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The convergence of staining-free optical imaging and digital staining technologies has become a central focus in digital pathology, presenting significant advantages in streamlining specimen preparation and expediting the rapid acquisition of histopathological information. Despite the inherent merits of optical coherence microscopy (OCM) as a staining-free technique, its widespread application in observing histopathological slides has been constrained. This study introduces a novel approach by combining wide-field OCM with digital staining technology for the imaging of histopathological slides. Through the optimization of the histology slide production process satisfying the ground growth for digital staining as well as pronounced contrast for OCM imaging, successful imaging of various mouse tissues was achieved. Comparative analyses with conventional staining-based bright field images were executed to evaluate the proposed methodology's efficacy. Moreover, the study investigates the generalization of digital staining color appearance to ensure consistent histopathology, considering tissue-specific and thickness-dependent variations.
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The recent surge in large-scale foundation models has spurred the development of efficient methods for adapting these models to various downstream tasks. Low-rank adaptation methods, such as LoRA, have gained significant attention due to their outstanding parameter efficiency and no additional inference latency. This paper investigates a more general form of adapter module based on the analysis that parallel and sequential adaptation branches learn novel and general features during fine-tuning, respectively. The proposed method, named Hydra, combines parallel and sequential branch to integrate capabilities, which is more expressive than existing single branch methods and enables the exploration of a broader range of optimal points in the fine-tuning process. In addition, the proposed method explicitly leverages the pre-trained weights by performing a linear combination of the pre-trained features. It allows the learned features to have better generalization performance across diverse downstream tasks. Furthermore, we perform a comprehensive analysis of the characteristics of each adaptation branch with empirical evidence. Through an extensive range of experiments, we substantiate the efficiency and demonstrate the superior performance of Hydra. This comprehensive evaluation underscores the potential impact and effectiveness of Hydra in a variety of applications. The source code of this work is publicly opened on https://github.com/extremebird/Hydra.
Assuntos
Redes Neurais de Computação , AlgoritmosRESUMO
Histone deacetylase 6 (HDAC6) induces the expression of pro-inflammatory cytokines in macrophages; therefore, HDAC inhibitors may be beneficial for the treatment of macrophage-associated immune disorders and chronic inflammatory diseases, including atherosclerosis and rheumatoid arthritis. Structure-activity relationship studies were conducted on various phenyl hydroxamate HDAC6 inhibitors with indolone/indazolone-based bi- or tricyclic ring moieties as the cap group aiming to develop novel anti-arthritic drug candidates. Several compounds exhibited nanomolar activity and HDAC6 selectivity greater than 500-fold over HDAC1. Compound 21, a derivative with the tetrahydroindazolone cap group, is a potent HDAC6 inhibitor with an IC50 of 18 nM and 217-fold selectivity over HDAC1 and showed favorable oral bioavailability in animals. Compound 21 increases the acetylation level of tubulin without affecting histone acetylation in cutaneous T-cell lymphoma cells and inhibits TNF-α secretion in LPS-stimulated macrophage cells. The anti-arthritic effects of compound 21 were evaluated using a rat adjuvant-induced arthritis (AIA) model. Treatment with compound 21 significantly reduced the arthritis score, and combination treatment with methotrexate showed a synergistic effect in AIA models. We identified a novel HDAC6 inhibitor, compound 21, with excellent in vivo anti-arthritic efficacy, which can lead to the development of oral anti-arthritic drugs.