Review
Environmental Sciences
Zakaria A. Mohamed, Mohamed Hashem, Saad Alamri, Alexandre Campos, Vitor Vasconcelos
Summary: Research on biological treatment of harmful cyanobacterial blooms and cyanotoxins has primarily focused on bacteria, with limited attention on algicidal fungi. This review highlights the potential of various fungal species in lysing cyanobacteria and degrading cyanotoxins, showcasing their selectivity against harmful algae and potential environmental applications.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Review
Engineering, Environmental
Marco Coha, Giulio Farinelli, Alberto Tiraferri, Marco Minella, Davide Vione
Summary: Produced water is the main by-product of fossil fuel extraction activities, which requires adequate treatment to purify its quality for recycling or discharge. Advanced oxidation processes are increasingly studied for the removal of organic pollutants in produced water, including various methods such as Fenton-based oxidation. Different oxidation methods can be used as a polishing stage or as an auxiliary treatment for further biological processes and membrane separation, with the potential for combination within the same system.
CHEMICAL ENGINEERING JOURNAL
(2021)
Article
Immunology
Nicole C. Ammerman, Eric L. Nuermberger, Andrew Owen, Steve P. Rannard, Caren Freel Meyers, Susan Swindells
Summary: This article provides an overview of the specific considerations and current preclinical advancements related to the development of long-acting technologies for tuberculosis drugs to treat latent infection, including target product profiles, suitability of drugs for long-acting formulations, ongoing research efforts, and translation to clinical studies.
CLINICAL INFECTIOUS DISEASES
(2022)
Article
Biochemical Research Methods
Zhixu Ni, Michele Wolk, Geoff Jukes, Karla Mendivelso Espinosa, Robert Ahrends, Lucila Aimo, Jorge Alvarez-Jarreta, Simon Andrews, Robert Andrews, Alan Bridge, Geremy C. Clair, Matthew J. Conroy, Eoin Fahy, Caroline Gaud, Laura Goracci, Juergen Hartler, Nils Hoffmann, Dominik Kopczyinki, Ansgar Korf, Andrea F. Lopez-Clavijo, Adnan Malik, Jacobo Miranda Ackerman, Martijn R. Molenaar, Claire O'Donovan, Tomas Pluskal, Andrej Shevchenko, Denise Slenter, Gary Siuzdak, Martina Kutmon, Hiroshi Tsugawa, Egon L. Willighagen, Jianguo Xia, Valerie B. O'Donnell, Maria Fedorova
Summary: Progress in mass spectrometry lipidomics has led to a rapid increase in research in biology and biomedicine, generating large datasets that require sophisticated solutions for automated data processing. To address this issue, various software tools have been developed, but researchers often face difficulties in choosing the most suitable approach, resulting in inefficient and time-consuming ad hoc testing.
Review
Chemistry, Multidisciplinary
Meng Sun, Jiani Yang, Yueyun Fan, Yinfeng Zhang, Jian Sun, Min Hu, Ke Sun, Jinfeng Zhang
Summary: This review explores the strategies for fabricating hybrid membrane nanovesicles (HMNVs) and the various types of HMNVs based on membrane components and chimera biotechnology. It also summarizes the current advancements in biomedical applications of HMNVs, including diagnosis, bioimaging, and treatment of different diseases. Finally, it presents the ongoing challenges and prospects for clinical translation of currently developed HMNVs.
Article
Immunology
Chunling Li, Shifu Wang, Hui Yu, Jiangxia Wang, Jikui Deng, Hongmei Wang, Chunzhen Hua, Zhiqiang Zhuo, Lei Chen, Jianhua Hao, Wei Gao, Hong Zhang, Ting Zhang, Hongmei Xu, Chuanqing Wang
Summary: There is inadequate research on childhood tuberculosis in China. A multicenter study was conducted using the cross-priming amplification (CPA) method to investigate the incidence and characteristics of childhood tuberculosis in suspected populations. The results showed that both pulmonary and extrapulmonary tuberculosis are common in children in China, with teenagers being particularly susceptible to infection. The occurrence of childhood tuberculosis is associated with a history of exposure to tuberculosis.
FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY
(2022)
Review
Environmental Sciences
Muhammad Adnan, Waqar Islam, Liu Gang, Han Y. H. Chen
Summary: Fungi play a major role in forest ecosystems by recycling organic matter and channeling nutrients. Different fungal communities respond to plant communities and environmental parameters and impact the forest ecosystem through their intrinsic participation. Traditional methods have limited the in-depth study of fungal communities, but recent biological methods have made significant breakthroughs in observing fungal diversity and their role in forest ecosystems.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Review
Pharmacology & Pharmacy
SeungHyun Park, KangJu Lee, WonHyoung Ryu
Summary: Novel MN technologies are expected in terms of designs, fabrication methods, materials, and possible application sites given the recent advances in DeMNs.
EXPERT OPINION ON DRUG DELIVERY
(2022)
Editorial Material
Optics
Walker Peterson, Kotaro Hiramatsu, Keisuke Goda
Summary: Coherent Raman scattering microscopy enables high-contrast imaging of tissues and single cells based on molecular vibrations. However, conventional techniques face a trade-off between Raman spectral bandwidth, imaging speed, and image fidelity. This trade-off can be overcome using emerging computational tools such as compressive sensing and machine learning, even though it is currently challenging to address through optical design.
LIGHT-SCIENCE & APPLICATIONS
(2023)
Article
Biochemistry & Molecular Biology
Matthew E. Griffin, Linda C. Hsieh-Wilson
Summary: This primer discusses key methods and recent breakthrough technologies for identifying, monitoring, and manipulating glycans in mammalian systems.
Review
Chemistry, Multidisciplinary
Min Soo Kim, Hochan Chang, Lei Zheng, Qiang Yan, Brian F. Pfleger, John Klier, Kevin Nelson, Erica L. -W. Majumder, George W. Huber
Summary: Environmental concerns have led to the development of biodegradable plastics, which can be degraded by microorganisms into small molecules. However, there are misconceptions surrounding the term "biodegradable" and this can lead to excessive consumption and increased littering. This review provides an overview of biodegradable plastics, clarifies definitions and terms, and discusses analytical techniques and applications.
Article
Computer Science, Information Systems
Rakhee Kallimani, Krishna Pai, Prasoon Raghuwanshi, Sridhar Iyer, Onel L. A. Lopez
Summary: In recent years, the increasing interest in Artificial Intelligence (AI) and Machine Learning (ML) has led to the emergence of the TinyML paradigm. TinyML is an embedded ML technique that enables ML applications on resource-constrained devices. However, there are challenges such as processing capacity optimization, improved reliability, and maintenance of learning models' accuracy that need to be addressed for effective implementation of TinyML.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Chemistry, Multidisciplinary
Abhijeet Pandey, Ajinkya N. Nikam, Gasper Fernandes, Sanjay Kulkarni, Bharath Singh Padya, Ruth Prassl, Subham Das, Alex Joseph, Prashant K. Deshmukh, Pravin O. Patil, Srinivas Mutalik
Summary: Black phosphorus has emerged as a promising material for various applications, including optoelectronics, 3D printing, and bioimaging, due to its unique properties like anisotropy and infrared bandgap. Researchers are exploring surface modifications to enhance stability and demonstrating the multifunctional role of black phosphorus in drug delivery, 3D printing, and wound dressing. Further research is ongoing to develop black phosphorus-based theranostic platforms for cancer therapy and other diseases.
Article
Biochemistry & Molecular Biology
Lidia Ciccone, Susanna Nencetti, Maria Marino, Chiara Battocchio, Giovanna Iucci, Iole Venditti, Martina Marsotto, Emiliano Montalesi, Simone Socci, Beatrice Bargagna, Elisabetta Orlandini
Summary: Epidemiological studies suggest that a fruit and vegetable-rich diet can reduce the incidence of neurodegenerative diseases. Resveratrol and its dimethylated metabolite, pterostibene, are known for their neuroprotective action. However, the clinical use of Res is limited due to its rapid metabolism and poor bioavailability. In this study, two fluorescent derivatives of pterostibene were proposed and synthesized, showing potential as tools for studying the metabolism and pharmacokinetics of pterostibene.
JOURNAL OF ENZYME INHIBITION AND MEDICINAL CHEMISTRY
(2022)
Article
Chemistry, Multidisciplinary
Gopika Gopan, K. Kezia Susan, Enakshy Rajan Jayadevan, Roy Joseph
Summary: A highly radiopaque compound was synthesized and characterized by various analytical techniques, showing noncytotoxicity in vitro experiments. It has the potential to be used for X-ray imaging in clinical scenarios.
Article
Oncology
Kanan T. Desai, Brian Befano, Zhiyun Xue, Helen Kelly, Nicole G. Campos, Didem Egemen, Julia C. Gage, Ana-Cecilia Rodriguez, Vikrant Sahasrabuddhe, David Levitz, Paul Pearlman, Jose Jeronimo, Sameer Antani, Mark Schiffman, Silvia de Sanjose
Summary: Limited access to effective cervical cancer screening programs in resource-limited settings leads to high cervical cancer burden. Human papillomavirus (HPV) testing is recognized as the preferable primary screening approach, providing long-term reassurance and adaptability to self-sampling. Visual inspection with acetic acid (VIA) is widely used in resource-limited settings, but it is subjective and inaccurate.
INTERNATIONAL JOURNAL OF CANCER
(2022)
Article
Multidisciplinary Sciences
Sivaramakrishnan Rajaraman, Prasanth Ganesan, Sameer Antani
Summary: In this study, the effect of model calibration on the performance of medical image classification tasks was systematically analyzed. The results show that calibration can significantly improve performance at the default classification threshold, but the differences are not significant at the PR-guided threshold. This observation holds for different image modalities and degrees of class imbalance.
Article
Multidisciplinary Sciences
Sivaramakrishnan Rajaraman, Gregg Cohen, Lillian Spear, Les Folio, Sameer Antani
Summary: Automated bone suppression methods can enhance the visibility of soft tissues in chest X-ray images and improve automated disease detection. The DeBoNet ensemble model, constructed using top-performing convolutional neural network models, outperformed individual models in terms of various metrics. Applying the best-performing bone-suppression model to CXR images showed improved performance in detecting pulmonary abnormalities consistent with COVID-19. Automatic bone suppression brings benefits to disease classification.
Article
Genetics & Heredity
Sivaramakrishnan Rajaraman, Ghada Zamzmi, Les R. Folio, Sameer Antani
Summary: By constructing an ensemble of CNN and ViT models, this study successfully detected TB-consistent findings in lateral CXRs, achieving significant performance improvement. The interpretation of CNN and ViT models' decisions also highlighted the discriminative image regions contributing to the final output.
FRONTIERS IN GENETICS
(2022)
Article
Oncology
Peng Guo, Zhiyun Xue, Sandeep Angara, Sameer K. Antani
Summary: This study proposes a novel deep learning-based image registration method to automatically align a sequence of cervical images. The proposed method achieves significant improvement in cervical boundary detection compared to unregistered images and maintains image integrity.
Article
Infectious Diseases
Maria Goretti Lopez-Ramos, Joan Vinent, Rob Aarnoutse, Angela Colbers, Eneritz Velasco-Arnaiz, Loreto Martorell, Lola Falcon-Neyra, Olaf Neth, Luis Prieto, Sara Guillen, Fernando Baquero-Artigao, Ana Mendez-Echevarria, David Gomez-Pastrana, Ana Belen Jimenez, Rebeca Lahoz, Jose Tomas Ramos-Amador, Antoni Soriano-Arandes, Begona Santiago, Rosa Farre, Claudia Fortuny, Dolors Soy, Antoni Noguera-Julian
Summary: In 2010, the WHO recommended increasing the daily doses of first-line anti-tuberculosis medicines in children. This study aimed to investigate the pharmacokinetics of a once-daily dose of isoniazid (INH) in infants under 6 months of age. The study found that the target adult levels were not reached in a few cases, but overall, the treatment was well tolerated and no major safety concerns were raised.
Editorial Material
Computer Science, Information Systems
K. C. Santosh, Sameer Antani
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Medicine, General & Internal
Sivaramakrishnan Rajaraman, Feng Yang, Ghada Zamzmi, Zhiyun Xue, Sameer Antani
Summary: Deep learning models have achieved state-of-the-art performance in segmenting anatomical and disease regions of interest (ROIs) in medical images. This study investigates the performance variations of an Inception-V3 UNet model using different image resolutions, lung ROI cropping, and aspect ratio adjustments in segmenting tuberculosis-consistent lesions in chest X-rays (CXRs), and identifies the optimal image resolution to improve segmentation performance.
Article
Medicine, General & Internal
Zhiyun Xue, Feng Yang, Sivaramakrishnan Rajaraman, Ghada Zamzmi, Sameer Antani
Summary: This paper investigates domain shift in medical imaging-based machine learning predictions. It proposes a new feature visualization method to explain the performance of object detection networks. The results provide valuable guidance for the analysis of training data and domain shift analysis in medical imaging machine learning research.
Article
Computer Science, Artificial Intelligence
Sivaramakrishnan Rajaraman, Feng Yang, Ghada Zamzmi, Zhiyun Xue, Sameer Antani
Summary: Lung segmentation in chest X-rays is crucial for accurate diagnosis of cardiopulmonary diseases. However, the shape of the lungs varies significantly across different developmental stages, which can impact the performance of deep learning models trained on adult populations when applied to pediatric lung segmentation. This study aims to analyze the generalizability of deep adult lung segmentation models to the pediatric population and proposes a systematic approach to improve performance. Novel evaluation metrics are introduced to assess segmentation performance and cross-domain generalization. The results show significant improvement in cross-domain generalization through the proposed approach.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Oncology
Didem Egemen, Rebecca B. Perkins, Li C. Cheung, Brian Befano, Ana Cecilia Rodriguez, Kanan Desai, Andreanne Lemay, Syed Rakin Ahmed, Sameer Antani, Jose Jeronimo, Nicolas Wentzensen, Jayashree Kalpathy-Cramer, Silvia De Sanjose, Mark Schiffman
Summary: This article emphasizes the importance of novel screening and diagnostic tests based on artificial intelligence image recognition algorithms. It provides a conceptual step-by-step approach to bridge the gap between the creation of AI algorithms and clinical efficacy. The article also highlights the need for rigorous evaluation, risk estimation, and development of guidelines for clinical use.
JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE
(2023)
Editorial Material
Medicine, General & Internal
Jonathan R. Spirnak, Sameer Antani
Summary: There has been an exponential increase in research on the applications of artificial intelligence (AI) in medicine in the past decade. The release of large language models like ChatGPT has sparked discussions on whether machine intelligence can surpass human capability. However, concerns have been raised regarding the social, legal, and moral implications of this powerful technology. The challenge in medicine is to harness AI to improve patient outcomes. Military medicine can greatly benefit from AI, but this requires the understanding and collaboration of the rising generations of military medical professionals.
Article
Computer Science, Information Systems
Feng Yang, Ghada Zamzmi, Sandeep Angara, Sivaramakrishnan Rajaraman, Andre Aquilina, Zhiyun Xue, Stefan Jaeger, Emmanouil Papagiannakis, Sameer K. K. Antani
Summary: This study aims to assess the inter-annotator agreement among multiple expert annotators when segmenting the same lesion(s)/abnormalities on medical images, and proposes three metrics for assessment.
Proceedings Paper
Computer Science, Interdisciplinary Applications
Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang, Zhiyun Xue, Sameer K. Antani
Summary: This article discusses the impact of underlying data characteristics on AI-based medical computer vision algorithms and presents recent works conducted in a research lab to enhance understanding of how these characteristics influence the design of medical decision-making algorithms and outcome reliability.
RECENT TRENDS IN IMAGE PROCESSING AND PATTERN RECOGNITION, RTIP2R 2022
(2023)
Article
Computer Science, Information Systems
Feng Yang, Pu Xuan Lu, Min Deng, Yi Xiang J. Wang, Sivaramakrishnan Rajaraman, Zhiyun Xue, Les R. Folio, Sameer K. Antani, Stefan Jaeger
Summary: This study presents a collection of annotations/segmentations of pulmonary radiological manifestations consistent with tuberculosis (TB), with the goal of advancing image segmentation methods and improving the fine-grained segmentation of TB findings in digital chest X-ray images.