Article
Biochemical Research Methods
Hsin-Yen Larry Wu, Polly Yingshan Hsu
Summary: This study describes a custom library construction method for super-resolution Ribo-seq in Arabidopsis, which can be applied to study genome-wide mRNA translation.
Article
Biochemical Research Methods
Alexander L. Cope, Felicity Anderson, John Favate, Michael Jackson, Amanda Mok, Anna Kurowska, Junchen Liu, Emma MacKenzie, Vikram Shivakumar, Peter Tilton, Sophie M. Winterbourne, Siyin Xue, Kostas Kavoussanakis, Liana F. Lareau, Premal Shah, Edward W. J. Wallace
Summary: riboviz 2 is an updated software package for comprehensive analysis and visualization of Ribo-seq data. It utilizes the Nextflow workflow management system for end-to-end processing and has been extensively tested on diverse species and library preparation strategies.
Article
Biochemical Research Methods
Mingzhe Xie, Ludong Yang, Gennong Chen, Yan Wang, Zhi Xie, Hongwei Wang
Summary: RiboChat is an interactive web platform for analyzing and annotating Ribo-seq data, which enables convenient decoding of translation information embedded within the data. It features a user-friendly interface and a cloud computing service, utilizing a chat conversation style to analyze data and find the best-matching analytics module.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Multidisciplinary Sciences
Suqin Cheng, Zhijie Xue, Can Li, Yufeng Liu, Longjun Xiang, Youqi Ke, Kaking Yan, Shiyong Wang, Ping Yu
Summary: This study successfully synthesized high-spin triangulene trimers on Au(111) through a surface-assisted dehydration reaction. Two approaches were compared, and the results showed that the dehydration reaction had higher chemoselectivity and product yield compared to the alkyne trimerization approach. The high-spin ground state and magnetic interactions among the triangulene units were identified, which are crucial for carbon-based spintronic devices.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Chao Sun, Andreas Nold, Claudia M. Fusco, Vidhya Rangaraju, Tatjana Tchumatchenko, Mike Heilemann, Erin M. Schuman
Summary: Neurons localize mRNAs and ribosomes in dendrites and axons for local protein synthesis to supply synapses. Study shows that ribosomes and nascent proteins positively correlate with synapse density and the amount of locally synthesized protein relates to spontaneous Ca2+ activity at synapses. Local and global plasticity result in a multifold increase in synaptic nascent protein with substantial heterogeneity between neighboring synapses.
Article
Biotechnology & Applied Microbiology
Xiaoyu Yang, Bo Song, Jie Cui, Lina Wang, Shuoshuo Wang, Linlin Luo, Lei Gao, Beixin Mo, Yu Yu, Lin Liu
Summary: This study reveals that translational reprogramming plays an important role in rice's response to salt stress, with the salt-tolerant cultivar SR86 adopting a more flexible translational adaptive strategy compared to the salt-sensitive cultivar NB. The differences in translational dynamics under salt stress between NB and SR86 may be due to their varying levels of ribosome stalling.
Article
Oncology
Yue Li, Baoming Wang, Chunyang Wang, Dandan Zhao, Zhengchuang Liu, Yanling Niu, Xiaojuan Wang, Wei Li, Jianhua Zhu, Houquan Tao, Tonghui Ma, Tao Li
Summary: DNA and RNA sequential sequencing were used to analyze the molecular profiles of 469 Chinese melanoma patients. The study revealed that some undruggable patients could still be recognized as actionable through the use of DNA and RNA sequencing, and RNA sequencing increased the proportion of druggable fusions. The findings highlight the significance of DNA and RNA sequential sequencing in understanding the genomic landscape and clinical treatment of Asian melanoma.
Article
Biochemistry & Molecular Biology
Pauline Francois, Hugo Arbes, Stephane Demais, Agnes Baudin-Baillieu, Olivier Namy
Summary: Ribosome profiling, a powerful tool for studying translation regulation, suffers from a lack of standardization in the bioinformatics part, hindering result reproducibility. A unique tool has been proposed to standardize the general steps of RiboSeq analysis, aiming to unify bioinformatics pipelines for translation research.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
Article
Computer Science, Artificial Intelligence
Nicolas Jacquelin, Romain Vuillemot, Stefan Duffner
Summary: This article introduces a context-agnostic unsupervised method for counting periodicity in videos. The method utilizes unsupervised training with a deep neural network to transform periodic temporal data into a lower-dimensional latent encoding and introduces a novel algorithm for reliable detection and counting of periods in complex time series.
PATTERN RECOGNITION LETTERS
(2022)
Article
Biochemistry & Molecular Biology
Tomoya Fujita, Takeshi Yokoyama, Mikako Shirouzu, Hideki Taguchi, Takuhiro Ito, Shintaro Iwasaki
Summary: This study investigated ribosome pause sites in Escherichia coli using different ribosome profiling strategies, revealing remarkable differences compared to eukaryotes. The identified pause sites were biochemically validated and provided a useful resource for ribosome stalling sites in bacteria.
Article
Biochemistry & Molecular Biology
Tomoya Fujita, Takeshi Yokoyama, Mikako Shirouzu, Hideki Taguchi, Takuhiro Ito, Shintaro Iwasaki
Summary: In this study, ribosome pause sites in Escherichia coli were surveyed using monosome and disome profiling strategies. Compared to eukaryotes, ribosome collisions in bacteria showed remarkable differences, and the identified pause sites were biochemically validated and showed puromycin resistance.
Article
Biochemical Research Methods
Michaela Frye, Susanne Bornelov
Summary: CONCUR is a standalone tool written in Perl for codon usage analysis in ribosome profiling experiments. It estimates codon counts at the ribosome E-, P- and A-sites using aligned reads in BAM format, and is freely available on https://github.com/susbo/concur.
Article
Biochemical Research Methods
Lingling Hou, Jinyang Zhang, Fangqing Zhao
Summary: Circular RNAs (circRNAs) play important roles in developmental processes and disease progression. Current short-read sequencing methods do not effectively reconstruct the full-length structure of circRNAs. This study presents the CIRI-long protocol, which combines rolling circular reverse transcription and nanopore sequencing to capture full-length circRNA sequences. The method can accurately detect full-length circRNAs in the range of 100-3,000 bp and can be completed in 1 day. The importance of this protocol is rated 10 out of 10.
Article
Biology
Qiuyue Ma, Yuxiao Wang, Shushun Li, Jing Wen, Lu Zhu, Kunyuan Yan, Yiming Du, Shuxian Li, Liping Yan, Zhijun Xie, Yunzhou Lyu, Fei Shen, Qianzhong Li
Summary: This study conducted ribosome footprint profiling and multi-omics strategy to investigate the lipid metabolism in Acer truncatum seed development. The transcriptional and proteomic features of the oil accumulation process were characterized. Additionally, key regulators influencing lipid biosynthesis were identified, and the role of post-translational regulation in lipid metabolism was revealed.
Article
Multidisciplinary Sciences
Thu Giang Nguyen, Christina Ritter, Eva Kummer
Summary: Mitochondria contain their own genetic information and translation system. Researchers have discovered that GTPBP10 plays a role in the folding of mitochondrial ribosomal RNA during the biogenesis process, which is related to bacterial ribosome biogenesis. Unlike bacteria, mitochondria require two biogenesis factors. This study reveals the process of maturation in the human mitoribosome and the interplay between GTPBP10 and GTPBP7.
NATURE COMMUNICATIONS
(2023)
Article
Biochemistry & Molecular Biology
Volodimir Olexiouk, Jeroen Crappe, Steven Verbruggen, Kenneth Verhegen, Lennart Martens, Gerben Menschaert
NUCLEIC ACIDS RESEARCH
(2016)
Article
Biochemistry & Molecular Biology
Chan Hyun Na, Mustafa A. Barbhuiya, Min-Sik Kim, Steven Verbruggen, Stephen M. Eacker, Olga Pletnikova, Juan C. Troncoso, Marc K. Halushka, Gerben Menschaert, Christopher M. Overall, Akhilesh Pandey
Article
Biochemistry & Molecular Biology
Daria Fijatkowska, Steven Verbruggen, Elvis Ndah, Veronique Jonckheere, Gerben Menschaert, Petra Van Damme
NUCLEIC ACIDS RESEARCH
(2017)
Article
Biochemical Research Methods
Steven Verbruggen, Elvis Ndah, Wim Van Criekinge, Siegfried Gessulat, Bernhard Kuster, Mathias Wilhelm, Petra Van Damme, Gerben Menschaert
MOLECULAR & CELLULAR PROTEOMICS
(2019)
Article
Computer Science, Interdisciplinary Applications
Alireza Karimi, Reza Razaghi, Siddharth Daniel D'costa, Saeed Torbati, Sina Ebrahimi, Seyed Mohammadali Rahmati, Mary J. Kelley, Ted S. Acott, Haiyan Gong
Summary: This study investigated the biomechanical properties of the conventional aqueous outflow pathway using fluid-structure interaction. The results showed that the distribution of aqueous humor wall shear stress within this pathway is not uniform, which may contribute to our understanding of the underlying selective mechanisms.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Robert V. Bergen, Jean-Francois Rajotte, Fereshteh Yousefirizi, Arman Rahmim, Raymond T. Ng
Summary: This article introduces a 3D generative model called TrGAN, which can generate medical images with important features and statistical properties while protecting privacy. By evaluating through a membership inference attack, the fidelity, utility, and privacy trade-offs of the model were studied.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Hoda Mashayekhi, Mostafa Nazari, Fatemeh Jafarinejad, Nader Meskin
Summary: In this study, a novel model-free adaptive control method based on deep reinforcement learning (DRL) is proposed for cancer chemotherapy drug dosing. The method models the state variables and control action in their original infinite spaces, providing a more realistic solution. Numerical analysis shows the superior performance of the proposed method compared to the state-of-the-art RL-based approach.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Hao Sun, Bao Li, Liyuan Zhang, Yanping Zhang, Jincheng Liu, Suqin Huang, Xiaolu Xi, Youjun Liu
Summary: In cases of moderate stenosis in the internal carotid artery, the A1 segment of the anterior cerebral artery or the posterior communicating artery within the Circle of Willis may show a hemodynamic environment with high OSI and low TAWSS, increasing the risk of atherosclerosis development and stenosis in the CoW.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Ilaria Toniolo, Paola Pirini, Silvana Perretta, Emanuele Luigi Carniel, Alice Berardo
Summary: This study compared the outcomes of endoscopic sleeve gastroplasty (ESG) and laparoscopic sleeve gastrectomy (LSG) in weight loss surgery using computational models of specific patients. The results showed significant differences between the two procedures in terms of stomach volume reduction and mechanical stimulation. A predictive model was proposed to support surgical planning and estimation of volume reduction after ESG.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Chun-You Chen, Ya-Lin Chen, Jeremiah Scholl, Hsuan-Chia Yang, Yu-Chuan (Jack) Li
Summary: This study evaluated the overall performance of a machine learning-based CDSS (MedGuard) in triggering clinically relevant alerts and intercepting inappropriate drug errors and LASA drug errors. The results showed that MedGuard has the ability to improve patients' safety by triggering clinically valid alerts.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Lingzhi Tang, Xueqi Wang, Jinzhu Yang, Yonghuai Wang, Mingjun Qu, HongHe Li
Summary: In this paper, a dynamical local feature fusion net for automatically recognizing aortic valve calcification (AVC) from echocardiographic images is proposed. The network segments high-echo areas and adjusts the selection of local features to better integrate global and local semantic representations. Experimental results demonstrate the effectiveness of the proposed approach.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
You-Lei Fu, Wu Song, Wanni Xu, Jie Lin, Xuchao Nian
Summary: This study investigates the combination of surface electromyographic signals (sEMG) and deep learning-based CNN networks to study the interaction between humans and products and the impact on body comfort. It compares the advantages and disadvantages of different CNN networks and finds that DenseNet has unique advantages over other algorithms in terms of accuracy and ease of training, while mitigating issues of gradient disappearance and model degradation.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Moritz Rempe, Florian Mentzel, Kelsey L. Pomykala, Johannes Haubold, Felix Nensa, Kevin Kroeninger, Jan Egger, Jens Kleesiek
Summary: In this study, a deep learning-based skull stripping algorithm for MRI was proposed, which works directly in the complex valued k-space and preserves the phase information. The results showed that the algorithm achieved similar results to the ground truth, with higher accuracy in the slices above the eye region. This approach not only preserves valuable information for further diagnostics, but also enables immediate anonymization of patient data before being transformed into the image domain.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Ziyang Chen, Laura Cruciani, Elena Lievore, Matteo Fontana, Ottavio De Cobelli, Gennaro Musi, Giancarlo Ferrigno, Elena De Momi
Summary: In this paper, a deep learning-based approach is proposed to recover 3D information of intra-operative scenes, which can enhance the safety of robot-assisted surgery by implementing depth estimation using stereo images.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Ao Leng, Bolun Zeng, Yizhou Chen, Puxun Tu, Baoxin Tao, Xiaojun Chen
Summary: This study presents a novel training system for zygomatic implant surgery, which offers a more realistic simulation and training solution. By integrating visual, haptic, and auditory feedback, the system achieves global rigid-body collisions and soft tissue simulation, effectively improving surgeons' proficiency.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Yingjie Wang, Xueqing Yin
Summary: This study developed an integrated computational model combining coronary flow and myocardial perfusion models to achieve physiologically accurate simulations. The model has the potential for clinical application in diagnosing insufficient myocardial perfusion.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Nitzan Avidan, Moti Freiman
Summary: This study aims to enhance the generalization capabilities of DNN-based MRI reconstruction methods for undersampled k-space data. By introducing a mask-aware DNN architecture and training method, the under-sampled data and mask are encoded within the model structure, leading to improved performance. Rigorous testing on the widely accessible fastMRI dataset reveals that this approach demonstrates better generalization capabilities and robustness compared to traditional DNN methods.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Enhao Zhang, Saeed Miramini, Lihai Zhang
Summary: This study investigates the combined effects of osteoporosis and diabetes on fracture healing process by developing numerical models. The results show that osteoporotic fractures have higher instability and disruption in mesenchymal stem cells' proliferation and differentiation compared to non-osteoporotic fractures. Moreover, when osteoporosis coexists with diabetes, the healing process of fractures can be severely impaired.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)
Article
Computer Science, Interdisciplinary Applications
Yunhao Bai, Wenqi Li, Jianpeng An, Lili Xia, Huazhen Chen, Gang Zhao, Zhongke Gao
Summary: This study proposes an effective MIL method for classifying WSI of esophageal cancer. The use of self-supervised learning for feature extractor pretraining enhances feature extraction from esophageal WSI, leading to more robust and accurate performance. The proposed framework outperforms existing methods, achieving an accuracy of 93.07% and AUC of 95.31% on a comprehensive dataset of esophageal slide images.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2024)