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Identifying Protein-Nucleotide Binding Residues via Grouped Multi-task Learning and Pre-trained Protein Language Models.
J Chem Inf Model
January 2025
School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
The accurate identification of protein-nucleotide binding residues is crucial for protein function annotation and drug discovery. Numerous computational methods have been proposed to predict these binding residues, achieving remarkable performance. However, due to the limited availability and high variability of nucleotides, predicting binding residues for diverse nucleotides remains a significant challenge.
View Article and Find Full Text PDFA simply synthesized, silver ions-doped porous gold microparticles-based SERS aptamer sensor for ultrasensitive and broad-range quantitative detection of IL-6.
Anal Chim Acta
January 2025
Key Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou, 510632, China. Electronic address:
Background: The multifunctional cytokine interleukin-6 (IL-6) plays a pivotal role in chronic and acute inflammatory responses, underscoring the importance of accurately determining IL-6 levels for early diagnosis, prevention, and treatment of inflammation.
Results: This study developed a versatile and innovative single-particle surface-enhanced Raman spectroscopy (SERS) sensing platform for the precise and sensitive quantification of IL-6 in complex samples using a novel one-pot synthesized, silver ions-doped three-dimensional porous gold microparticles (PGMs) with abundant hot spots for robust SERS enhancement. By rationally designing rich cytosine-Ag-cytosine base pairs between IL-6 aptamers and complementary chains on the PGMs, we harnessed the SERS-enhancing effect to achieve highly sensitive and specific IL-6 quantification within a wide range of 10 to 10 mg/mL and a limit of detection (LOD) of 0.
Interoception, cardiac health, and heart failure: The potential for artificial intelligence (AI)-driven diagnosis and treatment.
Physiol Rep
January 2025
Department of Physiology, School of Medicine, University of Louisville, Louisville, Kentucky, USA.
"I see, I forget, I read aloud, I remember, and when I do read purposefully by writing it, I do not forget it." This phenomenon is known as "interoception" and refers to the sensing and interpretation of internal body signals, allowing the brain to communicate with various body systems. Dysfunction in interoception is associated with cardiovascular disorders.
View Article and Find Full Text PDFTriple-action cancer therapy using laser-activated NO-releasing metallomicellar nanophotosensitizer for pyroptosis-driven immune reprogramming.
J Control Release
January 2025
Department of Biomedical Sciences and BioMedical Sciences Graduate Program (BMSGP), Chonnam National University Medical School, Gwangju 61469, Republic of Korea; DR Cure Inc., Hwasun 58128, Republic of Korea. Electronic address:
Cancer photoimmunotherapy represents an intelligent and highly efficient therapeutic approach that harnesses the photothermal effect to precisely target and ablate tumor tissues, while simultaneously modulating the immune system to achieve tumor elimination. The integration of multifunctional therapeutic modalities for combined photoimmunotherapy requires advanced drug delivery systems. However, the design of a single nanoagent capable of serving as a multifunctional nanophotosensitizer remains a significant challenge.
View Article and Find Full Text PDFMultimodal deep learning for predicting in-hospital mortality in heart failure patients using longitudinal chest X-rays and electronic health records.
Int J Cardiovasc Imaging
January 2025
Shanxi Cardiovascular Hospital, 18 Yifen Street, Taiyuan, 030024, Shanxi, China.
Amid an aging global population, heart failure has become a leading cause of hospitalization among older people. Its high prevalence and mortality rates underscore the importance of accurate mortality prediction for swift disease progression assessment and better patient outcomes. The evolution of artificial intelligence (AI) presents new avenues for predicting heart failure mortality.
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