Programmed cell death signatures-driven microglial transformation in Alzheimer’s disease: single-cell transcriptomics and functional validation by Mi-Mi Li, Ying-Xia Yang, Ya-Li Huang, Shu-Juan Wu, Wan-Li Huang, Li-Chao Ye, Ying-Ying Xu

“…In vitro, S100A4 knockdown in AbetaO-treated BV2 microglia improved cell viability, reduced LDH release, and partially alleviated apoptosis. …”
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Integrative machine learning and bioinformatics analysis to identify cellular senescence-related genes and potential therapeutic targets in ulcerative colitis and colorectal cancer by Tianle Xue, Yunpeng Chen, Xiaomeng Li, Zhixiang Zhou, Qiyang Chen

“…An integrated machine learning (IML) model—utilizing 12 algorithms with 10-fold cross-validation—was constructed to pinpoint key diagnostic biomarkers. …”
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The Growing Impact of Natural Language Processing in Healthcare and Public Health by Aadit Jerfy, Owen Selden, Rajesh Balkrishnan PhD

“…Automating labor intensive and tedious tasks with language processing algorithms, using text analytics systems and machine learning to analyze social media data and extracting insights from unstructured data allows for better public sentiment analysis, enhancement of risk prediction models, improved patient communication, and informed treatment decisions. …”
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Investigation of granuloma-targeted host-pathogen interactions identify vaccine correlates of immune protection associated with control of M. tuberculosis replication by David Forrest Ackart, Dr. Faye Lanni, Victoria Mitcham, Dr. G. Brooke Anderson, Dr. Michael Lyons, Dr. Marcela Henao-Tamayo, Dr Brendan Podell

“…While a number of blood transcriptomic signatures have been shown to predict clinical states of TB in human subjects, no correlates exist to indicate immune signatures that control bacterial growth, which would inform improved vaccine design. Methods: To identify correlates of protection, RS ratio in situ hybridization, a measure of M. tuberculosis (Mtb) replication rates within individual granulomas of infected tissue, was combined with high-dimensional multiplex immunohistochemistry to quantify granuloma-centric vaccine induced immune responses associated with the control of Mtb replication. …”
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Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder by Shagufta Almas, Fazli Wahid, Sikandar Ali, Ahmed Alkhyyat, Kamran Ullah, Jawad Khan, Youngmoon Lee

“…Unlike traditional CNN approaches, our method offers improved reliability by reducing time complexity, minimizing errors, and enhancing noise reduction. …”
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Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in gastric cancer, colorectal cancer, and inflammatory bowel disease by Daryll Philip, Rebecca Hodgkiss, Swarnima Kollampallath Radhakrishnan, Akshat Sinha, Animesh Acharjee

“…Conclusion These findings emphasize the potential of microbial and metabolic profiling in cross-disease characterization particularly for GIDs, advancing biomarker discovery for improved diagnostics and targeted therapies.…”
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A Robust Multispectral Reconstruction Network from RGB Images Trained by Diverse Satellite Data and Application in Classification and Detection Tasks by Xiaoning Zhang, Zhaoyang Peng, Yifei Wang, Fan Ye, Tengying Fu, Hu Zhang

“…However, the relatively high cost of multispectral sensors and lower spatial resolution limit the widespread application of multispectral data, and existing reconstruction algorithms suffer from a lack of diverse training datasets and insufficient reconstruction accuracy. …”
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The risks of telehealth in radiation oncology: challenges and mitigation strategies by Sotiri Stathakis, Niko Papanikolaou, Jessica Ashford, Jason Stephens, Aaron LaRose

“…The integration of telehealth into radiation oncology represents a significant evolution in healthcare delivery, driven by the potential for enhanced patient accessibility, convenience, and improved multidisciplinary collaboration and operational efficiency. …”
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Early detection of woody plant encroachment in Canadian prairies using UAV imagery and transformer-based deep learning by Yihan Pu, Xiaojing Lu, Irini Soubry, Xulin Guo

“…The results indicate that Transformers outperformed CNNs, with the largest SegFormer model (MIT-B5) achieving the highest overall accuracy (92.5 %), mean IoU (68.2 %), and F1-score (79.8 %). Transfer learning improved the model performance in SegFormer by more than 5 % in the mF1-score and 7 % in mIoU. …”
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Federated Learning Based on an Internet of Medical Things Framework for a Secure Brain Tumor Diagnostic System: A Capsule Networks Application by Roman Rodriguez-Aguilar, Jose-Antonio Marmolejo-Saucedo, Utku Köse

“…By utilizing specific brain MRI datasets, the model enables multiple local capsule networks (CapsNet) to achieve improved classification results. The average accuracy rate of the CapsNet model exceeds 97%. …”
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Mapping forest types along ecological gradient in Pakistan by Naveed Ahmad, Syed Ghias Ali

“…This study suggests that mapping of forest types through machine learning algorithms may be improved by incorporating other explanatory variables such as microclimate, soil types, nutrients, anthropogenic, demographic factors and spectral indices.…”
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Deep Learning in Defect Detection of Wind Turbine Blades: A Review by Katleho Masita, Ali N. Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…Addressing current limitations through interdisciplinary research and innovative algorithms will pave the way for sustainable and cost-effective wind energy systems, ultimately contributing to the global transition toward renewable energy.…”
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Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis. by Jessica L Nielson, Shelly R Cooper, John K Yue, Marco D Sorani, Tomoo Inoue, Esther L Yuh, Pratik Mukherjee, Tanya C Petrossian, Jesse Paquette, Pek Y Lum, Gunnar E Carlsson, Mary J Vassar, Hester F Lingsma, Wayne A Gordon, Alex B Valadka, David O Okonkwo, Geoffrey T Manley, Adam R Ferguson, TRACK-TBI Investigators

“…Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. …”
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Symmetrical Components Digital Filters for Microprocessor-Based Protection Input Signals by F. A. Romaniuk, V. Yu. Rumiantsev, Yu. V. Rumiantsev

“…The results of the research have demonstrated that the developed digital filters of the negative and zero sequences have 1.1–1.4 times higher performance as compared with similar Fourier filters accepted as reference and that they are distinguished by improved magnitudes of dynamic indicators.…”
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Experimental investigation of shaft misalignment effects on bearing reliability through vibration signal analysis using machine learning and deep learning by Fransiskus Tatas Dwi Atmaji, Jamasri, Hari Agung Yuniarto, I Made Miasa

“…Statistical time-domain feature extraction notably improved the performance of classical models, with KNN achieving a maximum accuracy of 92.9%. …”
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ANALYSIS OF ACOUSTIC INFORMATION PROTECTION METHODS IN CRITICAL APPLICATIONS by Mykhailo Mozhaiev, Oleksandr Mozhaiev, Yurii Gnusov, Volodymyr Strukov, Petro Klimushin, Dmytro Yevstrat

“…Further research is desirable to analyze the possible use of methods for synthesizing large ensembles of quasi-orthogonal discrete signals with improved ensemble, structural and correlation properties to ensure higher security indicators of acoustic channels in computer systems of critical applications. …”
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Role of Roadside Units in Cluster Head Election and Coverage Maximization for Vehicle Emergency Services by Ravneet Kaur, Robin Doss, Lei Pan, Chaitanya Singla, Selvarajah Thuseethan

“…Efficient clustering algorithms are critical for enabling the timely dissemination of emergency messages across maximum coverage areas in vehicular networks. …”
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Post-Quantum Cryptography Resilience in Telehealth Using Quantum Key Distribution by Don Roosan, Rubayat Khan, Saif Nirzhor, Fahmida Hai

“…Despite increased computational overhead, the DAG approach efficiently handled parallel transactions, indicating improved scalability compared to traditional linear blockchains. …”
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Cotton Crop Classification using Optical and Microwave Remote Sensing Datasets in Google Earth Engine by B. Meerasha, M. Sagayam

“…Incorporating common vegetation indices and Sentinel-2 data, combining with Sentinel-1 reflectance bands improved the overall crop classification accuracy by 0.2% and 0.6%, respectively. …”
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Architectural Exploration and Performance Enhancement of the CVA6 RISC-V Core Using the Gem5 Simulation Framework by Umer Shahid, Muhammad Tahir, Bilal Zafar, Ayesha Ahmad, Shanzay Wasim, Bisal Saeed

“…To further enhance the architecture, we integrated machine learning algorithms to optimize performance and resource efficiency. …”
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