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http://dx.doi.org/10.1097/PRS.0000000000001063 | DOI Listing |
BMC Public Health
January 2025
Praxis Gendolla, Essen, Germany.
Background: Despite the high global prevalence, burden, and direct and indicated costs, migraines are often under-diagnosed and undertreated. Understanding the prevalence of migraine and unmet needs is crucial for improving diagnosis and treatment across Europe (EU) countries; however, real-world studies are limited.
Methods: This retrospective cross-sectional survey utilized weighted patient-reported data from the 2020 National Health and Wellness Survey (NHWS) in five EU (5EU) countries (France, Germany, United Kingdom [UK], Italy, and Spain).
EClinicalMedicine
January 2025
Leicester Real World Evidence Unit, Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, LE5 4PW, UK.
Background: People with diabetes are at increased risk of hospitalisation, morbidity, and mortality following SARS-CoV-2 infection. Long-term outcomes for people with diabetes previously hospitalised with COVID-19 are, however, unknown. This study aimed to determine the longer-term physical and mental health effects of COVID-19 in people with and without diabetes.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
January 2025
Department of Obstetrics and Gynaecology, Erasmus MC, University Medical Center Rotterdam, Dr. Molewaterplein 40, Rotterdam, 3015 CE, Netherlands.
Background: Growing evidence demonstrates that maternal nutrition is crucial for the health of the mother-to-be, and early life course of the offspring. However, for most micronutrients, guidelines are inconsistent. This Delphi study aimed to investigate the level of expert consensus on maternal nutrition and micronutrient needs during preconception, pregnancy and lactation.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA.
Enzyme engineering is limited by the challenge of rapidly generating and using large datasets of sequence-function relationships for predictive design. To address this challenge, we develop a machine learning (ML)-guided platform that integrates cell-free DNA assembly, cell-free gene expression, and functional assays to rapidly map fitness landscapes across protein sequence space and optimize enzymes for multiple, distinct chemical reactions. We apply this platform to engineer amide synthetases by evaluating substrate preference for 1217 enzyme variants in 10,953 unique reactions.
View Article and Find Full Text PDFPlast Reconstr Surg Glob Open
January 2025
From the Division of Plastic and Reconstructive Surgery, Harvard Medical School, Massachusetts General Hospital, Boston, MA.
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