Publications by authors named "I Specht"

Background: Lifestyle interventions for weight loss are generally ineffective in achieving clinically meaningful long-term reductions in body weight and may contribute to negative behavior such as weight cycling or disordered eating. Negative focus on high weight may also contribute to weight stigma. Weight stigma includes negative attitudes and discriminatory behavior toward people with big bodies and can result in psychological stress and unfavorable health outcomes.

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Purpose Of Review: Despite decades of development and testing of weight-loss interventions, the adult populations worldwide have witnessed a continuous rise in body weight. There is an ongoing debate about how to move forward. Some argue that this rise calls for more intensive and possibly life-long treatments, including the new effective GLP1 weight loss medications, while others have called for a fundamental shift away from weight and on to a broader understanding of health.

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Background: We aimed to investigate the clinical, imaging and fluid biomarker characteristics in patients with antidiacylglycerol lipase alpha (DAGLA)-autoantibody-associated cerebellitis.

Methods: Serum and cerebrospinal fliud (CSF) samples from four index patients were subjected to comprehensive autoantibody screening by indirect immunofluorescence assay (IIFA). Immunoprecipitation, mass spectrometry and recombinant protein assays were used to identify the autoantigen.

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Introduction: Sufficient levels of vitamin D have been associated with higher chances for both clinical pregnancy and live birth among women undergoing assisted reproductive techniques, whereas low levels of maternal vitamin D have been associated with preeclampsia and late miscarriage. In Denmark, subgroups at risk for low vitamin D levels, including neonates and toddlers, are recommended to use supplementation. The aim was to study the level of vitamin D among neonates born after in vitro fertilization compared with neonates from the general population.

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Genome sequencing can offer critical insight into pathogen spread in viral outbreaks, but existing transmission inference methods use simplistic evolutionary models and only incorporate a portion of available genetic data. Here, we develop a robust evolutionary model for transmission reconstruction that tracks the genetic composition of within-host viral populations over time and the lineages transmitted between hosts. We confirm that our model reliably describes within-host variant frequencies in a dataset of 134,682 SARS-CoV-2 deep-sequenced genomes from Massachusetts, USA.

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