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Breast cancer ranks among the most prevalent malignant tumours and is the primary contributor to cancer‐related deaths in women. Breast imaging is essential for screening, diagnosis, and therapeutic surveillance. With the increasing demand for precision medicine, the heterogeneous nature of breast cancer makes it necessary to deeply mine and rationally utilize the tremendous amount of breast imaging information. With the rapid advancement of computer science, artificial intelligence (AI) has been noted to have great advantages in processing and mining of image information. Therefore, a growing number of scholars have started to focus on and research the utility of AI in breast imaging. Here, an overview of breast imaging databases and recent advances in AI research are provided, the challenges and problems in this field are discussed, and then constructive advice is further provided for ongoing scientific developments from the perspective of the National Natural Science Foundation of China. [ABSTRACT FROM AUTHOR]

The spatial layout of the coastal forts defense system of the Ming Dynasty of China has been studied in a relatively comprehensive way. Nonetheless, ancient defense mechanisms have not been fully revealed. Previous studies have focused more on the macro and meso levels. Studies into its microscopic construction mechanism need to be enhanced. This research attempts to quantify and validate the rationality of the ancient microscopic defense mechanism, using the ancient defense mechanism of Pu Zhuang Suo-Fort in Zhejiang Province as an instance. This study concentrates on the distribution of firepower strength beyond the walls of coastal defense forts, as well as the effect of wall height on firepower defense capabilities. There is a specific firepower attenuation area near the walls due to the firing blind area in the coastal forts defense system. And the construction of the moat plays an additive role in its defensive capability. Meanwhile, the height of the fort wall will also affect the range of the firing blind zone under Yangmacheng. In theory, there is a reasonable height range of the wall and a proper position of the moat. This height range can meet both good economy and defensive capabilities. In turn, the position of the moats and the height of the walls can verify the rationality of the construction mechanism of the coastal forts' defense system. [ABSTRACT FROM AUTHOR]

Microorganisms consume and transform dissolved organic matter (DOM) into various forms. However, it remains unclear whether the ecological patterns and drivers of DOM chemodiversity are analogous to those of microbial communities. Here, a large-scale investigation is conducted along the Chinese coasts to resolve the intrinsic linkages among the complex intertidal DOM pools, microbial communities and environmental heterogeneity. The abundance of DOM molecular formulae best fits log-normal distribution and follows Taylor's Law. Distance-decay relationships are observed for labile molecular formulae, while latitudinal diversity gradients are noted for recalcitrant molecular formulae. Latitudinal patterns are also observed for DOM molecular features. Negative cohesion, bacterial diversity, and molecular traits are the main drivers of DOM chemodiversity. Stochasticity analyses demonstrate that determinism dominantly shapes the DOM compositional variations. This study unveils the intrinsic mechanisms underlying the intertidal DOM chemodiversity and microbial communities from ecological perspectives, deepening our understanding of microbially driven chemical ecology., (© 2024. The Author(s).)

Background: Computed tomography coronary angiography (CTCA) image analysis enables plaque characterization and non-invasive fractional flow reserve (FFR) calculation. We analyzed various parameters derived from CTCA images and evaluated their associations with ischemia., Methods: 49 (61 lesions) patients underwent CTCA and invasive FFR. Lesions with diameter stenosis (DS) ≥ 50% were considered obstructive. CTCA image processing incorporating analytical and numerical methods were used to quantify anatomical parameters of lesion length (LL) and minimum lumen area (MLA); plaque characteristic parameters of plaque volume, low attenuation plaque (LAP) volume, dense calcium volume (DCV), normalized plaque volume (NP Vol), plaque burden, eccentricity index and napkin-ring (NR) sign; and hemodynamic parameters of resistance index, stenosis flow reserve (SFR) and FFR B . Ischemia was defined as FFR ≤ 0.8., Results: Plaque burden and plaque volume were inversely related to FFR. Multivariable logistic regression analysis identified the best anatomical, plaque and hemodynamic predictors, respectively, as DS (≥50% vs <50%; OR: 8.0; 95% CI: 1.6-39.4), normalized plaque volume (NP Vol) (≥4.3 vs <4.3; OR: 3.9; 95% CI: 1.1-14.0) and NR Sign (0 vs 1; OR: 13.6; 95% CI: 1.3-146.1), and FFR B (≤0.8 vs >0.8; OR: 44.4; 95% CI: 8.8-224.8). AUC increased from 0.70 with DS as the sole predictor to 0.81 after adding NP Vol and NR Sign; further addition of FFR B increased AUC to 0.93., Conclusion: Normalized plaque volume, napkin-ring derived from plaque analysis, and FFR B from numerical simulations on CTCA images substantially improved discrimination of ischemic lesions, compared to assessment by DS alone., (Copyright © 2018 Elsevier B.V. All rights reserved.)