ABSTRACT
Co-occurring mutations in KEAP1 in STK11/LKB1-mutant NSCLC activate NFE2L2/NRF2 to compensate for the loss of STK11-AMPK activity during metabolic adaptation. Characterizing the regulatory crosstalk between the STK11-AMPK and KEAP1-NFE2L2 pathways during metabolic stress is crucial for understanding the implications of co-occurring mutations. Here, we found that metabolic stress increased the expression and phosphorylation of SQSTM1/p62, which is essential for the activation of NFE2L2 and AMPK, synergizing antioxidant defense and tumor growth. The SQSTM1-driven dual activation of NFE2L2 and AMPK was achieved by inducing macroautophagic/autophagic degradation of KEAP1 and facilitating the AXIN-STK11-AMPK complex formation on the lysosomal membrane, respectively. In contrast, the STK11-AMPK activity was also required for metabolic stress-induced expression and phosphorylation of SQSTM1, suggesting a double-positive feedback loop between AMPK and SQSTM1. Mechanistically, SQSTM1 expression was increased by the PPP2/PP2A-dependent dephosphorylation of TFEB and TFE3, which was induced by the lysosomal deacidification caused by low glucose metabolism and AMPK-dependent proton reduction. Furthermore, SQSTM1 phosphorylation was increased by MAP3K7/TAK1, which was activated by ROS and pH-dependent secretion of lysosomal Ca2+. Importantly, phosphorylation of SQSTM1 at S24 and S226 was critical for the activation of AMPK and NFE2L2. Notably, the effects caused by metabolic stress were abrogated by the protons provided by lactic acid. Collectively, our data reveal a novel double-positive feedback loop between AMPK and SQSTM1 leading to the dual activation of AMPK and NFE2L2, potentially explaining why co-occurring mutations in STK11 and KEAP1 happen and providing promising therapeutic strategies for lung cancer.Abbreviations: AMPK: AMP-activated protein kinase; BAF1: bafilomycin A1; ConA: concanamycin A; DOX: doxycycline; IP: immunoprecipitation; KEAP1: kelch like ECH associated protein 1; LN: low nutrient; MAP3K7/TAK1: mitogen-activated protein kinase kinase kinase 7; MCOLN1/TRPML1: mucolipin TRP cation channel 1; MEFs: mouse embryonic fibroblasts; MTORC1: mechanistic target of rapamycin kinase complex 1; NAC: N-acetylcysteine; NFE2L2/NRF2: NFE2 like bZIP transcription factor 2; NSCLC: non-small cell lung cancer; PRKAA/AMPKα: protein kinase AMP-activated catalytic subunit alpha; PPP2/PP2A: protein phosphatase 2; ROS: reactive oxygen species; PPP3/calcineurin: protein phosphatase 3; RPS6KB1/p70S6K: ribosomal protein S6 kinase B1; SQSTM1/p62: sequestosome 1; STK11/LKB1: serine/threonine kinase 11; TCL: total cell lysate; TFEB: transcription factor EB; TFE3: transcription factor binding to IGHM enhancer 3; V-ATPase: vacuolar-type H+-translocating ATPase.
ABSTRACT
INTRODUCTION: We aimed to identify the clinical characteristics and risk factors for chronic immune thrombocytopenia (ITP) in patients with systemic lupus erythematosus (SLE). METHODS: We retrospectively reviewed patients diagnosed with SLE-associated ITP between January 2000 and December 2021. Patient characteristics were analyzed according to the progression of chronic thrombocytopenia. No response was defined as a platelet count <30 × 109/L or less than double the baseline count after treatment. Factors associated with chronic ITP were evaluated by logistic regression analysis. RESULTS: Among the 121 patients with SLE-associated ITP, 27 progressed to chronic ITP lasting more than 1 year after initial diagnosis. The median initial platelet count was significantly lower in patients with chronic thrombocytopenia than in those without the disease (16 vs. 51 × 109/L). Patients who did not achieve a response within 1 month of treatment exhibited a high probability of progressing to chronic ITP (55.6 vs. 22.3%, p < 0.001). Multivariable analysis revealed that severe thrombocytopenia at baseline (<20 × 109/L) (adjusted odds ratio [aOR] = 13.628, 95% confidence interval [CI] = 3.976-46.791) and no response within 1 month (aOR = 9.171, 95% CI = 2.776-30.298) were significantly associated with the risk of progression to chronic ITP in patients with SLE. Approximately one-quarter of the patients with SLE-associated ITP progressed to chronic ITP. CONCLUSION: Severe thrombocytopenia and failure to achieve a response within 1 month were risk factors for the development of chronic ITP in those patients.
ABSTRACT
The recent progress in the development of measurement systems for autonomous recognition had a substantial impact on emerging technology in numerous fields, especially robotics and automotive applications. In particular, time-of-flight (TOF) based light detection and ranging (LiDAR) systems enable to map the surrounding environmental information over long distances and with high accuracy. The combination of advanced LiDAR with an artificial intelligence platform allows enhanced object recognition and classification, which however still suffers from limitations of inaccuracy and misidentification. Recently, multi-spectral LiDAR systems have been employed to increase the object recognition performance by additionally providing material information in the short-wave infrared (SWIR) range where the reflection spectrum characteristics are typically very sensitive to material properties. However, previous multi-spectral LiDAR systems utilized band-pass filters or complex dispersive optical systems and even required multiple photodetectors, adding complexity and cost. In this work, we propose a time-division-multiplexing (TDM) based multi-spectral LiDAR system for semantic object inference by the simultaneous acquisition of spatial and spectral information. By utilizing the TDM method, we enable the simultaneous acquisition of spatial and spectral information as well as a TOF based distance map with minimized optical loss using only a single photodetector. Our LiDAR system utilizes nanosecond pulses of five different wavelengths in the SWIR range to acquire sufficient material information in addition to 3D spatial information. To demonstrate the recognition performance, we map the multi-spectral image from a human hand, a mannequin hand, a fabric gloved hand, a nitrile gloved hand, and a printed human hand onto an RGB-color encoded image, which clearly visualizes spectral differences as RGB color depending on the material while having a similar shape. Additionally, the classification performance of the multi-spectral image is demonstrated with a convolution neural network (CNN) model using the full multi-spectral data set. Our work presents a compact novel spectroscopic LiDAR system, which provides increased recognition performance and thus a great potential to improve safety and reliability in autonomous driving.
ABSTRACT
Red pepper powder (RPP) made from ground dried red pepper (Capsicum annuum L.) is prone to adulteration with fungal-spoiled RPP to gain unfair profits in Korea. This study aimed to investigate the effects of fungal infection on the ergosterol and phytosterol content of RPP and evaluate the potential of the sterol content as a marker for identifying fungal-spoiled RPP. Ergosterol was detected only in fungal-spoiled RPP and not in unspoiled RPP [Subject(s)
Capsicum
, Food Contamination
, Fungi
, Sterols
, Capsicum/microbiology
, Capsicum/chemistry
, Food Contamination/analysis
, Fungi/metabolism
, Fungi/isolation & purification
, Sterols/analysis
, Powders/chemistry
, Biomarkers/analysis
, Phytosterols/analysis
, Ergosterol/analysis
ABSTRACT
The colorimetric sensor-based electronic nose has been demonstrated to discriminate specific gaseous molecules for various applications, including health or environmental monitoring. However, conventional colorimetric sensor systems rely on RGB sensors, which cannot capture the complete spectral response of the system. This limitation can degrade the performance of machine learning analysis, leading to inaccurate identification of chemicals with similar functional groups. Here, we propose a novel time-resolved hyperspectral (TRH) data set from colorimetric array sensors consisting of 1D spatial, 1D spectral, and 1D temporal axes, which enables hierarchical analysis of multichannel 2D spectrograms via a convolution neural network (CNN). We assessed the outstanding classification performance of the TRH data set compared to an RGB data set by conducting a relative humidity (RH) concentration classification. The time-dependent spectral response of the colorimetric sensor was measured and trained as a CNN model using TRH and RGB sensor systems at different RH levels. While the TRH model shows a high classification accuracy of 97.5% for the RH concentration, the RGB model yields 72.5% under identical conditions. Furthermore, we demonstrated the detection of various functional volatile gases with the TRH system by using experimental and simulation approaches. The results reveal distinct spectral features from the TRH system, corresponding to changes in the concentration of each substance.
Subject(s)
Colorimetry , Electronic Nose , Neural Networks, Computer , Colorimetry/methods , Volatile Organic Compounds/analysisABSTRACT
Edible insects have a low environmental impact but are rich in nutrients and have been promoted as alternative protein sources. However, adding insect flour to bread negatively affects the overall quality, especially loaf volume and textural properties. Furthermore, relevant studies on chitin are limited. Therefore, this study examined chitin hydrolysis using lysozymes to enhance the quality characteristics in defatted mealworm (Tenebrio molitor L.) powder (DF-M)-supplemented bread. The chitin hydrolysis degree by lysozymes was evaluated using the 3,5-dinitrosalicylic acid assay and matrix-assisted laser desorption ionization-time-of-flight mass spectrometry. The amount of chitin oligomers increased with time, and no significant difference in the hydrolysis efficiency between water and 400 mM acetate buffer was observed. Enzymatic hydrolysis improved the DF-M water- and oil-binding and antioxidant capacities. In addition, chitin hydrolysis increased the volume and softened the texture of white bread. In particular, bread supplemented with DF-M hydrolyzed for 4 h at 10 % had the highest moisture content among the mealworm-added bread groups during storage for 5 days. Moreover, sensory evaluation showed a positive effect of chitin hydrolysis on acceptability. Our findings indicate that chitin hydrolysis can improve the quality of bread containing insect additives. In conclusion, this study provides novel insights into producing high-quality and functional bakery products from edible insects by the enzymatic hydrolysis of edible insect powders and could expand the applications of edible insects as food ingredients.
ABSTRACT
We present near-perfect sound absorption using a metasurface composed of meta-atoms (MAs) which are subwavelength Helmholtz resonators (HRs) with cavities non-uniformly partitioned by membranes. By embedding the membranes at different horizontal locations in the cavities, we break geometrical symmetry between the MAs so as to derive hybrid resonance between the MAs at our target frequency. The resonance frequency of each MA is determined by delicately adjusting the locations of the membranes, resulting in perfect absorption at the target frequency which is different from the resonance frequencies of MAs. The metasurface is designed to satisfy impedance matching conditions with air at one or more target frequencies with the aid of a theoretical model for frequency-dependent effective acoustic impedance. The theoretical model is established with physical reality by considering the higher-order eigenmodes of the membrane, the visco-thermal losses in narrow orifices, and the end corrections of the subwavelength HR. The designed metasurface is fabricated and its absorption performance is verified experimentally in an impedance tube. Near-perfect absorption of sound is achieved at the target frequency of 500 Hz, which is 12.3% lower than that of near-perfect absorption by previous metasurfaces inducing hybrid resonance between HRs without membranes.
ABSTRACT
With the increasing number of people affected by gluten consumption-related diseases, adhering to a gluten-free (GF) diet is the most effective preventive measure. Herein, we aimed to isolate and characterize the functional properties of autochthonous lactic acid bacteria (LAB) and yeast from various GF sourdoughs to determine their suitability in starter cultures for sourdough preparation. Three LAB, Weissella confusa BAQ2, Lactobacillus brevis AQ2, Leuconostoc citreum YC2, and Saccharomyces cerevisiae BW1, were identified. The isolated LAB exhibited greater TTA, faster acidification rates, and higher acid tolerance than commercial LAB. W. confusa BAQ2 exhibited the highest EPS production, W. confusa BAQ2 and L. brevis AQ2 showed high maltose utilization, and S. cerevisiae BW1 exhibited the highest CO2 production rate. Accordingly, all four microbial strains were mixed for the starter culture. The sourdough prepared with starter cultures exhibited differences in gas production depending on fermentation time, which influenced the volume of GF bread dough. GF bread prepared with fermented sourdough exhibited a 16% higher specific volume and enhanced crumb firmness and elasticity than that prepared using non-fermented sourdough. Thus, autochthonous LAB strains isolated from various GF sourdoughs can be used together to improve the quality of sourdough bread, demonstrating their potential for use in starter cultures for GF sourdough production.