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Hemostatic materials facilitate rapid hemostasis and significantly mitigate the potential of fatal hemorrhage in civilian and military traumas. However, most existing hemostatic materials are limited in material‐dependent forms and fail to integrate multifunctionality, thus constraining their versatility for differing settings and wound healing capacity. Herein, a facile, versatile armor strategy is proposed to endow various biomaterials with rapid hemostasis, infection prevention, and tissue healing capabilities. The armor is fabricated on the surface of substrates first through chemical cross‐linking of adhesive catechol (phenol) and collagen (polyamine) inspired by insect sclerotization, followed by zinc ions (Zn2+) chelation based on mussel‐inspired metal‐phenol coordination chemistry, referred to "metal‐phenol‐polyamine system". This armor facilitates clot formation by promoting platelet aggregation and activating both intrinsic and extrinsic coagulation pathways. Moreover, the integrated Zn2+ endows the armor with potent antibacterial properties against both Gram‐positive and Gram‐negative bacteria. Consequently, this strategy armors a hemostatic sponge that effectively controls bleeding in rabbit hemorrhage models and successfully facilitates the complete healing of epidermal traumas in rats within 14 days. This metal‐phenol‐polyamine system‐assisted armor provides a potential and universal strategy for efficient hemostasis and wound healing. [ABSTRACT FROM AUTHOR]

Braided neurovascular flow diverters (FDs) have revolutionized the treatment of aneurysms. However, dual antiplatelet therapy is mandatory for patients with FDs, which increases the risk of adverse side effects like bleeding complications. Surface modification would be of critical relevance to improve the biocompatibility and therefore clinical performance of FDs. Herein, a titanium dioxide (TiO2) covalently immobilized citric acid (CA) nanohybrid coating is fabricated on nitinol (NiTi) braided FDs by liquid phase deposition and dip‐coating, to inhibit thrombosis and promote re‐endothelialization. The CA molecules are covalently bound onto the pre‐deposited TiO2 nanoparticulate coating. The coating has a unique homogenously nanostructured morphology as well as super‐hydrophilicity. Both in vitro and in vivo results verify that the coated samples inhibit platelets and fibrinogen adhesion, delay coagulation time, and concomitantly promote re‐endothelialization. Such appealing properties are ascribed to the nature of CA and TiO2 per se as well as the nanostructured morphology. The present strategy may not only provide a new avenue to surface‐modify braided neurovascular FDs but also shed light on advanced nanohybrid materials for biomedical applications among others. [ABSTRACT FROM AUTHOR]

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Human-induced soil change is attracting increasing attention, yet how to quantitatively measure anthropogenic impact on changes in soil properties remains unclear. Eight selected soil properties--bulk density (BD), sand, silt, and clay content, pH, soil organic matter (SOM), total carbon (TC), and total nitrogen (TN)--at four soil depths (0-10, 10-20, 20-30, and 30-40 cm) were measured across three soil series (Gallion, Latanier and Sharkey) in south-central Louisiana, USA, to quantify changes in soil properties as a function of three contrasting land use types, i.e. forest, cropland, and Wetlands Reserve Program. Partial eta-squared values ([η.sup.2]) derived from two-way analysis of variance were used to quantitatively compare natural factors (soil series) and anthropogenic impact (land use) on these soil properties. Results showed that properties such as BD, pH, SOM, TC, and TN could be easily changed by anthropogenic disturbance, especially at 0-10 cm, while soil texture was mainly a natural factor. The anthropogenic factor accounted for 55.2%, 39.5%, 33.2%, and 36.0% of changes in the soil properties at 0-10, 10-20, 20-30, and 30-40 cm depth, respectively. These findings highlight the anthropogenic impact on selected soil properties. Additional keywords: anthropogenic impact, partial eta-squared ([η.sub.2]), principal component analysis, Wetlands Reserve Program (WRP)., Introduction Jenny (1941) published the famous soil-forming factor equation: s = f (cl, o, r, p, t, ...) where s, cl, o, r, p, and t refer to soil, climate, [...]

Context: The resection plan of pituitary adenoma (PA) needs preoperative observation of the sellar region. Radiomics prediction requires high-quality segmentations. Manual delineation is time-consuming and subject to rater variability.Objective: This work aims to create an automated segmentation method for the sellar region, several tools to extract invasiveness-related features, and evaluate their clinical usefulness by predicting the tumor consistency.Methods: Patients included were diagnosed with pituitary adenoma at Peking Union Medical College Hospital. A deep convolutional neural network, called gated-shaped U-net (GSU-Net), was created to automatically segment the sellar region into 8 classes. Five magnetic resonance imaging (MRI) features were extracted from the segmentation results, including tumor diameters, volume, optic chiasma height, Knosp grading system, and degree of internal carotid artery contact. The clinical usefulness of the proposed methods was evaluated by the diagnostic accuracy of the tumor consistency.Results: A total of 163 patients with confirmed pituitary adenoma were included as the first group and were randomly divided into a training data set and test data set (131 and 32 patients, respectively). Fifty patients with confirmed acromegaly were included as the second group. The Dice coefficient of pituitary adenoma in important image slices was 0.940. The proposed methods achieved accuracies of more than 80% for the prediction of 5 invasive-related MRI features. Methods derived from the automatic segmentation showed better performance than original methods and achieved areas under the curve of 0.840 and 0.920 for clinical models and radiomics models, respectively.Conclusion: The proposed methods could automatically segment the sellar region and extract features with high accuracy. The outstanding performance of the prediction of the tumor consistency indicates the methods' clinical usefulness for supporting neurosurgeons in judging patients' conditions, predicting prognosis, and other downstream tasks during the preoperative period. [ABSTRACT FROM AUTHOR]