Article
Biophysics
David Rodriguez-Larrea
Summary: The study demonstrates the use of simple neural networks to identify protein mutants, with poor generalization ability. By utilizing a thermal annealing protocol and examining multiple mutants in repeated experiments, the generalizability of the neural network can be improved.
BIOSENSORS & BIOELECTRONICS
(2021)
Review
Chemistry, Multidisciplinary
Yanfang Wu, J. Justin Gooding
Summary: This review provides an overview of the concepts, fabrication, and applications of nanopore sensors, with a focus on their potential and recent developments in quantitative analysis.
CHEMICAL SOCIETY REVIEWS
(2022)
Article
Multidisciplinary Sciences
Di Lu, Shuli Cheng, Liejun Wang, Shiji Song
Summary: In this paper, a new deep learning-based method for change detection is proposed, which utilizes multi-scale feature fusion and distribution strategies to improve the accuracy of change region detection. Experimental results demonstrate that this method outperforms other comparative methods.
SCIENTIFIC REPORTS
(2022)
Article
Environmental Sciences
Dujuan Cao, Changming Zhu, Xinxin Hu, Rigui Zhou
Summary: In this paper, a feature enhancement network named SE2-Det is proposed for arbitrary-oriented object detection in aerial images. The network combines semantic edge detection with arbitrary-oriented object detection to improve detection performance by enhancing target edge features and multi-scale information. A rotation-invariant spatial pooling pyramid is also introduced to handle dense objects with different directions.
Review
Chemistry, Multidisciplinary
Zheng-Li Hu, Ming-Zhu Huo, Yi-Lun Ying, Yi-Tao Long
Summary: Proteins play a crucial role in disease occurrence and treatment, making protein sequencing a game changer for proteomics and clinical diagnostics. While the biological nanopore approach has shown success in single-molecule DNA sequencing, challenges remain in sequentially identifying each amino acid of single proteins.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2021)
Review
Chemistry, Multidisciplinary
Pengrui Lv, Wenxin Zhang, Yongyi Yang, Huilin Gao, Shuang Li, Cherie S. Tan, Dong Ming
Summary: This paper reviews recent research advances in aptamer-based nanopore sensing techniques, including the classification and selection of nanopores, different strategies of aptamer-based nanopore sensing, and their applications in areas such as environmental analysis, precision diagnosis, pharmaceutical industry, and security. The paper also highlights the use of single-molecule nanopore sensors to study aptamer-target interactions.
CHEMISTRY-AN ASIAN JOURNAL
(2022)
Article
Remote Sensing
Tianlin Zhang, Hongzhen Chen, Shi Chen, Chunjiang Bian
Summary: Super-resolution reconstruction is important in remote-sensing image processing. To improve efficiency and performance, we propose an edge-enhanced efficient network (EESR) and construct a dataset for experimentation. Experimental results show that EESR outperforms other methods in terms of restoration accuracy and inference efficiency.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Multidisciplinary Sciences
Xiaolei Wang, Zirong Hu, Shouhai Shi, Mei Hou, Lei Xu, Xiang Zhang
Summary: In this paper, a convolutional network called Adaptive Feature Fusion UNet (AFF-UNet) was proposed to optimize the semantic segmentation performance of remote sensing imagery (RSI). The AFF-UNet model consists of dense skip connections architecture, an adaptive feature fusion module, a channel attention convolution block, and a spatial attention module. Experimental results showed that the proposed model achieved improvements in average F1 score and overall accuracy compared to DeepLabv3+, demonstrating better segmentation performance and object integrity.
SCIENTIFIC REPORTS
(2023)
Article
Geochemistry & Geophysics
Haopeng Zhang, Pengrui Wang, Zhiguo Jiang
Summary: Researchers proposed a cycle convolutional neural network (Cycle-CNN) method for single image super-resolution without paired data. Experimental results show that the method performs well in remote sensing images and is robust against noise and blur.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Luxiao Cheng, Lizhe Wang, Ruyi Feng, Jining Yan
Summary: This study proposes a multimodel fusion neural network that combines a convolutional neural network and a multilayer perceptron model to estimate fine-resolution population distributions from multisource data. Experimental results show that the model accurately captures the relationship between estimated and census populations, as well as identifies population density differences in densely populated areas and remote clusters better than other models.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Chemistry, Multidisciplinary
Chengzhen Hu, Wendong Jia, Yao Liu, Yuqin Wang, Panke Zhang, Hong-Yuan Chen, Shuo Huang
Summary: Acidic catecholamine metabolites, which have similar chemical structures, pose a challenge in designing sensing strategies. In this study, a programmable nano-reactor technique combined with a phenylboronic acid adapter was used to achieve single molecule sensing of these metabolites, and the regulation of their binding modes by pH was observed.
CHEMISTRY-A EUROPEAN JOURNAL
(2022)
Article
Environmental Sciences
Feifei Peng, Wei Lu, Wenxia Tan, Kunlun Qi, Xiaokang Zhang, Quansheng Zhu
Summary: This study proposes a multi-output network combining a graph neural network and a convolutional neural network for remote sensing scene classification. By constructing superpixel regions and utilizing spatial adjacency relationships, the network can handle geographical objects in remote sensing images. The experimental results demonstrate that the network achieves excellent accuracy.
Article
Chemistry, Multidisciplinary
Dario Dematties, Chenyu Wen, Mauricio David Perez, Dian Zhou, Shi-Li Zhang
Summary: The study utilizes deep learning for feature extraction using a bipath network (B-Net), which acquires prototypical pulses and the ability to recognize and extract features without pre-assigned parameters. Evaluation on simulated and experimental data shows small relative errors and stable trends in the B-Net results. The B-Net is capable of processing data with a signal-to-noise ratio equal to 1, something not possible for threshold-based algorithms.
Article
Environmental Sciences
Kunlun Qi, Chao Yang, Chuli Hu, Yonglin Shen, Shengyu Shen, Huayi Wu
Summary: This paper proposes a novel scene classification framework based on a deep Siamese convolutional network with rotation invariance regularization, aiming to improve the classification performance of remote sensing image scenes through data augmentation strategy.
Article
Computer Science, Artificial Intelligence
Quanli Wang, Xin Jin, Qian Jiang, Liwen Wu, Yunchun Zhang, Wei Zhou
Summary: Remote sensing image fusion aims to combine high-resolution single-band panchromatic (PAN) image with spectrally informative multispectral (MS) image to generate a panchromatic sharpened image with high resolution and color information, known as pansharpening. Existing methods based on single convolutional neural network (CNN) or transformer have limitations in acquiring long-range features or difficulty in training, resulting in loss of spatial details and colors. In this work, a dual-branch hybrid CNN-Transformer network (DBCT-Net) is proposed to utilize the strengths of CNN and transformer to enhance the fusion results. The network consists of a multi-branch dense connected block (MDCB-4) for obtaining spectral and textural information, an encoder-decoder transformer for injecting local and global information, and an image reconstruction module for effective fusion of texture and spectral features. Experimental results on various datasets demonstrate that DBCT-Net outperforms other methods in spatial preservation and spectral feature recovery.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Chemistry, Multidisciplinary
Jeffrey Gorman, Sarah R. E. Orsborne, Akshay Sridhar, Raj Pandya, Peter Budden, Alexander Ohmann, Naitik A. Panjwani, Yun Liu, Jake L. Greenfield, Simon Dowland, Victor Gray, Sean T. J. Ryan, Sara De Ornellas, Afaf H. El-Sagheer, Tom Brown, Jonathan R. Nitschke, Jan Behrends, Ulrich F. Keyser, Akshay Rao, Rosana Collepardo-Guevara, Eugen Stulz, Richard H. Friend, Florian Auras
Summary: This research demonstrates the assembly of pi-conjugated perylene diimides (PDIs) using DNA-encoded approach, allowing precise control over the number of electronically coupled molecules and providing a toolbox for constructing any stacking sequence of these semiconducting molecules. Utilizing a combination of interactions, including DNA guidance, hydrophobic-hydrophilic differentiation, and local geometry and electrostatic interactions, enables efficient molecular stacking with substantial intermolecular pi wave function overlap, leading to an evolution of excited states and triplet formation mechanism.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2022)
Article
Biochemistry & Molecular Biology
Diana Morzy, Michael Schaich, Ulrich F. Keyser
Summary: This study investigates the use of the non-ionic surfactant oPOE to improve the insertion efficiency of DNA nanostructures. The presence of aggregates hindered the interaction between hydrophobically modified constructs and the membrane, but the surfactant showed a strong facilitating effect when introduced separately from DNA.
Review
Chemistry, Multidisciplinary
Andrea Doricchi, Casey M. Platnich, Andreas Gimpel, Friederikee Horn, Max Earle, German Lanzavecchia, Aitziber L. Cortajarena, Luis M. Liz-Marzan, Na Liu, Reinhard Heckel, Robert N. Grass, Roman Krahne, Ulrich F. Keyser, Denis Garoli
Summary: This article discusses the latest advances in DNA-based data storage, highlighting its advantages over traditional storage methods, while also addressing current challenges and future directions for development.
Article
Chemistry, Multidisciplinary
Filip Boskovic, Ulrich Felix Keyser
Summary: This study presents a three-dimensional molecular construct that allows the identification of RNA transcript isoforms at the single-molecule level using solid-state nanopore microscopy. The newly designed RNA identifiers, which carry a unique sequence of structural colors, enable the simultaneous identification and relative quantification of multiple RNA targets without the need for amplification.
Article
Chemistry, Multidisciplinary
Kaikai Chen, Adnan Choudhary, Sarah E. Sandler, Christopher Maffeo, Caterina Ducati, Aleksei Aksimentiev, Ulrich F. Keyser
Summary: High-resolution analysis of biomolecules has greatly advanced biosensing, but there are limited methods available for high-resolution analysis of unlabeled single molecules in their native states. In this work, label-free electrical sensing of single molecules with nanometer resolution is demonstrated using a narrow solid-state nanopore. The super-resolution ability is attributed to the enhancement of the electric field at the tip of the nanopore induced by nanostructures. This work presents a general approach to improve the resolution of single-molecule nanopore sensing and has implications for label-free high-resolution DNA sequence mapping and digital information storage.
ADVANCED MATERIALS
(2023)
Article
Chemistry, Multidisciplinary
Jinbo Zhu, Ran Tivony, Filip Boskovic, Joana Pereira-Dias, Sarah E. Sandler, Stephen Baker, Ulrich F. Keyser
Summary: In this study, a nanopore sensor based on DNA dumbbell nanoswitches was established for multiplexed nucleic acid detection and bacterial identification. By assembling four DNA dumbbell nanoswitches on one carrier, simultaneous detection of four different sequences of nucleic acids was achieved. The high specificity of the dumbbell nanoswitch was verified by distinguishing single base variants in DNA and RNA targets using barcoded DNA carriers in multiplexed measurements. By combining multiple dumbbell nanoswitches with barcoded DNA carriers, different bacterial species could be identified even with high sequence similarity by detecting strain specific 16S ribosomal RNA (rRNA) fragments.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Chemistry, Multidisciplinary
Raphael P. B. Jacquat, Georg Krainer, Quentin A. E. Peter, Ali Nawaz Babar, Oliver Vanderpoorten, Catherine K. Xu, Timothy J. Welsh, Clemens F. Kaminski, Ulrich F. Keyser, Jeremy J. Baumberg, Tuomas P. J. Knowles
Summary: This paper presents an approach called nanocavity diffusional sizing (NDS) that relies on nanocavity confinement to measure the size of nanoscale particles and single biomolecules in solution. It uses particle residence times within nanofluidic cavities to determine their hydrodynamic radii. Experimental results show that the residence times scale linearly with the sizes of nanoscale colloids, protein aggregates, and single DNA oligonucleotides. NDS offers a new optofluidic approach for rapid and quantitative sizing of nanoscale particles with potential applications in nanobiotechnology, biophysics, and clinical diagnostics.
Article
Nanoscience & Nanotechnology
S. M. Leitao, V. Navikas, H. Miljkovic, B. Drake, S. Marion, G. Pistoletti Blanchet, K. Chen, S. F. Mayer, U. F. Keyser, A. Kuhn, G. E. Fantner, A. Radenovic
Summary: In current nanopore-based label-free single-molecule sensing technologies, stochastic processes make it challenging to control the selection, rate, and velocity of single-molecule translocations. This study proposes a method that uses a glass nanopore mounted on a three-dimensional nanopositioner to spatially select and deterministically translocate molecules tethered on a glass surface. By controlling the distance between the nanopore and glass surface, the region of interest on the molecule can be actively selected and scanned at a controlled number of times and velocity. The method demonstrates versatility in assessing DNA-protein complexes, DNA rulers, and DNA gaps, enabling single-nucleotide gap detection.
NATURE NANOTECHNOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Sophie L. Williams, Corella S. Casas-Delucchi, Federica Raguseo, Dilek Guneri, Yunxuan Li, Masashi Minamino, Emma E. Fletcher, Joseph T. P. Yeeles, Ulrich F. Keyser, Zoe A. E. Waller, Marco Di Antonio, Gideon Coster
Summary: This study investigates the effects of physiological quadruplex secondary structures on genome stability by reconstituting eukaryotic DNA replication in vitro. G-quadruplexes (G4s) and intercalated Motifs (iMs) are found to form during replication and thereby induce replisome stalling, leading to helicase-polymerase uncoupling and nascent DNA breakage. A single physiological G4 or iM structure stalls the eukaryotic replisome by inhibiting leading strand synthesis. Helicase-polymerase uncoupling occurs following replication stalling at G4s. iMs can induce breakage on nascent DNA. Stalled forks at G4s or iMs can be rescued by the accessory helicase Pif1. In vitro reconstitution shows that a single physiological G4 or iM secondary structure stalls the eukaryotic replisome by inhibiting leading strand synthesis.
Article
Chemistry, Multidisciplinary
Yunxuan Li, Sarah E. Sandler, Ulrich F. Keyser, Jinbo Zhu
Summary: Nanopores are powerful single-molecule sensors for identifying and characterizing small polymers like DNA. In this study, a programmable DNA carrier platform was introduced to capture specific DNA nanostructures, and controlled translocation experiments through glass nanopores were conducted to understand the relationship between nanopore signals and DNA physical properties. The results show that the volume and flexibility of DNA nanostructures in the nanopore primarily determine the ionic current drop. Additionally, this understanding of DNA topology allowed discrimination between circular single-stranded DNA molecules and linear ones with the same number of nucleotides using the nanopore signal.
Article
Chemistry, Multidisciplinary
Sara Rocchetti, Alexander Ohmann, Rohit Chikkaraddy, Gyeongwon Kang, Ulrich F. Keyser, Jeremy J. Baumberg
Summary: Developing highly enhanced plasmonic nanocavities allows direct observation of light-matter interactions at the nanoscale. With DNA origami, precise nanopositioning of single-quantum emitters in ultranarrow plasmonic gaps enables detailed study of their modified light emission. By developing nanoparticle-on-mirror constructs with DNA nanostructures as reliable and customizable spacers for nanoparticle binding, it is revealed that the traditional understanding of Purcell-enhanced molecular dye emission is misleading, and the enhanced dipolar dye polarizability greatly amplifies optical forces acting on the facet Au atoms, causing their rapid destabilization. Different dyes exhibit emission spectra dominated by inelastic (Raman) scattering rather than fluorescence, challenging the conventional theories in the field of quantum optics using plasmonics.
Article
Chemistry, Multidisciplinary
Jeffrey Mc Hugh, Stanislaw Makarchuk, Daria Mozheiko, Ana Fernandez-Villegas, Gabriele S. Kaminski Schierle, Clemens F. Kaminski, Ulrich F. Keyser, David Holcman, Nathalie Rouach
Summary: Dendrites and dendritic spines play crucial roles in neuronal communication by conveying information through voltage signals. Using nanopipettes, researchers were able to access and record voltage dynamics in fine dendrites, revealing diverse patterns such as spontaneous transients, bursting events, and oscillations. These voltage patterns were found to be more dependent on synaptic activity than on action potentials, and long-time recordings showed complex dynamics that may contribute to dendritic computations.
Article
Multidisciplinary Sciences
Eva Kreysing, Jeffrey Mc Hugh, Sarah K. Foster, Kurt Andresen, Ryan D. Greenhalgh, Eva K. Pillai, Andrea Dimitracopoulos, Ulrich F. Keyser, Kristian Franze
Article
Chemistry, Multidisciplinary
Jinbo Zhu, Jinglin Kong, Ulrich F. Keyser, Erkang Wang
Summary: DNA nanotechnology provides a unique opportunity for molecular computation, with the ACSD circuit utilizing DNA breathing and catalytic reactions to achieve controllable reorganization, suitable for biosensing applications.
Meeting Abstract
Biophysics
Ran Tivony, Marcus Fletcher, Kareem Al Nahas, Ulrich F. Keyser
BIOPHYSICAL JOURNAL
(2022)
