Article
Biochemistry & Molecular Biology
Rhonda Bacher, Li-Fang Chu, Cara Argus, Jennifer M. Bolin, Parker Knight, James A. Thomson, Ron Stewart, Christina Kendziorski
Summary: It has been found that equalizing the concentration of cDNA libraries prior to pooling in single-cell RNA-sequencing experiments can improve gene detection rates, enhance biological signals, and reduce technical artifacts. Numerical and in vitro experiments provide evidence to support this finding.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Biochemistry & Molecular Biology
Alice Nevone, Francesca Lattarulo, Monica Russo, Giada Panno, Paolo Milani, Marco Basset, Maria Antonietta Avanzini, Giampaolo Merlini, Giovanni Palladini, Mario Nuvolone
Summary: In the next-generation sequencing era, RT-qPCR remains widely used for quantifying nucleic acids due to its popularity, versatility, and cost-effectiveness. However, accurate measurement of transcriptional levels requires appropriate reference genes for normalization. Here, we present a strategy that utilizes publicly available transcriptomic datasets to select suitable reference genes for specific clinical or experimental settings and includes a pipeline for RT-qPCR assay design and validation. We demonstrated the efficacy of this strategy by identifying and validating reference genes for transcriptional studies of bone-marrow plasma cells in AL amyloidosis patients. This strategy can be applied to other settings with publicly available transcriptomic datasets.
Article
Biochemical Research Methods
Qizhi Li, Xubin Zheng, Jize Xie, Ran Wang, Mengyao Li, Man-Hon Wong, Kwong-Sak Leung, Shuai Li, Qingshan Geng, Lixin Cheng
Summary: A diagnostic model based on host gene expression was used to diagnose acute infections. However, its clinical usage was limited due to small sample sizes. In this study, a large-scale dataset was constructed and analyzed using a sophisticated strategy to build gene pair signatures for bacterial, viral, and noninfected patients. These signatures were further combined into an antibiotic decision model with strong performance in distinguishing bacterial and viral infections.
Article
Multidisciplinary Sciences
Barry Slaff, Caleb M. Radens, Paul Jewell, Anupama Jha, Nicholas F. Lahens, Gregory R. Grant, Andrei Thomas-Tikhonenko, Kristen W. Lynch, Yoseph Barash
Summary: Confounding factors on gene expression analysis have been extensively studied, while there is a lack of equivalent analysis and tools for RNA splicing; the authors develop an algorithm called MOCCASIN to correct the effect of known and unknown confounders on RNA splicing quantification.
NATURE COMMUNICATIONS
(2021)
Review
Urology & Nephrology
Michael S. Balzer, Ziyuan Ma, Jianfu Zhou, Amin Abedini, Katalin Susztak
Summary: Single cell methods have advanced significantly in the past few years, enabling the monitoring of gene and protein expression changes in individual cells. However, data analysis remains a critical bottleneck. This review provides an overview of commonly used analytical tools in the field to help researchers understand challenges and gain insights into typical readouts from single cell datasets in published literature.
JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY
(2021)
Article
Mathematical & Computational Biology
Antonio Miranda-Escalada, Farrokh Mehryary, Jouni Luoma, Darryl Estrada-Zavala, Luis Gasco, Sampo Pyysalo, Alfonso Valencia, Martin Krallinger
Summary: Efficiently exploiting drug-related information from scientific literature is increasingly challenging, especially for drug-gene/protein interactions. To address this, the DrugProt track was organized at BioCreative VII, releasing the DrugProt Gold Standard corpus and generating a silver standard knowledge graph. Participants implemented deep learning approaches, achieving high precision and recall values for certain relation types.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2023)
Article
Plant Sciences
Qizhang Wang, Chunqian Guo, Shipeng Yang, Qiwen Zhong, Jie Tian
Summary: The aim of this study was to identify suitable reference genes for gene expression analysis during different growth conditions in garlic. Nine candidate reference genes were selected using garlic transcriptome sequence data and their expression levels were evaluated in specific tissues under drought and cold stress. Several statistical methods were used to assess the stability of the reference gene expression levels. The most stable reference genes were identified, and their reliability was confirmed by evaluating the expression of a stress-responsive gene. This study provides a theoretical reference for gene expression analysis in garlic under stress conditions.
Article
Biochemical Research Methods
David Chisanga, Yang Liao, Wei Shi
Summary: In this paper, the authors compared the effects of Ensembl and RefSeq human annotations on gene expression quantification using a benchmark RNA-seq dataset. They found that using RefSeq gene annotation models led to better quantification accuracy, based on correlation with ground truths including gene expression data and microarray expression data. They also observed a decrease in the accuracy of RNA-seq quantification with the recent expansion of the RefSeq database.
BMC BIOINFORMATICS
(2022)
Article
Biochemistry & Molecular Biology
Xue Bai, Tao Chen, Yuan Wu, Mingyong Tang, Zeng-Fu Xu
Summary: This study identified a series of reference genes in tiger nut that can serve as internal controls for gene expression studies, providing convenience for qRT-PCR analysis. Among the various tissues, UCE2, UBL5, and Rubisco showed more stable expression patterns, with TUB4 and UCE2 identified as optimal reference genes for tuber development stages.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemical Research Methods
Chih-Hsuan Wei, Ling Luo, Rezarta Islamaj, Po-Ting Lai, Zhiyong Lu
Summary: Gene name normalization is a complex task in biomedical text mining research. GNorm2, an advanced tool, uses deep learning methods to achieve the highest levels of accuracy and efficiency in gene recognition and normalization.
Article
Mathematical & Computational Biology
Andrew Chatr-aryamontri, Lynette Hirschman, Karen E. Ross, Rose Oughtred, Martin Krallinger, Kara Dolinski, Mike Tyers, Tonia Korves, Cecilia N. Arighi
Summary: The COVID-19 pandemic has emphasized the need for real-time data communication among biomedical researchers. This has led to the importance of nontraditional sources like preprint publications and the development of natural language processing systems for COVID-19 data extraction and organization. The BioCreative COVID-19 text mining tool interactive demonstration track aimed to assess available tools and facilitate communication between developers and users, resulting in overall positive feedback.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2022)
Article
Agronomy
Chengjie Tu, Pei Xu, Runhua Han, Jing Luo, Letian Xu
Summary: This study assessed the stability of seven commonly used reference genes in Plagiodera versicolora and analyzed their expression under different biotic and abiotic conditions. The results showed that RPS18 and EF1A were the most reliable reference genes in different developmental stages and treatments.
Article
Biochemical Research Methods
Evgenia Chunikhina, Paul Logan, Yevgeniy Kovchegov, Anatoly Yambartsev, Debashis Mondal, Andrey Morgun
Summary: Omics technologies are powerful tools for analyzing patterns in gene expression data for thousands of genes. In order to remove undesirable technical noises and recover covariance matrix, a novel normalization technique called the covariance shift (C-SHIFT) method is proposed in this paper. The method, which is suitable for logarithmic gene expression data analysis, outperforms classical normalization techniques in numerical experiments on synthetic data and real biological data.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Mingrui Li, Yanli Li, Haide Qin, Justin D. Tubbs, Minghui Li, Chunhong Qiao, Jinran Lin, Qingyang Li, Fengmei Fan, Mengzhuang Gou, Junchao Huang, Jinghui Tong, Fude Yang, Yunlong Tan, Yin Yao
Summary: Schizophrenia is a severe neuropsychiatric disorder characterized by hallucinations, delusions, and cognition deficits. Abnormal DNA methylation may play a role in the development of schizophrenia, with DNA methylation changes affecting genes associated with nervous system development and neuronal networks. The study provides evidence that DNA methylation alterations in schizophrenia patients may serve as valuable resources for identifying diagnostic biomarkers and developing therapeutic targets.
MOLECULAR PSYCHIATRY
(2021)
Article
Horticulture
Rundong Yao, Xiaolou Huang, Hanqing Cong, Fei Qiao, Yunjiang Cheng, Yeyuan Chen
Summary: Real-Time PCR is a rapid and sensitive technique widely used to determine gene expression. This study identified 10 candidate reference genes in mangos and evaluated their stability using professional software. TUBB gene was found to be the most stable and suitable reference gene.
Article
Public, Environmental & Occupational Health
Bo Wang, Feifan Liu, Lynette Deveaux, Arlene Ash, Ben Gerber, Jeroan Allison, Carly Herbert, Maxwell Poitier, Karen MacDonell, Xiaoming Li, Bonita Stanton
Summary: This study used machine learning approaches to identify important predictors of non-responsiveness to interventions among adolescents in The Bahamas, including self-efficacy, perceived response cost, and parent monitoring. The findings suggest that machine learning techniques can help identify different types of adolescents, guiding the development of more effective interventions.
Article
Chemistry, Multidisciplinary
Lipei Jiang, Jiannan Zhu, Guangfang Li, Zhuang Rao, Zhengyun Wang, Hongfang Liu
Summary: A new method involving partial thermal reduction and galvanic replacement is reported to induce CuPt growth on a CuHHTP MOF, resulting in the construction of a CuPt@CuHHTP heterojunction. The size of the CuPt nanoparticles can be effectively regulated by modifying the reduction temperature. The CuPt NP@CuHHTP heterojunction nanoarrays exhibit high electrocatalytic activity and potential as an electrochemical H2O2 sensor with a low detection limit, high sensitivity, and outstanding selectivity.
CHEMISTRY-A EUROPEAN JOURNAL
(2023)
Article
Chemistry, Multidisciplinary
Jiannan Zhu, Jing Huang, Jiawei Dai, Lipei Jiang, You Xu, Rong Chen, Longhua Li, Xiaoqi Fu, Zhengyun Wang, Hongfang Liu, Guangfang Li
Summary: We developed trimetallic NiAuPd heterogeneous catalysts through a galvanic replacement reaction and a subsequent chemical reduction process, achieving efficient hydrogen generation from formic acid decomposition through Fermi level engineering and plasmonic effect.
Article
Environmental Sciences
Qiutang Huang, Zhongqiang Jia, Shenggan Wu, Feifan Liu, Yingnan Wang, Genmiao Song, Xiaoli Chang, Chunqing Zhao
Summary: To expand the usage of Fluxametamide in paddy fields, its potential toxicological effects on fish were investigated. The study found that Fluxametamide exhibited high toxicity to zebrafish Danio rerio, but only slightly inhibited the GABA-stimulated current of certain receptors. It also showed a high bioconcentration level in zebrafish, but rapidly decreased in concentration over a short period of time.
ENVIRONMENTAL POLLUTION
(2023)
Article
Chemistry, Multidisciplinary
Zhuang Rao, Deyu Zhu, You Xu, Minqiu Lan, Lipei Jiang, Zhengyun Wang, Beibei Tang, Hongfang Liu
Summary: An interconnected and zwitterion-functionalized covalent porous material (CPM) based on carbon nanotubes and a Schiff-base network (CNT@ZSNW-1) is developed as a highly efficient proton-conductive accelerator. The CNT@ZSNW-1 structure offers additional proton-conducting sites and promotes water retention capacity, leading to enhanced proton conductivity and peak power density in a composite proton-exchange membrane (PEM) with Nafion. This study provides a potential reference for the design and preparation of functionalized CPMs to expedite proton transfer in PEMs.
Article
Materials Science, Multidisciplinary
Huihai Wan, Tiansui Zhang, Zixuan Xu, Zhuang Rao, Guoan Zhang, Guangfang Li, Hongfang Liu
Summary: The effect of sulfate reducing bacteria (SRB) on galvanic corrosion between 2205 SS and X52 carbon steel in enriched artificial seawater was comprehensively investigated. This study is significant for understanding microbiologically influenced corrosion of bimetallic composite pipelines. Electrochemical tests revealed that galvanic effect was higher in the SRB-containing medium compared to the sterile medium. The coupling also accelerated the corrosion of 2205 SS, resulting in a 13-fold increase in weight loss.
Article
Geosciences, Multidisciplinary
Ruoxi Li, Jiuhou Lei, Jurgen Kusche, Tong Dang, Fuqing Huang, Xiaoli Luan, Shun-Rong Zhang, Maodong Yan, Ziyi Yang, Feifan Liu, Xiankang Dou
Summary: The volcanic eruption in Tonga in 2010 caused significant disturbances in the thermosphere, including global changes in neutral density and the formation of density waves. These effects were comparable to a moderate geomagnetic storm.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Biochemistry & Molecular Biology
Jie Kuang, Taimei Cai, Jiangbei Dai, Lihua Yao, Feifan Liu, Yue Liu, Jicheng Shu, Jieping Fan, Hailong Peng
Summary: A high-strength aerogel with a 3D hierarchically macro-meso-microporous structure (HPS-aerogel) was designed using biological macromolecules of chitin and chitosan. It showed high porosity, good mechanical properties, and excellent compression strength. The HPS-aerogel was also used as an adsorbent for the simultaneous removal of Cu(II) and Congo red from water, exhibiting promising adsorption capabilities.
INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
(2023)
Article
Chemistry, Multidisciplinary
Yanan Wei, Weihua Li, Hongfang Liu, Hongwei Liu
Summary: Hydrogels with excellent antibiofouling properties were prepared by in situ synthesis of spindle CaCO3-Chitosan/poly (vinyl alcohol) (SCC/PVA) hydrogels inspired by seashells. The morphologies, structure, and components of the hydrogels were characterized. The SCC/PVA hydrogels exhibited excellent underwater superoleophobicity properties and remarkable resistance to protein, bacteria, and algae adhesion. The SCC/PVA-3 hydrogel had the highest superoleophobicity and compressive strength, and significantly reduced the settlement of Navicula, Nitzschia, and Closterium on its surface, as well as inhibiting the adhesion of elegans in the South China Sea for 180 days.
JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY
(2023)
Article
Health Care Sciences & Services
Simon Suster, Timothy Baldwin, Jey Han Lau, Antonio Jimeno Yepes, David Martinez Iraola, Yulia Otmakhova, Karin Verspoor
Summary: The study proposes a quality assessment task that provides an overall quality rating for each body of evidence (BoE) and justification for different quality criteria. A machine learning system (EvidenceGRADEr) is developed to automate the quality assessment process using a new dataset. The results show that the system performs well for some quality criteria but struggles with others due to limited data availability. This technology has the potential to reduce reviewer workload and expedite evidence synthesis.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Computer Science, Information Systems
Anna Ostropolets, Yasser Albogami, Mitchell Conover, Juan M. Banda, William A. Baumgartner Jr, Clair Blacketer, Priyamvada Desai, Scott L. DuVall, Stephen Fortin, James P. Gilbert, Asieh Golozar, Joshua Ide, Andrew S. Kanter, David M. Kern, Chungsoo Kim, Lana Y. H. Lai, Chenyu Li, Feifan Liu, Kristine E. Lynch, Evan Minty, Maria Ines Neves, Ding Quan Ng, Tontel Obene, Victor Pera, Nicole Pratt, Gowtham Rao, Nadav Rappoport, Ines Reinecke, Paola Saroufim, Azza Shoaibi, Katherine Simon, Marc A. Suchard, Joel N. Swerdel, Erica A. Voss, James Weaver, Linying Zhang, George Hripcsak, Patrick B. Ryan
Summary: Objective observational studies should be robust and reproducible, but nonreproducibility is often caused by unclear reporting. This study aimed to assess how different interpretations of study logic can impact patient characteristics.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Yiyuan Pu, Daniel Beck, Karin Verspoor
Summary: This study explores the framing of literature-based discovery (LBD) as link prediction and graph embedding learning in the context of Alzheimer's Disease (AD). A four-stage approach is proposed to create and analyze an AD-specific knowledge graph and predict new knowledge based on time-sliced link prediction. The results show that neural network graph-embedding link prediction methods have promise for LBD, but the prediction setting is extremely challenging.
JOURNAL OF BIOMEDICAL INFORMATICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Jinghui Liu, Daniel Capurro, Anthony Nguyen, Karin Verspoor
Summary: With the increasing amount and growing variety of healthcare data, multimodal machine learning has become an important tool for clinical machine learning tasks. However, managing the differences in dimensionality and availability of data modalities, as well as handling missing modalities, remains challenging. In this study, a Transformer-based fusion model called ARMOUR is proposed to address these issues and achieve improved performance in clinical prediction tasks.
JOURNAL OF BIOMEDICAL INFORMATICS
(2023)
Article
Health Care Sciences & Services
Simon Suster, Timothy Baldwin, Karin Verspoor
Summary: This study analyzes two systems for assessing medical evidence quality and finds that they are well calibrated on most quality criteria but vary significantly by medical area. Therefore, practitioners should expect fluctuations in system reliability and predictive performance when adopting automated quality assessment.
JOURNAL OF CLINICAL EPIDEMIOLOGY
(2023)
Article
Computer Science, Theory & Methods
Tabinda Sarwar, Sattar Seifollahi, Jeffrey Chan, Xiuzhen Zhang, Vural Aksakalli, Irene Hudson, Karin Verspoor, Lawrence Cavedon
Summary: The primary objective of implementing Electronic Health Records (EHRs) is to improve the management of patients' health-related information. However, these records have also been extensively used for the secondary purpose of clinical research and to improve healthcare practice. But the presence of diverse data types and associated characteristics poses many challenges to the use of EHR data. In this article, we provide an overview of information found in EHR systems and their characteristics that could be utilized for secondary applications, as well as the methods used to address data quality issues.
ACM COMPUTING SURVEYS
(2023)