Article
Biochemical Research Methods
Loane Danes, Nicolas Tchitchek, Christophe Becavin
Summary: Bacnet is a user-friendly platform for building multi-omics websites, which assists bioinformaticians in constructing personalized user interfaces for studying non-reference organisms.
Article
Spectroscopy
Ya-Juan Liu, Michelle Kyne, Shuang Wang, Sheng Wang, Xi-Yong Yu, Cheng Wang
Summary: The optimization of Raman instruments has expanded our understanding of single-cell Raman spectroscopy. By improving the speed and sensitivity, as well as implementing advanced data mining methods, complex chemical and biological information within Raman spectral data can be revealed. This paper introduces a new Matlab Graphical User-Friendly Interface (GUI) called CELL IMAGE, which enables the analysis of cellular Raman spectroscopy data. The GUI includes three main steps: spectral processing, pattern recognition, and model validation, and offers various well-known methods for each step. A new subsampling optimization method is integrated into the GUI to estimate the minimum number of spectral collection points. The incorporation of the signal-to-noise ratio (SNR) in the binomial statistical model makes the new subsampling model more sophisticated and suitable for complicated Raman cell data. These embedded methods allow CELL IMAGE to convert spectral information into biological information, including single-cell visualization, cell classification, and biomolecular/drug quantification.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2022)
Article
Biochemistry & Molecular Biology
Luca Pinzi, Annachiara Tinivella, Luca Gagliardelli, Domenico Beneventano, Giulio Rastelli
Summary: Despite available in silico drug design tools, results are often challenging to integrate or utilize fully; Multi-target ligand rational design and drug repurposing are gaining attention; Computational tools and data-driven approaches can reveal new drug discovery opportunities, and LigAdvisor integrates various database information to facilitate drug discovery tasks.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Chemistry, Multidisciplinary
Shitao Shen, Xiaofeng Qin, Haoqiang Feng, Shuting Xie, Zichuan Yi, Mingliang Jin, Guofu Zhou, Eser Metin Akinoglu, Paul Mulvaney, Lingling Shui
Summary: In this paper, an electromicrofluidic assembly platform (eMAP) is proposed and validated for achieving 3D colloidal assembly within water droplets. By using dielectrophoresis and (di)electrowetting effects, reconfigurable colloidal configurations can be observed and dynamically programmed. This platform allows designable chemical and physical anisotropies for functional materials and devices, and enables high throughput mass production of microcapsules and optoelectronic units.
Article
Engineering, Biomedical
Rabi Ibrahim Saleh, Suntae Kim, Sang-Hyeon Lee, Hyukjoo Kwon, Hoon Eui Jeong, Chaenyung Cha
Summary: With the increasing importance of point-of-care testing (POCT) in medical diagnostics, there is a need for reliable and minimally invasive POCT devices. However, the limited and inconsistent sample collection on these devices hinders their accuracy. This study proposes a new biosensing platform modified with a functional polysuccinimide (PSI)-silica nanoparticle (SNP) composite system, which greatly enhances protein conjugation efficiency. Validation on a microneedle array (MN) shows that this PSI-SNP MN can detect a wide array of proteins with high sensitivity, comparable to conventional whole serum analysis, demonstrating its broad applicability in biomedical engineering.
ADVANCED HEALTHCARE MATERIALS
(2023)
Article
Plant Sciences
Huiying Miao, Chuchu Xia, Shunhao Yu, Jiansheng Wang, Yanting Zhao, Qiaomei Wang
Summary: A study found that the content of GBPs in Chinese kale sprouts changes during development, and the expression of the Epithiospecifier protein BoESP2 determines the pattern of GBPs. Manipulating BoESP2 through metabolic engineering can increase the levels of health-promoting ITCs in Chinese kale sprouts.
HORTICULTURE RESEARCH
(2023)
Article
Materials Science, Composites
Kai Yang, Yongruo Ren, Kangning Wu, Jianying Li, Zhenghong Jing, Zhijian Zhang, Jin-Yong Dong
Summary: This paper achieved significant increases in breakdown strength and charge injecting transition field of IPC through molten-state annealing. The multiphase structure evolution during the annealing process was investigated. The separation of EPR from the matrix and the increase in thickness of partial lamellas were found to be the influencing factors on the electrical properties. The electrohole recombination was proposed to be the main origin of high-energy electrons.
COMPOSITES SCIENCE AND TECHNOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Zhi-Peng Wu, Huabin Zhang, Shouwei Zuo, Yan Wang, Song Lin Zhang, Jing Zhang, Shuang-Quan Zang, Xiong Wen (David) Lou
Summary: A highly efficient bimetallic Ni-Fe selenide-derived OER electrocatalyst is reported in this study, with the structure-activity correlation of the active centers studied. It was found that the active center located on Ni sites showed moderate bindings with oxygenous intermediates, leading to enhanced OER performance.
ADVANCED MATERIALS
(2021)
Article
Chemistry, Multidisciplinary
Rui Wang, Zhen He, Jin-Long Wang, Jia-Yang Liu, Jian-Wei Liu, Shu-Hong Yu
Summary: This study presents a simple and effective method to create multi-layered structures in nanowire films, resulting in a photothermoelectric photodetector with broad-band responsivity, fast response speed, stability, and polarization sensitivity.
Article
Chemistry, Physical
Houquan Deng, Xunuo Lou, Wenqi Lu, Jian Zhang, Di Li, Shuang Li, Qingtang Zhang, Xuemei Zhang, Xiang Chen, Dewei Zhang, Yongsheng Zhang, Guodong Tang
Summary: By manipulating the band structure and introducing SnTe nanocrystals, ultrahigh thermoelectric performance of MnTe was achieved, with enhanced Seebeck coefficient and reduced lattice thermal conductivity. This novel strategy decouples electron and phonon transport of MnTe, contributing to a record high ZT value at 873 K for the Mn1.06Te-2% SnTe material, promoting MnTe-based materials as a robust candidate for waste heat recovery at medium temperature.
Article
Biochemical Research Methods
Teo Lemane, Rayan Chikhi, Pierre Peterlongo
Summary: Genome wide association studies aim to uncover the connections between genotypes and phenotypes. Recent research suggests the significance of using k-mers instead of single-nucleotide polymorphisms for such experiments. We introduce a tool called kmdiff, which enables faster and more memory-efficient differential k-mer analysis on large sequencing cohorts.
Article
Multidisciplinary Sciences
Wanyanhan Jiang, Han Chen, Lian Yang, Xiaoqi Pan
Summary: When comparing means of different groups, it is necessary to explore and compare data for influencing factors or relative indices. This can be a complex and challenging process, especially for users who lack statistical knowledge and coding experience. To address this issue, we developed moreThanANOVA, an interactive, user-friendly, open-source, and cloud-based application that automates distribution tests and correlative significance tests, allowing users to customize post-hoc analysis based on their considerations.
Article
Multidisciplinary Sciences
Lijing Ren, Denghui Zhang
Summary: This paper presents a novel QR code-based expansion-free and meaningful visual cryptography scheme (QEVCS) that can effectively protect the privacy of images without requiring any computation.
SCIENTIFIC REPORTS
(2022)
Article
Chemistry, Multidisciplinary
Sandra Ruiz-Gomez, Eva Maria Trapero, Claudia Fernandez-Gonzalez, Adolfo del Campo, Cecilia Granados-Miralles, Jose Emilio Prieto, Muhammad Waqas Khaliq, Miguel Angel Nino, Michael Foerster, Lucia Aballe, Juan de la Figuera
Summary: We have grown high-quality magnetite micrometric islandson ruthenium stripes on sapphire through a combination of magnetron sputtering (Ru film), high-temperature molecular beam epitaxy (oxide islands), and optical lithography. The magnetic domains on the magnetite islands can be modified by the application of current pulses through the Ru stripes in combination with magnetic fields.
CRYSTAL GROWTH & DESIGN
(2023)
Article
Biochemistry & Molecular Biology
Denis Yuen, Louise Cabansay, Andrew Duncan, Gary Luu, Gregory Hogue, Charles Overbeck, Natalie Perez, Walt Shands, David Steinberg, Chaz Reid, Nneka Olunwa, Richard Hansen, Elizabeth Sheets, Ash O'Farrell, Kim Cullion, Brian D. O'Connor, Benedict Paten, Lincoln Stein
Summary: Dockstore is an open source platform that facilitates the publishing, sharing, and finding of bioinformatics tools and workflows. It uses cloud technologies to increase the FAIRness of computational resources, promoting reproducibility in complex bioinformatics analyses. The platform supports various source repositories, analysis frameworks, and language technologies for authors to create a centralized catalogue of scientific software.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Biochemical Research Methods
Alex G. C. de Sa, Yangyang Long, Stephanie Portelli, Douglas E. Pires, David B. Ascher
Summary: Drug discovery is a complex and time-consuming process, with toxicity as one of the main reasons for clinical trial failures. toxCSM is a computational platform that uses graph-based signatures, molecular descriptors, and similarity scores to predict a range of toxicity properties. It outperforms alternative methods in terms of accuracy and is freely available as a user-friendly web server and API.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Chemistry, Medicinal
Saba Iftkha, Alex G. C. de Sa, Joao P. L. Velloso, Raghad Aljarf, Douglas E. V. Pires, David B. Ascher
Summary: Toxicity is a major concern in drug design, and current computational methods for predicting toxicity have limitations. To address this, we propose a new web-based computational method, cardioToxCSM, which accurately predicts cardiac toxicity outcomes.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Genetics & Heredity
Stephanie Portelli, Amanda Albanaz, Douglas Eduardo Valente Pires, David Benjamin Ascher
Summary: The researchers curated the most comprehensive database of missense mutations in amyotrophic lateral sclerosis (ALS) and identified distinct molecular drivers for different gene mutations, providing important clues for further ALS research.
JOURNAL OF MEDICAL GENETICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Christopher McMaster, Julia Chan, David F. L. Liew, Elizabeth Su, Albert G. Frauman, Wendy W. Chapman, Douglas E. V. Pires
Summary: The detection of adverse drug reactions (ADRs) is important for understanding medication safety. ADRs contribute to patient morbidity, accounting for 5%-10% of acute care hospital admissions globally. Spontaneous reporting of ADRs is the standard method, but it has high rates of under-reporting. Automated ADR reporting offers an alternative to increase reporting rates, although over-reporting of other drug-related adverse events may be a limitation.
JOURNAL OF BIOMEDICAL INFORMATICS
(2023)
Article
Chemistry, Medicinal
Raghad Aljarf, Simon Tang, Douglas E. V. Pires, David B. Ascher
Summary: Teratogenic drugs can cause severe fetal malformation and have a critical impact on fetal health, but the teratogenic risks of most approved drugs are unknown. In this study, researchers propose a novel predictive tool called embryoTox, which uses a graph-based signature representation of chemical structure to predict and classify molecules that are likely to be safe during pregnancy. The tool achieved high accuracy on cross-validation and blind tests, outperforming alternative approaches. The authors believe that embryoTox will provide a practical resource for screening libraries and identifying safe molecules for use during pregnancy. The tool is freely available online at https://biosig.lab.uq.edu.au/embryotox/.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Statistics & Probability
Tulio L. Criscuolo, Renato M. Assuncao, Rosangela H. Loschi, Wagner Meira Jr, Danna Cruz-Reyes
Summary: A common problem in data analysis is dealing with categorical predictors that have a large number of levels or categories. We propose a generative model that simultaneously fits the model and aggregates the categorical levels into larger groups. By representing the categorical predictor as a graph, where nodes are categories, we establish a probability distribution over meaningful partitions of this graph. Given the observed data, we obtain a posterior distribution for the levels aggregation, allowing us to infer the most probable clustering for the categories. Additionally, we extract inference about all other regression model parameters. Comparisons with state-of-the-art methods show that our approach has equally good predictive performance and more interpretable results. Our method strikes a balance between accuracy and interpretability, which is an important concern in statistics and machine learning.
ANNALS OF APPLIED STATISTICS
(2023)
Article
Biochemical Research Methods
Bruna Moreira da Silva, David B. Ascher, Douglas E. Pires
Summary: The ability to accurately identify B-cell epitopes is crucial for vaccine design, immunodiagnostic tests, and antibody production. Existing computational methods have limited performance and lack interpretability, hindering biological insights. To overcome these limitations, we developed epitope1D, a machine learning method that accurately identifies linear B-cell epitopes and offers interpretability through novel descriptors. Our model achieved high performance on cross-validation and blind tests, outperforming state-of-the-art tools. epitope1D represents a significant advance in predictive performance and allows for biologically meaningful features to be used for interpretation.
BRIEFINGS IN BIOINFORMATICS
(2023)
Review
Health Care Sciences & Services
Roberta Lins Goncalves, Adriana Silvina Pagano, Zilma Silveira Nogueira Reis, Ken Brackstone, Taina Costa Pereira Lopes, Sarah Almeida Cordeiro, Julia Macedo Nunes, Seth Kwaku Afagbedzi, Michael Head, Wagner Meira Jr, James Batchelor, Antonio Luiz Pinho Ribeiro
Summary: During the COVID-19 pandemic, the usability of telehealth systems in primary care for patients with noncommunicable diseases (NCDs) was evaluated. The majority of health professionals considered the usability of telehealth systems to be good, and patients expressed satisfaction using telehealth. The main challenges reported were related to technological issues, computer literacy, and lack of training.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Yunzhuo Zhou, Qisheng Pan, Douglas E. Pires, Carlos H. M. Rodrigues, David B. Ascher
Summary: Understanding the effects of mutations on protein stability is crucial. We developed DDMut, a fast and accurate siamese network, to predict changes in Gibbs Free Energy upon single and multiple point mutations. DDMut achieved high correlations and outperformed most available methods. It is a useful platform for understanding the functional consequences of mutations and guiding protein engineering.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Edre Moreira, Wagner Meira Jr, Marcos Andre Goncalves, Alberto H. F. Laender
Summary: In this article, we investigate hyperprolific authors, who are the most productive researchers in a given repository. We focus on a subset of these authors who exhibit sudden growth in published articles and co-authors, as well as concentration in specific journals, suggesting anomalous behavior. By analyzing data from the DBLP repository over the past 10 years, we propose discriminative dimensions to characterize hyperprolific authors, helping to identify anomalous ones. Using a ranking aggregation strategy, we identify the most prominent anomalous authors and find that their behavior differs significantly from moderately ranked authors. The top-ranked authors published over 48 journal articles in 2021 and collaborated with over 1,000 co-authors, with one author publishing over 140 articles in a single journal.
Article
Biochemistry & Molecular Biology
Adam Serghini, Stephanie Portelli, Guillaume Troadec, Catherine Song, Qisheng Pan, Douglas E. Pires, David B. Ascher
Summary: This study manually curated VHL gene mutations and used biophysical tools to characterize their effects, constructing a machine learning model to predict the risk of ccRCC development caused by VHL missense mutations. The results showed that the model accurately identified ccRCC-causing missense mutations and had a significant improvement compared to previous approaches.
HUMAN MOLECULAR GENETICS
(2023)
Review
Computer Science, Interdisciplinary Applications
Prabodi Senevirathna, Douglas E. V. Pires, Daniel Capurro
Summary: Adequate translation methods are essential for promptly translating digital health innovations to improve patient care. This study comprehensively analyzed quantification strategies and data-driven definitions for overdiagnosis reported in the literature. The findings revealed widely diverging results among studies, emphasizing the need for a standard method to quantify the impact of overdiagnosis.
JOURNAL OF BIOMEDICAL INFORMATICS
(2023)
Article
Neurosciences
Nikollas M. Benites, Beatriz Rodrigues, Carlos H. da Silveira, Christopher Kushmerick, Ricardo M. Leao
Summary: The dorsal cochlear nucleus (DCN) in the auditory brainstem integrates auditory and somatosensory information. Mature DCN fusiform neurons can be classified into quiet and active types, with significant changes in their electrophysiological properties before and after the onset of hearing.Activation of persistent sodium current after hearing onset leads to hyperpolarization of the activity threshold and the active state of the fusiform neuron. Other changes refine the passive membrane properties and increase the speed of action potential firing of fusiform neurons.
JOURNAL OF NEUROPHYSIOLOGY
(2023)
Article
Biochemical Research Methods
Yoochan Myung, Douglas E. Pires, David B. Ascher
Summary: In this study, the researchers explored the structural features of antibody-antigen interfaces by assessing concavity and interatomic interactions. They found that complementarity-determining regions utilized deeper concavity, with nanobodies showing the deepest use of concavity. Tryptophan residues, especially in nanobodies, were found to use deeper concavity, making them suitable for targeting concave antigen surfaces. Similarly, antigens utilized arginine to bind to deeper pockets of the antibody surface. These findings contribute to a better understanding of antibody specificity and can potentially enhance the effectiveness of antibody-based therapies.
Article
Biochemical Research Methods
Thanh Binh Nguyen, Alex G. C. de Sa, Carlos H. M. Rodrigues, Douglas E. Pires, David B. Ascher
Summary: This study developed a web-based resource named LEGO-CSM, which accurately models protein function in terms of Subcellular Localization, Enzyme Commission (EC) numbers, and Gene Ontology (GO) terms by leveraging graph-based signatures and supervised learning models using protein sequence and structure information. The models performed as well as or better than alternative approaches, achieving area under the receiver operating characteristic curve of up to 0.93 for subcellular localization, up to 0.93 for EC, and up to 0.81 for GO terms on independent blind tests.
