Introduction: Thyroid hormones are essential for placental development, and subtle disruptions may contribute to placenta previa (PP) and placental abruption (PA). This study evaluated thyroid hormone levels and derived log ratios to identify associations with delivery outcomes and predictors of PP/PA. Methods: In this prospective study, 347 singleton pregnancies at a tertiary obstetric center were included, excluding women with thyroid or chronic disease, smoking, thyroid-affecting medications, or fetal anomalies. Maternal demographic and obstetric data were collected from medical records. Dried blood spot samples were analyzed for thyroid-stimulating hormone (TSH), total thyroxine (TT4), and thyroglobulin (Tg), and urinary iodine concentration (UIC) was measured. Derived thyroid hormone log ratios—including TSH/TT4, TT4/Tg, TSH∙Tg, UIC/TT4 were calculated. Results: Correlations with PP/PA were: TSH (0.50 mU/L; r = –0.123, p = 0.022), Tg (9.42 µg/L; r = –0.119, p = 0.027), log(TSH/TT4) (–2.359 ± 0.283; r = –0.168, p = 0.002), log(TT4/Tg) (1.063±0.366; r = 0.187, p = 0.0005), log(TSH·Tg) (0.574±0.511; r = –0.216, p < 0.001). Logistic regression: log(TSH·Tg) [OR (odds ratio) = 0.16, p = 0.016; log(UIC/TT4) OR = 0.01, p = 0.055. Receiver operating characteristic analysis showed area under the curve 0.857, sensitivity/specificity pair = 100%/61.2% at cutoff < 0.4958, criterion = 0.4958. Conclusions: Log(TSH·Tg) is a strong independent predictor of PP/PA with high sensitivity and moderate specificity. It outperforms individual thyroid measures and may support early risk stratification by reflecting subtle maternal thyroid dysregulation affecting placental development.
This paper develops a nonlinear growth framework to examine how human capital shapes long-run growth and convergence, with emphasis on middle-income-trap dynamics. Human capital is modelled as a determinant of absorptive capacity that facilitates technology adoption. Departing from constant-elasticity specifications, the model allows the productivity effect of education to vary with attainment, capturing saturation and composition effects along the development path. Empirically, the analysis combines production-function and macro-Mincerian approaches within a rolling-threshold framework to identify level-dependent nonlinearities. The results show that human capital strongly promotes growth at low attainment levels but that its marginal effect declines and may become statistically non-positive beyond a critical schooling threshold. These findings reconcile mixed evidence in the human-capital - growth literature by highlighting the nonlinear role of education in middle-income-trap dynamics. From a policy perspective, the findings suggest that expanding years of schooling alone may be insufficient to sustain growth beyond middle-income levels without parallel improvements in education quality, innovation capacity, and institutional upgrading.
Mediterranean fish species are integral to both commercial fishing and aquaculture, providing a vital source of food and economic stability in the region. However, the health of these fish populations is threatened by various pathogens, including bacteria and parasites. While most research on fish microbiomes and pathogen prevalence is conducted on a limited number of samples collected over a short period, we include a temporal element in our analysis by using data spanning several years and seasons. Using biannual fish-sampling data, we extract and sequence DNA from gill samples of Mediterranean fish species to identify prevalent bacterial pathogens and analyze yearly and seasonal trends in the prevalence of four genera of interest: Vibrio, Shewanella, Photobacterium, and Psychrobacter. Utilizing a sample pooling method and 16s rRNA NGS revealed the presence of many potential pathogenic species, as well as showing Shewanella, Photobacterium, and Psychrobacter groups to be the most prevalent, and the most abundant groups in sampled fish gills. The abundance of these genera fluctuated throughout sampling years, indicating possible changes in the environmental conditions shaping fish microbiomes. These findings not only provide a wealth of ecological data but may also contribute to food security by improving pathogen-monitoring efforts.
This systematic review examines the Comparative Analysis of Language Teaching Methods, focusing on Communicative Language Teaching (CLT), Task-Based Language Teaching (TBLT), and the Direct Method. The study aims to provide a comprehensive overview of these methods, including their historical evolution, core principles, and practical application in educational settings. Through a thorough examination, the effectiveness of each method in terms of language acquisition, learner engagement, and overall proficiency is discerned. The review contributes to the existing body of knowledge in language education and serves as a valuable resource for language educators, policymakers, and researchers. By critically evaluating each method, key principles and best practices are identified, offering insights for the development of more effective language teaching strategies. The scope and significance of the study lie in its potential to inform stakeholders about the strengths and limitations of different methods, guiding the advancement of language education practices. The literature review explores the historical development of language teaching methods, and current trends in language education, and highlights the adaptability of language instruction to meet diverse learning preferences and objectives.
Introduction:The CIAO project was launched in Spring 2020 to address the need to make sense of the numerous and disparate data available on COVID-19 pathogenesis. Based on a crowdsourcing model of large-scale collaboration, the project has exploited the Adverse Outcome Pathway (AOP) knowledge management framework built to support chemical risk assessment driven by mechanistic understanding of the biological perturbations at the different organizational levels. Hence the AOPs might have real potential to integrate data produced through different approaches and from different disciplines as experienced in the context of COVID-19. In this study, we aim to address the effectiveness of the AOP framework (i) in supporting an interdisciplinary collaboration for a viral disease and (ii) in working as the conceptual mediator of a crowdsourcing model of collaboration.Methods:We used a survey disseminated among the CIAO participants, a workshop open to all interested CIAO contributors, a series of interviews with some participants and a self-reflection on the processes.Results:The project has supported genuine interdisciplinarity with exchange of knowledge. The framework provided a common reference point for discussion and collaboration. The diagram used in the AOPs assisted with making explicit what are the different perspectives brought to the knowledge about the pathways. The AOP-Wiki showed up many aspects about its usability for those not already in the world of AOPs. Meanwhile their use in CIAO highlighted needed adaptations. Introduction of new Wiki elements for modulating factors was potentially the most disruptive one. Regarding how well AOPs support a crowdsourcing model of large-scale collaboration, the CIAO project showed that this is successful when there is a strong central organizational impetus and when clarity about the terms of the collaboration is brought as early as possible.Discussion:Extrapolate the successful CIAO approach and related processes to other areas of science where the AOP could foster interdisciplinary and systematic organization of the knowledge is an exciting perspective.
