studies have shown the possibility of super-resolution imaging through fluorescence lifetime fluctuations. In this paper, we proposed the ltSOFI scheme that explored the possibility of super-resolution reconstruction from the blinking of fluorescence lifetime. The proof-of-concept for ltSOFI was demonstrated through numerical simulation of high-order cumulant analysis on fluorescence lifetime blinking emitters. As a tentative experimental demonstration, we obtained super-resolution lifetime imaging from time-lapse FLIM recording of HeLa cells expressing a cAMP sensor using ltSOFI method. The ltSOFI method is expected to initiate a new dimension in the lifetime domain for blinking-based super-resolution microscopy. Moreover, the existing fluorescence lifetime imaging microscopy and super-resolution nanoscopy can benefit from the implementation of ltSOFI to significantly improve the imaging spatial resolution of fluorescence lifetime images. In addition, the proof-of-concept demonstration achieved by the numerical simulation and tentative experiment will provide a new perspective for obtaining fluorescence lifetime images with much finer details.

A novel time-difference electrical impedance tomography algorithm using multi-frequency information.

BACKGROUND: Electrical impedance tomography (EIT) is a noninvasive, radiation-free, and low-cost imaging modality for monitoring the conductivity distribution inside a patient. Nowadays, time-difference EIT (tdEIT) is used extensively as it has fast imaging speed and can reflect the dynamic changes of diseases, which make it attractive for a number of medical applications. Moreover, modeling errors are compensated to some extent by subtraction of voltage measurements collected before and after the change. However, tissue conductivity varies with frequency and tdEIT does not efficiently exploit multi-frequency information as it only uses measurements associated with a single frequency. METHODS: This paper proposes a tdEIT algorithm that imposes spectral constraints on the framework of the linear least squares problem. Simulation and phantom experiments are conducted to compare the proposed spectral constraints algorithm (SC) with the damped least squares algorithm (DLS), which is a stable tdEIT algorithm used in clinical practice. The condition number and rank of the matrices needing inverses are analyzed, and image quality is evaluated using four indexes. The possibility of multi-tissue imaging and the influence of spectral errors are also explored. RESULTS: Significant performance improvement is achieved by combining multi-frequency and time-difference information. The simulation results show that, in one-step iteration, both algorithms have the same condition number and rank, but SC effectively reduces image noise by 20.25% compared to DLS. In addition, deformation error and position error are reduced by 8.37% and 7.86%, respectively. In two-step iteration, the rank of SC is greatly increased, which suggests that more information is employed in image reconstruction. Image noise is further reduced by an average of 32.58%, and deformation error and position error are also reduced by 20.20% and 31.36%, respectively. The phantom results also indicate that SC has stronger noise suppression and target identification abilities, and this advantage is more obvious with iteration. The results of multi-tissue imaging show that SC has the unique advantage of automatically extracting a single tissue to image. CONCLUSIONS: SC enables tdEIT to utilize multi-frequency information in cases where the spectral constraints are known and then provides higher quality images for applications.

An on-line processing strategy for head movement interferences removal of dynamic brain electrical impedance tomography based on wavelet decomposition.

BACKGROUND: Head movement interferences are a common problem during prolonged dynamic brain electrical impedance tomography (EIT) clinical monitoring. Head movement interferences mainly originate from body movements of patients and nursing procedures performed by medical staff, etc. These body movements will lead to variation in boundary voltage signals, which affects image reconstruction. METHODS: This study employed a data preprocessing method based on wavelet decomposition to inhibit head movement interferences in brain EIT data. Mixed Gaussian models were applied to describe the distribution characteristics of brain EIT data. We identified head movement signal through the differences in distribution characteristics of corresponding wavelet decomposition coefficients between head movement artifacts and normal signals, and then managed the contaminated data with improved on-line wavelet processing methods. RESULTS: To validate the efficacy of the method, simulated signal experiments and human data experiments were performed. In the simulation experiment, the simulated movement artifact was significantly reduced and data quality was improved with indicators' increase in PRD and correlation coefficient. Human data experiments demonstrated that this method effectively suppressed head movement in signals and reduce artifacts resulting from head movement artifacts in images. CONCLUSION: In this paper, we proposed an on-line strategy to manage the head movement interferences from the brain EIT data based on the distribution characteristics of wavelet coefficients. Our strategy is capable of reducing the movement interference in the data and improving the reconstructed images. This work would improve the clinical practicability of brain EIT and contribute to its further promotion.

Theoretical and experimental investigation of broadband dispersion tailoring of high-order mode in the hybrid microsphere cavity.

The large normal dispersion of the fundamental mode (TEn=1 mode) in the whispering gallery modes (WGM) microsphere is detrimental to the visible comb generation. Herein, we demonstrate that this fundamental limitation can be removed by considering the high-order radial modes (TEn=2 mode) of the hybrid microsphere cavity (HMC). The studied HMC consists of a high-refractive-index coating (TiO2 or HfO2) and silica microsphere. The simulated electric field energy distribution and measured Q value in our experiment show that optical confinement of the coating effectively excites the TEn=2 mode and reduces the free spectral range (FSR) and modal dispersion. In addition, the observed redshift of WGM and decreased trend of FSR are in accordance with simulations. The zero-dispersion wavelength can be linearly shifted to a shorter wavelength or even into the visible region with the reduction of coating thickness or refractive index and larger microcavity, which advances the visible comb generation.

Numerical study of a DoFP polarimeter based on the self-organized nanograting array.

The self-organized nanograting manufactured by irradiating the transparent materials with the femtosecond laser has aroused wide interests in photonic applications in recent years. Although the mechanism of nanograting formatting has not yet been fully understood, the essential property of the optical birefringence can be precisely acquired by controlling the energy fluence of the femtosecond laser. In this paper, we proposed a novel application of the self-organized nanograting in a division-of-focal-plane polarimeter. Based on the rigid-coupled-wave algorithm, the optical characteristics of the nanograting and the polarimeter were comprehensively analyzed and discussed.

Fast detection and data compensation for electrodes disconnection in long-term monitoring of dynamic brain electrical impedance tomography.

BACKGROUND: Electrode disconnection is a common occurrence during long-term monitoring of brain electrical impedance tomography (EIT) in clinical settings. The data acquisition system suffers remarkable data loss which results in image reconstruction failure. The aim of this study was to: (1) detect disconnected electrodes and (2) account for invalid data. METHODS: Weighted correlation coefficient for each electrode was calculated based on the measurement differences between well-connected and disconnected electrodes. Disconnected electrodes were identified by filtering out abnormal coefficients with discrete wavelet transforms. Further, previously valid measurements were utilized to establish grey model. The invalid frames after electrode disconnection were substituted with the data estimated by grey model. The proposed approach was evaluated on resistor phantom and with eight patients in clinical settings. RESULTS: The proposed method was able to detect 1 or 2 disconnected electrodes with an accuracy of 100%; to detect 3 and 4 disconnected electrodes with accuracy of 92 and 84% respectively. The time cost of electrode detection was within 0.018 s. Further, the proposed method was capable to compensate at least 60 subsequent frames of data and restore the normal image reconstruction within 0.4 s and with a mean relative error smaller than 0.01%. CONCLUSIONS: In this paper, we proposed a two-step approach to detect multiple disconnected electrodes and to compensate the invalid frames of data after disconnection. Our method is capable of detecting more disconnected electrodes with higher accuracy compared to methods proposed in previous studies. Further, our method provides estimations during the faulty measurement period until the medical staff reconnects the electrodes. This work would improve the clinical practicability of dynamic brain EIT and contribute to its further promotion.

2 µm laser oscillation of Ho3+:Tm3+-codoped silica microspheres.

2 µm laser oscillation with a low threshold has been achieved in Ho3+:Tm3+-codoped silica microspheres (HTCSMs). Ho3+:Tm3+-codoped solgel functionalization film is applied to the surface of a silica microsphere, and an optical tapered fiber is adopted to couple an 808 nm continuous-wave laser to serve as the pump light source. Multimode and single-mode laser oscillations around 2 µm within the eye-safe wave band are observed due to the I75→I85 transitions of Ho3+ ions sensitized by Tm3+. The morphology characteristics of microspheres determine the multimode laser oscillation spectrum. The free spectral range is in good accordance with the calculated value based on Mie scattering theory. The HTCSM laser oscillation shows characteristics of good capability, simple process, high flexibility, and low cost.

Ex-Vivo Characterization of Bioimpedance Spectroscopy of Normal, Ischemic and Hemorrhagic Rabbit Brain Tissue at Frequencies from 10 Hz to 1 MHz.

Stroke is a severe cerebrovascular disease and is the second greatest cause of death worldwide. Because diagnostic tools (CT and MRI) to detect acute stroke cannot be used until the patient reaches the hospital setting, a portable diagnostic tool is urgently needed. Because biological tissues have different impedance spectra under normal physiological conditions and different pathological states, multi-frequency electrical impedance tomography (MFEIT) can potentially detect stroke. Accurate impedance spectra of normal brain tissue (gray and white matter) and stroke lesions (ischemic and hemorrhagic tissue) are important elements when studying stroke detection with MFEIT. To our knowledge, no study has comprehensively measured the impedance spectra of normal brain tissue and stroke lesions for the whole frequency range of 1 MHz within as short as possible an ex vivo time and using the same animal model. In this study, we established intracerebral hemorrhage and ischemic models in rabbits, then measured and analyzed the impedance spectra of normal brain tissue and stroke lesions ex vivo within 15 min after animal death at 10 Hz to 1 MHz. The results showed that the impedance spectra of stroke lesions significantly differed from those of normal brain tissue; the ratio of change in impedance of ischemic and hemorrhagic tissue with regard to frequency was distinct; and tissue type could be discriminated according to its impedance spectra. These findings further confirm the feasibility of detecting stroke with MFEIT and provide data supporting further study of MFEIT to detect stroke.

Exploratory study on the methodology of fast imaging of unilateral stroke lesions by electrical impedance asymmetry in human heads.

Stroke has a high mortality and disability rate and should be rapidly diagnosed to improve prognosis. Diagnosing stroke is not a problem for hospitals with CT, MRI, and other imaging devices but is difficult for community hospitals without these devices. Based on the mechanism that the electrical impedance of the two hemispheres of a normal human head is basically symmetrical and a stroke can alter this symmetry, a fast electrical impedance imaging method called symmetrical electrical impedance tomography (SEIT) is proposed. In this technique, electrical impedance tomography (EIT) data measured from the undamaged craniocerebral hemisphere (CCH) is regarded as reference data for the remaining EIT data measured from the other CCH for difference imaging to identify the differences in resistivity distribution between the two CCHs. The results of SEIT imaging based on simulation data from the 2D human head finite element model and that from the physical phantom of human head verified this method in detection of unilateral stroke.

Multi-Path Fusion in SFCF-Net for Enhanced Multi-Frequency Electrical Impedance Tomography.

Multi-frequency electrical impedance tomography (mfEIT) offers a nondestructive imaging technology that reconstructs the distribution of electrical characteristics within a subject based on the impedance spectral differences among biological tissues. However, the technology faces challenges in imaging multi-class lesion targets when the conductivity of background tissues is frequency-dependent. To address these issues, we propose a spatial-frequency cross-fusion network (SFCF-Net) imaging algorithm, built on a multi-path fusion structure. This algorithm uses multi-path structures and hyper-dense connections to capture both spatial and frequency correlations between multi-frequency conductivity images, which achieves differential imaging for lesion targets of multiple categories through cross-fusion of information. According to both simulation and physical experiment results, the proposed SFCF-Net algorithm shows an excellent performance in terms of lesion imaging and category discrimination compared to the weighted frequency-difference, U-Net, and MMV-Net algorithms. The proposed algorithm enhances the ability of mfEIT to simultaneously obtain both structural and spectral information from the tissue being examined and improves the accuracy and reliability of mfEIT, opening new avenues for its application in clinical diagnostics and treatment monitoring.

A preliminary study on the application of electrical impedance tomography based on cerebral perfusion monitoring to intracranial pressure changes.

Background: In intracranial pathologic conditions of intracranial pressure (ICP) disturbance or hemodynamic instability, maintaining appropriate ICP may reduce the risk of ischemic brain injury. The change of ICP is often accompanied by the change of intracranial blood status. As a non-invasive functional imaging technique, the sensitivity of electrical impedance tomography (EIT) to cerebral hemodynamic changes has been preliminarily confirmed. However, no team has conducted a feasibility study on the dynamic detection of ICP by EIT technology from the perspective of non-invasive whole-brain blood perfusion monitoring. In this study, human brain EIT image sequence was obtained by in vivo measurement, from which a variety of indicators that can reflect the tidal changes of the whole brain impedance were extracted, in order to establish a new method for non-invasive monitoring of ICP changes from the level of cerebral blood perfusion monitoring. Methods: Valsalva maneuver (VM) was used to temporarily change the cerebral blood perfusion status of volunteers. The electrical impedance information of the brain during this process was continuously monitored by EIT device and real-time imaging was performed, and the hemodynamic indexes of bilateral middle cerebral arteries were monitored by transcranial Doppler (TCD). The changes in monitoring information obtained by the two techniques were compared and observed. Results: The EIT imaging results indicated that the image sequence showed obvious tidal changes with the heart beating. Perfusion indicators of vascular pulsation obtained from EIT images decreased significantly during the stabilization phase of the intervention (PAC: 242.94 ± 100.83, p < 0.01); perfusion index which reflects vascular resistance increased significantly in the stable stage of intervention (PDT: 79.72 ± 18.23, p < 0.001). After the intervention, the parameters gradually returned to the baseline level before compression. The changes of EIT indexes in the whole process are consistent with the changes of middle cerebral artery velocity related indexes shown in TCD results. Conclusion: The EIT image combined with the blood perfusion index proposed in this paper can reflect the decrease of cerebral blood flow under the condition of increased ICP in real time and intuitively. With the advantages of high time resolution and high sensitivity, EIT provides a new idea for non-invasive bedside measurement of ICP.

Semi-Supervised Thyroid Nodule Detection in Ultrasound Videos.

Deep learning techniques have been investigated for the computer-aided diagnosis of thyroid nodules in ultrasound images. However, most existing thyroid nodule detection methods were simply based on static ultrasound images, which cannot well explore spatial and temporal information following the clinical examination process. In this paper, we propose a novel video-based semi-supervised framework for ultrasound thyroid nodule detection. Especially, considering clinical examinations that need to detect thyroid nodules at the ultrasonic probe positions, we first construct an adjacent frame guided detection backbone network by using adjacent supporting reference frames. To further reduce the labour-intensive thyroid nodule annotation in ultrasound videos, we extend the video-based detection in a semi-supervised manner by using both labeled and unlabeled videos. Based on the detection consistency in sequential neighbouring frames, a pseudo label adaptation strategy is proposed for the refinement of unpredicted frames. The proposed framework is validated on 996 transverse viewed and 1088 longitudinal viewed ultrasound videos. Experimental results demonstrated the superior performance of our proposed method in the ultrasound video-based detection of thyroid nodules.

Electrical impedance tomography provides information of brain injury during total aortic arch replacement through its correlation with relative difference of neurological biomarkers.

Postoperative neurological dysfunction (PND) is one of the most common complications after a total aortic arch replacement (TAAR). Electrical impedance tomography (EIT) monitoring of cerebral hypoxia injury during TAAR is a promising technique for preventing the occurrence of PND. This study aimed to explore the feasibility of electrical impedance tomography (EIT) for warning of potential brain injury during total aortic arch replacement (TAAR) through building the correlation between EIT extracted parameters and variation of neurological biomarkers in serum. Patients with Stanford type A aortic dissection and requiring TAAR who were admitted between December 2021 to March 2022 were included. A 16-electrode EIT system was adopted to monitor each patient's cerebral impedance intraoperatively. Five parameters of EIT signals regarding to the hypothermic circulatory arrest (HCA) period were extracted. Meanwhile, concentration of four neurological biomarkers in serum were measured regarding to time before and right after surgery, 12 h, 24 h and 48 h after surgery. The correlation between EIT parameters and variation of serum biomarkers were analyzed. A total of 57 TAAR patients were recruited. The correlation between EIT parameters and variation of biomarkers were stronger for patients with postoperative neurological dysfunction (PND(+)) than those without postoperative neurological dysfunction (PND(-)) in general. Particularly, variation of S100B after surgery had significantly moderate correlation with two parameters regarding to the difference of impedance between left and right brain which were MRAIabs and TRAIabs (0.500 and 0.485 with p < 0.05, respectively). In addition, significantly strong correlations were seen between variation of S100B at 24 h and the difference of average resistivity value before and after HCA phase (ΔARVHCA), the slope of electrical impedance during HCA (kHCA) and MRAIabs (0.758, 0.758 and 0.743 with p < 0.05, respectively) for patients with abnormal S100B level before surgery. Strong correlations were seen between variation of TAU after surgery and ΔARVHCA, kHCA and the time integral of electrical impedance for half flow of perfusion (TARVHP) (0.770, 0.794 and 0.818 with p < 0.01, respectively) for patients with abnormal TAU level before surgery. Another two significantly moderate correlations were found between TRAIabs and variation of GFAP at 12 h and 24 h (0.521 and 0.521 with p < 0.05, respectively) for patients with a normal GFAP serum level before surgery. The correlations between EIT parameters and serum level of neurological biomarkers were significant in patients with PND, especially for MRAIabs and TRAIabs, indicating that EIT may become a powerful assistant for providing a real-time warning of brain injury during TAAR from physiological perspective and useful guidance for intensive care units.

Magnetic nanometer combined with microwave: Novel rapid thawing promotes phenolics release in frozen-storage lychee.

Magnetic nanometer combined with microwave thawing (MN-MT) could become a novel solution to challenges uneven and overheating of microwave thawing (MT), while retaining high thawing efficiency, compared to conventional water immersion thawing (WT). In this study, MN-MT was applied to thaw fruit (lychee as an example) for the first time, and was evaluated by comparison with WT, MT and water immersion combined with microwave thawing (WI-MT). Results showed that MN-MT could significantly shorten the thawing time of frozen lychee by 80.67%, 25.86% and 18.83% compared to WT, MT and WI-MT, respectively. Compared to WT, MN-MT was the only thawing treatment which significantly enhanced the release of quercetin-3-O-rutinose-7-O-α-l-rhamnoside, according to HPLC-DAD. Meanwhile, thermal-sensitive procyanidin B2, phenylpropionic acid and protocatechuic acid were found to be protected from degradations only by MN-MT based on UPLC-ESI-QTOF-MS/MS results. In summary, MN-MT is a potential novel treatment for rapid thawing and quality maintenance of frozen fruits.