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A precise radiotherapy plan is crucial to ensure accurate segmentation of glioblastomas (GBMs) for radiation therapy. However, the traditional manual segmentation process is labor‐intensive and heavily reliant on the experience of radiation oncologists. In this retrospective study, a novel auto‐segmentation method is proposed to address these problems. To assess the method's applicability across diverse scenarios, we conducted its development and evaluation using a cohort of 148 eligible patients drawn from four multicenter datasets and retrospective data collection including noncontrast CT, multisequence MRI scans, and corresponding medical records. All patients were diagnosed with histologically confirmed high‐grade glioma (HGG). A deep learning‐based method (PKMI‐Net) for automatically segmenting gross tumor volume (GTV) and clinical target volumes (CTV1 and CTV2) of GBMs was proposed by leveraging prior knowledge from multimodal imaging. The proposed PKMI‐Net demonstrated high accuracy in segmenting, respectively, GTV, CTV1, and CTV2 in an 11‐patient test set, achieving Dice similarity coefficients (DSC) of 0.94, 0.95, and 0.92; 95% Hausdorff distances (HD95) of 2.07, 1.18, and 3.95 mm; average surface distances (ASD) of 0.69, 0.39, and 1.17 mm; and relative volume differences (RVD) of 5.50%, 9.68%, and 3.97%. Moreover, the vast majority of GTV, CTV1, and CTV2 produced by PKMI‐Net are clinically acceptable and require no revision for clinical practice. In our multicenter evaluation, the PKMI‐Net exhibited consistent and robust generalizability across the various datasets, demonstrating its effectiveness in automatically segmenting GBMs. The proposed method using prior knowledge in multimodal imaging can improve the contouring accuracy of GBMs, which holds the potential to improve the quality and efficiency of GBMs' radiotherapy. [ABSTRACT FROM AUTHOR]

In recent years, there has been a significant focus on bioactive dressings suitable for treating chronic and acute wounds. Electrospinning nanofibers are considered advanced dressing options due to their high porosity and permeability to air and water, effective barrier properties against external pathogens, and excellent resemblance to the extracellular matrix for wound healing and skin regeneration. This article reviews the recent advancements in the application of electrospinning nanofibers for bioactive wound healing. The review begins with an overview of the wound healing process and electrospinning methods. It then explores the advantages and disadvantages of different synthetic and natural polymers used in the preparation of electrospinning wound dressings. The natural polymers discussed in this review include collagen, gelatin, silk fibroin, chitosan, hyaluronic acid, and sodium alginate. Additionally, the review delves into commonly used synthetic polymers like polyvinyl alcohol, polyvinyl chloride, polyethylene lactone, polylactide, and polyurethane for wound dressing applications. Furthermore, the review examines the blending of natural and synthetic polymers to create high‐performance wound dressings. It also explores the incorporation of functional additives, such as antimicrobial agents, growth factors, and natural extracts, into electrospinning nanofibers to expedite wound healing and tissue repair. In conclusion, electrospinning is an emerging technology that provides unique opportunities for designing more effective wound dressings and care products. [ABSTRACT FROM AUTHOR]

Four methods were applied to dry yam slices, and then, starches were isolated from dried yam slices. Starch isolated from fresh yam was as the study control, and physicochemical properties and in vitro digestibility of starches were studied. The results showed that the amylose content ranged from 12.62% to 28.25%, water-binding capacity (WBC) from 111.67% to 262.88%, paste clarity from 2.1% to 6.23%, resistant starch (RS) from 66.60% to 88.49% and crystallinity from 11.27% to 25.52%. Compared with the control starch, hot air-drying at 60 °C significantly decreased amylose content, paste clarity, RS and crystallinity, while increasing the WBC. Low levels of rapidly digestible starch and glucose and high RS levels were found in the starch from freeze-drying yam. Digestibility of the starches was significantly correlated with amylose content, WBC, paste clarity and swelling power. The starch samples were divided into three groups by principal component analysis (PCA). [ABSTRACT FROM AUTHOR]

Contents of total flavonoids, total phenolics, total triterpenes, total condensed tannin and total saponins in peels, flesh and endocarps of Chaenomeles speciosa (CSP) and Chaenomeles sinensis (CSS) were determined by colorimetric method, while 5 phenolics (vanillic, gallic, chlorogenic, ferulic and p-coumaric acids), 2 triterpenes (oleanolic and ursolic acids), and 3 flavonoids (rutin, catechin and epicatechin) were identified and quantified by high-performance liquid chromatography-mass spectrometry (HPLC-MS) and HPLC, and antioxidant and α-glucosidase inhibitory activities of them also were evaluated as well as their digestive characteristics. In the correlation analysis, total phenolics, vanillic acid, catechin, ursolic acid and oleanolic acid all contribute to DPPH· scavenge capacity, gallic acid contributes to total ferric reducing antioxidant power, while total triterpenes, total saponins, chlorogenic acid and ferullic acid contribute to α-glucosidase inhibitory activity. In the principal component analysis, endocarps of CSP and CSS both show better quality than their peels and flesh, respectively. In vitro digestion can increase contents of total flavonoids, total condensed tannin and total saponins, while contents of total phenolics and total triterpenes decreased greatly. Our study would contribute to the full use of discarded parts of the 2 Chaenomeles and be helpful to establish a good foundation for further research of CSP and CSS. [ABSTRACT FROM AUTHOR]