Review
Plant Sciences
Beena Alam, Junwen Li, Qun Ge, Mueen Alam Khan, Juwu Gong, Shahid Mehmood, Youlu Yuan, Wankui Gong
Summary: Endophytic fungi are host-associated fungal communities that provide beneficial effects to their hosts while gaining advantages through multidimensional interactions with host plants and other microbiomes. Secondary metabolites play a key role in these interactions and have various biological applications in modern medicine, agriculture, and industry. Research on endophytic fungi has revealed their biodiversity, ecological distribution, and potential for further study in the field of endophytic biology.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Microbiology
Qianliang Ming, Xiuning Huang, Yimo He, Lingyue Qin, Yu Tang, Yanxia Liu, Yuting Huang, Hongwei Zhang, Peng Li
Summary: Endophytic fungi are a rich source of natural products with vast chemical diversity. In this study, the whole genome of an endophyte, Dactylonectria alcacerensis CT-6, was sequenced for the first time. Genomic analysis revealed numerous unknown biosynthetic gene clusters for secondary metabolites in D. alcacerensis CT-6. This study provides a foundation for further exploration of the chemical constituents of D. alcacerensis CT-6 using genome-mining strategies.
Review
Biotechnology & Applied Microbiology
Sushma Mishra, Pramod Kumar Sahu, Vishad Agarwal, Namrata Singh
Summary: Plant secondary metabolites have potential applications in various industries, but their direct isolation from plants may lead to over-harvesting and loss of biodiversity. Endophytic microbes have the ability to produce metabolites similar to those of their host plants, providing a sustainable and commercially valuable resource.
APPLIED MICROBIOLOGY AND BIOTECHNOLOGY
(2021)
Article
Microbiology
Kolathuru Puttamadaiah Ramesha, Nagabhushana Chandra Mohana, Siddaiah Chandra Nayaka, Sreedharamurthy Satish
Summary: The study found that epigenetic modification in Nigrospora sphaerica can activate new metabolites, including the induction of cryptic metabolites through the activation of potential biosynthetic gene clusters and the silencing of phomalactone in some treatments. Additionally, HDAC treatments showed a significant increase in cryptic metabolite induction, supporting the activation of cryptic metabolites with biological significance.
FRONTIERS IN MICROBIOLOGY
(2021)
Review
Microbiology
Humberto E. Ortega, Daniel Torres-Mendoza, Zuleima E. Caballero, Luis Cubilla-Rios
Summary: Endophytic fungi, despite being the least studied among microorganisms, have gained attention for their high biological diversity and production of novel bioactive compounds to protect host plants against stress. These compounds, such as alkaloids, peptides, and terpenoids, show significant biological activities that could be useful for medical applications.
Article
Biotechnology & Applied Microbiology
Ramy S. Yehia
Summary: The study identified a new crystallized compound, C-HMMP, from the endophytic fungus Colletotrichum acutatum residing in Angelica sinensis and assessed its in vitro antimicrobial, antibiofilm, antioxidant, antimalarial, and anti-proliferative properties. C-HMMP showed effective antimicrobial activity against various pathogenic bacteria and fungi, as well as excellent antibiofilm activity. It also exhibited dose-dependent antimalarial and radical scavenging activities, and notable anti-proliferative activity against HepG-2, HeLa, and MCF-7 cell lines.
JOURNAL OF MICROBIOLOGY AND BIOTECHNOLOGY
(2023)
Article
Microbiology
Kumaravel Kaliaperumal, Limbadri Salendra, Yonghong Liu, Zhiran Ju, Sunil Kumar Sahu, Sanniyasi Elumalai, Kumaran Subramanian, Nahaa M. Alotaibi, Nawaf Alshammari, Mohd Saeed, Rohini Karunakaran
Summary: Fungus-derived secondary metabolites have biomedical potential and chemical diversity. Mining endophytic fungi for drug candidates is an ongoing process. In this study, seven secondary metabolites were extracted from endophytic fungi derived from a sponge and subjected to characterization and bioactivity screening. One of the compounds, averufin (1), displayed strong anticancer activity.
FRONTIERS IN MICROBIOLOGY
(2023)
Review
Biochemistry & Molecular Biology
Juntai Zhu, Lixia Song, Shengnan Shen, Wanxin Fu, Yaying Zhu, Li Liu
Summary: This review focuses on Aspergillus-derived alkaloids, compounds with diverse biological activities and structural diversity.
Review
Chemistry, Medicinal
Duo Cao, Peng Sun, Sumana Bhowmick, Yahui Wei, Bin Guo, Yanhong Wei, Luis A. J. Mur, Zhenliang Sun
Summary: Studies have shown that endophytic fungi isolated from Huperzia serrata are a rich source of natural products, with 9 strains capable of producing Huperzine A and more than 200 secondary metabolites identified to date. Some of these metabolites have cholinesterase-inhibitory or antibacterial activity, making them potential targets for pharmaceutical industries.
Article
Multidisciplinary Sciences
Ali Rahnavard, Brendan Mann, Abhigya Giri, Ranojoy Chatterjee, Keith A. Crandall
Summary: Proteins and metabolites are important data for studying the biological processes and clinical information of COVID-19, but there are limited methods to analyze such diverse and unstructured data. By integrating proteomics and metabolomics data, we found biological indicators associated with lung, liver, and gastrointestinal dysfunction in relation to disease severity, as well as proteins playing critical roles in responses to injury or infection within these anatomical sites.
SCIENTIFIC REPORTS
(2022)
Article
Microbiology
Nan Ma, Dengpan Yin, Ying Liu, Ziyong Gao, Yu Cao, Tongtong Chen, Ziyi Huang, Qiaojun Jia, Dekai Wang
Summary: This study identified the rhizosphere soil and endophytic fungal communities of F. dibotrys in five different ecological regions in China using high-throughput sequencing methods. The study found significant correlations between soil physicochemical properties and active components of F. dibotrys, as well as the association between soil microbes and key secondary metabolites. This research provides a deeper understanding of soil-plant-fungal symbioses and secondary metabolites in F. dibotrys, and offers a scientific basis for improving the quality of F. dibotrys using biological fertilization strategies.
FRONTIERS IN MICROBIOLOGY
(2023)
Review
Biochemistry & Molecular Biology
Ruihong Zheng, Shoujie Li, Xuan Zhang, Changqi Zhao
Summary: Secondary metabolites from plant endophytic fungi are increasingly attracting attention as potential lead compounds in drug discovery due to their high biological activities. This review summarized the chemical structures of 449 new metabolites from a total of 134 journal articles and described various biological activities and structure-activity relationship of some compounds.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Review
Pharmacology & Pharmacy
Naike Ye, Zekai Yang, Yuchen Liu
Summary: This article reviews the recent advances in using density functional theory (DFT) in molecular modeling studies of COVID-19 pharmaceuticals. It provides an overview of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) drugs and targets, introduces the basic principles and application methods of DFT, discusses different approaches of applying DFT, and highlights important factors to consider when incorporating DFT in future drug modeling research.
DRUG DISCOVERY TODAY
(2022)
Review
Microbiology
Kunlong Yang, Jun Tian, Nancy P. Keller
Summary: Post-translational modifications (PTMs) are important for regulating secondary metabolite biosynthesis in Aspergillus species. Histone modifications can be manipulated to activate silent biosynthetic gene clusters (BGCs), while non-histone PTMs also play critical roles in regulating secondary metabolism.
ENVIRONMENTAL MICROBIOLOGY
(2022)
Article
Computer Science, Software Engineering
Ngan Nguyen, Ondrej Strnad, Tobias Klein, Deng Luo, Ruwayda Alharbi, Peter Wonka, Martina Maritan, Peter Mindek, Ludovic Autin, David S. Goodsell, Ivan Viola
Summary: This new technique allows for rapid modeling and construction of scientifically accurate mesoscale biological models based on a few 2D microscopy scans and the latest knowledge available about the biological entity. Utilizing statistical and rule-based modeling approaches, the 3D models are fast to author, construct, and revise. In addition to incorporating imaging evidence and statistical properties in the construction of the models, further information can be included by defining rules.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2021)
Article
Green & Sustainable Science & Technology
Meghdad Pirsaheb, Sajad Moradi, Mohsen Shahlaei, Xiangke Wang, Negin Farhadian
JOURNAL OF CLEANER PRODUCTION
(2019)
Article
Chemistry, Physical
Sajad Moradi, Solmaz Khani, Mohabbat Ansari, Mohsen Shahlaei
JOURNAL OF MOLECULAR LIQUIDS
(2019)
Article
Environmental Sciences
Meghdad Pirsaheb, Sajad Moradi, Mohsen Shahlaei, Xiangke Wang, Negin Farhadian
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2019)
Article
Spectroscopy
Sajad Moradi, Negin Farhadian, Fatemeh Balaei, Mohabbat Ansari, Mohsen Shahlaei
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2020)
Article
Engineering, Electrical & Electronic
Maryam Haghighi, Mohsen Shahlaei, Mohsen Irandoust, Alireza Hassanpour
JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS
(2020)
Article
Chemistry, Analytical
Giti Paimard, Mohsen Shahlaei, Pouran Moradipour, Hamzeh Akbari, Mahsa Jafari, Elham Arkan
SENSORS AND ACTUATORS B-CHEMICAL
(2020)
Article
Spectroscopy
Mahtab Amoorahim, Mohammad Reza Ashrafi-Kooshk, Sajjad Esmaeili, Mohsen Shahlaei, Sajad Moradi, Reza Khodarahmi
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2020)
Article
Chemistry, Multidisciplinary
Amir Kiani, Mohsen Shahlaei, Mahdi Rahpeyma, Hadi Adibi
Summary: Angiogenesis plays a crucial role in cancer progression and other non-neoplastic diseases. Isatin-based compounds have shown potential as anticancer agents, with some exhibiting antiangiogenic effects. Specifically, (Z)-3-((5-(benzylthio)-4H-1,2,4-triazol-3-yl)imino)-5-haloindolin-2-one macromolecules showed the highest cytotoxicity and ability to reduce MMP-2 and MMP-9 levels in cancer cell lines. Further investigation is needed to understand the molecular mechanisms of these compounds.
JOURNAL OF THE IRANIAN CHEMICAL SOCIETY
(2021)
Article
Engineering, Electrical & Electronic
Maryam Haghighi, Mohsen Shahlaei, Kiumars Bahrami, Homa Targhan
Summary: A new electrochemical sensor using RGO/Ti-MOF-modified GCE was introduced for the electro-catalytic oxidation and determination of Propranolol, showing high sensitivity and low detection limit. The synthesized composite exhibited excellent performance in phosphate buffer solution, significantly reducing the oxidation over-potential of Propranolol.
JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS
(2021)
Article
Chemistry, Multidisciplinary
Maryam Haghighi, Mehdi Rezaei, Payam Sariaslani, Sajad Moradi, Mohsen Shahlaei
Summary: A modified carbon paste electrode based on nanomagnetic core-shell and reduced graphene oxide was developed for sensitive determination of lamotrigine, with a detection limit of 0.7 nM. The electrochemical sensor was successfully applied for quantification of lamotrigine in tablet and plasma samples under optimized conditions.
MONATSHEFTE FUR CHEMIE
(2021)
Article
Chemistry, Multidisciplinary
Meghdad Pirsaheb, Sajad Moradi, Mohsen Shahlaei, Negin Farhadian
NEW JOURNAL OF CHEMISTRY
(2020)
Correction
Chemistry, Multidisciplinary
Sajad Moradi, Amin Nowroozi, Mohsen Shahlaei
Review
Chemistry, Multidisciplinary
Sajad Moradi, Amin Nowroozi, Mohsen Shahlaei
Article
Pharmacology & Pharmacy
Seyran Saeidi, Elham Esmaeili, Mohabbat Ansari, Sajad Moradi, Mohsen Shahlaei
JOURNAL OF REPORTS IN PHARMACEUTICAL SCIENCES
(2019)
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)