Psychological Distress Across Adulthood: Equating Scales in Three British Birth Cohorts

Valid and reliable life-course and cross-cohort comparisons of psychological distress are limited by differences in measures used. We aimed to examine adulthood distribution of symptoms and cross-cohort trends by equating the scales of psychological-distress measures administered in the 1946, 1958, and 1970 British birth cohorts. We used data from these three birth cohorts (N = 32,242) and an independently recruited calibration sample (n = 5,800) to inform the equating of scales. We used two approaches to equating scales (equipercentile linking and multiple imputation) and two index measures (General Health Questionnaire-12 and Malaise-9) to compare means, distributions, and prevalence of distress across adulthood. Although we consistently observed an inverse U shape of distress across adulthood, we also observed measure and method differences in point estimates, particularly for cross-cohort comparisons. Sensitivity analysis suggested that multiple imputation yielded more accurate estimates than equipercentile linking. Although we observed an inverse-U-shaped trajectory of psychological distress across adulthood, differences in point estimates between measures and methods did not allow for clear conclusions regarding between-cohorts trends

The accuracy of chromosomal microarray testing for identification of embryonic mosaicism in human blastocysts

A dança é uma forma ancestral de magia, invenção dos deuses que a ensinaram aos homens, diz-nos a mitologia hindu. Envolvido no mistério e movimento da dança, o dançarino pode encantar; porém, antes de tudo é preciso que encante a si mesmo. Não seria este também o caminho do professor? Fazer para si para poder fazer ou propor aos educandos, encantar-se para poder encantar; criar para poder seguir com as crianças a aventura da criação; ousar para poder encorajar? Nesta direção, a pergunta que percorre o presente artigo é assim formulada: como contribuir com o processo de encantamento dos professores, como alimentar a sensibilidade, nos percursos da formação universitária? Buscando respostas no processo de pesquisa, identifica-se na experiência com as danças circulares, tradição de diferentes povos, um profícuo caminho pelo qual aquele espaço de encantamento, de inteireza, de educação estética, igualmente, pode ser provocado

Representing Organic Matter Thermodynamics in Biogeochemical Reations via Substrate-Explicit Modeling

Predictive biogeochemical modeling requires data-model integration that enables explicit representation of the sophisticated roles of microbial processes that transform substrates. Data from high-resolution organic matter (OM) characterization are increasingly available and can serve as a critical resource for this purpose, but their incorporation into biogeochemical models is often prohibited due to an over-simplified description of reaction networks. To fill this gap, we proposed a new concept of biogeochemical modeling—termed substrate-explicit modeling—that enables parameterizing OM-specific oxidative degradation pathways and reaction rates based on the thermodynamic properties of OM pools. Based on previous developments in the literature, we characterized the resulting kinetic models by only two parameters regardless of the complexity of OM profiles, which can greatly facilitate the integration with reactive transport models for ecosystem simulations by alleviating the difficulty in parameter identification. The two parameters include maximal growth rate (μmax) and harvest volume (Vh) (i.e., the volume that a microbe can access for harvesting energy). For every detected organic molecule in a given sample, our approach provides a systematic way to formulate reaction kinetics from chemical formula, which enables the evaluation of the impact of OM character on biogeochemical processes across conditions. In a case study of two sites with distinct OM thermodynamics using ultra high-resolution metabolomics datasets derived from Fourier transform ion cyclotron resonance mass spectrometry analyses, our method predicted how oxidative degradation is primarily driven by thermodynamic efficiency of OM consistent with experimental rate measurements (as shown by correlation coefficients of up to 0.61), and how biogeochemical reactions can vary in response to carbon and/or oxygen limitations. Lastly, we showed that incorporation of enzymatic regulations into substrate- explicit models is critical for more reasonable predictions. This result led us to present integrative biogeochemical modeling as a unifying framework that can ideally describe the dynamic interplay among microbes, enzymes, and substrates to address advanced questions and hypotheses in future studies. Altogether, the new modeling concept we propose in this work provides a foundational platform for unprecedented predictions of biogeochemical and ecosystem dynamics through enhanced integration with diverse experimental data and extant modeling approaches

Representing Organic Matter Thermodynamics in Biogeochemical Reations via Substrate-Explicit Modeling

Predictive biogeochemical modeling requires data-model integration that enables explicit representation of the sophisticated roles of microbial processes that transform substrates. Data from high-resolution organic matter (OM) characterization are increasingly available and can serve as a critical resource for this purpose, but their incorporation into biogeochemical models is often prohibited due to an over-simplified description of reaction networks. To fill this gap, we proposed a new concept of biogeochemical modeling—termed substrate-explicit modeling—that enables parameterizing OM-specific oxidative degradation pathways and reaction rates based on the thermodynamic properties of OM pools. Based on previous developments in the literature, we characterized the resulting kinetic models by only two parameters regardless of the complexity of OM profiles, which can greatly facilitate the integration with reactive transport models for ecosystem simulations by alleviating the difficulty in parameter identification. The two parameters include maximal growth rate (μmax) and harvest volume (Vh) (i.e., the volume that a microbe can access for harvesting energy). For every detected organic molecule in a given sample, our approach provides a systematic way to formulate reaction kinetics from chemical formula, which enables the evaluation of the impact of OM character on biogeochemical processes across conditions. In a case study of two sites with distinct OM thermodynamics using ultra high-resolution metabolomics datasets derived from Fourier transform ion cyclotron resonance mass spectrometry analyses, our method predicted how oxidative degradation is primarily driven by thermodynamic efficiency of OM consistent with experimental rate measurements (as shown by correlation coefficients of up to 0.61), and how biogeochemical reactions can vary in response to carbon and/or oxygen limitations. Lastly, we showed that incorporation of enzymatic regulations into substrate- explicit models is critical for more reasonable predictions. This result led us to present integrative biogeochemical modeling as a unifying framework that can ideally describe the dynamic interplay among microbes, enzymes, and substrates to address advanced questions and hypotheses in future studies. Altogether, the new modeling concept we propose in this work provides a foundational platform for unprecedented predictions of biogeochemical and ecosystem dynamics through enhanced integration with diverse experimental data and extant modeling approaches