Several studies have highlighted that reading comprehension is determined by different linguistic skills: semantics, syntax, and morphology, in addition to one's own competence in reading fluency (accuracy, speed, and prosody). On the other hand, according to the Linguistic Interdependence Hypothesis, linguistic skills developed in one's own native language (L1) facilitate the development of these skills in a second one (L2). In this study, we wanted to explore the linguistic abilities that determine reading comprehension in Spanish (L1) and in English (L2) in Secondary Education students. To do this, 73 Secondary Education Students (1st and 3rd year) participated in this study. The students carried out a battery of tasks in English and Spanish, all of them related to reading comprehension (expository text) and different linguistic skills, which included syntactic awareness tasks, synonymy judgment tasks (vocabulary), and morphological awareness tasks. The results indicated a positive correlation between linguistic competencies in both languages (indicating a transfer effect between languages), which were determined by school year, with a lower performance in the 1st year than in the 3rd year. Moreover, we found more skills with correlations in English reading comprehension than in Spanish. Finally, reading comprehension in L1 was mainly explained English reading comprehension, while English reading comprehension was predicted by grade, and syntactic awareness, as well as Spanish reading comprehension. This could be explained by the different levels of exposure to L1 and L2 of sample subjects, as the linguistic variables have different influences on the reading comprehension of both languages.
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http://dx.doi.org/10.3389/fpsyg.2021.789207 | DOI Listing |
Giant cell arteritis (GCA), a systemic vasculitis affecting large and medium-sized arteries, poses significant diagnostic and management challenges, particularly in preventing irreversible complications like vision loss. Recent advancements in artificial intelligence (AI) technologies, including machine learning (ML) and deep learning (DL), offer promising solutions to enhance diagnostic accuracy and optimize treatment strategies for GCA. This systematic review, conducted according to the PRISMA 2020 guidelines, synthesizes existing literature on AI applications in GCA care, with a focus on diagnostic accuracy, treatment outcomes, and predictive modeling.
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Background: Historically, the readability of consent forms in medicine have been above the average reading level of patients. This can create challenges in obtaining truly informed consent, but the implications on clinical trial participant retention are not fully explored. To address this gap, we seek to analyze clinical trial consent forms by determining their readability and relationship with the associated trial's participant dropout rate.
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State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China.
Sugarcane has the most complex polyploid genome in the world, and sugar-related traits are one of the most important aims in sugarcane breeding. It is essential to construct a representative pan-transcriptome that contains all transcripts of a species for studies on genetic diversity, population expression, and omics analyses in sugarcane. In this study, we constructed the first comprehensive pan-transcriptome for sugarcane, and 8434 highly reliable open reading frames were found, which were not aligned with any published sugarcane genome.
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