Article
Plant Sciences
Gigi Y. Wong, Anthony A. Millar
Summary: This study developed a bioinformatic workflow called TRUEE to rank miRNA-target interactions (MTIs) based on miRNA-mediated cleavage signals. The workflow was used to determine the miRNA targetome in Arabidopsis and revealed the limited number of functional MTIs. The study provides insights into the scope of miRNA-mediated regulation in plants.
Article
Biochemical Research Methods
Bin Wang, Jun-Long Zhong, Xiang-He Xu, Biao Wu, Jie Shang, Ning Jiang, Hua-Ding Lu
Summary: The study identified key genes, miRNAs, and circRNAs for osteoarthritis, predicted potentially effective drugs, and identified the most meaningful biomarkers for the disease through analyzing DEGs, miRNAs, circRNAs, and a protein-drug network.
COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING
(2021)
Article
Zoology
Imtiaz Ul Hassan, Hafiz Mamoon Rehman, Ziran Liu, Liangji Zhou, Muhammad Kaleem Samma, Chengdong Wang, Zixin Rong, Xufeng Qi, Dongqing Cai, Hui Zhao
Summary: This study conducted a genome-wide analysis in mice, Xenopus tropicalis, zebrafish, and humans, and identified ZSWIM gene family members in these species. The expression patterns of these genes were examined in different tissues using RNA sequencing and quantitative real-time polymerase chain reaction (qRT-PCR), and they were found to have tissue-specific properties. In Xenopus embryos, the expression patterns of ZSWIM family genes were analyzed using whole-mount in situ hybridization and qRT-PCR, revealing distinct expression profiles during embryonic development. This study provides a foundation for further research to explore the functions of ZSWIM gene family members.
ZOOLOGICAL RESEARCH
(2023)
Article
Agronomy
Binqi Li, Muhammad Moaaz Ali, Tianxin Guo, Shariq Mahmood Alam, Shaista Gull, Junaid Iftikhar, Ahmed Fathy Yousef, Walid F. A. Mosa, Faxing Chen
Summary: In this study, 21 putative SWEET genes were identified and characterized from the loquat genome. Comprehensive bioinformatics analysis revealed the physicochemical properties, gene organization, conserved motifs, and phylogenetic relationships of the EjSWEET genes. The expression patterns of EjSWEET genes in different tissues of loquat were also analyzed. The study provides a foundation for further functional analysis of the SWEET gene family in loquat.
Article
Genetics & Heredity
Klaudia Pawlina-Tyszko, Tomasz Szmatola
Summary: This study compared three bioinformatic algorithms for gene sequencing and found that different programs may generate different results. Validation using RT-qPCR showed strong correlation for some miRNAs. The results demonstrated the good performance of the tested programs, but indicated the possibility of discrepancies between NGS and qPCR methods.
FUNCTIONAL & INTEGRATIVE GENOMICS
(2023)
Article
Hematology
Pierre R. Moreau, Vanesa Tomas Bosch, Maria Bouvy-Liivrand, Kadri Ounap, Tiit Ord, Heidi H. Pulkkinen, Petri Polonen, Merja Heinaniemi, Seppo Yla-Herttuala, Johanna P. Laakkonen, Suvi Linna-Kuosmanen, Minna U. Kaikkonen
Summary: This study aimed to characterize microRNA-related regulatory mechanisms in the aorta during atherosclerosis. The research analyzed miRNA expression changes in different cell types under proatherogenic stimuli and found common miRNA species dominating in all cell types. The study identified potential mechanisms by which miRNAs affect atherogenesis in a cell-type-specific manner.
ARTERIOSCLEROSIS THROMBOSIS AND VASCULAR BIOLOGY
(2021)
Article
Biochemical Research Methods
Laxman Ramya, Divakar Swathi, Santhanahalli Siddalingappa Archana, Maharajan Lavanya, Sivashanmugam Parthipan, Sellappan Selvaraju
Summary: The study established a bioinformatics pipeline for analyzing fragmented sperm RNA, with TopHat2 identified as the most effective tool. EdgeR and limma were found to identify the largest number of significantly differentially expressed genes with biological relevance in the differential gene expression analysis.
ANALYTICAL BIOCHEMISTRY
(2021)
Article
Biochemical Research Methods
Himangi Srivastava, Drew Ferrell, George Popescu
Summary: NetSeekR is a network analysis R package that enables analysis of time series RNA-Seq data, correlation and regulatory network inference, and summarization of comparative genomics study results using network analysis methods. The pipeline integrates multiple genomic analysis tools and allows for hypothesis building, functional analysis, and genomics discovery from large-scale NGS data.
BMC BIOINFORMATICS
(2022)
Article
Reproductive Biology
Chong Tang, Yeming Xie, Mei Guo, Wei Yan
Summary: AASRA is an all-in-one sncRNA annotation pipeline that offers high-speed, simultaneous annotation of all known sncRNA species while distinguishing mature from precursor microRNAs, and identifying novel sncRNA variants in sequencing reads.
BIOLOGY OF REPRODUCTION
(2021)
Article
Biotechnology & Applied Microbiology
Jieyin Zhao, Peng Wang, Wenju Gao, Yilei Long, Yuxiang Wang, Shiwei Geng, Xuening Su, Yang Jiao, Quanjia Chen, Yanying Qu
Summary: This study identified 32 DUF668 genes in cotton, classified into four subgroups, with most located in the nucleus of G. hirsutum. Transcriptome analysis revealed differential expression of GhDUF668 genes in different tissues under various stresses, with increased expression in roots and stems. Certain Gh_DUF668 genes in G. hirsutum may have evolved resistance to adverse stress, as indicated by promoter and expression analyses.
Review
Biochemistry & Molecular Biology
Mst Shamima Khatun, Md Ashad Alam, Watshara Shoombuatong, Md Nurul Haque Mollah, Hiroyuki Kurata, Md Mehedi Hasan
Summary: This article reviews the development of bioinformatics tools for miRNA target prediction, discusses the progress and limitations of existing miRNA databases, and explores the challenges and future directions of next-generation algorithms in predicting miRNA targets.
CURRENT MEDICINAL CHEMISTRY
(2022)
Article
Chemistry, Multidisciplinary
Veronica Quarato, Salvatore D'Antona, Petronilla Battista, Roberta Zupo, Rodolfo Sardone, Isabella Castiglioni, Danilo Porro, Marco Frasca, Claudia Cava
Summary: This study explored differentially expressed genes in the hippocampus of Alzheimer's disease patients, identifying potential drug targets and gene networks involved in various biological processes. The findings shed light on the genetic mechanisms of the disease and provide insights for further research.
APPLIED SCIENCES-BASEL
(2022)
Article
Biochemical Research Methods
Weiliang Huang, Maureen A. Kane
Summary: Metaproteomics by mass spectrometry is a powerful method for analyzing proteins in complex samples, providing insights into the functional composition of microbiota. Human gastrointestinal microbiota plays important roles in human health, and metaproteomics reveals novel associations between microbiota and diseases. The MAPLE microbiome analysis pipeline offers a user-friendly solution for optimal proteome inference and comprehensive comparison of microbiota composition.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Agronomy
Xiaohui Yin, Yi Yuan, Xiaowen Han, Shuo Han, Yiting Li, Dongfang Ma, Zhengwu Fang, Shuangjun Gong, Junliang Yin
Summary: This study systematically identified and characterized a plant-specific gene family, TaDUF668s, in wheat. Through evolutionary analysis and expression profiling, it provided a comprehensive understanding of TaDUF668s and laid a foundation for further functional studies.
Article
Multidisciplinary Sciences
Timothy Fuqua, Jeff Jordan, Aliaksandr Halavatyi, Christian Tischer, Kerstin Richter, Justin Crocker
Summary: The study presents a semi-automated pipeline for fixing, staining, and imaging Drosophila embryos, with a liquid handling robot at its core. The efficiency of this pipeline is demonstrated, along with detailed technical overview and implementation steps.
SCIENTIFIC REPORTS
(2021)
Review
Spectroscopy
Erica Gianazza, Beatrice Zoanni, Alice Mallia, Maura Brioschi, Gualtiero Colombo, Cristina Banfi
Summary: This narrative review highlights the potential of lipoprotein-associated proteins in cardiovascular risk assessment and emphasizes the importance of high-throughput proteomic analysis.
MASS SPECTROMETRY REVIEWS
(2023)
Article
Computer Science, Artificial Intelligence
Enea Parimbelli, Tommaso Mario Buonocore, Giovanna Nicora, Wojtek Michalowski, Szymon Wilk, Riccardo Bellazzi
Summary: The increasing complexity of machine learning models has led to the development of black-box models, which are accurate but difficult to interpret. This article introduces AraucanaXAI, a novel method that generates explanations for machine learning predictions. The method uses surrogate, locally-fitted classification and regression trees to provide post-hoc explanations with superior fidelity, ability to handle non-linear decision boundaries, and support for both classification and regression. The authors also provide an open-source implementation and evaluate its performance in medical AI applications, including cases of disagreement with expert opinions and limited data reliability.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2023)
Article
Biology
Marco Penso, Sara Moccia, Enrico G. Caiani, Gloria Caredda, Maria Luisa Lampus, Maria Ludovica Carerj, Mario Babbaro, Mauro Pepi, Mattia Chiesa, Gianluca Pontone
Summary: In this study, an automatic deep learning-based algorithm was proposed to classify coronary artery stenosis lesions according to the CCTA images. The experimental results showed that the algorithm achieved high accuracy and sensitivity in classifying significant coronary artery stenosis and in CAD-RADS classification.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Computer Science, Information Systems
Laurence Saint Q. N. Ngankem, Cristiana Larizza, Antonino Nocera, Giuseppe Rombola, Silvana Quaglini, Riccardo Bellazzi, Maria Laura Costantino, Giustina Casagrande
Summary: Intradialytic hypotension (IDH) is a common complication in hemodialysis patients, but there is no consensus on its definition, making it difficult to evaluate its effects and causes. This study aims to investigate whether different IDH definitions, all correlated with increased mortality risk, have the same onset mechanisms or dynamics. The analysis showed that certain factors like diabetes or heart disease presence and low pre-dialysis diastolic blood pressure have universal relevance in highlighting an increased risk of IDH.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2023)
Letter
Health Care Sciences & Services
Nicola Cosentino, Giancarlo Marenzi, Mattia Chiesa
JOURNAL OF GENERAL INTERNAL MEDICINE
(2023)
Article
Developmental Biology
Giulia Fiorentino, Andrew Smith, Giovanna Nicora, Riccardo Bellazzi, Fulvio Magni, Silvia Garagna, Maurizio Zuccotti
Summary: In this study, a spatial proteomics approach was used to analyze the protein composition of follicles at different growth stages in the mouse ovary. Proteins involved in the mutual relationship among oocytes, follicle cells, stroma, and the vascular network were identified and their quantitative changes during follicular differentiation were determined, providing important insights into folliculogenesis.
MOLECULAR HUMAN REPRODUCTION
(2023)
Article
Biochemistry & Molecular Biology
Paolo Enrico, Giuseppe Delvecchio, Nunzio Turtulici, Rosario Aronica, Alessandro Pigoni, Letizia Squarcina, Filippo Villa, Cinzia Perlini, Maria Rossetti, Marcella Bellani, Antonio Lasalvia, Chiara Bonetto, Paolo Scocco, Armando D'Agostino, Stefano Torresani, Massimiliano Imbesi, Francesca Bellini, Angelo Veronese, Luisella Bocchio-Chiavetto, Massimo Gennarelli, Matteo Balestrieri, Gualtiero Colombo, Annamaria Finardi, Mirella Ruggeri, Roberto Furlan, Paolo Brambilla, GET UP Grp
Summary: Psychosis onset is a transdiagnostic event that can lead to various psychiatric disorders, and current diagnosis is based on clinical observation. This study used a data-driven unsupervised machine learning model to cluster first-episode psychosis patients based on immune gene expression levels, identifying two distinct subgroups. One subgroup showed high expression of inflammatory and immune-activating genes, while the other subgroup was balanced and included both patients and healthy controls. These findings suggest the importance of immunomarkers in the pathogenesis of psychosis.
MOLECULAR PSYCHIATRY
(2023)
Article
Cardiac & Cardiovascular Systems
Oronzo Catalano, Giulia Bendotti, Teresa L. Aloi, Alberto Ferrari Bardile, Mirella Memmi, Patrick Gambelli, Daniela Zanaboni, Alessandra Gualco, Emanuela Cattaneo, Antonio Mazza, Mauro Frascaroli, Esmeralda Eshja, Riccardo Bellazzi, Paolo Poggi, Giovanni Forni, Maria Teresa La Rovere
Summary: This study demonstrates vulnerability regression in real life in patients with asymptomatic mild to moderate carotid atherosclerosis using magnetic resonance imaging. The study also shows that a secondary prevention program can promote vulnerability regression in asymptomatic patients.
JOURNAL OF THE AMERICAN HEART ASSOCIATION
(2023)
Article
Respiratory System
M. Vitacca, A. Malovini, A. Spanevello, P. Ceriana, M. Paneroni, M. Maniscalco, B. Balbi, L. Rizzello, R. Murgia, R. Bellazzi, N. Ambrosino
Summary: Due to the low availability of pulmonary rehabilitation (PR) for individuals recovering from a COPD exacerbation (ECOPD), this study aimed to identify subpopulations with different responses to PR based on clustering analysis of baseline characteristics. The results can be used to define priority criteria for PR.
Article
Medicine, General & Internal
Byorn W. L. Tan, Bryce W. Q. Tan, Amelia L. M. Tan, Emily R. Schriver, Alba Gutierrez-Sacristan, Priyam Das, William Yuan, Meghan R. Hutch, Noelia Garcia Barrio, Miguel Pedrera Jimenez, Noor Abu-el-rub, Michele Morris, Bertrand Moal, Guillaume Verdy, Kelly Cho, Yuk-Lam Ho, Lav P. Patel, Arianna Dagliati, Antoine Neuraz, Jeffrey G. Klann, Andrew M. South, Shyam Visweswaran, David A. Hanauer, Sarah E. Maidlow, Mei Liu, Danielle L. Mowery, Ashley Batugo, Adeline Makoudjou, Patric Tippmann, Daniela Zoeller, Gabriel A. Brat, Yuan Luo, Paul Avillach, Riccardo Bellazzi, Luca Chiovato, Alberto Malovini, Valentina Tibollo, Malarkodi Jebathilagam Samayamuthu, Pablo Serrano Balazote, Zongqi Xia, Ne Hooi Will Loh, Lorenzo Chiudinelli, Clara-Lea Bonzel, Chuan Hong, Harrison G. Zhang, Griffin M. Weber, Isaac S. Kohane, Tianxi Cai, Gilbert S. Omenn, John H. Holmes, Kee Yuan Ngiam
Summary: This retrospective observational study analyzed data from 12,891 COVID-19 patients and found that age, severe COVID-19, severe acute kidney injury (AKI), and ischemic heart disease were associated with worse mortality outcomes. The severity of AKI was associated with poorer kidney function recovery, while the use of remdesivir was associated with better recovery. In patients without chronic kidney disease, age, male sex, severe AKI, and hypertension were associated with post-AKI kidney function impairment. COVID-19-associated AKI was also linked to higher mortality and worse long-term kidney function recovery.
Letter
Biochemistry & Molecular Biology
Harrison G. Zhang, Jacqueline P. Honerlaw, Monika Maripuri, Malarkodi Jebathilagam Samayamuthu, Brendin R. Beaulieu-Jones, Huma S. Baig, Sehi L'Yi, Yuk-Lam Ho, Michele Morris, Vidul Ayakulangara Panickan, Xuan Wang, Griffin M. Weber, Katherine P. Liao, Shyam Visweswaran, Bryce W. Q. Tan, William Yuan, Nils Gehlenborg, Sumitra Muralidhar, Rachel B. Ramoni, Isaac S. Kohane, Zongqi Xia, Kelly Cho, Tianxi Cai, Gabriel A. Brat, James R. Aaron, Giuseppe Agapito, Adem Albayrak, Giuseppe Albi, Mario Alessiani, Anna Alloni, Danilo F. Amendola, Francois Angoulvant, Li L. L. J. Anthony, Bruce J. Aronow, Fatima Ashraf, Andrew Atz, Paul Avillach, Paula S. Azevedo, James Balshi, Brett K. Beaulieu-Jones, Douglas S. Bell, Antonio Bellasi, Riccardo Bellazzi, Vincent Benoit, Michele Beraghi, Jose Luis Bernal-Sobrino, Melodie Bernaux, Romain Bey, Surbhi Bhatnagar, Alvar Blanco-Martinez, Clara-Lea Bonzel, John Booth, Silvano Bosari, Florence T. Bourgeois, Robert L. Bradford, Gabriel A. Brat, Stephane Breant, Nicholas W. Brown, Raffaele Bruno, William A. Bryant, Mauro Bucalo, Emily Bucholz, Anita Burgun, Tianxi Cai, Mario Cannataro, Aldo Carmona, Charlotte Caucheteux, Julien Champ, Jin Chen, Krista Y. Chen, Luca Chiovato, Lorenzo Chiudinelli, Kelly Cho, James J. Cimino, Tiago K. Colicchio, Sylvie Cormont, Sebastien Cossin, Jean B. Craig, Juan Luis Cruz-Bermudez, Jaime Cruz-Rojo, Arianna Dagliati, Mohamad Daniar, Christel Daniel, Priyam Das, Batsal Devkota, Audrey Dionne, Rui Duan, Julien Dubiel, Scott L. DuVall, Loic Esteve, Hossein Estiri, Shirley Fan, Robert W. Follett, Thomas Ganslandt, Noelia Garcia-Barrio, Lana X. Garmire, Nils Gehlenborg, Emily J. Getzen, Alon Geva, Tobias Gradinger, Alexandre Gramfort, Romain Griffier, Nicolas Griffon, Olivier Grisel, Alba Gutierrez-Sacristan, Larry Han, David A. Hanauer, Christian Haverkamp, Derek Y. Hazard, Bing He, Darren W. Henderson, Martin Hilka, Yuk-Lam Ho, John H. Holmes, Chuan Hong, Kenneth M. Huling, Meghan R. Hutch, Richard W. Issitt, Anne Sophie Jannot, Vianney Jouhet, Ramakanth Kavuluru, Mark S. Keller, Chris J. Kennedy, Daniel A. Key, Katie Kirchoff, Jeffrey G. Klann, Isaac S. Kohane, Ian D. Krantz, Detlef Kraska, Ashok K. Krishnamurthy, Sehi L'Yi, Trang T. Le, Judith Leblanc, Guillaume Lemaitre, Leslie Lenert, Damien Leprovost, Molei Liu, Ne Hooi Will Loh, Qi Long, Sara Lozano-Zahonero, Yuan Luo, Kristine E. Lynch, Sadiqa Mahmood, Sarah E. Maidlow, Adeline Makoudjou, Alberto Malovini, Kenneth D. Mandl, Chengsheng Mao, Anupama Maram, Patricia Martel, Marcelo R. Martins, Jayson S. Marwaha, Aaron J. Masino, Maria Mazzitelli, Arthur Mensch, Marianna Milano, Marcos F. Minicucci, Bertrand Moal, Taha Mohseni Ahooyi, Jason H. Moore, Cinta Moraleda, Jeffrey S. Morris, Michele Morris, Karyn L. Moshal, Sajad Mousavi, Danielle L. Mowery, Douglas A. Murad, Shawn N. Murphy, Thomas P. Naughton, Carlos Tadeu Breda Neto, Antoine Neuraz, Jane Newburger, Kee Yuan Ngiam, Wanjiku F. M. Njoroge, James B. Norman, Jihad Obeid, Marina P. Okoshi, Karen L. Olson, Gilbert S. Omenn, Nina Orlova, Brian D. Ostasiewski, Nathan P. Palmer, Nicolas Paris, Lav P. Patel, Miguel Pedrera-Jimenez, Emily R. Pfaff, Ashley C. Pfaff, Danielle Pillion, Sara Pizzimenti, Hans U. Prokosch, Robson A. Prudente, Andrea Prunotto, Victor Quiros-Gonzalez, Rachel B. Ramoni, Maryna Raskin, Siegbert Rieg, Gustavo Roig-Dominguez, Pablo Rojo, Paula Rubio-Mayo, Paolo Sacchi, Carlos Saez, Elisa Salamanca, Malarkodi Jebathilagam Samayamuthu, L. Nelson Sanchez-Pinto, Arnaud Sandrin, Nandhini Santhanam, Janaina C. C. Santos, Fernando J. Sanz Vidorreta, Maria Savino, Emily R. Schriver, Petra Schubert, Juergen Schuettler, Luigia Scudeller, Neil J. Sebire, Pablo Serrano-Balazote, Patricia Serre, Arnaud Serret-Larmande, Mohsin Shah, Zahra Shakeri Hossein Abad, Domenick Silvio, Piotr Sliz, Jiyeon Son, Charles Sonday, Andrew M. South, Anastasia Spiridou, Zachary H. Strasser, Amelia L. M. Tan, Bryce W. Q. Tan, Byorn W. L. Tan, Suzana E. Tanni, Deanne M. Taylor, Ana I. Terriza-Torres, Valentina Tibollo, Patric Tippmann, Emma M. S. Toh, Carlo Torti, Enrico M. Trecarichi, Yi-Ju Tseng, Andrew K. Vallejos, Gael Varoquaux, Margaret E. Vella, Guillaume Verdy, Jill-Jenn Vie, Shyam Visweswaran, Michele Vitacca, Kavishwar B. Wagholikar, Lemuel R. Waitman, Xuan Wang, Demian Wassermann, Griffin M. Weber, Martin Wolkewitz, Scott Wong, Zongqi Xia, Xin Xiong, Ye Ye, Nadir Yehya, William Yuan, Alberto Zambelli, Harrison G. Zhang, Daniela Zoller, Valentina Zuccaro, Chiara Zucco
Article
Cell & Tissue Engineering
Roman Vuerich, Elena Groppa, Simone Vodret, Nadja Annelies Ruth Ring, Chiara Stocco, Fleur Bossi, Chiara Agostinis, Matteo Cauteruccio, Andrea Colliva, Mohammad Ramadan, Francesca Simoncello, Federica Benvenuti, Anna Agnelli, Franca Dore, Flavia Mazzarol, Massimo Moretti, Alice Paulitti, Silvia Palmisano, Nicolo De Manzini, Mattia Chiesa, Manuel Casaburo, Angela Raucci, Daniela Lorizio, Giulio Pompilio, Roberta Bulla, Giovanni Papa, Serena Zacchigna
Summary: Nonhealing wounds have a negative impact on the quality of life for patients and health systems. Skin substitutes have been used, but have limited efficacy due to inadequate vascularization. The use of the stromal vascular fraction (SVF) from adipose tissue shows promise in overcoming this limitation, but additional research is needed to determine its precise mechanism of action.
NPJ REGENERATIVE MEDICINE
(2023)
Article
Computer Science, Interdisciplinary Applications
Tommaso Mario Buonocore, Claudio Crema, Alberto Redolfi, Riccardo Bellazzi, Enea Parimbelli
Summary: In the era of digital healthcare, the underused textual information in hospitals could be effectively utilized with task-specific, fine-tuned biomedical language representation models. However, less-resourced languages face challenges in accessing in-domain adaptation resources. To address this issue, our study investigates two accessible approaches to derive biomedical language models in languages like Italian, and demonstrates that data quantity is a harder constraint than data quality for biomedical adaptation. The models developed from our investigations have the potential to unlock important research opportunities for Italian healthcare institutions and academia, and also provide insights towards building generalizable biomedical language models for less-resourced languages and different domains.
JOURNAL OF BIOMEDICAL INFORMATICS
(2023)
Article
Medicine, General & Internal
Damiano Baldassarre, Licia Iacoviello, Roberta Baetta, Maria Carla Roncaglioni, Gianluigi Condorelli, Giuseppe Remuzzi, Gianfranco Gensini, Luigi Frati, Walter Ricciardi, Pier Giulio Conaldi, Antonio Uccelli, Fabio Blandini, Silvano Bosari, Giovanni Scambia, Massimo Fini, Antonio Di Malta, Mauro Amato, Fabrizio Veglia, Alice Bonomi, Catherine Klersy, Francesca Colazzo, Martino Pengo, Francesca Gorini, Luciana Auteri, Giuseppe Ferrante, Marta Baviera, Giuseppe Ambrosio, Alberico Catapano, Alessandro Gialluisi, Alexis Elias Malavazos, Serenella Castelvecchio, Massimiliano Marco Corsi-Romanelli, Rosanna Cardani, Maria Teresa La Rovere, Valentina Agnese, Bianca Pane, Daniele Prati, Laura Spinardi, Giovanna Liuzzo, Eloisa Arbustini, Maurizio Volterrani, Marco Visconti, Jose Pablo Werba, Stefano Genovese, Grzegorz Bilo, Cecilia Invitti, Anna Di Blasio, Carolina Lombardi, Andrea Faini, Debora Rosa, Luisa Ojeda-Fernandez, Andreana Foresta, Amalia De Curtis, Augusto Di Castelnuovo, Simonetta Scalvini, Antonia Pierobon, Alessandra Gorini, Luca Valenti, Livio Luzi, Annarosa Racca, Manuela Bandi, Elena Tremoli, Lorenzo Menicanti, Gianfranco Parati, Giulio Pompilio
Summary: The CV-PREVITAL study is a multicentre, prospective, randomised, controlled, open-label interventional trial aiming to compare the effectiveness of an educational and motivational mobile health intervention with usual care in reducing cardiovascular risk. The trial plans to enrol approximately 80,000 subjects without overt cardiovascular diseases and evaluate the short-term endpoints, as well as conduct a long-term follow-up to assess the incidence of major adverse cardiovascular events.
Article
Pharmacology & Pharmacy
N. M. Bogari, R. M. Allam, A. Dannoun, M. Athar, A. Bouazzaoui, O. Elkhateeb, M. Poraueddu, S. A. Amer, A. Elsayed, G. I. Colombo
Summary: This study investigates the relationship between genetic variation and biological function on a genomic scale, focusing on the rs2383206 gene and its association with the development of coronary artery disease (CAD) in a Saudi population. The study found a higher prevalence of the GG genotype in rs2383206 among CAD patients compared to controls, suggesting an increased risk for CAD. The findings highlight the potential of this genetic variant as a target for future functional studies.
EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES
(2023)
Article
Biology
Seyyed Bahram Borgheai, Alyssa Hillary Zisk, John McLinden, James Mcintyre, Reza Sadjadi, Yalda Shahriari
Summary: This study proposed a novel personalized scheme using fNIRS and EEG as the main tools to predict and compensate for the variability in BCI systems, especially for individuals with severe motor deficits. By establishing predictive models, it was found that there were significant associations between the predicted performances and the actual performances.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Hongliang Guo, Hanbo Liu, Ahong Zhu, Mingyang Li, Helong Yu, Yun Zhu, Xiaoxiao Chen, Yujia Xu, Lianxing Gao, Qiongying Zhang, Yangping Shentu
Summary: In this paper, a BDSMA-based image segmentation method is proposed, which improves the limitations of the original algorithm by combining SMA with DE and introducing a cooperative mixing model. The experimental results demonstrate the superiority of this method in terms of convergence speed and precision compared to other methods, and its successful application to brain tumor medical images.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jingfei Hu, Linwei Qiu, Hua Wang, Jicong Zhang
Summary: This study proposes a novel semi-supervised point consistency network (SPC-Net) for retinal artery/vein (A/V) classification, addressing the challenges of specific tubular structures and limited well-labeled data in CNN-based approaches. The SPC-Net combines an AVC module and an MPC module, and introduces point set representations and consistency regularization to improve the accuracy of A/V classification.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Omair Ali, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis, Christian Klaes
Summary: This study introduces a novel hybrid model called ConTraNet, which combines the strengths of CNN and Transformer neural networks, and achieves significant improvement in classification performance with limited training data.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Juan Antonio Valera-Calero, Dario Lopez-Zanoni, Sandra Sanchez-Jorge, Cesar Fernandez-de-las-Penas, Marcos Jose Navarro-Santana, Sofia Olivia Calvo-Moreno, Gustavo Plaza-Manzano
Summary: This study developed an easy-to-use application for assessing the diagnostic accuracy of digital pain drawings (PDs) compared to the classic paper-and-pencil method. The results demonstrated that digital PDs have higher reliability and accuracy compared to paper-and-pencil PDs, and there were no significant differences in assessing pain extent between the two methods. The PAIN EXTENT app showed good convergent validity.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Biao Qu, Jialue Zhang, Taishan Kang, Jianzhong Lin, Meijin Lin, Huajun She, Qingxia Wu, Meiyun Wang, Gaofeng Zheng
Summary: This study proposes a deep unrolled neural network, pFISTA-DR, for radial MRI image reconstruction, which successfully preserves image details using a preprocessing module, learnable convolution filters, and adaptive threshold.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Alireza Rafiei, Milad Ghiasi Rad, Andrea Sikora, Rishikesan Kamaleswaran
Summary: This study aimed to improve machine learning model prediction of fluid overload by integrating synthetic data, which could be translated to other clinical outcomes.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jinlian Ma, Dexing Kong, Fa Wu, Lingyun Bao, Jing Yuan, Yusheng Liu
Summary: In this study, a new method based on MDenseNet is proposed for automatic segmentation of nodular lesions from ultrasound images. Experimental results demonstrate that the proposed method can accurately extract multiple nodules from thyroid and breast ultrasound images, with good accuracy and reproducibility, and it shows great potential in other clinical segmentation tasks.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jiabao Sheng, SaiKit Lam, Jiang Zhang, Yuanpeng Zhang, Jing Cai
Summary: Omics fusion is an important preprocessing approach in medical image processing that assists in various studies. This study aims to develop a fusion methodology for predicting distant metastasis in nasopharyngeal carcinoma by mitigating the disparities in omics data and utilizing a label-softening technique and a multi-kernel-based neural network.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Zhenxiang Xiao, Liang He, Boyu Zhao, Mingxin Jiang, Wei Mao, Yuzhong Chen, Tuo Zhang, Xintao Hu, Tianming Liu, Xi Jiang
Summary: This study systematically investigates the functional connectivity characteristics between gyri and sulci in the human brain under naturalistic stimulus, and identifies unique features in these connections. This research provides novel insights into the functional brain mechanism under naturalistic stimulus and lays a solid foundation for accurately mapping the brain anatomy-function relationship.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Qianqian Wang, Mingyu Zhang, Aohan Li, Xiaojun Yao, Yingqing Chen
Summary: The development of PARP-1 inhibitors is crucial for the treatment of various cancers. This study investigates the structural regulation of PARP-1 by different allosteric inhibitors, revealing the basis of allosteric inhibition and providing guidance for the discovery of more innovative PARP-1 inhibitors.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Qing Xu, Wenting Duan
Summary: In this paper, a dual attention supervised module, named DualAttNet, is proposed for multi-label lesion detection in chest radiographs. By efficiently fusing global and local lesion classification information, the module is able to recognize targets with different sizes. Experimental results show that DualAttNet outperforms baselines in terms of mAP and AP50 with different detection architectures.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Kaja Gutowska, Piotr Formanowicz
Summary: The primary aim of this research is to propose algorithms for identifying significant reactions and subprocesses within biological system models constructed using classical Petri nets. These solutions enable two analysis methods: importance analysis for identifying critical individual reactions to the model's functionality and occurrence analysis for finding essential subprocesses. The utility of these methods has been demonstrated through analyses of an example model related to the DNA damage response mechanism. It should be noted that these proposed analyses can be applied to any biological phenomenon represented using the Petri net formalism. The presented analysis methods extend classical Petri net-based analyses, enhancing our comprehension of the investigated biological phenomena and aiding in the identification of potential molecular targets for drugs.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Hansle Gwon, Imjin Ahn, Yunha Kim, Hee Jun Kang, Hyeram Seo, Heejung Choi, Ha Na Cho, Minkyoung Kim, Jiye Han, Gaeun Kee, Seohyun Park, Kye Hwa Lee, Tae Joon Jun, Young-Hak Kim
Summary: Electronic medical records have potential in advancing healthcare technologies, but privacy issues hinder their full utilization. Deep learning-based generative models can mitigate this problem by creating synthetic data similar to real patient data. However, the risk of data leakage due to malicious attacks poses a challenge to traditional generative models. To address this, we propose a method that employs local differential privacy (LDP) to protect the model from attacks and preserve the privacy of training data, while generating medical data with reasonable performance.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Siwei Tao, Zonghan Tian, Ling Bai, Yueshu Xu, Cuifang Kuang, Xu Liu
Summary: This study proposes a transfer learning-based method to address the phase retrieval problem in grating-based X-ray phase contrast imaging. By generating a training dataset and using deep learning techniques, this method improves image quality and can be applied to X-ray 2D and 3D imaging.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
