To determine the impact of low versus atmospheric oxygen tension during only the pre-maturation phase of biphasic capacitation in vitro maturation. The study involved sibling oocytes (532 cumulus-oocyte complexes [COCs] from 20 participants [mean age 29.5 ± 2.5 years]) with polycystic ovary syndrome undergoing CAPA-IVM without gonadotrophins. After oocyte pick-up (OPU), COCs were randomized to undergo pre-maturation under low or atmospheric oxygen, then IVM culture at 20
Anthracnose, caused by Colletotrichum spp., is a major postharvest disease affecting dragon fruit (Hylocereus undatus) in Vietnam. In this study, a fungal strain was isolated from infected dragon fruits and identified based on morphological characteristics and multi-locus phylogenetic analysis (ITS region, and ACT, CHS-1, CAL, GAPDH, TUB2 genes) as C. truncatum DH31.1. The antifungal activity of a thermostable mutant chitinase I168L, derived from 42 kDa chitinase of Trichoderma asperellum SH16, was evaluated against C. truncatum. In vitro assays demonstrated that 60 U of I168L inhibited fungal growth, resulting in a colony diameter of 2.4 cm after 7 d, compared to 3.1 cm when treated with the same concentration of the wild-type chitinase. In vivo tests on dragon fruit showed that I168L effectively suppressed fungal growth at both 28 °C and 35 °C. Application of I168L with 100 U prevented C. truncatum DH31.1 infection for up to 4 d, with lesion diameters of only 0.2 cm after 7 d. Furthermore, curative application of I168L on post-infection dragon fruits reduced lesion expansion to 0.48 cm within 3 d. These findings highlight the potential of the thermostable mutant chitinase I168L as a promising biocontrol agent for postharvest disease management in dragon fruit.
Deep learning has demonstrated remarkable success across domains such as image, audio, video, and text processing. However, its application to tabular data remains challenging due to the heterogeneous nature of features and the lack of positional information, which complicates feature interaction modeling. While deep learning approaches for tabular data have achieved performance levels comparable to traditional methods like gradient boosting machines, their adoption in real-world scenarios is limited by issues of interpretability and robustness. We introduce FusANet (Fusion Attention Neural Network), a novel parametric transformer-style architecture for tabular data that fuses a dataset-level global attention map with instance-level local self-attention using a cross-attention fusion module. FusANet (i) learns a shared, pre-initialized global attention matrix Wglobal to capture population-wide feature relationships, (ii) retains sample-specific interactions via local multi-head self-attention, and (iii) fuses these views with cross-attention to produce robust predictions and dual-level explanations. Across 10 benchmark tabular datasets, we show FusANet achieves average improvements up to 19.72 % in classification accuracy and up to 24.25 % relative RMSE reduction on regression task versus strong parametric state-of-the-art models and performs competitively with gradient-boosted trees, while offering dataset- and instance-level attributions.
In the Internet of Things era, flexible photodetectors have received significant attention for applications in wearable electronics and human-machine interfaces. ZnO nanorods, known as a large bandgap semiconductor, is a promising candidate for flexible photodetectors; however, it still has some limitations for practical use, especially low response and humidity interference. Thus, to overcome these challenges, our study on surface engineering of ZnO nanorods via a sulfurization strategy to form ZnO/ZnS core/shell structure by using a lowcost, fast, and green route is proposed. Furthermore, sulfurized ZnO-based flexible photodetectors using laser-patterned carbon electrodes are developed. The effects of the sulfurization strategy on the sensing performance and humidity resistance of devices were investigated in detail. When tested under UV light of 365 nm, the sulfurized device exhibits a high responsivity and detectivity of 14.1 A/W and 9.1 x 1012 Jones, respectively, which are 16-fold higher than those of the bare ZnO device. Additionally, the sulfurized device demonstrated remarkable stability in 95 % RH and high flexibility retaining 92 % of its responsivity after 1500 bending cycles. In general, with the results obtained from this study, we believe that our strategy opens a new pathway for developing low-cost flexible PDs for wearable and green applications.
Utilizing agricultural waste as a sustainable resource, we report the biosynthesis of graphene quantum dots (GQDs) derived from starch extracted from Artocarpus heterophyllus (jackfruit) seeds, an abundant yet underutilized byproduct. GQDs were synthesized via a one-step hydrothermal method, yielding fluorescent nanodots with an average diameter of 3.3 nm. Their structural and optical properties were confirmed through FTIR, XRD, UV-Vis spectroscopy, and photoluminescence analyses. The resulting GQDs exhibited notable biological and environmental functionalities. The antioxidant and anti-inflammatory activities of the synthesized graphene quantum dots were evaluated, and IC50 values for 2,2 '-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), 2,2diphenyl-1-picrylhydrazyl, and bovine serum albumin assays were determined as 5.84, 14.62 and 26.32 mu g/ mL, respectively. The photocatalytic performance of GQDs was demonstrated, degrading 86.42 % of methylene blue (10 mu g/mL) under UV irradiation within 60 min at a 200 mu g/mL concentration. To enhance antibacterial performance, copper oxide nanoparticles (CuO NPs), synthesized using Syzygium nervosum leaf extract, were incorporated with GQDs through a thermal-assisted synthesis strategy, forming CuO@GQDs hybrid nanocomposites. The composite showed markedly improved antibacterial efficacy, particularly against Staphylococcus aureus, achieving over 90 % inhibition at 100 mu g/mL. Minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) analyses revealed a strong synergistic interaction between CuO NPs and GQDs. This study highlights the dual role of GQDs as both bioactive agents and functional enhancers in nanocomposites, and demonstrates a green, waste-to-nanomaterial approach for developing multifunctional platforms for biomedical and environmental applications.
