CO2 per se activates carbon dioxide receptors.

Carbon dioxide has been used in traps for more than six decades to monitor mosquito populations and help make informed vector management decisions. CO2 is sensed by gustatory receptors (GRs) housed in neurons in the maxillary palps. CO2-sensitive GRs have been identified from the vinegar fly and mosquitoes, but it remains to be resolved whether these receptors respond to CO2 or bicarbonate. As opposed to the vinegar fly, mosquitoes have three GR subunits, but it is assumed that subunits GR1 and GR3 form functional receptors. In our attempt to identify the chemical species that bind these receptors, we discovered that GR2 and GR3 are essential for receptor function and that GR1 appears to function as a modulator. While Xenopus oocytes coexpressing Culex quinquefasciatus subunits CquiGR1/3 and CquiGR1/2 were not activated, CquiGR2/3 gave robust responses to sodium bicarbonate. Interestingly, CquiGR1/2/3-coexpressing oocytes gave significantly lower responses. That the ternary combination is markedly less sensitive than the GR2/GR3 combination was also observed with orthologs from the yellow fever and the malaria mosquito. By comparing responses of CquiGR2/CquiGR3-coexpressing oocytes to sodium bicarbonate samples (with or without acidification) and measuring the concentration of aqueous CO2, we showed that there is a direct correlation between dissolved CO2 and receptor response. We then concluded that subunits GR2 and GR3 are essential for these carbon dioxide-sensitive receptors and that they are activated by CO2 per se, not bicarbonate

An Attention-based Multi-Scale Feature Learning Network for Multimodal Medical Image Fusion

Medical images play an important role in clinical applications. Multimodal medical images could provide rich information about patients for physicians to diagnose. The image fusion technique is able to synthesize complementary information from multimodal images into a single image. This technique will prevent radiologists switch back and forth between different images and save lots of time in the diagnostic process. In this paper, we introduce a novel Dilated Residual Attention Network for the medical image fusion task. Our network is capable to extract multi-scale deep semantic features. Furthermore, we propose a novel fixed fusion strategy termed Softmax-based weighted strategy based on the Softmax weights and matrix nuclear norm. Extensive experiments show our proposed network and fusion strategy exceed the state-of-the-art performance compared with reference image fusion methods on four commonly used fusion metrics.Comment: 8 pages, 8 figures, 3 table

Conceptual Study and Performance Analysis of Tandem Dual-Antenna Spaceborne SAR Interferometry

Multi-baseline synthetic aperture radar interferometry (MB-InSAR), capable of mapping 3D surface model with high precision, is able to overcome the ill-posed problem in the single-baseline InSAR by use of the baseline diversity. Single pass MB acquisition with the advantages of high coherence and simple phase components has a more practical capability in 3D reconstruction than conventional repeat-pass MB acquisition. Using an asymptotic 3D phase unwrapping (PU), it is possible to get a reliable 3D reconstruction using very sparse acquisitions but the interferograms should follow the optimal baseline design. However, current spaceborne SAR system doesn't satisfy this principle, inducing more difficulties in practical application. In this article, a new concept of Tandem Dual-Antenna SAR Interferometry (TDA-InSAR) system for single-pass reliable 3D surface mapping using the asymptotic 3D PU is proposed. Its optimal MB acquisition is analyzed to achieve both good relative height precision and flexible baseline design. Two indicators, i.e., expected relative height precision and successful phase unwrapping rate, are selected to optimize the system parameters and evaluate the performance of various baseline configurations. Additionally, simulation-based demonstrations are conducted to evaluate the performance in typical scenarios and investigate the impact of various error sources. The results indicate that the proposed TDA-InSAR is able to get the specified MB acquisition for the asymptotic 3D PU, which offers a feasible solution for single-pass 3D SAR imaging.Comment: 16 pages, 20 figure

The Effect of Consistency on Short-Term Memory for Scenes

Which is more detectable, the change of a consistent or an inconsistent object in a scene? This question has been debated for decades. We noted that the change of objects in scenes might simultaneously be accompanied with gist changes. In the present study we aimed to examine how the alteration of gist, as well as the consistency of the changed objects, modulated change detection. In Experiment 1, we manipulated the semantic content by either keeping or changing the consistency of the scene. Results showed that the changes of consistent and inconsistent scenes were equally detected. More importantly, the changes were more accurately detected when scene consistency changed than when the consistency remained unchanged, regardless of the consistency of the memory scenes. A phase-scrambled version of stimuli was adopted in Experiment 2 to decouple the possible confounding effect of low-level factors. The results of Experiment 2 demonstrated that the effect found in Experiment 1 was indeed due to the change of high-level semantic consistency rather than the change of low-level physical features. Together, the study suggests that the change of consistency plays an important role in scene short-term memory, which might be attributed to the sensitivity to the change of semantic content

Biogeographical Variation and Population Genetic Structure of Sporisorium scitamineum

A total of 100 Sporisorium scitamineum isolates were investigated by inter simple sequence repeat (ISSR) and single primer-sequence related amplified polymorphism (SP-SRAP) markers. These isolates were clearly assorted into three distinct clusters regardless of method used: either cluster analysis or by principal component analysis (PCA) of the ISSR, SP-SRAP, or ISSR + SP-SRAP data set. The total gene diversity (Ht) and gene diversity between subpopulations (Hs) were estimated to be 0.34 to 0.38 and 0.22 to 0.29, respectively, by analyzing separately the ISSR and SP-SRAP data sets, and to be 0.26–0.36 by analyzing ISSR + SP-SRAP data set. The gene diversity attributable to differentiation among populations (Gst) was estimated to be 0.35 and 0.22, and the gene flow (Nm) was 0.94 and 1.78, respectively, when analyzing separately ISSR and SP-SRAP data set, and was 0.27 and 1.33, respectively, when analyzing ISSR + SP-SRAP data set. Our study showed that there is considerable genetic variation in the analyzed 100 isolates, and the environmental heterogeneity has played an important role for this observed high degree of variation. The genetic differentiation of sugarcane smut fungus depends to a large extent on the heterogeneity of their habitats and is the result of long-term adaptations of pathogens to their ecological environments

SPHR-SAR-Net: Superpixel High-resolution SAR Imaging Network Based on Nonlocal Total Variation

High-resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolution SAR imaging algorithms face several challenges. Firstly, these algorithms tend to focus on local information, neglecting non-local information between different pixel patches. Secondly, speckle is more pronounced and difficult to filter out in high-resolution SAR images. Thirdly, the process of high-resolution SAR imaging generally involves high time and computational complexity, making real-time imaging difficult to achieve. To address these issues, we propose a Superpixel High-Resolution SAR Imaging Network (SPHR-SAR-Net) for rapid despeckling in high-resolution SAR mode. Based on the concept of superpixel techniques, we initially combine non-convex and non-local total variation as compound regularization. This approach more effectively despeckles and manages the relationship between pixels while reducing bias effects caused by convex constraints. Subsequently, we solve the compound regularization model using the Alternating Direction Method of Multipliers (ADMM) algorithm and unfold it into a Deep Unfolded Network (DUN). The network's parameters are adaptively learned in a data-driven manner, and the learned network significantly increases imaging speed. Additionally, the Deep Unfolded Network is compatible with high-resolution imaging modes such as spotlight, staring spotlight, and sliding spotlight. In this paper, we demonstrate the superiority of SPHR-SAR-Net through experiments in both simulated and real SAR scenarios. The results indicate that SPHR-SAR-Net can rapidly perform high-resolution SAR imaging from raw echo data, producing accurate imaging results

Dendritic cell immunoreceptor (DCIR) is associated with anti-cyclic citrullinated peptides (anti-CCP) antibody - negative rheumatoid arthritis in Chinese Han population

RheumatologySCI(E)CPCI-S(ISTP)0MEETING ABSTRACTnull1

Comparative Epigenomic Analysis of Murine and Human Adipogenesis

We report the generation and comparative analysis of genome-wide chromatin state maps, PPARγ and CTCF localization maps, and gene expression profiles from murine and human models of adipogenesis. The data provide high-resolution views of chromatin remodeling during cellular differentiation and allow identification of thousands of putative preadipocyte- and adipocyte-specific cis-regulatory elements based on dynamic chromatin signatures. We find that the specific locations of most such elements differ between the two models, including at orthologous loci with similar expression patterns. Based on sequence analysis and reporter assays, we show that these differences are determined, in part, by evolutionary turnover of transcription factor motifs in the genome sequences and that this turnover may be facilitated by the presence of multiple distal regulatory elements at adipogenesis-dependent loci. We also utilize the close relationship between open chromatin marks and transcription factor motifs to identify and validate PLZF and SRF as regulators of adipogenesis.National Institutes of Health (U.S.) (DK63906)American Diabetes Association (Career Development Award)Pennington Biomedical Research FoundationNORC Center (Grant #1P30 DK072476