1,433 research outputs found
Mutual Guidance and Residual Integration for Image Enhancement
Previous studies show the necessity of global and local adjustment for image
enhancement. However, existing convolutional neural networks (CNNs) and
transformer-based models face great challenges in balancing the computational
efficiency and effectiveness of global-local information usage. Especially,
existing methods typically adopt the global-to-local fusion mode, ignoring the
importance of bidirectional interactions. To address those issues, we propose a
novel mutual guidance network (MGN) to perform effective bidirectional
global-local information exchange while keeping a compact architecture. In our
design, we adopt a two-branch framework where one branch focuses more on
modeling global relations while the other is committed to processing local
information. Then, we develop an efficient attention-based mutual guidance
approach throughout our framework for bidirectional global-local interactions.
As a result, both the global and local branches can enjoy the merits of mutual
information aggregation. Besides, to further refine the results produced by our
MGN, we propose a novel residual integration scheme following the
divide-and-conquer philosophy. The extensive experiments demonstrate the
effectiveness of our proposed method, which achieves state-of-the-art
performance on several public image enhancement benchmarks.Comment: 17 pages, 15 figure
From NeRFLiX to NeRFLiX++: A General NeRF-Agnostic Restorer Paradigm
Neural radiance fields (NeRF) have shown great success in novel view
synthesis. However, recovering high-quality details from real-world scenes is
still challenging for the existing NeRF-based approaches, due to the potential
imperfect calibration information and scene representation inaccuracy. Even
with high-quality training frames, the synthetic novel views produced by NeRF
models still suffer from notable rendering artifacts, such as noise and blur.
To address this, we propose NeRFLiX, a general NeRF-agnostic restorer paradigm
that learns a degradation-driven inter-viewpoint mixer. Specially, we design a
NeRF-style degradation modeling approach and construct large-scale training
data, enabling the possibility of effectively removing NeRF-native rendering
artifacts for deep neural networks. Moreover, beyond the degradation removal,
we propose an inter-viewpoint aggregation framework that fuses highly related
high-quality training images, pushing the performance of cutting-edge NeRF
models to entirely new levels and producing highly photo-realistic synthetic
views. Based on this paradigm, we further present NeRFLiX++ with a stronger
two-stage NeRF degradation simulator and a faster inter-viewpoint mixer,
achieving superior performance with significantly improved computational
efficiency. Notably, NeRFLiX++ is capable of restoring photo-realistic
ultra-high-resolution outputs from noisy low-resolution NeRF-rendered views.
Extensive experiments demonstrate the excellent restoration ability of
NeRFLiX++ on various novel view synthesis benchmarks.Comment: 17 pages, 16 figures. Project Page:
https://redrock303.github.io/nerflix_plus/. arXiv admin note: text overlap
with arXiv:2303.0691
CHST12: a potential prognostic biomarker related to the immunotherapy response in pancreatic adenocarcinoma
BackgroundPancreatic adenocarcinoma (PAAD) is characterized by lower immunogenicity with a poor response rate to immune checkpoint inhibitors (ICIs) and exhibits the poorest prognosis of all solid tumors, which results in the highest tumor-related mortality among malignancies. However, the underlying mechanisms are poorly understood. In addition, diverse carbohydrate sulfotransferases (CHSTs), which are involved in the sulfation process of these structures, play an important role in the metastatic spread of tumor cells. Aberrant glycosylation is beginning to emerge as an influencing factor in tumor immunity and immunotherapy. Therefore, it might serve as a biomarker of the immunotherapeutic response in tumors. The purpose of the study was to evaluate the role of CHST12 in PAAD prognosis and its relevance to the immunotherapeutic response.MethodsA comprehensive investigation of the interactions between CHST12 expression and the immune microenvironment as well as the clinical significance of CHST12 in PAAD was conducted. Data derived from the Cancer Genome Atlas (TCGA) database were analyzed using univariate and multivariate approaches, the Tumor Immune Estimation Resource (TIMER), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. Publicly available datasets were analyzed in this study. These data can be found on websites such as http://www.xiantao.love and https://www.proteinatlas.org. An assessment of the predictive value of CHST12 for PAAD prognosis was conducted using univariate and multivariate Cox regression analysis, Kaplan–Meier analysis, and nomograms. The TIMER algorithm calculates the proportions of six types of immune cells. The TIDE algorithm was used to indicate the characteristics of tumors that respond to ICI therapy.ResultsThe mRNA and protein levels of CHST12 showed the opposite trend. CHST12 mRNA expression was significantly upregulated in PAAD. According to Cox regression analysis, CHST12 RNA expression acts as a protective factor for overall survival [hazard ratio (HR), 0.617, P < 0.04]. Functional annotation indicated that CHST12-associated differentially expressed genes (DEGs) were related to the signaling activity of receptor tyrosine kinases and the regulation of ubiquitin-protein transferase. These are usually involved in tumor development and may be related to the treatment responses of immune checkpoint inhibitors (ICIs). There was significantly higher CHST12 mRNA expression in PAAD samples than in non-malignant samples.ConclusionsIn PAAD, elevated CHST12 mRNA expression might regulate immune cell infiltration into the tumor microenvironment (TME) and may predict clinical outcomes
Acute effects of vagus nerve stimulation parameters on gastric motility assessed with magnetic resonance imaging
BackgroundVagus nerve stimulation (VNS) is an emerging bioelectronic therapy for regulating food intake and controlling gastric motility. However, the effects of different VNS parameters and polarity on postprandial gastric motility remain incompletely characterized.MethodsIn anesthetized rats (N = 3), we applied monophasic electrical stimuli to the left cervical vagus and recorded compound nerve action potential (CNAP) as a measure of nerve response. We evaluated to what extent afferent or efferent pathway could be selectively activated by monophasic VNS. In a different group of rats (N = 13), we fed each rat a gadolinium- labeled meal and scanned the rat stomach with oral contrast- enhanced magnetic resonance imaging (MRI) while the rat was anesthetized. We evaluated the antral and pyloric motility as a function of pulse amplitude (0.13, 0.25, 0.5, 1 mA), width (0.13, 0.25, 0.5 ms), frequency (5, 10 Hz), and polarity of VNS.Key ResultsMonophasic VNS activated efferent and afferent pathways with about 67% and 82% selectivity, respectively. Primarily afferent VNS increased antral motility across a wide range of parameters. Primarily efferent VNS induced a significant decrease in antral motility as the stimulus intensity increased (R = - .93, P < .05 for 5 Hz, R = - .85, P < .05 for 10 Hz). The VNS with either polarity tended to promote pyloric motility to a greater extent given increasing stimulus intensity.Conclusions and InferencesMonophasic VNS biased toward the afferent pathway is potentially more effective for facilitating occlusive contractions than that biased toward the efferent pathway.We investigated a possible differential effect of primarily afferent versus efferent cervical VNS on gastric motility under a range of VNS parameters. Gastric MRI data revealed that primarily afferent VNS induced stronger antral contractions relative to primarily efferent VNS. These results could serve as an index for optimizing VNS parameters for promoting gastric motility. Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155957/1/nmo13853_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155957/2/nmo13853.pd
A signal processing approach for enriched region detection in RNA polymerase II ChIP-seq data
International audienc
Tris(piperazinediium) phosphatododecamolybo(V,VI)phosphate
The title compound, (C4H12N2)3[PMo12O40] or (H2pip)3[PMo12O40] (pip is piperazine), was prepared under hydrothermal conditions. The asymmetric unit contains one-sixth of a mixed-valent Mo(V,VI) pseudo-Keggin-type [PMo12O40]6− anion and half a piperazinediium cation, (H2pip)2+. The discrete Keggin-type [PMo12O40]6- anion has site symmetry and the three (H2pip)2+ cations each have site symmetry at the centres of the molecules. The central P atom is on special position , which is a roto-inversion position and generates the disorder of the PO4 tetrahedron. Furthermore, six doubly bridging oxide groups are also disordered with an occupancy factor of 0.5 for each O atom. The anions and cations are linked by an extensive network of intermolecular N—H⋯O and C—H⋯O hydrogen bonds
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