RESUMEN
In commercial forestry and large-scale plant propagation, the utilization of artificial intelligence techniques for automated somatic embryo analysis has emerged as a highly valuable tool. Notably, image segmentation plays a key role in the automated assessment of mature somatic embryos. However, to date, the application of Convolutional Neural Networks (CNNs) for segmentation of mature somatic embryos remains unexplored. In this study, we present a novel application of CNNs for delineating mature somatic conifer embryos from background and residual proliferating embryogenic tissue and differentiating various morphological regions within the embryos. A semantic segmentation CNN was trained to assign pixels to cotyledon, hypocotyl, and background regions, while an instance segmentation network was trained to detect individual cotyledons for automated counting. The main dataset comprised 275 high-resolution microscopic images of mature Pinus radiata somatic embryos, with 42 images reserved for testing and validation sets. The evaluation of different segmentation methods revealed that semantic segmentation achieved the highest performance averaged across classes, achieving F1 scores of 0.929 and 0.932, with IoU scores of 0.867 and 0.872 for the cotyledon and hypocotyl regions respectively. The instance segmentation approach demonstrated proficiency in accurate detection and counting of the number of cotyledons, as indicated by a mean squared error (MSE) of 0.79 and mean absolute error (MAE) of 0.60. The findings highlight the efficacy of neural network-based methods in accurately segmenting somatic embryos and delineating individual morphological parts, providing additional information compared to previous segmentation techniques. This opens avenues for further analysis, including quantification of morphological characteristics in each region, enabling the identification of features of desirable embryos in large-scale production systems. These advancements contribute to the improvement of automated somatic embryogenesis systems, facilitating efficient and reliable plant propagation for commercial forestry applications.
RESUMEN
Most scholars focus on the prevalence and democratic effects of (partisan) news exposure. This focus misses large parts of online activities of a majority of politically disinterested citizens. Although political content also appears outside of news outlets and may profoundly shape public opinion, its prevalence and effects are under-studied at scale. This project combines three-wave panel survey data from three countries (total N = 7,266) with online behavioral data from the same participants (over 106M visits). We create a multi-lingual classifier to identify political content both in news and outside (e.g. in shopping or entertainment sites). We find that news consumption is infrequent: just 3.4% of participants' online browsing comprised visits to news sites. Only between 14% (NL) and 36% (US) of these visits were to news about politics. The overwhelming majority of participants' visits were to non-news sites. Although only 1.6\% of those visits related to politics, in absolute terms, citizens encounter politics more frequently outside of news than within news. Out of every 10 visits to political content, 3.4 come from news and 6.6 from non-news sites. Furthermore, exposure to political content outside news domains had the same - and in some cases stronger - associations with key democratic attitudes and behaviors as news exposure. These findings offer a comprehensive analysis of the online political (not solely news) ecosystem and demonstrate the importance of assessing the prevalence and effects of political content in non-news sources.
RESUMEN
Introduction: The oral brush cytology is an alternative method developed to improve the efficacy of conventional cytology in oral potentially malignant disorder (OPMD), and salivary lactate dehydrogenase (LDH) which is a cytoplasmic enzyme has been widely used as a marker for diagnosing various diseases. The purpose of the study is to evaluate the brush biopsy findings and salivary LDH levels for the early diagnosis of premalignant and malignant lesions of the oral cavity. Materials and Methods: Patients with deleterious habits including tobacco-related lesions such as leukoplakia, tobacco pouch keratosis, and oral cancer were included in the study. For each patient, saliva sample was collected, brush biopsy was done and smears were prepared. Collected saliva samples were analysed for salivary LDH levels and prepared smears were analysed for dysplastic changes and statistical analysis was performed. Results: Out of 80 samples, 30 were leukoplakia, 45 were tobacco pouch keratosis and 5 were oral cancer, and 13 samples showed positive dysplastic changes, 26 samples showed atypical dysplastic changes and 41 samples showed no signs of dysplastic changes and concluded as negative. On comparing the results of brush biopsy findings and salivary LDH levels, the mean salivary LDH value for positive dysplasia was elevated and the P value was statistically significant (P value: 0.00). Conclusion: Brush biopsy showed good potential in detecting premalignant lesions and salivary LDH levels showed a marked increase which can be used as a diagnostic biomarker and serve as a potent diagnostic aid for early detection of malignancy.