Downstream Sensor Research Articles

Dynamic detection of soluble intermediates during methanol electrooxidation

Methanol electrooxidation at a Pt band electrode is studied in a microfluidic flow cell (MFFC) with simultaneous electrochemical detection of formic acid at a down-stream sensor (detector) Pd electrode. Detection of formic acid at the Pd electrode is possible through either a fast voltammetry or a potential step procedure. In both cases, maximizing the detection signal (oxidation current) requires Pd oxide formation and reduction before detection. Pd oxide formation is needed to oxidize surface-bound carbonaceous species while Pd oxide reduction is needed to reactivate the electrode surface. Although formic acid alone is easily detected and provides a stable detection signal at the Pd sensor electrode, simultaneous formation of formaldehyde during methanol oxidation degrades the detection signal at the Pd electrode over time. We show that dynamic detection of sub-millimolar formic acid concentrations in 2M methanol is possible at a time resolution down to 2 s. Dynamic detection during methanol oxidation at platinum shows that production of soluble intermediates occurs at all potentials where an oxidation current is observed. Furthermore, a higher faradaic efficiency to formic acid occurs during the main methanol oxidation peak in the positive-going sweep compared to the negative-going sweep, and is higher still at potentials above 1V. This work shows that microfluidic flow cells can be used for fast and dynamic detection of soluble reaction intermediates by using down-stream electrodes with custom potential step or sweep sequences.

Development and experimental testing of an innovative nondestructive thermal sensor utilizing the thermal interrogation method for detecting leakage in water plastic pipes

Leak detection in water pipelines is still an important issue in real-world industrial systems. Thus, a new nondestructive thermal sensor design based on the thermal interrogation method has been developed to detect and estimate the real-time leaks in water plastic pipes without environmental interference. The proposed thermal interrogation method utilizes a combination of heat flux and temperature measurements on the upstream and downstream outside plastic pipe surfaces. These measurements are obtained by using heat flux sensors and thermocouples that are covered by thin-film polyimide electric heaters. The interrogation method approach delivers that at constant input heat flux, the difference in sensor temperature values is dependent on the leakage volume flow rates. The sensor was tested over a range of water leakage volume flow rate from 0.1 m3/h to 1.3 m3/h and a range of water temperature from 21 °C to 25 °C. The water leakage volume flow rates were correlated to the difference in temperature values between the upstream and downstream sensors. The measurement results reveal that this sensor can be used to detect and estimate the real-time water leakage volume flow rate with high accuracy and repeatability for plastic pipes.

Porcine deltacoronavirus nucleocapsid protein antagonizes JAK-STAT signaling pathway by targeting STAT1 through KPNA2 degradation.

Porcine deltacoronavirus (PDCoV) is an enteric pathogenic coronavirus that causes acute and severe watery diarrhea in piglets and has the ability of cross-species transmission, posing a great threat to swine production and public health. The interferon (IFN)-mediated signal transduction represents an important component of virus-host interactions and plays an essential role in regulating viral infection. Previous studies have suggested that multifunctional viral proteins encoded by coronaviruses antagonize the production of IFN via various means. However, the function of these viral proteins in regulating IFN-mediated signaling pathways is largely unknown. In this study, we demonstrated that PDCoV and its encoded nucleocapsid (N) protein antagonize type I IFN-mediated JAK-STAT signaling pathway. We identified that PDCoV infection stimulated but delayed the production of IFN-stimulated genes (ISGs). In addition, PDCoV inhibited JAK-STAT signal transduction by targeting the nuclear translocation of STAT1 and ISGF3 formation. Further evidence showed that PDCoV N is the essential protein involved in the inhibition of type I IFN signaling by targeting STAT1 nuclear translocation via its C-terminal domain. Mechanistically, PDCoV N targets STAT1 by interacting with it and subsequently inhibiting its nuclear translocation. Furthermore, PDCoV N inhibits STAT1 nuclear translocation by specifically targeting KPNA2 degradation through the lysosomal pathway, thereby inhibiting the activation of downstream sensors in the JAK-STAT signaling pathway. Taken together, our results reveal a novel mechanism by which PDCoV N interferes with the host antiviral response.IMPORTANCEPorcine deltacoronavirus (PDCoV) is a novel enteropathogenic coronavirus that receives increased attention and seriously threatens the pig industry and public health. Understanding the underlying mechanism of PDCoV evading the host defense during infection is essential for developing targeted drugs and effective vaccines against PDCoV. This study demonstrated that PDCoV and its encoded nucleocapsid (N) protein antagonize type I interferon signaling by targeting STAT1, which is a crucial signal sensor in the JAK-STAT signaling pathway. Further experiments suggested that PDCoV N-mediated inhibition of the STAT1 nuclear translocation involves the degradation of KPNA2, and the lysosome plays a role in KPNA2 degradation. This study provides new insights into the regulation of PDCoV N in the JAK-STAT signaling pathway and reveals a novel mechanism by which PDCoV evades the host antiviral response. The novel findings may guide us to discover new therapeutic targets and develop live attenuated vaccines for PDCoV infection.

Abstract 2065: Development of a genetically validated, cell-based reporter assay for ADAR1 editing activity

Abstract Adenosine Deaminase Acting on RNA (ADAR) enzymes perform adenosine to inosine base editing in RNA, particularly targeting adenosines located within a specific double-stranded stem-loop motif. The ADAR1 gene encodes both a universally expressed isoform (p110) and an interferon-inducible isoform (p150), which plays a role in innate immunity by mediating interferon signaling. In the context of healthy, uninfected cells, ADAR1 performs A-to-I editing on endogenous double-stranded RNA to prevent it from activating downstream dsRNA sensors RIG-I and MDA5, which in-turn activate a pro-inflammatory response. Loss of function mutations in ADAR1 result in aberrant activation of the dsRNA sensors and are involved in autoimmune disorders. ADAR1 dysfunction also impacts cancer cell growth, proliferation, and response to immunotherapy. ADAR1 expression is increased in several types of cancer and ADAR1 knock-out has been demonstrated to improve the response to certain immunotherapies such PD-1/PD-L1 blockade and to circumvent tumor immunotherapy resistance mechanisms, making ADAR1 an attractive target for therapeutic development. We have developed and validated a high-throughput, cell-based assay for measuring ADAR1 editing activity. Several ADAR editing reporter constructs were designed and evaluated for their relative response to ADAR1 over-expression. They all feature an ADAR1 hairpin target with a stop codon (UAG) which is susceptible to ADAR1-mediated editing to a tryptophan (UUG), located upstream of a firefly luciferase gene. We show that increasing transient expression of ADAR1 led to proportional increased activity of the downstream firefly luciferase, indicating dose-dependent transcript editing by ADAR1. Selected reporters were used in conjunction with ADAR2 overexpression to identify an ADAR1-biased reporter. Thus, a reporter with low luciferase activity in response to ADAR2 expression was chosen to establish stable HEK293 cell lines (which express low levels of ADAR1) with and without constitutively expressed ADAR1 protein. ADAR1-overexpressing HEK293 cells displayed high luciferase activity, in accordance with high ADAR1-mediated editing of the reporter transcript, which was decreased in response to siRNA-mediated knockdown of ADAR1 expression or pharmacological inhibition of ADAR1 activity. Sequencing of the reporter RNA confirmed that changes in reporter activity were correlated with editing of the RNA transcript. Finally, these validated ADAR1 editing reporter cell lines were further engineered to constitutively express Renilla luciferase under the control of a CMV promoter, serving as an internal control for the toxicity of ADAR1 inhibitors. In conclusion, our robust cell-based assay provides a well-validated resource to identify modulators of ADAR1 editing activity in a cellular context. Citation Format: Valerie Sapp, Jim Bilakovics, Ava Burr, Fernando Martins, Pavel Shashkin, Veronique Baron, Henry Zhu, Junguk Park. Development of a genetically validated, cell-based reporter assay for ADAR1 editing activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2065.

An asynchronous wireless network for capturing event-driven data from large populations of autonomous sensors

Networks of spatially distributed radiofrequency identification sensors could be used to collect data in wearable or implantable biomedical applications. However, the development of scalable networks remains challenging. Here we report a wireless radiofrequency network approach that can capture sparse event-driven data from large populations of spatially distributed autonomous microsensors. We use a spectrally efficient, low-error-rate asynchronous networking concept based on a code-division multiple-access method. We experimentally demonstrate the network performance of several dozen submillimetre-sized silicon microchips and complement this with large-scale in silico simulations. To test the notion that spike-based wireless communication can be matched with downstream sensor population analysis by neuromorphic computing techniques, we use a spiking neural network machine learning model to decode prerecorded open source data from eight thousand spiking neurons in the primate cortex for accurate prediction of hand movement in a cursor control task.

Application of Deep Learning in Predicting Particle Concentration of Gas–Solid Two-Phase Flow

Particle concentration is an important parameter for describing the state of gas–solid two-phase flow. This study compares the performance of three methods, namely, Back-Propagation Neural Networks (BPNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTM), in handling gas–solid two-phase flow data. The experiment utilized seven parameters, including temperature, humidity, upstream and downstream sensor signals, delay, pressure difference, and particle concentration, as the dataset. The evaluation metrics, such as prediction accuracy, were used for comparative analysis by the experimenters. The experiment results indicate that the prediction accuracies of the RNN, LSTM, and BPNN experiments were 92.4%, 92.7%, and 92.5%, respectively. Future research can focus on further optimizing the performance of the BPNN, RNN, and LSTM to enhance the accuracy and efficiency of gas–solid two-phase flow data processing.

Adaptive time-step unscented kalman filtering (ATS-UKF) based observer design for urea selective catalytic reduction (SCR) performance of diesel engines

To reduce the number of sensors in the SCR catalyst, state feedback and fault diagnosis information are provided. Firstly, a model based on the coupling of flow, heat transfer, and gas-solid phase catalytic reaction in the SCR system is investigated in this paper. The parabolic partial differential equations are simplified by the variable substitution method and the method of lines approach (MOL). The simplified system of equations is solved by backward differentiation formulas (BDF) with adaptive adjustment time step strategy. Meanwhile, the chemical reaction parameters are accurately calibrated per second using the Levenberg-Marquardt method. Secondly, the ATS-UKF is designed in this paper, and to ensure the synchronisation between the ATS-UKF and the SCR model calculations, the time step of solving the BDF by the SCR model is taken as the time step of propagating the sigma points. Two observation scenarios are assumed: (1) no downstream NH3 concentration sensor, ammonia coverage and downstream NH3 concentration are observed by ATS-UKF; (2) no downstream NOx sensor, ammonia coverage and downstream NOx concentration are observed by ATS-UKF. Finally, the paper carries out bench tests. In the first case, the ammonia coverage obtained by the ATS-UKF reached 0.99 with respect to the model-calculated value R². The mean absolute error (MAE) between the observed and experimental values of the ATS-UKF for the downstream NH3 concentration was 2.76 ppm. In the second case, the ammonia coverage obtained by the ATS-UKF reached 0.99 with respect to the model-calculated value R², and the MAE between the observed and experimental values of the ATS-UKF for the downstream NOx concentration was 1.53 ppm. Environmental ImplicationThe Adaptive Time-Step Unscented Kalman Filtering (ATS-UKF) enhances urea Selective Catalytic Reduction (SCR) in diesel engines, improving environmental outcomes. This method minimizes sensor dependence, enabling more precise SCR system management and effective emission reduction. By advancing emission control technologies, ATS-UKF contributes to global air pollution mitigation efforts, supporting cleaner air and environmental sustainability. Its innovative approach in monitoring and predicting SCR performance marks a significant step towards eco-friendly diesel engine operation.

Abstract A170: Discovery of small molecule inhibitors of ADAR1

Abstract Background: Adenosine deaminase acting on RNA 1 (ADAR1) is an RNA editing enzyme that catalyzes the deamination of adenosine to inosine in double-stranded (ds) RNA. Cellular dsRNAs are edited by ADAR1 to prevent their recognition by cytoplasmic dsRNA sensors such as MDA5 and PKR. Loss of ADAR1 has been shown to induce the activation of these sensors in cancer cells with high intrinsic type 1 interferon signaling, leading to cell death. Accent has developed a Type I Interferon Stimulated Gene (TISG) score through analysis of publicly available datasets that is predictive of sensitivity to ADAR1 loss. As 15-30% of primary tumors in TCGA display elevated type I interferon signaling, ADAR1 has become an attractive oncology target. Here we describe the development of an in vitro and cellular assay suite that was used to progress chemical matter identified from a high-throughput screen (HTS) into single-digit nanomolar inhibitors of cellular ADAR1. Materials and Methods: A HAP-1 cell model of ADAR1 loss was used in rescue experiments to validate a small molecule inhibition approach towards the targeting of ADAR1 activity. A high-throughput screening-compatible biochemical assay was developed and applied to screen diversity libraries, leading to the identification of a chemical series of ADAR1 inhibitors. The mechanism of inhibition of the series was characterized by substrate-competition and orthogonal substrate binding assays. Iterative optimization of the series resulted in cell-permeable compounds of sufficient potency to be tested in a suite of ADAR1 cellular assays. Results: ADAR1 loss or catalytic site-mutant cells were more sensitive to exogenous Interferon-β than parental cells, leading to decreased growth and viability of HAP-1 cells. We demonstrate knock-out of ADAR1 or loss of catalytic activity results in activation of PKR upon interferon-β treatment in the HAP-1 model, unlike parental cells. Development of a label-free biochemical assay of sufficient sensitivity to be run under steady-state conditions, showing linear reaction progress curves over multiple rounds of ADAR1 turnover, enabled high-throughput screening. A hit series was identified that showed RNA substrate non-competitive behavior in orthogonal RNA binding assays. To further assist understanding of series mechanism, a crystallization system was developed that produced a novel human ADAR1 structure to 1.45Å resolution. A suite of in vitro and cellular assays were used to further optimize and identify small molecules with robust inhibition of cellular ADAR1, as read out by cellular RNA editing assays, as well as activation of downstream dsRNA sensor pathways: secretion of interferon B and phosphorylation of PKR. Consistent with our target hypothesis, treatment of the TISG-high squamous cell carcinoma OE21 cell line with potent ADAR1 inhibitors results in cell growth inhibition. Conclusions: Accent developed a suite of assays that led to the identification of small molecule inhibitors targeting ADAR1. Citation Format: Shane M Buker, Stephen J Blakemore, P. Ann Boriack-Sjodin, Cindy Collins, Robert A Copeland, Kenneth W Duncan, Anna Ericsson, Alexandra Garadino, April Greene-Colozzi, Nathalie Leger, Gordon Lockbaum, Anugraha Raman, Scott Ribich, Allen Sickmier, Brian S Sparling, Jie Wu, Serena Silver. Discovery of small molecule inhibitors of ADAR1 [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A170.

Towards better traffic volume estimation: Jointly addressing the underdetermination and nonequilibrium problems with correlation-adaptive GNNs

Traffic volume is an indispensable ingredient to provide fine-grained information for traffic management and control. However, due to the limited deployment of traffic sensors, obtaining full-scale volume information is far from easy. Existing work on this topic focuses primarily on improving the overall estimation accuracy of a particular method and ignores the underlying challenges of volume estimation, thereby having inferior performance in some critical tasks. This paper studies two key problems with regard to traffic volume estimation: (1) underdetermined traffic flows caused by fully undetected paths that can allow arbitrary volume values without violating the conservation law, where using local side information is insufficient to tackle, and (2) nonequilibrium traffic flows arise when traffic flows vary in density over space and time due to congestion propagation delay, which produce time-shifted volume readings to varying degrees. Here we demonstrate a graph-based deep learning method that offers a data-driven, equation-free, and correlation-adaptive approach to address the above issues and perform accurate network-wide traffic volume estimation. Particularly, in order to quantify the dynamic and nonlinear speed-volume relationships for the estimation of underdetermined flows, a speed pattern-adaptive adjacency matrix based on graph attention is developed and integrated into the graph convolution process, to capture nonlocal correlations between volumes. To measure the impacts of nonequilibrium flows, a temporal masked and clipped attention combined with a gated temporal convolution layer is customized to capture time-asynchronous correlations between upstream and downstream sensors under varying impacts of congestion delay. We then evaluate our model on a real-world highway traffic volume dataset and compare it with several benchmark models. It is demonstrated that the proposed model achieves high estimation accuracy even under 20% sensor coverage rate and outperforms other baselines significantly, especially on underdetermined and nonequilibrium flow locations. Furthermore, comprehensive quantitative model analysis is also carried out to justify the model designs. The source code and datasets are publicly available at: .

LOC102549726/miR-760-3p network is involved in the progression of ISO-induced pathological cardiomyocyte hypertrophy via endoplasmic reticulum stress

Pathological cardiac hypertrophy (CH) is featured by myocyte enlargement and cardiac malfunction. Multiple signaling pathways have been implicated in diverse pathological and physiological processes in CH. However, the function of LOC102549726/miR-760-3p network in CH remains unclear. Here, we characterize the functional role of LOC102549726/miR-760-3p network in CH and delineate the underlying mechanism. The expression of LncRNA LOC102549726 and hypertrophic markers was significantly increased compared to the control, while the level of miR-760-3p was decreased. Next, we examined ER stress response in a hypertrophic cardiomyocyte model. The expression of ER stress markers was greatly enhanced after incubation with ISO. The hypertrophic reaction, ER stress response, and increased potassium and calcium ion channels were alleviated by genetic downregulation of LOC102549726. It has been demonstrated that LOC102549726 functions as a competitive endogenous RNA (ceRNA) of miR-760-3p. Overexpression of miR-760-3p decreased cell surface area and substantially mitigated ER stress response; protein levels of potassium and calcium channels were also significantly up-regulated compared to the NC control. In contrast, miR-760-3p inhibition increased cell size, aggravated CH and ER stress responses, and reduced ion channels. Collectively, in this study we demonstrated that the LOC102549726/miR-760-3p network was a crucial regulator of CH development. Ion channels mediate the ER stress response and may be a downstream sensor of the LOC102549726/miR-760-3p network. Therefore, these findings advance our understanding of pathological CH and provide new insights into therapeutic targets for cardiac remodeling.

Automated streamflow measurements in high‐elevation Alpine catchments

AbstractSalt dilution is a well‐established streamflow measurement method in creeks, which works particularly well downstream of turbulent flow sections as the mixing of the salt tracer is enhanced. Usually, salt dilution measurements are performed manually, which considerably limits the observations of rare peak flow events. These events are particularly important for constructing robust rating curves and avoiding large uncertainties in the extrapolation of streamflow values. An additional challenge is the variability of the river cross section, especially after larger discharge events, leading to nonstationary rating curves. Therefore, discharge measurements well distributed over time are needed to construct a reliable streamflow–water level relationship and to detect changes caused by erosion and deposition processes. To overcome these two issues, we used an automated streamflow measuring systems at three different sites with contrasting hydrological and hydraulic characteristics in the Alps. This system allowed us to measure discharge at nearly maximum flow of the observation period (2020–2021) at all three sites and to detect abrupt changes in the rating curve by performing event‐based salt injections. The uncertainty in the measurements was quantified, and the streamflow was compared with official gauging stations in the same catchment. Based on a very large dataset of almost 300 measurements, we were able to evaluate the reliability of the system and identify the primary sources of uncertainty in the experimental setup. One key aspect was the site selection for the downstream electrical conductivity sensors, as measurement location strongly controls the signal‐to‐noise ratio in the recorded breakthrough curves.

Japanese encephalitis virus NS4B inhibits interferon beta production by targeting TLR3 and TRIF

Japanese encephalitis virus (JEV) is a flavivirus transmitted by mosquitoes, causing epidemics of encephalitis in humans and reproductive disorders in pigs. This virus is predominantly distributed in Asian countries and causes tens of thousands of infections in humans annually. Interferon (IFN) is an essential component of host defense against viral infection. Multiple studies have indicated that multifunctional nonstructural proteins of flaviviruses suppress the host IFN response via various strategies to facilitate viral replication. The flaviviruses encoded nonstructural protein 4B (NS4B) is a multifunctional hydrophobic nonstructural protein widely involved in viral replication, pathogenesis and host immune evasion. In this study, we demonstrated that NS4B of JEV suppressed the induction of IFN-β production, mainly through targeting the TLR3 and TRIF (a TIR domain-containing linker that induces IFN-β) proteins in the TLR3 pathway. In a dual-luciferase reporter assay, JEV NS4B significantly inhibited the activation of IFN-β promoter induced by TLR3 and simultaneously treated with poly (I:C). Moreover, NS4B also inhibited the activation of IFN-β promoter triggered by interferon regulatory factor 3 (IRF3)/5D or its upstream molecules in TLR3 signaling pathway. Furthermore, NS4B inhibited the phosphorylation of IRF3 under the stimulation of TLR3 and TRIF molecules. Mechanistically, JEV NS4B interacts with TLR3 and TRIF and confirmed by co-localization and co-immunoprecipitation assay, thereby inhibiting the activation of downstream sensors in the TLR3-mediated pathway. Overall, our results provide a novel mechanism by which JEV NS4B interferes with the host's antiviral response through targeting TLR3 receptor signaling pathway.

Genetic Analysis Reveals a Requirement for the Hybrid Sensor Kinase RscS in para-Aminobenzoic Acid/Calcium-Induced Biofilm Formation by Vibrio fischeri.

The marine bacterium Vibrio fischeri initiates symbiotic colonization of its squid host, Euprymna scolopes, by forming and dispersing from a biofilm dependent on the symbiosis polysaccharide locus (syp). Historically, genetic manipulation of V. fischeri was needed to visualize syp-dependent biofilm formation in vitro, but recently, we discovered that the combination of two small molecules, para-aminobenzoic acid (pABA) and calcium, was sufficient to induce wild-type strain ES114 to form biofilms. Here, we determined that these syp-dependent biofilms were reliant on the positive syp regulator RscS, since the loss of this sensor kinase abrogated biofilm formation and syp transcription. These results were of particular note because loss of RscS, a key colonization factor, exerts little to no effect on biofilm formation under other genetic and medium conditions. The biofilm defect could be complemented by wild-type RscS and by an RscS chimera that contains the N-terminal domains of RscS fused to the C-terminal HPT domain of SypF, the downstream sensor kinase. It could not be complemented by derivatives that lacked the periplasmic sensory domain or contained a mutation in the conserved site of phosphorylation, H412, suggesting that these cues promote signaling through RscS. Lastly, pABA and/or calcium was able to induce biofilm formation when rscS was introduced into a heterologous system. Taken together, these data suggest that RscS is responsible for recognizing pABA and calcium, or downstream consequences of those cues, to induce biofilm formation. This study thus provides insight into signals and regulators that promote biofilm formation by V. fischeri. IMPORTANCE Bacterial biofilms are common in a variety of environments. Infectious biofilms formed in the human body are notoriously hard to treat due to a biofilm's intrinsic resistance to antibiotics. Bacteria must integrate signals from the environment to build and sustain a biofilm and often use sensor kinases that sense an external signal, which triggers a signaling cascade to elicit a response. However, identifying the signals that kinases sense remains a challenging area of investigation. Here, we determine that a hybrid sensor kinase, RscS, is crucial for Vibrio fischeri to recognize para-aminobenzoic acid and calcium as cues to induce biofilm formation. This study thus advances our understanding of the signal transduction pathways leading to biofilm formation.

AMPK-endoplasmic reticulum stress axis contributes to lipopolysaccharide-caused mitochondrial dysfunction by regulating mitochondria-associated membrane function in bovine hepatocytes

Mitochondrial homeostasis is closely associated with cellular homeostasis process, whereas mitochondrial dysfunction contributes to apoptosis and mitophagy. Hence, analyzing the mechanism of lipopolysaccharide (LPS)-caused mitochondrial damage is necessary to understand how cellular homeostasis is maintained in bovine hepatocytes. Mitochondria-associated membranes (MAM), a connection between endoplasmic reticulum (ER) and mitochondria, is important to control mitochondrial function. To investigate the underlying mechanisms of the LPS-caused mitochondrial dysfunction, hepatocytes isolated from dairy cows at ∼160 d in milk (DIM) were pretreated with the specific inhibitors of adenosine 5'-monophosphate-activated protein kinase (AMPK), ER stress, RNA-activated protein kinase-like ER kinase (PERK), inositol-requiring enzyme 1α (IRE1α), c-Jun N-terminal kinase, and autophagy followed by a 12 I1/4g/mL LPS treatment. The results showed that inhibiting ER stress with 4-phenylbutyric acid decreased the levels of autophagy and mitochondrial damage with AMPK inactivation in LPS-treated hepatocytes. The AMPK inhibitor compound C pretreatment alleviated LPS-induced ER stress, autophagy and mitochondrial dysfunction by regulating the expression of MAM-related genes, such as mitofusin 2 (MFN2), PERK, and IRE1α. Moreover, inhibiting PERK and IRE1α mitigated autophagy and mitochondrial dynamic disruption by regulating the MAM function. Additionally, blocking c-Jun N-terminal kinase, the downstream sensor of IRE1α, could reduce the levels of autophagy and apoptosis and restore the balance of mitochondrial fusion and fission by modulating the B cell leukemia 2 (BCL-2)/BCL-2 interacting protein 1 (BECLIN1) complex in the LPS-treated bovine hepatocytes. Furthermore, autophagy blockage with chloroquine could intervene in LPS-caused apoptosis to restore mitochondrial function. Collectively, these findings suggest that the AMPK-ER stress axis is involved in the LPS-caused mitochondrial dysfunction by mediating the MAM activity in bovine hepatocytes.

A New Contactless Cross-Correlation Velocity Measurement System for Gas–Liquid Two-Phase Flow

Based on the principle of Contactless Conductivity Detection (CCD), a new contactless cross-correlation velocity measurement system with a three-electrode construction is developed in this work and applied to the contactless velocity measurement of gas–liquid two-phase flow in small channels. To achieve a compact design and to reduce the influence of the slug/bubble deformation and the relative position change on the velocity measurement, an electrode of the upstream sensor is reused as an electrode of the downstream sensor. Meanwhile, a switching unit is introduced to ensure the independence and consistency of the upstream sensor and the downstream sensor. To further improve the synchronization of the upstream sensor and the downstream sensor, fast switching and time compensation are also introduced. Finally, with the obtained upstream and downstream conductance signals, the velocity measurement is achieved by the principle of cross-correlation velocity measurement. To test the measurement performance of the developed system, experiments are carried out on a prototype with a small channel of 2.5 mm. The experimental results show that the compact design (three-electrode construction) is successful, and its measurement performance is satisfactory. The velocity range for the bubble flow is 0.312–0.816 m/s, and the maximum relative error of the flow rate measurement is 4.54%. The velocity range for the slug flow is 0.161 m/s–1.250 m/s, and the maximum relative error of the flow rate measurement is 3.70%.

Enhancing detection of Listeria monocytogenes in food products using an enzyme

There is a need to identify the presence of microorganisms, in particular human pathogens, in food processing facilities and products. Adhesion of pathogens to surfaces poses a detection challenge with biofilms greatly hindering detection by precluding the transfer of specific material to downstream sensors. Enzymes that disrupt biofilms can therefore enhance detection of foodborne pathogens through facilitating their release from abiotic and biotic surfaces. In this study, a recombinant enzyme, CAase, was applied to improve detection of biofilm-embedded Listeria monocytogenes on food and food contact surfaces. Microbiological and molecular detection methods demonstrated that biofilms treated with enzyme for longer than 4 h resulted in a significant increase in the number of cells released into the media compared to untreated controls. This work demonstrates the benefits of inclusion of enzymes and biosurfactants within sample processing and detection protocols because of their ability to contribute to a more rapid, accurate, reliable, and repeatable microbial detection assay when biofilm embedded pathogens are present. •Sample preparation for detecting microbial pathogen in foods. • Enzymatic treatment of biofilms to facilitate microbial pathogen detection. • Method to detect microbial pathogens in foods and on food contact surfaces.

Lactoferrin suppresses the progression of colon cancer under hyperglycemia by targeting WTAP/m6A/NT5DC3/HKDC1 axis

BackgroundAlthough the relationship between type 2 diabetes (T2D) and the increased risk of colorectal carcinogenesis is widely defined in clinical studies, the therapeutic methods and molecular mechanism of T2D-induced colon cancer and how does hyperglycemia affect the progression is still unknown. Here, we studied the function of lactoferrin (LF) in suppressing the progression of colon cancer in T2D mice, and uncovered the related molecular mechanisms in DNA 5mC and RNA m6A levels.MethodsWe examined the effects of LF (50% iron saturation) on the migration and invasion of colon tumor cells under high concentration of glucose. Then, transcriptomics and DNA methylation profilings of colon tumor cells was co-analyzed to screen out the special gene (NT5DC3), and the expression level of NT5DC3 in 75 clinical blood samples was detected by q-PCR and western blot, to investigate whether NT5DC3 was a biomarker to distinguish T2D patients and T2D-induced colon cancer patients from healthy volunteers. Futhermore, in T2D mouse with xenografted colon tumor models, the inhibitory effects of LF and NT5DC3 protein on colon tumors were investigated. In addition, epigenetic alterations were measured to examine the 5mC/m6A modification sites of NT5DC3 regulated by LF. Utilizing siRNA fragments of eight m6A-related genes, the special gene (WTAP) regulating m6A of NT5DC was proved, and the effect of LF on WTAP/NT5DC3/HKDC1 axis was finally evaluated.ResultsA special gene NT5DC3 was screened out through co-analysis of transcriptomics and DNA methylation profiling, and HKDC1 might be a downstream sensor of NT5DC3. Mechanistically, LF-dependent cellular DNA 5mC and RNA m6A profiling remodeling transcriptionally regulate NT5DC3 expression. WTAP plays a key role in regulating NT5DC3 m6A modification and subsequently controls NT5DC3 downstream target HKDC1 expression. Moreover, co-treatment of lactoferrin and NT5DC3 protein restrains the growth of colon tumors by altering the aberrant epigenetic markers. Strikingly, clinical blood samples analysis demonstrates NT5DC3 protein expression is required to direct the distinction of T2D or T2D-induced colon cancer with healthy humans.ConclusionsTogether, this study reveals that lactoferrin acts as a major factor to repress the progression of colon cancer under hyperglycemia, thus, significantly expanding the landscape of natural dietary mediated tumor suppression.Graphical

Stabilization of a multi-frequency open cavity flow with gradient-enriched machine learning control

We stabilize an open cavity flow experiment to 1 % of its original fluctuation level. For the first time, a multi-modal feedback control is automatically learned for this configuration. The key enabler is automatic in situ optimization of control laws with machine learning augmented by a gradient descent algorithm, named gradient-enriched machine learning control (Cornejo Maceda et al., J. Fluid Mech., vol. 917, 2021, A42, gMLC). The physical interpretation of the feedback mechanism is assisted by a novel cluster-based control law visualization for the flow dynamics and corresponding actuation commands. Starting points of the control experiment are two unforced open cavity benchmark configurations: a narrow-bandwidth regime with a single dominant frequency and a mode-switching regime where two frequencies compete. The flow is forced by a dielectric barrier discharge actuator located at the leading edge and is monitored by a downstream hot-wire sensor over the trailing edge. The feedback law is optimized with respect to the monitored fluctuation level. As reference, the self-oscillations of the mixing layer are mitigated with steady actuation. Then, a feedback controller is optimized with gMLC. As expected, feedback control outperforms steady actuation by achieving a better amplitude reduction with approximately 1 % of the actuation energy required for similarly effective steady forcing. Intriguingly, optimized laws learned for one regime perform well for the other untested regime as well. The proposed control strategy can be expected to be applicable for many other shear flow experiments.

Close agreement between deterministic versus stochastic modeling of first-passage time to vesicle fusion

Ca2+-dependent cell processes, such as neurotransmitter or endocrine vesicle fusion, are inherently stochastic due to large fluctuations in Ca2+ channel gating, Ca2+ diffusion, and Ca2+ binding to buffers and target sensors. However, previous studies revealed closer-than-expected agreement between deterministic and stochastic simulations of Ca2+ diffusion, buffering, and sensing if Ca2+ channel gating is not Ca2+ dependent. To understand this result more fully, we present a comparative study complementing previous work, focusing on Ca2+ dynamics downstream of Ca2+ channel gating. Specifically, we compare deterministic (mean-field/mass-action) and stochastic simulations of vesicle exocytosis latency, quantified by the probability density of the first-passage time (FPT) to the Ca2+-bound state of a vesicle fusion sensor, following a brief Ca2+ current pulse. We show that under physiological constraints, the discrepancy between FPT densities obtained using the two approaches remains small even if as few as ∼50 Ca2+ ions enter per single channel-vesicle release unit. Using a reduced two-compartment model for ease of analysis, we illustrate how this close agreement arises from the smallness of correlations between fluctuations of the reactant molecule numbers, despite the large magnitude of fluctuation amplitudes. This holds if all relevant reactions are heteroreaction between molecules of different species, as is the case for bimolecular Ca2+ binding to buffers and downstream sensor targets. In this case, diffusion and buffering effectively decorrelate the state of the Ca2+ sensor from local Ca2+ fluctuations. Thus, fluctuations in the Ca2+ sensor’s state underlying the FPT distribution are only weakly affected by the fluctuations in the local Ca2+ concentration around its average, deterministically computable value.

RNA-Editing Enzyme ADAR1 p150 Isoform Is Critical for Germinal Center B Cell Response.

Adenosine deaminase acting on RNA (ADAR)1 is the principal enzyme for adenosine-to-inosine editing, an RNA modification-avoiding cytosolic nucleic acid sensor's activation triggered by endogenous dsRNAs. Two ADAR1 isoforms exist in mammals, a longer IFN-inducible and mainly cytoplasm-localized p150 isoform and a shorter constitutively expressed and primarily nucleus-localized p110 isoform. Studies of ADAR1 mutant mice have demonstrated that ADAR1 is essential for multiple physiological processes, including embryonic development, innate immune response, and B and T lymphocyte development. However, it remained unknown whether ADAR1 plays a role in the humoral immune response. In this study, we conditionally delete Adar1 in activated B cells and show that ADAR1-deficient mice have a defective T cell-dependent Ab response and diminished germinal center (GC) B cells. Using various double mutant mice concurrently deficient in ADAR1 and different downstream dsRNA sensors, we demonstrate that ADAR1 regulates the GC response by preventing hyperactivation of the melanoma differentiation-associated protein 5 (MDA5) but not the protein kinase R or RNase L pathway. We also show that p150 is exclusively responsible for ADAR1's function in the GC response, and the p110 isoform cannot substitute for the p150's role, even when p110 is constitutively expressed in the cytoplasm. We further demonstrated that the dsRNA-binding but not the RNA-editing activity is required for ADAR1's function in the GC response. Thus, our data suggest that the ADAR1 p150 isoform plays a crucial role in regulating the GC B cell response.