AIGAN: Attention–encoding Integrated Generative Adversarial Network for the reconstruction of low-dose CT and low-dose PET images

Medical Image Analysis, Journal Year: 2023, Volume and Issue: 86, P. 102787 - 102787

Published: Feb. 28, 2023

Language: Английский

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Harnessing Artificial Intelligence in Multimodal Omics Data Integration: Paving the Path for the Next Frontier in Precision Medicine

Annual Review of Biomedical Data Science, Journal Year: 2024, Volume and Issue: 7(1), P. 225 - 250

Published: May 20, 2024

The integration of multiomics data with detailed phenotypic insights from electronic health records marks a paradigm shift in biomedical research, offering unparalleled holistic views into and disease pathways. This review delineates the current landscape multimodal omics integration, emphasizing its transformative potential generating comprehensive understanding complex biological systems. We explore robust methodologies for ranging concatenation-based to transformation-based network-based strategies, designed harness intricate nuances diverse types. Our discussion extends incorporating large-scale population biobanks dissecting high-dimensional layers at single-cell level. underscores emerging role large language models artificial intelligence, anticipating their influence as near-future pivot approaches. Highlighting both achievements hurdles, we advocate concerted effort toward sophisticated models, fortifying foundation groundbreaking discoveries precision medicine.

Language: Английский

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A New Theranostic Platform Against Gram‐Positive Bacteria Based on Near‐Infrared‐Emissive Aggregation‐Induced Emission Nanoparticles

Small, Journal Year: 2024, Volume and Issue: 20(28)

Published: Feb. 11, 2024

Abstract Infections induced by Gram‐positive bacteria pose a great threat to public health. Antibiotic therapy, as the first chosen strategy against bacteria, is inevitably associated with antibiotic resistance selection. Novel therapeutic strategies for discrimination and inactivation of are thus needed. Here, specific type aggregation‐induced emission luminogen (AIEgen) near‐infrared fluorescence novel antibiotic‐free proposed. With combination positively charged group into highly twisted architecture, self‐assembled AIEgens (AIE nanoparticles (NPs)) at relatively low concentration (5 µ m ) exhibited binding photothermal effect living both in vitro vivo. Moreover, toxicity assays demonstrated excellent biocompatibility AIE NPs this concentration. All these properties make generation theranostic platform combating highlight their promising potential vivo tracing such bacteria.

Language: Английский

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Positron emission tomography molecular imaging‐based cancer phenotyping

Cancer, Journal Year: 2022, Volume and Issue: 128(14), P. 2704 - 2716

Published: April 13, 2022

During the past several decades, numerous studies have provided insights into biological characteristics of cancer cells and identified various hallmarks acquired in tumorigenic processes. However, it is still challenging to image these distinctive traits facilitate management patients clinical settings. The rapidly evolving field positron emission tomography (PET) imaging has opportunities investigate cancer's vivo. This article reviews current status PET on characterizing discusses future directions strategies facilitating vivo phenotyping.

Language: Английский

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Role of Radiomics-Based Baseline PET/CT Imaging in Lymphoma: Diagnosis, Prognosis, and Response Assessment

Molecular Imaging and Biology, Journal Year: 2022, Volume and Issue: 24(4), P. 537 - 549

Published: Jan. 14, 2022

Language: Английский

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Stacking Ensemble Learning–Based [¹⁸F]FDG PET Radiomics for Outcome Prediction in Diffuse Large B-Cell Lymphoma

Journal of Nuclear Medicine, Journal Year: 2023, Volume and Issue: 64(10), P. 1603 - 1609

Published: July 27, 2023

This study aimed to develop an analytic approach based on [18F]FDG PET radiomics using stacking ensemble learning improve the outcome prediction in diffuse large B-cell lymphoma (DLBCL). Methods: In total, 240 DLBCL patients from 2 medical centers were divided into training set (n = 141), internal testing 61), and external 38). Radiomics features extracted pretreatment scans at patient level 4 semiautomatic segmentation methods (SUV threshold of 2.5, SUV 4.0 [SUV4.0], 41% SUVmax, mean liver uptake [PERCIST]). All harmonized with ComBat method. The intraclass correlation coefficient was used evaluate reliability by different methods. Features most reliable method selected Pearson analysis LASSO (least absolute shrinkage selection operator) algorithm. A applied build radiomics-only combined clinical-radiomics models for 2-y progression-free survival overall machine classifiers (support vector machine, random forests, gradient boosting decision tree, adaptive boosting). Confusion matrix, receiver-operating-characteristic curve analysis, model performance. Results: Among methods, SUV4.0 yielded highest interobserver reliability, 830 (66.7%) features. constructed achieved best discrimination For set, areas under accuracy stacking-based 0.771 0.789, respectively. prediction, area 0.725 0.763 set. also demonstrated a more distinct risk stratification than International Prognostic Index all sets (log-rank test, P < 0.05). Conclusion: that incorporates clinical characteristics could enable improved DLBCL.

Language: Английский

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Cellular senescence imaging and senolysis monitoring in cancer therapy based on a β-galactosidase-activated aggregation-induced emission luminogen

Acta Biomaterialia, Journal Year: 2024, Volume and Issue: 179, P. 340 - 353

Published: March 30, 2024

Language: Английский

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A Versatile Theranostic Nanoplatform with Aggregation‐Induced Emission Properties: Fluorescence Monitoring, Cellular Organelle Targeting, and Image‐Guided Photodynamic Therapy

Small, Journal Year: 2023, Volume and Issue: 19(21)

Published: Feb. 17, 2023

Abstract Photosensitizers (PSs) play a key role in the photodynamic therapy (PDT) of tumors. However, commonly used PSs are prone to intrinsic fluorescence aggregation‐caused quenching and photobleaching; this drawback severely limits clinical application PDT, necessitating new phototheranostic agents. Herein, multifunctional theranostic nanoplatform (named TTCBTA NP) is designed constructed achieve monitoring, lysosome‐specific targeting, image‐guided PDT. with twisted conformation D‐A structure encapsulated amphiphilic Pluronic F127 form nanoparticles (NPs) ultrapure water. The NPs exhibit biocompatibility, high stability, strong near‐infrared emission, desirable reactive oxygen species (ROSs) production capacity. also show high‐efficiency photo‐damage, negligible dark toxicity, excellent fluorescent tracing, accumulation lysosome for tumor cells. Furthermore, obtain images good resolution MCF‐7 tumors xenografted BALB/c nude mice. Crucially, present ablation ability PDT effect by generating abundant ROSs upon laser irradiation. These results demonstrate that NP may enable highly efficient

Language: Английский

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Therapeutic potential of tumor treating fields for malignant brain tumors

Cancer Reports, Journal Year: 2023, Volume and Issue: 6(5)

Published: March 29, 2023

Abstract Background Malignant brain tumors are among the most threatening diseases of central nervous system, and despite increasingly updated treatments, prognosis has not been improved. Tumor treating fields (TTFields) an emerging approach in cancer treatment using intermediate‐frequency low‐intensity electric field can lead to development novel therapeutic options. Recent Findings A series biological processes induced by TTFields exert anti‐cancer effects have identified. studies shown that alter bioelectrical state macromolecules organelles involved biology. Massive alterations cell proteomics transcriptomics caused were related as well multiple organelle structures activities. This review addresses mechanisms recent advances application therapy malignant tumors, especially glioblastoma (GBM). Conclusions As a strategy, promising results many clinical trials, GBM, continue evolve. growing number patients with being enrolled ongoing demonstrating TTFields‐based combination therapies improve outcomes.

Language: Английский

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AI-driven antimicrobial peptides for drug development

Methods in microbiology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

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