664 research outputs found

    Evaluation of pollen viability, stigma receptivity and fertilization success in Lagerstroemia indica L.

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    To provide theoretical basis for artificial pollination in Lagerstroemia indica L., pollen viability and stigma receptivity were tested and the morphological change of stigma was observed. Pollen viability tested by in vitro culture, stigma receptivity examined by benzidine-H2O2 testing and fruit set estimated by field artificial pollination were analyzed in this study. The maximum pollen viability was observed at 10:00 am one day of anthesis (DA), of which ‘Hong Wei’ (46.2%) was significantly lower than that of ‘Yin Wei’ (56.8%) and ‘Zi Wei’ (62.5%). The stigma receptivity of the three crape myrtle cultivars was sustained for eight days, which was 95.7 to 96.9% at 1 DA to two days after anthesis (DAA), then declined to 75.5 to 79.9% at 3 to 4 DAA and 50.6 to 59.7% at 5 to 6 DAA, and only 29.5% at 7 DAA. Higher stigma receptivity was associated with columnar style, upward stigma, green and wet papillae and copious exudates at stage 1 (1 DA to 2 DAA). Frequencies of fruit set at stage 1 (74.4%) and stage 2 (3 to 4 DAA) (78.9%) were significantly higher than that at stage 3 (5 to 6 DAA) (21.9%). So, selecting pollen at 10:00 am 1 DA and stigma of 1 DA to 4 DAA was a strategy to enhance fruit set in the future artificial hybridizations for crape myrtle.Key words: Lagerstroemia indica L., dimorphic pollen, pollen viability, stigma receptivity, fruit set

    Effect of dexmedetomidine on miR-144-3p expression and epithelial mesenchymal transition in gastric cancer cells

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    Purpose: To investigate the effect of dexmedetomidine (DEX) on epithelial mesenchymal transition (EMT) in gastric cancer cells, and the role of microRNA-144-3p (miR-144-3p) in the process.Methods: The effect of DEX on miRNA expression profile was analyzed using GEO database(https://www.ncbi.nlm.nih.gov/gds/). Human gastric cancer cells were cultured in vitro, and one group of cells was treated with saline for 48 h (control group). Cells treated with DEX at doses of 0.01, 0.1 and 1.0 μmol/L for 48 h were marked as low-, medium- and high-DEX concentration groups. The mRNA expression levels of miR-144-3p, ZEB1, E-cadherin and vimentin were determined using real-time quantitative polymerase chain reaction (RT-PCR), while the protein expressions of ZEB1, E-cadherin and vimentin were assayed with Western blotting. Cell proliferation was determined with CCK-8 assay, while metastasis was measured using Transwell assay.Results: The GEO database demonstrated that the expression of miR-144-3p in rat cardiomyocytes was significantly decreased after DEX treatment (p < 0.05). The expression of miR-144-3p was decreased in all groups, when compared to the control group, but the expressions of ZEB1 and vimentin were increased, while that of E-cadherin was down-regulated (p < 0.05). Cell proliferation in the high-DEX concentration group was decreased (p < 0.05). The degrees of cell invasion and migration were increased in the medium- and high-DEX concentration groups (p < 0.05).Conclusion: DEX promotes the metastasis of gastric cancer cells by regulation of epithelialmesenchymal transition (EMT) and the expression of miR-144-3p. This finding provides a new insight into the treatment of gastric cancer

    Two-family outbreak of botulism associated with the consumption of smoked ribs in Sichuan Province, China

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    SummaryBackgroundOn September 22, 2013, two patients from Sichuan Province, China presented with symptoms of food-borne botulism, a rare but fatal illness caused by the consumption of foods containing Clostridium botulinum neurotoxins.MethodsInvestigators reviewed the medical charts and food consumption histories, and interviewed patients and family members. Food samples and clinical specimens were tested for botulinum toxin and neurotoxin-producing Clostridium species by standard methods.ResultsThe first two index cases presented with cranial neuropathies and flaccid paralysis, and required mechanical ventilation. There were 12 confirmed outbreak-associated cases. Botulinum toxin type A was identified in the smoked ribs, and all of the patients had consumed the smoked ribs from the same local restaurant. The smoked ribs contained no added salt, sugar, or preservative. Botulinum toxin production likely resulted from the cold-smoking preparation method and inappropriate refrigeration.ConclusionsSmoked ribs produced by a local restaurant, contaminated with type A botulism, was the contributor to this outbreak. The supervision of food safety should be strengthened to prevent future outbreaks in China

    Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study

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    Background: Developing effective and generalizable predictive models is critical for disease prediction and clinical decision-making, often requiring diverse samples to mitigate population bias and address algorithmic fairness. However, a major challenge is to retrieve learning models across multiple institutions without bringing in local biases and inequity, while preserving individual patients\u27 privacy at each site. Objective: This study aims to understand the issues of bias and fairness in the machine learning process used in the predictive health care domain. We proposed a software architecture that integrates federated learning and blockchain to improve fairness, while maintaining acceptable prediction accuracy and minimizing overhead costs. Methods: We improved existing federated learning platforms by integrating blockchain through an iterative design approach. We used the design science research method, which involves 2 design cycles (federated learning for bias mitigation and decentralized architecture). The design involves a bias-mitigation process within the blockchain-empowered federated learning framework based on a novel architecture. Under this architecture, multiple medical institutions can jointly train predictive models using their privacy-protected data effectively and efficiently and ultimately achieve fairness in decision-making in the health care domain. Results: We designed and implemented our solution using the Aplos smart contract, microservices, Rahasak blockchain, and Apache Cassandra-based distributed storage. By conducting 20,000 local model training iterations and 1000 federated model training iterations across 5 simulated medical centers as peers in the Rahasak blockchain network, we demonstrated how our solution with an improved fairness mechanism can enhance the accuracy of predictive diagnosis. Conclusions: Our study identified the technical challenges of prediction biases faced by existing predictive models in the health care domain. To overcome these challenges, we presented an innovative design solution using federated learning and blockchain, along with the adoption of a unique distributed architecture for a fairness-aware system. We have illustrated how this design can address privacy, security, prediction accuracy, and scalability challenges, ultimately improving fairness and equity in the predictive health care domain
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