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Article ; Online: Simulation of Folding Kinetics for Aligned RNAs.

Huang, Jiabin / Voß, Björn

2021 Volume 12, Issue 3

Abstract: Studying the folding kinetics of an RNA can provide insight into its function and is thus a valuable method for RNA analyses. Computational approaches to the simulation of folding kinetics suffer from the exponentially large folding space that needs to ... ...

Abstract	Studying the folding kinetics of an RNA can provide insight into its function and is thus a valuable method for RNA analyses. Computational approaches to the simulation of folding kinetics suffer from the exponentially large folding space that needs to be evaluated. Here, we present a new approach that combines structure abstraction with evolutionary conservation to restrict the analysis to common parts of folding spaces of related RNAs. The resulting algorithm can recapitulate the folding kinetics known for single RNAs and is able to analyse even long RNAs in reasonable time. Our program RNAliHiKinetics is the first algorithm for the simulation of consensus folding kinetics and addresses a long-standing problem in a new and unique way.
MeSH term(s)	Algorithms ; Computer Simulation ; Kinetics ; Models, Chemical ; Nucleic Acid Conformation ; RNA/chemistry ; RNA/genetics
Chemical Substances	RNA (63231-63-0)
Language	English
Publishing date	2021-02-26
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2527218-4
ISSN	2073-4425 ; 2073-4425
ISSN (online)	2073-4425
ISSN	2073-4425
DOI	10.3390/genes12030347
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A Multiscale Approach to Deep Blind Image Quality Assessment.

Liu, Manni / Huang, Jiabin / Zeng, Delu / Ding, Xinghao / Paisley, John

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

2023 Volume PP

Abstract: Faithful measurement of perceptual quality is of significant importance to various multimedia applications. By fully utilizing reference images, full-reference image quality assessment (FR-IQA) methods usually achieves better prediction performance. On ... ...

Abstract	Faithful measurement of perceptual quality is of significant importance to various multimedia applications. By fully utilizing reference images, full-reference image quality assessment (FR-IQA) methods usually achieves better prediction performance. On the other hand, no-reference image quality assessment (NR-IQA), also known as blind image quality assessment (BIQA), which does not consider the reference image, makes it a challenging but important task. Previous NR-IQA methods have focused on spatial measures at the expense of information in the available frequency bands. In this paper, we present a multiscale deep blind image quality assessment method (BIQA, M.D.) with spatial optimal-scale filtering analysis. Motivated by the multi-channel behavior of the human visual system and contrast sensitivity function, we decompose an image into a number of spatial frequency bands by multiscale filtering and extract features for mapping an image to its subjective quality score by applying convolutional neural network. Experimental results show that BIQA, M.D. compares well with existing NR-IQA methods and generalizes well across datasets.
Language	English
Publishing date	2023-02-28
Publishing country	United States
Document type	Journal Article
ISSN	1941-0042
ISSN (online)	1941-0042
DOI	10.1109/TIP.2023.3245991
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Grounded Text-to-Image Synthesis with Attention Refocusing

Phung, Quynh / Ge, Songwei / Huang, Jia-Bin

2023

Abstract: Driven by the scalable diffusion models trained on large-scale datasets, text-to-image synthesis methods have shown compelling results. However, these models still fail to precisely follow the text prompt involving multiple objects, attributes, or ... ...

Abstract	Driven by the scalable diffusion models trained on large-scale datasets, text-to-image synthesis methods have shown compelling results. However, these models still fail to precisely follow the text prompt involving multiple objects, attributes, or spatial compositions. In this paper, we reveal the potential causes in the diffusion model's cross-attention and self-attention layers. We propose two novel losses to refocus attention maps according to a given spatial layout during sampling. Creating the layouts manually requires additional effort and can be tedious. Therefore, we explore using large language models (LLM) to produce these layouts for our method. We conduct extensive experiments on the DrawBench, HRS, and TIFA benchmarks to evaluate our proposed method. We show that our proposed attention refocusing effectively improves the controllability of existing approaches. Comment: Project page: https://attention-refocusing.github.io/
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2023-06-08
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: First case of bloodstream infection caused by

Both, Anna / Huang, Jiabin / Wenzel, Philipp / Aepfelbacher, Martin / Rohde, Holger / Christner, Martin / Hentschke, Moritz

New microbes and new infections

2023 Volume 53, Page(s) 101117

Abstract: Members of ... ...

Abstract	Members of the
Language	English
Publishing date	2023-03-28
Publishing country	England
Document type	Journal Article
ZDB-ID	2750179-6
ISSN	2052-2975
ISSN	2052-2975
DOI	10.1016/j.nmni.2023.101117
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Article ; Online: A bacterial effector protein promotes nuclear translocation of Stat3 to induce IL-10.

Berneking, Laura / Bekere, Indra / Rob, Sören / Schnapp, Marie / Huang, Jiabin / Ruckdeschel, Klaus / Aepfelbacher, Martin

European journal of cell biology

2023 Volume 102, Issue 4, Page(s) 151364

Abstract: The multifunctional Yersinia effector YopM inhibits effector triggered immunity and increases production of the anti-inflammatory cytokine Interleukin-10 (IL-10) to suppress the host immune response. Previously it was shown that YopM induces IL-10 gene ... ...

Abstract	The multifunctional Yersinia effector YopM inhibits effector triggered immunity and increases production of the anti-inflammatory cytokine Interleukin-10 (IL-10) to suppress the host immune response. Previously it was shown that YopM induces IL-10 gene expression by elevating phosphorylation of the serine-threonine kinase RSK1 in the nucleus of human macrophages. Using transcriptomics, we found that YopM strongly affects expression of genes belonging to the JAK-STAT signaling pathway. Further analysis revealed that YopM mediates nuclear translocation of the transcription factor Stat3 in Y. enterocolitica infected macrophages and that knockdown of Stat3 inhibited YopM-induced IL-10 gene expression. YopM-induced Stat3 translocation did not depend on autocrine IL-10, activation of RSK1 or tyrosine phosphorylation of Stat3. Thus, besides activation of RSK1, stimulation of nuclear translocation of Stat3 is another mechanism by which YopM increases IL-10 gene expression in macrophages.
MeSH term(s)	Humans ; Bacterial Proteins/genetics ; Bacterial Proteins/metabolism ; Interleukin-10/genetics ; Interleukin-10/metabolism ; Bacterial Outer Membrane Proteins/genetics ; Bacterial Outer Membrane Proteins/metabolism ; Macrophages/metabolism ; Gene Expression Regulation ; STAT3 Transcription Factor/genetics ; STAT3 Transcription Factor/metabolism ; Phosphorylation
Chemical Substances	Bacterial Proteins ; Interleukin-10 (130068-27-8) ; Bacterial Outer Membrane Proteins ; STAT3 Transcription Factor
Language	English
Publishing date	2023-10-02
Publishing country	Germany
Document type	Journal Article
ZDB-ID	391967-5
ISSN	1618-1298 ; 0070-2463 ; 0171-9335
ISSN (online)	1618-1298
ISSN	0070-2463 ; 0171-9335
DOI	10.1016/j.ejcb.2023.151364
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Association of Homocysteine Level with Adverse Outcomes in Patients with Acute Ischemic Stroke: A Meta-Analysis.

Zhang, Heng / Huang, Jiabin / Zhou, Yongjing / Fan, Yu

Current medicinal chemistry

2021 Volume 28, Issue 36, Page(s) 7583–7591

Abstract: Background: Studies on the prognostic value of homocysteine level have yielded controversial results in patients with acute ischemic stroke (AIS). The aim of this meta-analysis was to evaluate the prognostic utility of homocysteine among patients with ... ...

Abstract	Background: Studies on the prognostic value of homocysteine level have yielded controversial results in patients with acute ischemic stroke (AIS). The aim of this meta-analysis was to evaluate the prognostic utility of homocysteine among patients with AIS in terms of recurrent stroke, poor functional outcome or all-cause mortality. Methods: Two independent authors searched the articles published in PubMed and Embase databases prior to March 31, 2020. Original studies that investigated the value of homocysteine level in predicting recurrent stroke, poor functional outcome (modified Rankin Scale ≥ 3) or all-cause mortality in AIS patients were eligible. Results: Eleven articles (10 studies) that enrolled 19,435 patients with AIS were included. Meta-analysis indicated that the patients with the highest homocysteine level had an increased risk of all-cause mortality (risk ratio [RR] 1.40; 95% confidence interval [CI] 1.26-1.55). However, elevated homocysteine level was not significantly associated with recurrent stroke (RR 1.28; 95% CI 0.99-1.65) or poor functional outcome (RR 1.71; 95% CI 0.77-3.83). Conclusion: Elevated homocysteine level is independently associated with a higher risk of all-cause mortality but not recurrent stroke or poor functional outcome in patients with AIS. However, additional well-designed studies are required to confirm the findings of this meta-analysis.
MeSH term(s)	Brain Ischemia ; Homocysteine ; Humans ; Ischemic Stroke ; Prognosis ; Stroke
Chemical Substances	Homocysteine (0LVT1QZ0BA)
Language	English
Publishing date	2021-05-12
Publishing country	United Arab Emirates
Document type	Meta-Analysis
ZDB-ID	1319315-6
ISSN	1875-533X ; 0929-8673
ISSN (online)	1875-533X
ISSN	0929-8673
DOI	10.2174/0929867328666210419131016
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Zs.A 4432: Show issues

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Article ; Online: Transcriptomic analysis of differentially alternative splicing patterns in mice with inflammatory and neuropathic pain.

Zhai, Mingzhu / Huang, Jiabin / Yang, Shaomin / Li, Na / Zeng, Jun / Zheng, Yi / Sun, Wuping / Wu, Benqing

Molecular pain

2024 Volume 20, Page(s) 17448069241249455

Abstract: Although the molecular mechanisms of chronic pain have been extensively studied, a global picture of alternatively spliced genes and events in the peripheral and central nervous systems of chronic pain is poorly understood. The current study analyzed the ...

Abstract	Although the molecular mechanisms of chronic pain have been extensively studied, a global picture of alternatively spliced genes and events in the peripheral and central nervous systems of chronic pain is poorly understood. The current study analyzed the changing pattern of alternative splicing (AS) in mouse brain, dorsal root ganglion, and spinal cord tissue under inflammatory and neuropathic pain. In total, we identified 6495 differentially alternatively spliced (DAS) genes. The molecular functions of shared DAS genes between these two models are mainly enriched in calcium signaling pathways, synapse organization, axon regeneration, and neurodegeneration disease. Additionally, we identified 509 DAS in differentially expressed genes (DEGs) shared by these two models, accounting for a small proportion of total DEGs. Our findings supported the hypothesis that the AS has an independent regulation pattern different from transcriptional regulation. Taken together, these findings indicate that AS is one of the important molecular mechanisms of chronic pain in mammals. This study presents a global description of AS profile changes in the full path of neuropathic and inflammatory pain models, providing new insights into the underlying mechanisms of chronic pain and guiding genomic clinical diagnosis methods and rational medication.
MeSH term(s)	Animals ; Neuralgia/genetics ; Neuralgia/metabolism ; Alternative Splicing/genetics ; Inflammation/genetics ; Gene Expression Profiling ; Transcriptome/genetics ; Mice, Inbred C57BL ; Male ; Ganglia, Spinal/metabolism ; Mice ; Spinal Cord/metabolism ; Spinal Cord/pathology ; Gene Expression Regulation ; Disease Models, Animal
Language	English
Publishing date	2024-04-08
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2174252-2
ISSN	1744-8069 ; 1744-8069
ISSN (online)	1744-8069
ISSN	1744-8069
DOI	10.1177/17448069241249455
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Expressive Text-to-Image Generation with Rich Text

Ge, Songwei / Park, Taesung / Zhu, Jun-Yan / Huang, Jia-Bin

2023

Abstract: Plain text has become a prevalent interface for text-to-image synthesis. However, its limited customization options hinder users from accurately describing desired outputs. For example, plain text makes it hard to specify continuous quantities, such as ... ...

Abstract	Plain text has become a prevalent interface for text-to-image synthesis. However, its limited customization options hinder users from accurately describing desired outputs. For example, plain text makes it hard to specify continuous quantities, such as the precise RGB color value or importance of each word. Furthermore, creating detailed text prompts for complex scenes is tedious for humans to write and challenging for text encoders to interpret. To address these challenges, we propose using a rich-text editor supporting formats such as font style, size, color, and footnote. We extract each word's attributes from rich text to enable local style control, explicit token reweighting, precise color rendering, and detailed region synthesis. We achieve these capabilities through a region-based diffusion process. We first obtain each word's region based on attention maps of a diffusion process using plain text. For each region, we enforce its text attributes by creating region-specific detailed prompts and applying region-specific guidance, and maintain its fidelity against plain-text generation through region-based injections. We present various examples of image generation from rich text and demonstrate that our method outperforms strong baselines with quantitative evaluations. Comment: ICCV 2023. Project webpage: https://rich-text-to-image.github.io/
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Graphics ; Computer Science - Machine Learning
Subject code	004
Publishing date	2023-04-13
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Temporally Consistent Semantic Video Editing

Xu, Yiran / AlBahar, Badour / Huang, Jia-Bin

2022

Abstract: Generative adversarial networks (GANs) have demonstrated impressive image generation quality and semantic editing capability of real images, e.g., changing object classes, modifying attributes, or transferring styles. However, applying these GAN-based ... ...

Abstract	Generative adversarial networks (GANs) have demonstrated impressive image generation quality and semantic editing capability of real images, e.g., changing object classes, modifying attributes, or transferring styles. However, applying these GAN-based editing to a video independently for each frame inevitably results in temporal flickering artifacts. We present a simple yet effective method to facilitate temporally coherent video editing. Our core idea is to minimize the temporal photometric inconsistency by optimizing both the latent code and the pre-trained generator. We evaluate the quality of our editing on different domains and GAN inversion techniques and show favorable results against the baselines. Comment: Project page: https://video-edit-gan.github.io/
Keywords	Computer Science - Computer Vision and Pattern Recognition
Publishing date	2022-06-21
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-Segmentation.

Chen, Yun-Chun / Lin, Yen-Yu / Yang, Ming-Hsuan / Huang, Jia-Bin

IEEE transactions on pattern analysis and machine intelligence

2021 Volume 43, Issue 10, Page(s) 3632–3647

Abstract: We present an approach for jointly matching and segmenting object instances of the same category within a collection of images. In contrast to existing algorithms that tackle the tasks of semantic matching and object co-segmentation in isolation, our ... ...

Abstract	We present an approach for jointly matching and segmenting object instances of the same category within a collection of images. In contrast to existing algorithms that tackle the tasks of semantic matching and object co-segmentation in isolation, our method exploits the complementary nature of the two tasks. The key insights of our method are two-fold. First, the estimated dense correspondence fields from semantic matching provide supervision for object co-segmentation by enforcing consistency between the predicted masks from a pair of images. Second, the predicted object masks from object co-segmentation in turn allow us to reduce the adverse effects due to background clutters for improving semantic matching. Our model is end-to-end trainable and does not require supervision from manually annotated correspondences and object masks. We validate the efficacy of our approach on five benchmark datasets: TSS, Internet, PF-PASCAL, PF-WILLOW, and SPair-71k, and show that our algorithm performs favorably against the state-of-the-art methods on both semantic matching and object co-segmentation tasks.
Language	English
Publishing date	2021-09-03
Publishing country	United States
Document type	Journal Article
ISSN	1939-3539
ISSN (online)	1939-3539
DOI	10.1109/TPAMI.2020.2985395
Database	MEDical Literature Analysis and Retrieval System OnLINE

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