The radiomics features of the temporal lobe region related to menopause based on MR-T2WI can be used as potential biomarkers for AD.

Menopause may be an important pathogenic factor for Alzheimer's disease (AD). The M1 polarization of microglia and neuroinflammatory responses occur in the early pathogenetic stages of AD. Currently, no effective monitoring markers are available for AD's early pathological manifestations. Radiomics is an automated feature generation method for the extraction of hundreds of quantitative phenotypes (radiomics features) from radiology images. In this study, we retrospectively analyzed the magnetic resonance T2-weighted imaging (MR-T2WI) on the temporal lobe region and clinical data of both premenopausal and postmenopausal women. There were three significant differences were identified for select radiomic features in the temporal lobe between premenopausal and postmenopausal women, i.e. the texture feature Original-glcm-Idn (OI) based on the Original image, the filter-based first-order feature Log-firstorder-Mean (LM), and the texture feature Wavelet-LHH-glrlm-Run Length Nonuniformity (WLR). In humans, these three features were significantly correlated with the timing of menopause. In mice, these features were also different between the sham and ovariectomy (OVX) groups and were significantly associated with neuronal damage, microglial M1 polarization, neuroinflammation, and cognitive decline in the OVX groups. In AD patients, OI was significantly associated with cognitive decline, while LM was associated with anxiety and depression. OI and WLR could distinguish AD from healthy controls. In conclusion, radiomics features based on brain MR-T2WI scans have the potential to serve as biomarkers for AD and noninvasive monitoring of pathological progression in the temporal lobe of the brain in women undergoing menopause.

MRI study on the influence of lumbosacral vertebral body and disc factors on lumbar lordosis in children.

PURPOSE: To evaluate the influence of vertebral and disc wedging on the contribution of lumbar lordosis and the change of disc thickness before and after walking based on MRI. METHODS: Cross-sectional study. A total of 96 normally developing children, aged 5.7 ± 3.0 years old, 55 boys and 41 girls. They were divided into 3 groups: Pre-walking group, Walking group, and Post-walking group. PARAMETERS: lumbar lordosis Angle (LLA), the sum of the lumbar disc wedge Angle (∑D), the sum of the lumbar vertebral body wedge Angle (∑B), disc height (DH). RESULTS: (1) LLA, ∑D, ∑B, and DHL1-S1 were 33.2 ± 8.7°, 14.1 ± 8.6°, 11.9 ± 8.6°, and 6.9 ± 1.2 mm, 7.6 ± 1.4 mm, 8.2 ± 1.6 mm, 8.9 ± 1.7 mm, 8.5 ± 1.8 mm. (2) The difference in LLA values between the Pre-walking and the Post-walking group was statistically significant. DH were significantly different among the three groups. (3) In the Post-walking group, LLA value of girls was significantly higher than that of boys, and DHL3 - 4 and DHL4 - 5 values of girls were significantly lower than that of boys. (4) Age had a low positive correlation with LLA and ∑D and a moderate to strong positive correlation with DH; LLA showed a moderate positive correlation with ∑D, and a low positive correlation with ∑B and DH. CONCLUSION: Age and walking activity are the influencing factors of lumbar lordosis and disc thickening. Walking activity can significantly increase lumbar lordosis, and age is the main factor promoting lumbar disc thickening. DHL4-5 was the thickest lumbar intervertebral disc with the fastest intergroup thickening. Disc wedging contributes more to lumbar lordosis than vertebral wedging.

Unobtrusive Sensors for Synchronous Monitoring of Different Breathing Parameters in Care Environments.

Respiratory problems are common amongst older people. The rapid increase in the ageing population has led to a need for developing technologies that can monitor such conditions unobtrusively. This paper presents a novel study that investigates Wi-Fi and ultra-wideband (UWB) antenna sensors to simultaneously monitor two different breathing parameters: respiratory rate, and exhaled breath. Experiments were carried out with two subjects undergoing three breathing cases in breaths per minute (BPM): (1) slow breathing (12 BPM), (2) moderate breathing (20 BPM), and (3) fast breathing (28 BPM). Respiratory rates were captured by Wi-Fi sensors, and the data were processed to extract the respiration rates and compared with a metronome that controlled the subjects' breathing. On the other hand, exhaled breath data were captured by a UWB antenna using a vector network analyser (VNA). Corresponding reflection coefficient data (S11) were obtained from the subjects at the time of exhalation and compared with S11 in free space. The exhaled breath data from the UWB antenna were compared with relative humidity, which was measured with a digital psychrometer during the breathing exercises to determine whether a correlation existed between the exhaled breath's water vapour content and recorded S11 data. Finally, captured respiratory rate and exhaled breath data from the antenna sensors were compared to determine whether a correlation existed between the two parameters. The results showed that the antenna sensors were capable of capturing both parameters simultaneously. However, it was found that the two parameters were uncorrelated and independent of one another.

Analysis of Wi-SUN FAN Network Formation Time.

The Wi-SUN FAN (Wireless Smart Ubiquitous Network Field Area Network) standard is attracting great interest in various applications such as smart meters, smart cities and Internet of Things (IoT) devices due to the attractive features that the standard offers, such as multihop and mesh topologies, a relatively high data rate, frequency hopping, and interoperability between manufacturers. However, the process of connecting nodes in Wi-SUN FAN networks, which includes discovering, joining, and forming the network, has been shown to be slow, especially in multihop environments, which has motivated research and experimentation to analyze this process. In the existing literature, to measure network formation time, some authors have performed experiments with up to 100 devices, which is a costly and time-consuming methodology. Others have used simulation tools that are difficult to replicate, because little information is available about the methodology used or because they are proprietary. Despite these efforts, there is still a lack of information to adequately assess the formation time of Wi-SUN FAN networks, since the experimental tests reported in the literature are expensive and time-consuming. Therefore, alternatives such as computer simulation have been explored to speed up performance analysis in different scenarios. With this perspective, this paper is focused on the implementation of the Wi-SUN FAN network formation process using the Contiki-NG open source operating system and the Cooja simultor, where a functionality was added that makes it possible to efficiently analyze the network performance, thereby facilitating the implementation of new techniques to reduce network training time. The simulation tool was integrated into Contiki-NG and has been used to estimate the network formation times in various indoor environments. The correspondence between the experimental and numerical results obtained shows that our proposal is efficient to study the formation process of this type of networks.

Rectenna System Development Using Harmonic Balance and S-Parameters for an RF Energy Harvester.

With the escalating demand for Radio Frequency Identification (RFID) technology and the Internet of Things (IoT), there is a growing need for sustainable and autonomous power solutions to energize low-powered devices. Consequently, there is a critical imperative to mitigate dependency on batteries during passive operation. This paper proposes the conceptual framework of rectenna architecture-based radio frequency energy harvesters' performance, specifically optimized for low-power device applications. The proposed prototype utilizes the surroundings' Wi-Fi signals within the 2.4 GHz frequency band. The design integrates a seven-stage Cockroft-Walton rectifier featuring a Schottky diode HSMS286C and MA4E2054B1-1146T, a low-pass filter, and a fractal antenna. Preliminary simulations conducted using Advanced Design System (ADS) reveal that a voltage of 3.53 V can be harvested by employing a 1.57 mm thickness Rogers 5880 printed circuit board (PCB) substrate with an MA4E2054B1-1146T rectifier prototype, given a minimum power input of -10 dBm (0.1 mW). Integrating the fabricated rectifier and fractal antenna successfully yields a 1.5 V DC output from Wi-Fi signals, demonstrable by illuminating a red LED. These findings underscore the viability of deploying a fractal antenna-based radio frequency (RF) harvester for empowering small electronic devices.

On the Use and Construction of Wi-Fi Fingerprint Databases for Large-Scale Multi-Building and Multi-Floor Indoor Localization: A Case Study of the UJIIndoorLoc Database.

Large-scale multi-building and multi-floor indoor localization has recently been the focus of intense research in indoor localization based on Wi-Fi fingerprinting. Although significant progress has been made in developing indoor localization algorithms, few studies are dedicated to the critical issues of using existing and constructing new Wi-Fi fingerprint databases, especially for large-scale multi-building and multi-floor indoor localization. In this paper, we first identify the challenges in using and constructing Wi-Fi fingerprint databases for large-scale multi-building and multi-floor indoor localization and then provide our recommendations for those challenges based on a case study of the UJIIndoorLoc database, which is the most popular publicly available Wi-Fi fingerprint multi-building and multi-floor database. Through the case study, we investigate its statistical characteristics with a focus on the three aspects of (1) the properties of detected wireless access points, (2) the number, distribution and quality of labels, and (3) the composition of the database records. We then identify potential issues and ways to address them using the UJIIndoorLoc database. Based on the results from the case study, we not only provide valuable insights on the use of existing databases but also give important directions for the design and construction of new databases for large-scale multi-building and multi-floor indoor localization in the future.

Non-Contact Heart Rate Monitoring Method Based on Wi-Fi CSI Signal.

This paper introduces an innovative non-contact heart rate monitoring method based on Wi-Fi Channel State Information (CSI). This approach integrates both amplitude and phase information of the CSI signal through rotational projection, aiming to optimize the accuracy of heart rate estimation in home environments. We develop a frequency domain subcarrier selection algorithm based on Heartbeat to subcomponent ratio (HSR) and design a complete set of signal filtering and subcarrier selection processes to further enhance the accuracy of heart rate estimation. Heart rate estimation is conducted by combining the peak frequencies of multiple subcarriers. Extensive experimental validations demonstrate that our method exhibits exceptional performance under various environmental conditions. The experimental results show that our subcarrier selection method for heart rate estimation achieves an average accuracy of 96.8%, with a median error of only 0.8 bpm, representing an approximately 20% performance improvement over existing technologies.

Wi-AM: Enabling Cross-Domain Gesture Recognition with Commodity Wi-Fi.

RF-based gesture recognition systems outperform computer vision-based systems in terms of user privacy. The integration of Wi-Fi sensing and deep learning has opened new application areas for intelligent multimedia technology. Although promising, existing systems have multiple limitations: (1) they only work well in a fixed domain; (2) when working in a new domain, they require the recollection of a large amount of data. These limitations either lead to a subpar cross-domain performance or require a huge amount of human effort, impeding their widespread adoption in practical scenarios. We propose Wi-AM, a privacy-preserving gesture recognition framework, to address the above limitations. Wi-AM can accurately recognize gestures in a new domain with only one sample. To remove irrelevant disturbances induced by interfering domain factors, we design a multi-domain adversarial scheme to reduce the differences in data distribution between different domains and extract the maximum amount of transferable features related to gestures. Moreover, to quickly adapt to an unseen domain with only a few samples, Wi-AM adopts a meta-learning framework to fine-tune the trained model into a new domain with a one-sample-per-gesture manner while achieving an accurate cross-domain performance. Extensive experiments in a real-world dataset demonstrate that Wi-AM can recognize gestures in an unseen domain with average accuracy of 82.13% and 86.76% for 1 and 3 data samples.

Indoor Navigation in Facilities with Repetitive Structures.

Most facilities are structured in a repetitive manner. In this paper, we propose an algorithm and its partial implementation for a cellular guide in such facilities without GPS use. The complete system is based on iBeacons-like components, which operate on BLE technology, and their integration into a navigation application. We assume that the user's location is determined with sufficient accuracy. Our main goal revolves around leveraging the repetitive structure of the given facility to optimize navigation in terms of storage requirements, energy efficiency in the cellular device, algorithmic complexity, and other aspects. To the best of our knowledge, there is no prior experience in addressing this specific aim. In order to provide high performance in real time, we rely on optimal saving and the use of pre-calculated and stored navigation sub-routes. Our implementation seamlessly integrates iBeacon communications, a pre-defined indoor map, diverse data structures for efficient information storage, and a user interface, all working cohesively under a single supervision. Each module can be considered, developed, and improved independently. The approach is mainly directed to places, such as passenger ships, hotels, colleges, and so on. Because of the fact that there are "replicated" parts on different floors, stored once and used for multiple routes, we reduce the amount of information that must be stored, thus helping to reduce memory usage and as a result, yielding a better running time and energy consumption.

Lyapunov Drift-Plus-Penalty-Based Cooperative Uplink Scheduling in Dense Wi-Fi Networks.

In high-density network environments with multiple access points (APs) and stations, individual uplink scheduling by each AP can severely interfere with the uplink transmissions of neighboring APs and their associated stations. In congested areas where concurrent uplink transmissions may lead to significant interference, it would be beneficial to deploy a cooperative scheduler or a central coordinating entity responsible for orchestrating cooperative uplink scheduling by assigning several neighboring APs to support the uplink transmission of a single station within a proximate service area to alleviate the excessive interference. Cooperative uplink scheduling facilitated by cooperative information sharing and management is poised to improve the likelihood of successful uplink transmissions in areas with a high concentration of APs and stations. Nonetheless, it is crucial to account for the queue stability of the stations and the potential delays arising from information exchange and the decision-making process in uplink scheduling to maintain the overall effectiveness of the cooperative approach. In this paper, we propose a Lyapunov drift-plus-penalty framework-based cooperative uplink scheduling method for densely populated Wi-Fi networks. The cooperative scheduler aggregates information, such as signal-to-interference-plus-noise ratio (SINR) and queue status. During the aggregation procedure, propagation delays are also estimated and utilized as a value of expected cooperation delays in scheduling decisions. Upon aggregating the information, the cooperative scheduler calculates the Lyapunov drift-plus-penalty value, incorporating a predefined model parameter to adjust the system accordingly. Among the possible scheduling candidates, the proposed method proceeds to make uplink decisions that aim to reduce the upper bound of the Lyapunov drift-plus-penalty value, thereby improving the network performance and stability without a severe increase in cooperation delay in highly congested areas. Through comprehensive performance evaluations, the proposed method effectively enhances network performance with an appropriate model parameter. The performance improvement is particularly notable in highly congested areas and is achieved without a severe increase in cooperation delays.

Contention-Less Multi-Link Synchronous Transmission for Throughput Enhancement and Heterogeneous Fairness in Wi-Fi 7.

Multi-link operation (MLO) is a new and essential mechanism of IEEE 802.11be Extremely High Throughput (Wi-Fi 7) that can increase throughput and decrease latency in Wireless Local Area Networks (WLANs). The MLO enables a Multi-Link Device (MLD) to perform Simultaneous Transmission and Reception (STR) in different frequency bands. However, not all MLDs can support STR due to cross-link or in-device coexistence interference, while an STR-unable MLD (NSTR-MLD) can transmit multiple frames simultaneously in more than two links. This study focuses on the problems when NSTR-MLDs share a link with Single-Link Devices (SLDs). We propose a Contention-Less Synchronous Transmission (CLST) mechanism to improve fairness between NSTR-MLDs and SLDs while increasing the total network throughput. The proposed mechanism classifies links as MLD Dominant Links (MDLs) and Heterogeneous Coexistence Links (HCLs). In the proposed mechanism, an NSTR-MLD obtains a Synchronous Transmission Token (STT) through a virtual channel contention in the HCL but does not actually transmit a frame in the HCL, which is compensated for by a synchronous transmission triggered in the MDL. Moreover, the CLST mechanism allows additional subsequent transmissions up to the accumulated STT without further contention. Extensive simulation results confirm the outstanding performance of the CLST mechanism in terms of total throughput and fairness compared to existing synchronous transmission mechanisms.

CSI-F: A Human Motion Recognition Method Based on Channel-State-Information Signal Feature Fusion.

The recognition of human activity is crucial as the Internet of Things (IoT) progresses toward future smart homes. Wi-Fi-based motion-recognition stands out due to its non-contact nature and widespread applicability. However, the channel state information (CSI) related to human movement in indoor environments changes with the direction of movement, which poses challenges for existing Wi-Fi movement-recognition methods. These challenges include limited directions of movement that can be detected, short detection distances, and inaccurate feature extraction, all of which significantly constrain the wide-scale application of Wi-Fi action-recognition. To address this issue, we propose a direction-independent CSI fusion and sharing model named CSI-F, one which combines Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU). Specifically, we have introduced a series of signal-processing techniques that utilize antenna diversity to eliminate random phase shifts, thereby removing noise influences unrelated to motion information. Later, by amplifying the Doppler frequency shift effect through cyclic actions and generating a spectrogram, we further enhance the impact of actions on CSI. To demonstrate the effectiveness of this method, we conducted experiments on datasets collected in natural environments. We confirmed that the superposition of periodic actions on CSI can improve the accuracy of the process. CSI-F can achieve higher recognition accuracy compared with other methods and a monitoring coverage of up to 6 m.

Loom: A Modular Open-Source Approach to Rapidly Produce Sensor, Actuator, Datalogger Systems.

In the face of rising population, erratic climate, resource depletion, and increased exposure to natural hazards, environmental monitoring is increasingly important. Satellite data form most of our observations of Earth. On-the-ground observations based on in situ sensor systems are crucial for these remote measurements to be dependable. Providing open-source options to rapidly prototype environmental datalogging systems allows quick advancement of research and monitoring programs. This paper introduces Loom, a development environment for low-power Arduino-programmable microcontrollers. Loom accommodates a range of integrated components including sensors, various datalogging formats, internet connectivity (including Wi-Fi and 4G Long Term Evolution (LTE)), radio telemetry, timing mechanisms, debugging information, and power conservation functions. Additionally, Loom includes unique applications for science, technology, engineering, and mathematics (STEM) education. By establishing modular, reconfigurable, and extensible functionality across components, Loom reduces development time for prototyping new systems. Bug fixes and optimizations achieved in one project benefit all projects that use Loom, enhancing efficiency. Although not a one-size-fits-all solution, this approach has empowered a small group of developers to support larger multidisciplinary teams designing diverse environmental sensing applications for water, soil, atmosphere, agriculture, environmental hazards, scientific monitoring, and education. This paper not only outlines the system design but also discusses alternative approaches explored and key decision points in Loom's development.

Prediction of microvascular invasion in hepatocellular carcinoma patients with MRI radiomics based on susceptibility weighted imaging and T2-weighted imaging.

BACKGROUND: The accurate identification of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) is of great clinical importance. PURPOSE: To develop a radiomics nomogram based on susceptibility-weighted imaging (SWI) and T2-weighted imaging (T2WI) for predicting MVI in early-stage (Barcelona Clinic Liver Cancer stages 0 and A) HCC patients. MATERIALS AND METHODS: A prospective cohort of 189 participants with HCC was included for model training and testing, and an additional 34 participants were enrolled for external validation. ITK-SNAP was used to manually segment the tumour, and PyRadiomics was used to extract radiomic features from the SWI and T2W images. Variance filtering, student's t test, least absolute shrinkage and selection operator regression and random forest (RF) were applied to select meaningful features. Four machine learning classifiers, including K-nearest neighbour, RF, logistic regression and support vector machine-based models, were established. Independent clinical and radiological risk factors were also determined to establish a clinical model. The best radiomics and clinical models were further evaluated in the validation set. In addition, a nomogram was constructed from the radiomic model and independent clinical factors. Diagnostic efficacy was evaluated by receiver operating characteristic curve analysis with fivefold cross-validation. RESULTS: AFP levels greater than 400 ng/mL [odds ratio (OR) 2.50; 95% confidence interval (CI) 1.239-5.047], tumour diameter greater than 5 cm (OR 2.39; 95% CI 1.178-4.839), and absence of pseudocapsule (OR 2.053; 95% CI 1.007-4.202) were found to be independent risk factors for MVI. The areas under the curve (AUCs) of the best radiomic model were 1.000 and 0.882 in the training and testing cohorts, respectively, while those of the clinical model were 0.688 and 0.6691. In the validation set, the radiomic model achieved better diagnostic performance (AUC = 0.888) than the clinical model (AUC = 0.602). The combination of clinical factors and the radiomic model yielded a nomogram with the best diagnostic performance (AUC = 0.948). CONCLUSION: SWI and T2WI-derived radiomic features are valuable for noninvasively and accurately identifying MVI in early-stage HCC. Furthermore, the integration of radiomics and clinical factors yielded a predictive nomogram with satisfactory diagnostic performance and potential clinical benefits.

A Knockout of the IFITM3 Gene Increases the Sensitivity of WI-38 VA13 Cells to the Influenza A Virus.

One of the ways to regulate the sensitivity of human cells to the influenza virus is to knock out genes of the innate immune response. Promising targets for the knockout are genes of the interferon-inducible transmembrane protein (IFITM) family, in particular the IFITM3 gene, whose product limits the entry of a virus into the cell by blocking the fusion of the viral and endosomal membranes. In this study, by means of genome-editing system CRISPR/Cas9, monoclonal cell lines with an IFITM3 knockout were obtained based on WI-38 VA13 cells (human origin). It was found that such cell lines are more sensitive to infection by influenza A viruses of various subtypes. Nevertheless, this feature is not accompanied by an increased titer of newly formed viral particles in a culture medium.

"The real ethernet": The transnational history of global Wi-Fi connectivity.

Wi-Fi is an integral and invaluable part of our media practices. Wireless networks are blended into our media environment and, in terms of infrastructural importance, have become comparable with electricity or water. This article offers a new transnational perspective on the underexplored history of IEEE 802.11 standards by focusing on the tensions between the United States and Europe in terms of development trajectories of wireless technology. The goal is to analyze the standardization of wireless networking through a transnational lens and to contribute to enhanced understanding of the global proliferation of Wi-Fi technology. Four particular aspects of the transnational development of Wi-Fi technology are discussed: the rivalry between US and European standards, the constitutive choice to focus on data transmission, radio spectrum availability, and the peculiarities of network authentication.

Cell Strain-Derived Induced Pluripotent Stem Cells as an Isogenic Approach To Investigate Age-Related Host Response to Flaviviral Infection.

The expansion of the geographical footprint of dengue viruses (DENVs) and their mosquito vectors have affected more than half of the global population, including older adults who appear to show elevated risk of severe dengue. Despite this epidemiological trend, how aging contributes to increased dengue pathogenesis is poorly understood. A limitation has been the lack of useful in vitro experimental approaches; cell lines commonly used for infection studies are immortal and hence do not age. Cell strains such as WI-38 and MRC-5 with diploid genomes do age with in vitro passaging, but these cell strains were isolated decades ago and are now mostly highly passaged. Here, we show that reprogramming of cell strains with finite life span into induced pluripotent stem cells (iPSCs), followed by conversion back into terminally differentiated cells, can be an approach to derive genetically identical cells at different stages of aging. The iPSC-derived differentiated cells were susceptible to wild-type DENV infection and produced greater levels of type I interferon expression with increased passaging, despite similar levels of infection. In contrast, infection with the attenuated DENV-2 PDK53 and YF17D-204 strains showed reduced and increased levels of infection with increasing passages, respectively; the latter could be clinically pertinent, as YF17D-204 vaccination in older adults is associated with increased risk of severe adverse outcome. The differences in infection susceptibility and host response collectively suggest the potential of iPSC-derived cell strains as a genetically controlled approach to understanding how aging impacts viral pathogenesis. IMPORTANCE Aging has been a risk factor for poor clinical outcome in several infectious diseases, including dengue. However, age-dependent responses to dengue and other flaviviral infection or vaccination have remained incompletely understood due partly to lack of suitable laboratory tools. We thus developed an in vitro approach to examine age-related changes in host response to flaviviral infection. Notably, this approach uses cell strains with diploid rather than aneuploidic genomes, which are unstable. Conversion of these cells into iPSCs ensures sustainability of this resource, and reprogramming back into terminally differentiated cells would, even with a limited number of passages, produce cells at different stages of aging for infection studies. Our findings suggest that this in vitro system has the potential to serve as a genetically controlled approach to define the age-related response to flavivirus infection.

Oxygen nanobubble water affects wound healing of fibroblast WI-38 cells.

This study investigated the usefulness of oxygen nanobubble water (O2NBW) for wound repair by analyzing its effect on the wound-healing process in human lung fibroblasts (WI-38 cells). The WI-38 cells were treated with 0%, 50%, and 100% O2NBW. The cell viability, reactive oxygen species (ROS) production, and wound healing following treatment were determined to elucidate the effects of O2NBW. Our findings revealed that O2NBW had no cytotoxic effects on WI-38 cells, but instead increased cell numbers. The production of ROS was inhibited in the presence of O2NBW. Further, O2NBW induced migration and wound closure in WI-38 cells. In addition, the mRNA expression levels of antioxidant enzymes and wound-healing-related genes were evaluated. The results demonstrated that O2NBW enhanced the expression levels of all representative genes. In conclusion, our findings suggest that O2NBW could affect ROS production and wound healing in WI-38 cells and genes associated with the antioxidant system and wound healing.

A new continuous noninvasive finger cuff device (Vitalstream) for cardiac output that communicates wirelessly via bluetooth or Wi-Fi.

BACKGROUND: The new noninvasive Vitalstream (VS) continuous physiological monitor (Caretaker Medical LLC, Charlottesville, Virginia), allows continuous cardiac output by a low pump-inflated, finger cuff that pneumatically couples arterial pulsations via a pressure line to a pressure sensor for detection and analysis. Physiological data are communicated wirelessly to a tablet-based user interface via Bluetooth or Wi-Fi. We evaluated its performance against thermodilution cardiac output in patients undergoing cardiac surgery. METHODS: We compared the agreement between thermodilution cardiac output to that obtained by the continuous noninvasive system during cardiac surgery pre and post-cardiac bypass. Thermodilution cardiac output was performed routinely when clinically indicated by an iced saline cold injectate system. All comparisons between VS and TD/CCO data were post-processed. In order to match the VS CO readings to the averaged discrete TD bolus data, the averaged CO readings of the ten seconds of VS CO data points prior to a sequence of TD bolus injections was matched. Time alignment was based on the medical record time and the VS time-stamped data points. The accuracy against reference TD measurements was assessed via Bland-Altman analysis of the CO values and standard concordance analysis of the ΔCO values (with a 15% exclusion zone). RESULTS: Analysis of the data compared the accuracy of the matched measurement pairs of VS and TD/CCO VS absolute CO values with and without initial calibration to the discrete TD CO values, as well as the trending ability, i.e., ΔCO values of the VS physiological monitor compared to those of the reference. The results were comparable with other non-invasive as well as invasive technologies and Bland-Altman analyses showed high agreement between devices in a diverse patient population. The results are significant regarding the goal of expanding access to effective, wireless and readily implemented fluid management monitoring tools to hospital sections previously not covered because of the limitations of traditional technologies. CONCLUSION: This study demonstrated that the agreement between the VS CO and TD CO was clinically acceptable with a percent error (PE) of 34.5 to 38% with and without external calibration. The threshold for an acceptable agreement between the VS and TD was considered to be below 40% which is below the threshold recommended by others.

Circ-BICC1 Knockdown Alleviates Lipopolysaccharide (LPS)-Induced WI-38 Cell Injury Through miR-338-3p/MYD88 Axis.

Circular RNAs (circRNAs) play important roles in human diseases, including infantile pneumonia. In this article, we aimed to investigate the functions of circ-BICC1 in lipopolysaccharide (LPS)-induced injury of WI-38 cells. Quantitative real-time polymerase chain reaction (qRT-PCR) assay was performed for the levels of circ-BICC1, BICC1, microRNA-338-3p (miR-338-3p), and myeloid differentiation primary response 88 (MYD88). Cell Counting Kit-8 (CCK-8) assay, 5-ethynyl-2'-deoxyuridine (EdU) assay, and flow cytometry analysis were conducted to evaluate cell viability, proliferation, and apoptosis, respectively. Enzyme-linked immunosorbent assay (ELISA) kits were used for the concentrations of interleukin-1ß (IL-1ß) and tumor necrosis factor-α (TNF-α). The levels of oxidative stress markers were detected with commercial kits. Dual-luciferase reporter assay was adopted to analyze the interaction between circ-BICC1 and miR-338-3p, as well as MYD88 and miR-338-3p. Western blot assay was employed for the protein level of MYD88. Circ-BICC1 level was increased in pneumonia patients' blood samples and LPS-treated WI-38 cells. LPS treatment suppressed WI-38 cell viability and promoted cell apoptosis, inflammation, and oxidative stress. Circ-BICC1 knockdown reversed the effect of LPS-induced WI-38 cell injury. For mechanism analysis, circ-BICC1 could function as the sponge for miR-338-3p and miR-338-3p inhibition reversed the effect of circ-BICC1 knockdown on LPS-induced WI-38 cell injury. MYD88 was identified as the target of miR-338-3p. MiR-338-3p overexpression relieved LPS-induced injury of WI-38 cells, while the impact was abolished by elevating MYD88. Circ-BICC1 silencing remitted LPS-triggered WI-38 cell damage by adsorbing miR-338-3p and regulating MYD88.