Article
Computer Science, Information Systems
Puneet Singh, Amit Chatterjee, Laxman Singh Rajput, Sanjeev Kumar, Vennampally Nataraj, Vimal Bhatia, Shashi Prakash
Summary: Charcoal rot is a destructive fungal disease affecting soybeans and other crops, characterized by the pathogen Macrophomina phaseolina. A laser biospeckle sensor was developed to efficiently analyze disease development, symptom identification, and genetic resistance in soybean crops. The sensor showed strong correlation with lesion length, indicating early detection capabilities for disease management.
Article
Plant Sciences
Jovana Sucur Elez, Kristina Petrovic, Marina Crnkovic, Slobodan Krsmanovic, Milos Rajkovic, Zeljko Kaitovic, Dorde Malencic
Summary: The study evaluated oxidative stress and lesion length in soybean seedlings infected with the fungus Macrophomina phaseolina to determine the most tolerant soybean cultivar. Superoxide anion radical production and superoxide-dismutase (SOD) activity were highest in the Favorit cultivar, indicating its tolerance to M. phaseolina. In contrast, the Victoria cultivar showed high radical production, low SOD activity, and enhanced lipid peroxidation, suggesting its susceptibility to the pathogen. No significant differences were observed in the oxidative stress parameters of the Atlas and Rubin cultivars compared to the control. The Victoria cultivar had the longest lesion length, while the Atlas and Rubin cultivars displayed the shortest lengths, indicating their tolerance to the pathogen.
Article
Food Science & Technology
Samaneh Tajdinian, Mostafa Rahmati-Joneidabad, Mohamad Hamed Ghodoum Parizipour
Summary: The application of algae in sustainable agriculture is considered crucial for integrated disease management. This study investigated the effect of foliar application of brown alga on reducing the symptoms of charcoal rot disease in strawberries and improving plant growth indices. The results showed that algae-treated infected plants exhibited symptom remission and improved growth indices. Biochemical analysis further revealed the influence of algae treatment on defense responses in the plants.
FRONTIERS IN SUSTAINABLE FOOD SYSTEMS
(2022)
Article
Plant Sciences
Sajjad Hyder, Amjad Shahzad Gondal, Zarrin Fatima Rizvi, Rashid Iqbal, Abdul Hannan, Shahbaz Talib Sahi
Summary: This study identified M. phaseolina and investigated the antagonistic effects of several fungi. Trichoderma harzianum and Penicillium spp. showed positive effects on disease severity and plant growth.
PAKISTAN JOURNAL OF BOTANY
(2022)
Article
Agronomy
Sonja Tancic Zivanov, Bosko Dedic, Sandra Cvejic, Sinisa Jocic, Vladimir Miklic
Summary: This study tested sunflower hybrids and inbred lines for tolerance to Macrophomina phaseolina under field conditions, identifying highly tolerant varieties for future breeding programs. It was found that using both inoculation methods together provided reliable screening results, with stem lesion length being a key trait for assessing disease severity.
Article
Agronomy
Aly Derbalah, Tarek Essa, Said Mohamed Kamel, Reda Ibrahim Omara, Mahmoud Abdelfatah, Abdelhamed Elshaer, Mohsen Mohamed Elsharkawy
Summary: This study fabricated silver oxide nanostructures and evaluated their antifungal activity against Macrophomina phaseolina in strawberries. The results showed that silver oxide nanoparticles significantly inhibited the growth of the pathogen and improved the yield of the strawberry crop.
PEST MANAGEMENT SCIENCE
(2022)
Article
Biotechnology & Applied Microbiology
Victor Hugo Ramos-Garcia, Nubia Andrea Villota-Salazar, Juan Manuel Gonzalez-Prieto, Diana Cortes-Espinosa
Summary: Fungal phytopathogens utilize chromatin remodeling to influence their infection and lifecycle in plants. Macrophomina phaseolina is a significant phytopathogenic fungus with described biological features, but its epigenetic mechanisms in development and virulence remain incompletely studied. The inhibition of histone deacetylases by valproic acid and sodium butyrate alters M. phaseolina's growth, morphology, and virulence.
WORLD JOURNAL OF MICROBIOLOGY & BIOTECHNOLOGY
(2022)
Article
Agricultural Economics & Policy
Otilia Cotuna, Mirela Paraschivu, Veronica Sarateanu
Summary: Charcoal rot of sunflower roots and stems is widespread in arid climate areas, causing significant losses, with the climate change favoring its spread. The pathogen Macrophomina phaseolina's long-term survival in soil makes control almost impossible, emphasizing the need for prevention and biological control methods in control strategies.
SCIENTIFIC PAPERS-SERIES MANAGEMENT ECONOMIC ENGINEERING IN AGRICULTURE AND RURAL DEVELOPMENT
(2022)
Article
Green & Sustainable Science & Technology
A. Bandopadhyay, T. Roy, S. Alam, S. Majumdar, N. Das
Summary: This study investigated the biological management of diseases caused by Macrophomina phaseolina using pesticide-tolerant rhizobacteria. The selected strains of Bacillus and Pseudomonas showed potential in disease control and plant growth promotion through various mechanisms. The results demonstrated that treatment with Pseudomonas aeruginosa significantly improved the plant health index of cowpea. The findings suggest that these selected pesticide-tolerant rhizobacteria can be utilized for sustainable agriculture.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2022)
Article
Plant Sciences
Hafiz Muhammad Khalid Abbas, Rashid Mahmood, Salik Nawaz Khan, Anser Ali
Summary: The study found that different concentrations of N, P, and K fertilizers have varying effects on the growth of Macrophomina phaseolina, with most fertilizers having little impact on mycelial growth but significant effects on sclerotia. Some fertilizers can significantly reduce sclerotia count, while others can increase it.
BANGLADESH JOURNAL OF BOTANY
(2021)
Article
Agronomy
Edelweiss Airam Rangel-Montoya, Carmen Sanjuana Delgado-Ramirez, Edgardo Sepulveda, Rufina Hernandez-Martinez
Summary: Two strains of B. amyloliquefaciens (BsA3MX and BsC11MX) were identified, which grew well under low pH and high salinity conditions, and inhibited the growth of M. phaseolina through the combined action of volatile and diffusible compounds. Additionally, they exhibited several beneficial traits, including the production of siderophores and indole-3-acetic acid, ACC-deaminase activity, phosphate and zinc solubilization, and reduction of microsclerotia germination. Greenhouse assays showed that the BsA3MX strain alleviated plant damage caused by M. phaseolina and promoted foliage and root growth.
Article
Plant Sciences
Ofir Degani, Asaf Gordani, Elhanan Dimant, Assaf Chen, Onn Rabinovitz
Summary: This study explores the control of charcoal rot disease (CRD) in cotton caused by the fungus Macrophomina phaseolina using different Trichoderma species and Azoxystrobin. The results show that the biological treatment with Trichoderma species can significantly improve crop growth and yield, while adding chemical treatment can enhance the effectiveness of Trichoderma species. In field experiments, seed dressing and irrigation with Trichoderma metabolites result in the highest yields. The study also highlights the importance of reducing chemical treatment dosages and implementing early irrigation for disease suppression.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Plant Sciences
Manish Mathur, Preet Mathur
Summary: This study investigated the impact of climate change scenarios, soil variables, and habitat heterogeneity on the habitat suitability of Macrophomina phaseolina. The results showed that temperature was the most important regulating factor, and the population of this pathogen decreased as the coefficient of variation increased. Soil variables had minimal influence on the pathogen's habitat.
AUSTRALASIAN PLANT PATHOLOGY
(2023)
Article
Microbiology
Nilanjan Sinha, Sourav Kumar Patra, Sanjay Ghosh
Summary: This article investigates the secretome of the necrotrophic fungus M. phaseolina and identifies potential virulence factors and important degrading enzymes. The study is significant for understanding the characteristics of M. phaseolina and plant-pathogen interactions.
FRONTIERS IN MICROBIOLOGY
(2022)
Article
Plant Sciences
Shirley Jacquet, Shuxian Li, Rouf Mian, My Abdelmajid Kassem, Layla Rashad, Sonia Viera, Francisco Reta, Juan Reta, Jiazheng Yuan
Summary: This study evaluated the resistance of wild soybean accessions to charcoal rot and successfully selected disease-resistant lines. The results showed that accession PI 507794 exhibited the highest level of resistance to charcoal rot, while PI 487431 and PI 483660B were susceptible. Using root and hypocotyl as assessment parameters provided a rapid method for identifying potential resistant genotypes.
Article
Biochemical Research Methods
Yang Yang, Timothy M. Walker, Samaneh Kouchaki, Chenyang Wang, Timothy E. A. Peto, Derrick W. Crook, David A. Clifton
Summary: The study utilized deep graph learning to predict anti-tuberculosis drug resistance with satisfactory results. The model performed well even with incomplete phenotypic data and successfully identified relevant genes and SNPs associated with drug resistance.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Elham Khalili, Shahin Ramazi, Faezeh Ghanati, Samaneh Kouchaki
Summary: Phosphorylation of proteins is a significant post-translational modification that plays a crucial role in plant functionality. Accurate prediction of plant phosphorylation sites is vital, and this study develops machine learning-based techniques to improve the prediction of protein phosphorylation sites in soybean. The proposed technique achieves high accuracy and specificity, and can be used to automatically analyze data and predict potential protein phosphorylation sites in plants.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Respiratory System
Philip W. Fowler, Ivan Barilar, Simone Battaglia, Emanuele Borroni, Angela Pires Brandao, Alice Brankin, Andrea Maurizio Cabibbe, Joshua Carter, Daniela Maria Cirillo, Pauline Claxton, David A. Clifton, Ted Cohen, Jorge Coronel, Derrick W. Crook, Viola Dreyer, Sarah G. Earle, Vincent Escuyer, Lucilaine Ferrazoli, George Fu Gao, Jennifer Gardy, Saheer Gharbia, Kelen Teixeira Ghisi, Arash Ghodousi, Ana Luiza Gibertoni Cruz, Louis Grandjean, Clara Grazian, Ramona Groenheit, Jennifer L. Guthrie, Wencong He, Harald Hoffmann, Sarah J. Hoosdally, Martin Hunt, Zamin Iqbal, Nazir Ahmed Ismail, Lisa Jarrett, Lavania Joseph, Ruwen Jou, Priti Kambli, Rukhsar Khot, Jeff Knaggs, Anastasia Koch, Donna Kohlerschmidt, Samaneh Kouchaki, Alexander S. Lachapelle, Ajit Lalvani, Simon Grandjean Lapierre, Ian F. Laurenson, Brice Letcher, Wan-Hsuan Lin, Chunfa Liu, Dongxin Liu, Kerri M. Malone, Ayan Mandal, Mikael Mansjo, Daniela Matias, Graeme Meintjes, Flavia de Freitas Mendes, Matthias Merker, Marina Mihalic, James Millard, Paolo Miotto, Nerges Mistry, David Moore, Kimberlee A. Musser, Dumisani Ngcamu, Hoang Ngoc Nhung, Stefan Niemann, Kayzad Soli Nilgiriwala, Camus Nimmo, Nana Okozi, Rosangela Siqueira Oliveira, Shaheed Vally Omar, Nicholas Paton, Timothy E. A. Peto, Juliana Maira Watanabe Pinhata, Sara Plesnik, Zully M. Puyen, Marie Sylvianne Rabodoarivelo, Niaina Rakotosamimanana, Paola M. Rancoita, Priti Rathod, Esther Robinson, Gillian Rodger, Camilla Rodrigues, Timothy C. Rodwell, Aysha Roohi, David Santos-Lazaro, Sanchi Shah, Thomas Andreas Kohl, Grace Smith, Walter Solano, Andrea Spitaleri, Philip Supply, Utkarsha Surve, Sabira Tahseen, Nguyen Thuy Thuong, Guy Thwaites, Katharina Todt, Alberto Trovato, Christian Utpatel, Annelies Van Rie, Srinivasan Vijay, Timothy M. Walker, A. Sarah Walker, Robin Warren, Jim Werngren, Maria Wijkander, Robert J. Wilkinson, Daniel J. Wilson, Penelope Wintringer, Yu-Xin Xiao, Yang, Zhao Yanlin, Shen-Yuan Yao, Baoli Zhu
Summary: This study determines the epidemiological cut-off values (ECOFF/ECVs) for 13 anti-tuberculosis compounds, which will facilitate the measurement of drug susceptibility in Mycobacterium tuberculosis. These findings can contribute to personalized tuberculosis treatment.
EUROPEAN RESPIRATORY JOURNAL
(2022)
Article
Biology
Philip W. Fowler, Carla Wright, Helen Spiers, Tingting Zhu, Elisabeth M. L. Baeten, Sarah W. Hoosdally, Ana L. Gibertoni Cruz, Aysha Roohi, Samaneh Kouchaki, Timothy M. Walker, Timothy E. A. Peto, Grant Miller, Chris Lintott, David Clifton, Derrick W. Crook, A. Sarah Walker
Summary: Tuberculosis is a respiratory disease that can be treated with antibiotics. It is important to test the susceptibility of each infection to different antibiotics for a good treatment outcome. Through the BashTheBug project on the Zooniverse citizen science platform, volunteers can accurately determine the minimum inhibitory concentration (MIC) of multiple drugs.
Article
Infectious Diseases
Timothy M. Walker, Paolo Miotto, Claudio U. Koser, Philip W. Fowler, Jeff Knaggs, Zamin Iqbal, Martin Hunt, Leonid Chindelevitch, Maha R. Farhat, Daniela Maria Cirillo, Inaki Comas, James Posey, Shaheed V. Omar, Timothy E. A. Peto, Anita Suresh, Swapna Uplekar, Sacha Laurent, Rebecca E. Colman, Carl-Michael Nathanson, Matteo Zignol, Ann Sarah Walker, Derrick W. Crook, Nazir Ismail, Timothy C. Rodwell
Summary: This study aimed to generate a WHO-endorsed catalogue of mutations for drug resistance prediction in Mycobacterium tuberculosis complex (MTBC) and provide a global standard for interpreting molecular information. The research analyzed MTBC isolates from 45 countries and identified mutations associated with resistance to different antituberculosis drugs. The findings can encourage the implementation of molecular diagnostics by national tuberculosis programs.
Article
Biochemistry & Molecular Biology
[Anonymous]
Summary: This study presents a comprehensive resistance prediction for tuberculosis using a large dataset of Mycobacterium tuberculosis isolates. The data includes whole-genome sequencing and minimum inhibitory concentrations to 13 antitubercular drugs. The dataset provides valuable information on the genotypic and phenotypic characteristics of drug resistance, and has the potential to advance our understanding of rare resistance phenotypes. The open-source nature of the data compendium encourages future research in the field.
Article
Biochemistry & Molecular Biology
Camilla Rodrigues, David Moore, Derrick W. Crook, Daniela M. Cirillo, Philip W. Fowler, Zamin Iqbal, Nazir A. Ismail, Nerges Mistry, Stefan Niemann, Tim E. A. Peto, Guy Thwaites, A. Sarah Walker, Timothy MWalker, Daniel J. Wilson, Sarah G. Earle, Daniel J. Wilson, Clara Grazian, A. Sarah Walker, Martin Hunt, Jeff Knaggs, Zamin Iqbal
Summary: The emergence of drug-resistant tuberculosis is a global health concern. Whole-genome sequencing can uncover new resistance mechanisms. This study identified uncatalogued variants associated with minimum inhibitory concentration and improved our knowledge of antimicrobial resistance in M. tuberculosis.
Article
Multidisciplinary Sciences
Elaheh Kalantari, Samaneh Kouchaki, Christine Miaskowski, Kord Kober, Payam Barnaghi
Summary: This study used network analysis to investigate the relationships among co-occurring symptoms in oncology patients during their treatment. Eight unique symptom clusters were identified. The findings suggest that these relationships vary depending on the chemotherapy cycle and cancer type. The evaluation of centrality measures provides insights into potential targets for symptom management interventions.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Information Systems
Omid Rohanian, Samaneh Kouchaki, Andrew Soltan, Jenny Yang, Morteza Rohanian, Yang Yang, David Clifton
Summary: Early detection of COVID-19 can assist with triage, monitoring, and assessment of potential patients, reducing strain on hospitals. Machine learning techniques are used to detect potential cases using routine clinical data, but protecting sensitive information is an understudied area.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Infectious Diseases
Lindsay Sonnenkalb, Joshua James Carter, Andrea Spitaleri, Zamin Iqbal, Martin Hunt, Kerri Marie Malone, Christian Utpatel, Daniela Maria Cirillo, Camilla Rodrigues, Kayzad Soli Nilgiriwala, Philip William Fowler, Matthias Merker, Stefan Niemann
Summary: This study identified genetic variations that confer resistance to bedaquiline and clofazimine, and established a mutation catalogue using experimental evolution, protein modelling, genome sequencing, and phenotypic data analysis. The findings advance the understanding of drug resistance mechanisms in Mycobacterium tuberculosis complex strains and provide important genetic testing evidence for the design of effective treatments.
Article
Biochemical Research Methods
Omid Rohanian, Mohammadmahdi Nouriborji, Samaneh Kouchaki, David A. Clifton
Summary: This article introduces six lightweight biomedical models obtained either by knowledge distillation or continual learning on the Pubmed dataset. Through evaluation on three biomedical tasks, these models perform on par with their larger BioBERT counterparts, with lower parameter ranges.
Article
Computer Science, Information Systems
Mohammad Amin Zare, Reza Boostani, Mokhtar Mohammadi, Samaneh Kouchaki
Summary: Due to the role of emotions in human learning and decision-making, emotional weights/neurons have been considered in shallow neural networks. To address the low convergence rate and learning instability, heuristic upgrading and stochastic learning techniques are introduced. The proposed dopamine based adaptive emotional neural network outperforms state-of-the-art methods in terms of accuracy and convergence rate.
Article
Biotechnology & Applied Microbiology
Martin Hunt, Brice Letcher, Kerri M. Malone, Giang Nguyen, Michael B. Hall, Rachel M. Colquhoun, Leandro Lima, Michael C. Schatz, Srividya Ramakrishnan, Zamin Iqbal
Summary: Minos is a tool that combines outputs from different variant callers, improving the recall of variant calling. It has been benchmarked on bacterial samples and large cohorts of Mycobacterium tuberculosis, demonstrating its ability to build variant maps and correlate with phenotypic resistance.
Article
Engineering, Biomedical
Alexey Youssef, Samaneh Kouchaki, Farah Shamout, Jacob Armstrong, Rasheed El-Bouri, Thomas Taylor, Drew Birrenkott, Baptiste Vasey, Andrew Soltan, Tingting Zhu, David A. Clifton, David W. Eyre
Summary: COVID-19 is a global health threat, and predicting the need for respiratory support in patients is crucial. Traditional Early Warning Scores are found to perform sub-optimally in this aspect, while a new model based on GBT algorithm shows higher accuracy and sensitivity in predicting respiratory deterioration within 24 hours.
HEALTHCARE TECHNOLOGY LETTERS
(2021)
Article
Medical Informatics
Andrew A. S. Soltan, Samaneh Kouchaki, Tingting Zhu, Dani Kiyasseh, Thomas Taylor, Zaamin B. Hussain, Tim Peto, Andrew J. Brent, David W. Eyre, David A. Clifton
Summary: The study aimed to develop and validate early-detection models for COVID-19 using routinely collected health-care data. The models achieved high sensitivity, specificity, and negative predictive values for detecting COVID-19 in patients presenting to the emergency department and admitted to the hospital.
LANCET DIGITAL HEALTH
(2021)