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Accurate optic disc (OD) segmentation has a great significance for computer-aided diagnosis of different types of eye diseases. Due to differences in image acquisition equipment and acquisition methods, the resolution, size, contrast, and clarity of images from different datasets show significant differences, resulting in poor generalization performance of deep learning networks. To solve this problem, this study proposes a multi-level segmentation network. The network includes data quality enhancement module (DQEM), coarse segmentation module (CSM), localization module (OLM), and fine segmentation stage module (FSM). In FSM, W-Net is proposed for the first time, and boundary loss is introduced in the loss function, which effectively improves the performance of OD segmentation. We generalized the model in the REFUGE test dataset, GAMMA dataset, Drishti-GS1 dataset, and IDRiD dataset, respectively. The results show that our method has the best OD segmentation performance in different datasets compared with state-of-the-art networks.
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Accurate and automated segmentation of brain tissue images can significantly streamline clinical diagnosis and analysis. Manual delineation needs improvement due to its laborious and repetitive nature, while automated techniques encounter challenges stemming from disparities in magnetic resonance imaging (MRI) acquisition equipment and accurate labeling. Existing software packages, such as FSL and FreeSurfer, do not fully replace ground truth segmentation, highlighting the need for an efficient segmentation tool. To better capture the essence of cerebral tissue, we introduce nnSegNeXt, an innovative segmentation architecture built upon the foundations of quality assessment. This pioneering framework effectively addresses the challenges posed by missing and inaccurate annotations. To enhance the model's discriminative capacity, we integrate a 3D convolutional attention mechanism instead of conventional convolutional blocks, enabling simultaneous encoding of contextual information through the incorporation of multiscale convolutional features. Our methodology was evaluated on four multi-site T1-weighted MRI datasets from diverse sources, magnetic field strengths, scanning parameters, temporal instances, and neuropsychiatric conditions. Empirical evaluations on the HCP, SALD, and IXI datasets reveal that nnSegNeXt surpasses the esteemed nnUNet, achieving Dice coefficients of 0.992, 0.987, and 0.989, respectively, and demonstrating superior generalizability across four distinct projects with Dice coefficients ranging from 0.967 to 0.983. Additionally, extensive ablation studies have been implemented to corroborate the effectiveness of the proposed model. These findings represent a notable advancement in brain tissue analysis, suggesting that nnSegNeXt holds the promise to significantly refine clinical workflows.
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The use of stem cell-based treatment systems is prevalent in regenerative medicine. To enhance the regenerative capabilities of stem cells, growth factors are typically incorporated into the treatment system. Nonetheless, traditional hydrogel-encapsulated or heparinized scaffolds that bind factors have limitations. In this study, we prepared a biomaterial strategy using uniform poly(lactic-co-glycolic) acid (PLGA) microspheres (uPLGA-Ms) fabricated by microfluidic to sustain delivery of insulin-like growth factor 1 (IGF-1), a critical protein for hMSCs biological functions. The uPLGA-Ms loaded IGF-1 were highly monodispersed through precise manipulation of the flow rate of the two-phase of the flow-focusing microchannle. The results showed that the uPLGA-Ms stabilize IGF-1 and provide a more efficient sustained delivery and cost-effective of growth factor. Gene expression analysis demonstrated the uPLGA delivery of IGF-1 results in a (enhanced) supported hMSCs expansion, survival, stemness, and secretion abilities comparable with the conventional soluble IGF-1 group. In summary, this material-based strategy to stabilize and sustain delivery of growth factor has broad potential to regeneration of various tissues and organs.
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Introduction: The primary objective of the current study was to evaluate the effects of Flammulina velutipes mushroom residue (FVMR) in a fermented total mixed ration (FTMR) diet on the fattening effect and rumen microorganisms in Guizhou black male goats. Methods: A total of 22 Guizhou black male goats were allocated into two groups using the Randomized Complete Block Design (RCBD) experimental design. The average initial weight was 22.41 ± 0.90 kg and with 11 goats in each group. The control group (group I) was fed the traditional fermentation total mixed ration (FTMR) diet without FVMR. Group II was fed the 30% FVMR in the FTMR diet. Results: The results showed that compared with group I, the addition of FVMR in the goat diet could reduce the feed cost and feed conversion ratio (FCR) of group II (p < 0.01). Notably, the apparent digestibility of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), and dry matter (DM) were higher in group II (p < 0.01). The levels of growth hormone (GH), immunoglobulin A (IgA), and immunoglobulin M (IgM) in group II were higher than that of group I (p < 0.01), which the level of glutamic oxalacetic transaminase (ALT) and interleukin-6 (IL-6) was noticeably lower than that of group I (p < 0.01). 30% FVMR in FTMR diets had no effect on rumen fermentation parameters and microbial composition at the phylum level of Guizhou black male goats (p > 0.05). However, at the genus level, the relative abundance of bacteroidal_bs11_gut_group, Christensenellaceae_R-7_group and Desulfovibrio in group II was lower than in group I (p < 0.05), and the relative abundance of Lachnospiraceae_ND3007_group was higher than in group I (p < 0.01). Discussion: In conclusion, the results of the current study indicated that 30% FVMR in the FTMR diet improves rumen fermentation and rumen microbial composition in Guizhou black male goats, which improves growth performance, apparent digestibility, and immunity.
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Mitophagy influences the progression and prognosis of ischemic stroke (IS). However, whether DNA methylation in the brain is associated with altered mitophagy in hypoxia-injured neurons remains unclear. Here, miR-138-5p was found to be highly expressed in exosomes secreted by astrocytes stimulated with oxygen and glucose deprivation/re-oxygenation (OGD/R), which could influence the recovery of OGD/R-injured neurons through autophagy. Mechanistically, miR-138-5p promotes the stable expression of Ras homolog enriched in brain like 1(Rhebl1) through DNA-methyltransferase-3a (DNMT3A), thereby enhancing ubiquitin-dependent mitophagy to maintain mitochondrial homeostasis. Furthermore, we employed glycosylation engineering and bioorthogonal click reactions to load mirna onto the surface of microglia and deliver them to injured region utilising the inflammatory chemotactic properties of microglia to achieve drug-targeted delivery to the central nervous system (CNS). Our findings demonstrate miR-138-5p improves mitochondrial function in neurons through the miR-138-5p/DNMT3A/Rhebl1 axis. Additionally, our engineered cell vector-targeted delivery system could be promising for treating IS. STATEMENT OF SIGNIFICANCE: : In this study, we demonstrated that miR-138-5p in exosomes secreted by astrocytes under hypoxia plays a critical role in the treatment of hypoxia-injured neurons. And we find a new target of miR-138-5p, DNMT3A, which affects neuronal mitophagy and thus exerts a protective effect by regulating the methylation of Rbebl1. Furthermore, we have developed a carrier delivery system by combining miR-138-5p with the cell membrane of microglia and utilized the inflammatory chemotactic properties of microglia to deliver this system to the brain via intravenous injection. This groundbreaking study not only provides a novel therapeutic approach for ischemia-reperfusion treatment but also establishes a solid theoretical foundation for further research on targeted drug delivery for central nervous system diseases with promising clinical applications.
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Background: Preclinical studies demonstrated that immune checkpoint inhibitors combined with antiangiogenic drugs have a synergistic anti-tumor effect. This present phase II trial aimed to evaluate the efficacy and safety of apatinib combined with camrelizumab in patients with recurrent/metastatic nasopharyngeal carcinoma (RM-NPC). Methods: Patients with RM-NPC were administered with apatinib at 250 mg orally once every day and with camrelizumab at 200 mg via intravenous infusion every 2 weeks until the disease progressed or toxicity became unacceptable. The objective response rate (ORR) was the primary endpoint, assessed using RECIST version 1.1. Progression-free survival (PFS), overall survival (OS), disease control rate (DCR) and safety were the key secondary endpoints. This study was registered with ClinicalTrials.gov, NCT04350190. Results: This study enrolled 26 patients with RM-NPC between January 14, 2021 and September 15, 2021. At data cutoff (March 31, 2023), the median duration of follow-up was 16 months (ranging from 1 to 26 months). The ORR was 38.5% (10/26), the disease control rate (DCR) was 61.5% (16/26), and the median PFS was 6 months (IQR 3.0-20.0). The median OS was 14 months (IQR 6.0-21.25). Treatment-related grade 3 or 4 adverse events occurred in seven (26.9%) patients, and comprised anemia (7.7%), stomatitis (3.8%), headache (3.8%), pneumonia (7.7%), and myocarditis (3.8%). There were no serious treatment-related adverse events or treatment-related deaths. Conclusion: In patients with RM-NPC, apatinib plus camrelizumab showed promising antitumor activity and manageable toxicities.