Iron Uptake via DMT1 Integrates Cell Cycle with JAK-STAT3 Signaling to Promote Colorectal Tumorigenesis

Dietary iron intake and systemic iron balance are implicated in colorectal cancer (CRC) development, but the means by which iron contributes to CRC are unclear. Gene expression and functional studies demonstrated that the cellular iron importer, divalent metal transporter 1 (DMT1), is highly expressed in CRC through hypoxia-inducible factor 2alpha-dependent transcription. Colon-specific Dmt1 disruption resulted in a tumor-selective inhibitory effect of proliferation in mouse colon tumor models. Proteomic and genomic analyses identified an iron-regulated signaling axis mediated by cyclin-dependent kinase 1 (CDK1), JAK1, and STAT3 in CRC progression. A pharmacological inhibitor of DMT1 antagonized the ability of iron to promote tumor growth in a CRC mouse model and a patient-derived CRC enteroid orthotopic model. Our studies implicate a growth-promoting signaling network instigated by elevated intracellular iron levels in tumorigenesis, offering molecular insights into how a key dietary component may contribute to CRC

Comparison of Satellite Repeat Shift Time for GPS, BDS, and Galileo Navigation Systems by Three Methods

The characteristic of the satellite repeat shift time can reflect the status of the satellite operation, and is also one of the key factors of the sidereal filtering multipath correction. Although some methods have been developed to calculate the repeat shift time, few efforts have been made to analyze and compare the performance of this feature for the GPS (Global Positioning System), BDS (BeiDou System), and Galileo in depth. Hence, three methods used for calculating the repeat shift time are presented, and used to compare and analyze the three global systems in depth, named the broadcast ephemeris method (BEM), correlation coefficient method (CCM), and aspect repeat time method (ARTM). The experiment results show that the repeat shift time of each satellite is different. Also, the difference between the maximum and minimum varies from different systems. The maximum difference is about 25 s for the BDS IGSO (Inclined Geosynchronous Orbit) and the minimum is merely 10 s for the GPS system. Furthermore, for the same satellite, the shift time calculated by the three methods is almost identical, and the maximum difference is only about 7 s between the CCM and the ARTM method for the BDS MEO (Medium Earth Orbit) satellite. Although the repeat shift time is different daily for the same satellite and the same method, the changes are very small. Moreover, in terms of the STD (Standard Deviation) of the BS (between satellites) and MS (mean shift for the same satellite), the GPS system is the best, the performance of the BDS system is medium, and the Galileo performs slightly worse than the GPS and BDS

Analysis of the Influence of Flood on the L4 Combination Observation of GPS and GLONASS Satellites

With global warming, extreme weather such as floods and waterlogging occurs more frequently and seriously in recent years. During the flood, the surrounding environment of the GNSS (Global Navigation Satellite System) station will change as the volume of water increases. Considering the multipath error is directly relevant to the observation environment, thus, the influence of flood on the L4 combination observation (a geometry-free ionosphere-free linear combination of carrier phase) which is related to the multipath error of GPS (Global Positioning System) and GLONASS satellites is investigated in depth. In addition, the ground track repetition periods of GPS and GLONASS satellites are analyzed in the sky plot to illustrate the rationality of chosen reference day. Based on the results of the satellite sky plot, one and eight days are adopted to demonstrate the influence of flood on L4 combination observation for GPS and GLONASS satellites, respectively. Real data sets collected at the ZHNZ GNSS observation station during the flood from DOY (Day of Year) 193 to DOY 204, 2021 are used. Experimental results show that the flood has a significant impact on the L4 combination observation of GPS and GLONASS satellites, and the fluctuation of L4 under flood performs much larger than that of without flood. For GPS satellites, the maximum RMS (root mean square) increase rate of L4 under flood is approximately 186.67% on the G31 satellite. Even for the minimum RMS increase rate, it can reach approximately 23.52%, which is the G02 satellite. Moreover, the average RMS increase rate of GPS and GLONASS satellites can reach approximately 109.53% and 43.65%, respectively. In addition, the influence of rainfall and hardware device are also investigated, which can further demonstrate that the fluctuation of L4 is mainly caused by the flood but not by the rainfall and hardware device elements. Thus, based on the above results, the influence of flood on L4 observation should be taken into account during the applications of L4 used, such as the retrieval of soil moisture and vegetation water content based on GNSS L4 combination observation

Theory and Experiment Analysis on the Influence of Floods on a GNSS Pseudo-Range Multipath and CNR Signal Based on Two Cases Study in China

The surrounding environment of a GNSS observation station is changed during a flood, and this results in a more serious multipath than in a normal environment. Considering that the multipath error is largely related to the pseudo-range multipath and CNR (Carrier-to-noise ratio) of the GNSS signal, the influence of floods on a pseudo-range multipath and CNR is analyzed in theory and through experiment. To ensure the accuracy of the analysis results, the ground track repeat period of GPS, GLONASS, and BDS satellites is investigated from the perspective of theory and skyplots. Two real cases study collected in Zhengzhou and Xinxiang, China, in 2021, are used to demonstrate the influence of floods on a pseudo-range multipath and CNR in detail. Experimental results show that the pseudo-range multipath of a GPS satellite performs more seriously during a flood. The maximum RMS increase rate is approximately 17.85%, and the average of all other satellites with a whole arc is approximately 6.55%. In addition, the CNR of three GNSS systems performs a decrease during a flood. For GPS and GLONASS satellites, the decrease performs more seriously at a high elevation angle than that at a low elevation angle. The maximum decrease is approximately 5 dB-Hz for the GPS satellite and approximately 7 dB-Hz for the GLONASS satellite. In terms of the BDS system, the CNR of all three orbital type satellites decreases during a flood. The average decrease is approximately 2 dB-Hz for BDS MEO and GEO satellites, and about 1 dB-Hz for the BDS IGSO satellite

Accurate Retrieval of the Whole Flood Process from Occurrence to Recession Based on GPS Original CNR, Fitted CNR, and Seamless CNR Series

The CNR (Carrier-to-Noise Ratio) of GPS (Global Positioning System) satellites is highly relevant to the multipath error. The multipath error is more serious in the flood environment since the reflection and diffraction coefficients of water are much higher compared to dry soil. Thus, the amplitude of CNR will decrease in the flood environment. In this study, the relationship between multipath error, flooding, and CNR is introduced in theory. Then, by using the characteristic of the orbital repetition period, the stability of CNR between 2 adjacent days in a static observation environment is demonstrated by 32 MGEX (Multi-GNSS Experiment) stations in different latitude and longitude regions of the world. The results show that the average RMS of different CNRs between two adjacent days is only about 0.62 dB-Hz. In addition, the correlation coefficient of CNRs between two adjacent days is analyzed. The correlation coefficient of the original signal CNR is 0.997. Moreover, after mitigating the influence of random noise and lower CNR, the correlation coefficients of the fitted CNRs larger than 40 dB-Hz can reach 0.999. Thus, based on the fluctuation in original CNR, fitted CNR, and seamless series characteristics of CNR, the whole flood process from occurrence to recession can be retrieved. A flood that occurred in Zhengzhou City, China, from DOY 200 to DOY 202, 2021 is used to demonstrate the process of retrieval. The experimental results indicate that the flood appeared at about 15:30 pm on DOY 200, reached a peak at approximately 8:30 am on DOY 202, and totally subsided at about 10:00 am on DOY 202. In conclusion, the CNR can be effectively used to retrieve the whole process of the flood, which lays a foundation for researching flood detection and warning based on GPS satellites

An improved triple‐frequency cycle slip detection and repair method based on wavelet packet transform and adaptive threshold for BeiDou System satellite

Abstract Cycle slip detection and repair is one of the key factors of Global Navigation Satellite System carrier phase high precision positioning. Although various methods have been proposed to detect and repair the cycle slip, they are still limited by kinds of factors and the effect is not ideal, especially in real‐time triple‐frequency high precise positioning applications for BeiDou Systems (BDSs). Traditional methods only improve the algorithm from the detection level, but the observation level and the threshold of detection always be ignored. Research indicates that the noise of observation seriously affects the success rate of cycle slip detection, and the threshold of detection largely depends on the satellite type and data sampling rate. A new triple‐frequency cycle slip detection and repair method, based on wavelet packet transform and adaptive threshold strategy, is proposed to detect and repair the cycle slip for real‐time BDS triple‐frequency positioning applications. The key idea of the proposed method is the use of both the wavelet packet transform and elevation model to mitigate random noise and the satellite‐induced code bias from the observation level, and the adaptive threshold strategy to adjust the threshold of detection based on satellite type and data sampling rate in the detection level. Real datasets are collected to evaluate the performance of the proposed method. Experimental results indicated that the proposed method can effectively detect and repair all types of cycle slips, such as single‐frequency small cycle slip, large cycle slip, and particular cycle slip, improve the success rate and reliability, and lay a solid foundation for BDS high‐precision positioning

HA-Unet: A Modified Unet Based on Hybrid Attention for Urban Water Extraction in SAR Images

Urban water plays a significant role in the urban ecosystem, but urban water extraction is still a challenging task in automatic interpretation of synthetic aperture radar (SAR) images. The influence of radar shadows and strong scatters in urban areas may lead to misclassification in urban water extraction. Nevertheless, the local features captured by convolutional layers in Convolutional Neural Networks (CNNs) are generally redundant and cannot make effective use of global information to guide the prediction of water pixels. To effectively emphasize the identifiable water characteristics and fully exploit the global information of SAR images, a modified Unet based on hybrid attention mechanism is proposed to improve the performance of urban water extraction in this paper. Considering the feature extraction ability and the global modeling capability in SAR image segmentation, the Channel and Spatial Attention Module (CSAM) and the Multi-head Self-Attention Block (MSAB) are both introduced into the proposed Hybrid Attention Unet (HA-Unet). In this work, Resnet50 is adopted as the backbone of HA-Unet to extract multi-level features of SAR images. During the feature extraction process, CSAM based on local attention is adopted to enhance the meaningful water features and ignore unnecessary features adaptively in feature maps of two shallow layers. In the last two layers of the backbone, MSAB is introduced to capture the global information of SAR images to generate global attention. In addition, two global attention maps generated by MSAB are aggregated together to reconstruct the spatial feature relationship of SAR images from high-resolution feature maps. The experimental results on Sentinel-1A SAR images show that the proposed urban water extraction method has a strong ability to extract water bodies in the complex urban areas. The ablation experiment and visualization results vividly indicate that both CSAM and MSAB contribute significantly to extracting urban water accurately and effectively

E-Region Field-Aligned Irregularities in the Middle of a Solar Eclipse Observed by a Bistatic Radar

The Wuhan Ionospheric Oblique Backscatter Sounding System (WIOBSS) was applied as a bistatic radar to record the ionospheric E-region responses to a solar eclipse on 22 July 2009. The transmitter was located in Wuhan and the receiver was located in Huaian. The receiver observed anomalous echoes with larger Doppler shifts at the farther ranges compared with the echoes reflected by Es. According to the simulated ray propagation paths of the reflected and scattered waves, we considered that the anomalous echoes were scattered by E-region field-aligned irregularities (FAIs). The locations of the FAIs recorded by the WIOBSS were estimated with the International Geomagnetic Reference Field (IGRF) and the observed propagation parameters. These irregularities occurred at around the eclipse maximum and lasted for ~20–40 min. The steep plasma density gradient induced by the fast drop photo ionization under the lunar shadow was beneficial to the occurrence of gradient drift instability to generate the FAIs. They were different from the gravity wave-induced irregularities occurring in the recovery phase of the solar eclipse

HA-Unet: A Modified Unet Based on Hybrid Attention for Urban Water Extraction in SAR Images

Urban water plays a significant role in the urban ecosystem, but urban water extraction is still a challenging task in automatic interpretation of synthetic aperture radar (SAR) images. The influence of radar shadows and strong scatters in urban areas may lead to misclassification in urban water extraction. Nevertheless, the local features captured by convolutional layers in Convolutional Neural Networks (CNNs) are generally redundant and cannot make effective use of global information to guide the prediction of water pixels. To effectively emphasize the identifiable water characteristics and fully exploit the global information of SAR images, a modified Unet based on hybrid attention mechanism is proposed to improve the performance of urban water extraction in this paper. Considering the feature extraction ability and the global modeling capability in SAR image segmentation, the Channel and Spatial Attention Module (CSAM) and the Multi-head Self-Attention Block (MSAB) are both introduced into the proposed Hybrid Attention Unet (HA-Unet). In this work, Resnet50 is adopted as the backbone of HA-Unet to extract multi-level features of SAR images. During the feature extraction process, CSAM based on local attention is adopted to enhance the meaningful water features and ignore unnecessary features adaptively in feature maps of two shallow layers. In the last two layers of the backbone, MSAB is introduced to capture the global information of SAR images to generate global attention. In addition, two global attention maps generated by MSAB are aggregated together to reconstruct the spatial feature relationship of SAR images from high-resolution feature maps. The experimental results on Sentinel-1A SAR images show that the proposed urban water extraction method has a strong ability to extract water bodies in the complex urban areas. The ablation experiment and visualization results vividly indicate that both CSAM and MSAB contribute significantly to extracting urban water accurately and effectively