A Convexity-Preserving Level-Set Method for the Segmentation of Tumor Organoids.

Tumor organoid cultures play a crucial role in clinical practice, particularly in guiding medication by accurately determining the morphology and size of the organoids. However, segmenting individual tumor organoids is challenging due to their inhomogeneous internal intensity and overlapping structures. This paper proposes a convexity-preserving level-set segmentation 4 model based on the characteristics of tumor organoid images to segment individual tumor organoids precisely. Considering the predominant spherical shape exhibited by organoid growth, we propose a level-set model that includes a data-driven term, a curvature term, and a regularization term. The data-driven term pulls the contour to the vicinity of the boundary; the curvature term ensures the maintenance of convexity in the targeted segmentation, and the regularization term controls the smoothness and propagation of the contour. The proposed model aids in overcoming interference from factors such as overlap and noise, enabling the evolving curve to converge to the actual boundary of the target accurately. Furthermore, we propose a selectable and targeted initialization method that guarantees precise segmentation of specific regions of interest. Experiments on 51 pancreatic ductal adenocarcinoma organoid images show that our model achieved excellent segmentation results. The average Dice value and computation time are 98.81±0.48% and 20.67 s. Compared with the C-V and CPLSE models, it is more accurate and takes less time.

Leveraging genomic signatures of oral microbiome-associated antibiotic resistance genes for diagnosing pancreatic cancer.

Growing evidence has increasingly suggested a potential linkage between the oral microbiome and various diseases, including pancreatic ductal adenocarcinoma (PDAC). However, the utilization of gene-level information derived from the oral microbiome for diagnosing PDAC remains unexplored. In this study, we sought to investigate the novel potential of leveraging genomic signatures associated with antibiotic resistance genes (ARGs) within the oral microbiome for the diagnosis of PDAC. By conducting an analysis of oral microbiome samples obtained from PDAC patients, we successfully identified specific ARGs that displayed distinct sequence abundance profiles correlated with the presence of PDAC. In the healthy group, three ARGs were found to be enriched, whereas 21 ARGs were enriched in PDAC patients. Remarkably, these ARGs from oral microbiome exhibited promising diagnostic capabilities for PDAC (AUROC = 0.79), providing a non-invasive and early detection method. Our findings not only provide novel modal data for diagnosing PDAC but also shed light on the intricate interplay between the oral microbiome and PDAC.

Gastrointestinal bleeding due to obstruction of the superior mesenteric vein.

ABSTRACT: Gastrointestinal bleeding is a common clinical symptom. Finding the underlying cause is the first step for treatment. In a few patients, this can be difficult. The present work reports on the unusual case of a 53-year-old man who presented gastrointestinal bleeding. No bleeding site was found by gastrocolonoscopy or interventional examination, but after multidisciplinary consultation, we discovered that the cause of gastrointestinal bleeding was the obstruction of the upper mesenteric vein.

Injectable Nanocomposite Immune Hydrogel Dressings: Prevention of Tumor Recurrence and Anti-Infection after Melanoma Resection.

Complex wound repair due to tumor recurrence and infection following tumor resection presents significant clinical challenges. In this study, a bifunctional nanocomposite immune hydrogel dressing, SerMA-LJC, is developed to address the issues associated with repairing infected damaged tissues and preventing tumor recurrence. Specifically, the immune dressing is composed of methacrylic anhydride-modified sericin (SerMA) and self-assembled nanoparticles (LJC) containing lonidamine (Lon), JQ1, and chlorine e6 (Ce6). In vitro and in vivo experiments demonstrate that the nanocomposite hydrogel dressing can trigger immunogenic cell death (ICD) and has a potent anti-tumor effect. Moreover, this dressing can mitigate the acidic microenvironment of tumor cells and suppress the overexpression of PD-L1 on the tumor cell surface, thereby altering the immunosuppressive tumor microenvironment and augmenting the anti-tumor immune response. Further, the RNA sequencing analysis revealed that the hydrogel dressing significantly impacts pathways associated with positive regulation of immune response, apoptotic process, and other relevant pathways, thus triggering a potent anti-tumor immune response. More importantly, the dressing generates a substantial amount of reactive oxygen species (ROS), which can effectively kill Staphylococcus aureus and promote infectious wound healing. In conclusion, this dual-function nanocomposite immune hydrogel dressing exhibits promise in preventing tumor recurrence and promoting infectious wound healing.

A novel adjustable PHBV basement film for enhancing the efficacy of glaucoma surgery by inhibiting scar formation.

Trabeculectomy is the primary surgical approach used to treat glaucoma, but scarring of the filtering passage (filtering bleb) after surgery often leads to treatment failure. To address this issue, we have developed a drug release system called RSG/Pd@ZIF-8 PHBV film. This system enables the sustained release of an anti-fibrosis drug, aiming to prevent scarring. In vitro, the film has the function of continuous Rosiglitazone (RSG) release, with accelerated release after laser irradiation. The antibacterial experiments revealed that the film exhibited antibacterial rates of 87.0 % against E.coli and 97.1 % against S.aureus, respectively. Moreover, we confirmed its efficacy in a rabbit eye model undergoing trabeculectomy. After implantation of the film, we observed a prolonged postoperative period for reducing intraocular pressure (IOP), increased survival rate of filtering blebs, and improved long-term surgical outcomes in vivo. Additionally, the film exhibited excellent biosafety. In summary, the designed sustained-release film in this study possesses the aforementioned functionalities, allowing for the regulation of anti-scarring drug release without causing harm post-surgery. This personalized and precise anti-scarring strategy represents a significant advancement.

A three-gene random forest model for diagnosing idiopathic pulmonary fibrosis based on circadian rhythm-related genes in lung tissue.

BACKGROUND: The disorder of circadian rhythm could be a key factor mediating fibrotic lung disease Therefore, our study aims to determine the diagnostic value of circadian rhythm-related genes (CRRGs) in IPF. METHODS: We retrieved the data on CRRGs from previous studies and the GSE150910 dataset. The participants from the GSE150910 dataset were divided into training and internal validation sets. Next, we used several various bioinformatics methods and machine learning algorithms to screen genes. Next, we identified SEMA5A, COL7A1, and TUBB3, which were included in the random forest (RF) diagnostic model. Finally, external validation was conducted on data retrieved from the GSE184316 datasets. RESULTS: The results revealed that the RF diagnostic model could diagnose patients with IPF in the internal validation set with the area under the ROC curve (AUC) value of 0.905 and in the external validation with the AUC value of 0.767. Furthermore, real-time quantitative PCR and western blotting results revealed a significant decrease in SEMA5A (p < 0.05) expression level and an increase in COL7A1 and TUBB3 expression levels in TGF-ß1-treated normal human lung fibroblasts. CONCLUSION: We constructed an RF diagnostic model based on SEMA5A, COL7A1, and TUBB3 expression in lung tissue for diagnosing patients with IPF.