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Introduction: The majority of young women use oral contraceptives (OCs). Use of OCs has been associated with lower myofibrillar protein and tendon collagen synthesis rates, but it is unknown whether OCs will limit the adaptive response of myotendinous tissue to resistance training.Design and Methods: Fourteen healthy untrained young regular OC users (24 ± 1 years, fat% 32 ± 1, 35 ± 2 ml⋅min-1⋅kg-1) and 14 NOC users (non-OC, controls) (24 ± 1 years, fat% 32 ± 2, 34 ± 2 ml⋅min-1⋅kg-1) performed a 10-week supervised lower extremity progressive resistance training program. Before and after the intervention biopsies from the vastus lateralis muscle and the patellar tendon were obtained. Muscle (quadriceps) and tendon cross-sectional area (CSA) was determined by magnetic resonance imaging (MRI) scans, and muscle fiber CSA was determined by histochemistry. Maximal isometric knee extension strength was assessed by dynamometry while 1 repetition maximum (RM) was determined during knee extension.Results: Training enhanced CSA in both muscle (p < 0.001) and tendon (p < 0.01). A trend toward a greater increase in muscle CSA was observed for OC (11%) compared to NOC (8%) (interaction p = 0.06). Analysis of mean muscle fiber type CSA showed a trend toward an increase in type II muscle fiber area in both groups (p = 0.11, interaction p = 0.98), whereas type I muscle fiber CSA increased in the OC group (n = 9, 3821 ± 197 to 4490 ± 313 mm2, p < 0.05), but not in NOC (n = 7, 4020 ± 348 to 3777 ± 354 mm2, p = 0.40) (interaction p < 0.05). Post hoc analyses indicated that the effect of OCs on muscle mass increase was induced by the OC-users (n = 7), who used OCs containing 30 μg ethinyl estradiol (EE), whereas the response in users taking OCs with 20 μg EE (n = 7) did not differ from NOC. Both the OC and NOC group experienced an increase in maximal knee strength (p < 0.001) and 1RM leg extension (p < 0.001) after the training period with no difference between groups.Conclusion: Use of OCs during a 10-week supervised progressive resistance training program was associated with a trend toward a greater increase in muscle mass and a significantly greater increase in type I muscle fiber area compared to controls. Yet, use of OCs did not influence the overall increase in muscle strength related to training.

Background: Diffuse large B‐cell lymphoma (DLBCL) is the most common form of lymphoma. European guidelines recommend FDG‐PET/CT for staging and end of treatment (EOT) response assessment, mid‐treatment response assessment is optional. We compared the Lugano classification and PET Response Criteria In Solid Tumours (PERCIST) for FDG‐PET/CT response assessment in DLBCL head‐to‐head. Methods: We retrospectively included patients with DLBCL who underwent first‐line R‐CHOP(‐like) therapy (2013−2020). Interim and EOT FDG‐PET/CT response were reevaluated using the Lugano classification and PERCIST. Response was dichotomized into complete metabolic response (CMR) versus non‐CMR (interim and EOT) and responders versus nonresponders (interim only). The cutoff for nonresponse at interim was a Deauville score of 5 (DS5) with the Lugano classification and a partial metabolic response with ≤66% reduction in SULpeak using PERCIST (PERCIST66). Results: In multivariable Cox regression (N = 170), DS5 at interim, PERCIST66 at interim, non‐CMR at EOT with the Lugano classification and non‐CMR at EOT with PERCIST were predictive of progression‐free survival (PFS). The Lugano classification and PERCIST agreed perfectly at interim and EOT and with 98.4% for the identification of nonresponders at interim. The accuracy for predicting events within 2 years of diagnosis was 84.2% for DS‐5 at interim, 87.6% for PERCIST66 at interim, 86% for non‐CMR with the Lugano classification at EOT and 83.3% for non‐CMR with PERCIST at EOT. Conclusion: The Lugano classification and PERCIST were equally predictive of PFS. Nonresponse at interim and non‐CMR at EOT were predictive of poor PFS with comparable accuracy for predicting events within 2 years. [ABSTRACT FROM AUTHOR]

Abstract Aims Recent updates of international treatment guidelines for heart failure with reduced ejection fraction (HFrEF) differ regarding the use of angiotensin receptor neprilysin inhibitor (ARNI) as first‐line treatment. The American Heart Association/American College of Cardiology/Heart Failure Society of America (AHA/ACC/HFSA) 2022 guidelines gives ARNI a Class IA recommendation for HFrEF patients while the European Society of Cardiology's guidelines are less clear when ARNI could be considered as first line treatment option in de novo patients. This study aimed to model the clinical and budgetary outcomes of implementing these guidelines, comparing conservative ARNI prescription patterns with less conservative in Sweden and in the United Kingdom. Methods and results A health economic model was developed to compare different treatment patterns for HFrEF. Incident cohorts were included on an annual basis and followed over 10 years. The model included treatment specific all‐cause mortality and hospitalization rates, as well as drug acquisition, monitoring, and hospitalization costs. Increasing the use of ARNI could lead to about 7000–12 300 life years gained and 2600–4600 hospitalizations prevented in Sweden. These health benefits come with an additional cost of 112–195 million euros. Similar results were estimated for the United Kingdom, albeit on a larger population. Conclusions Increasing the proportion of patients receiving ARNI instead of angiotensin converting enzyme inhibitors as first‐line treatment of HFrEF will lead to a considerable number of additional life years gained and prevented hospitalizations but with additional cost in terms of health care expenditure in Sweden and in the United Kingdom.

Background Atopic diseases, obesity and neuropsychiatric disorders are lifestyle-related and environmental-related chronic inflammatory disorders, and the incidences have increased in the last years.Objective To outline the design of the 18-year follow-up of the Copenhagen Prospective Study on Asthma in Childhood (COPSAC2000) birth cohort, where risk factors of atopic diseases, obesity and neuropsychiatric disorders are identified through extensive characterisation of the environment, along with deep clinical phenotyping and biosampling for omics profiling.Methods COPSAC2000 is a Danish prospective clinical birth cohort study of 411 children born to mothers with asthma who were enrolled at 1 month of age and closely followed at the COPSAC clinical research unit through childhood for the development of atopic diseases. At the 18-year follow-up visit, biomaterial (hair, blood, urine, faeces, throat, and skin swabs, nasal lining fluid and scraping, and hypopharyngeal aspirates) and extensive information on environmental exposures and risk behaviours were collected along with deep metabolic characterisation and multiorgan investigations including anthropometrics, heart, lungs, kidneys, intestines, bones, muscles and skin. Neuropsychiatric diagnoses were captured from medical records and registers accompanied by electronic questionnaires on behavioural traits and psychopathology.Results A total of 370 (90%) of the 411 cohort participants completed the 18-year visit. Of these, 25.1% had asthma, 23.4% had a body mass index >25 kg/m2 and 16.8% had a psychiatric diagnosis in childhood. A total of 68.7% drank alcohol monthly, and when drinking, 22.2% drank >10 units. Of the participants, 31.4% were currently smoking, and of these, 24.1% smoked daily. A total of 23.8% had tried taking drugs, and 19.7% reported having done self-destructive behaviour. The mean screen time per day was 6.0 hours.Conclusion This huge dataset on health and habits, exposures, metabolism, multiorgan assessments and biosamples from COPSAC2000 by age 18 provides a unique opportunity to explore risk factors and underlying mechanisms of atopic disease and other lifestyle-related, non-communicable diseases such as obesity and neuropsychiatric disorders, which are highly prevalent in the community and our cohort.

Vertical transmission of metabolic constituents from mother to child contributes to the manifestation of disease phenotypes in early life. This study probes the vertical transmission of metabolites from mothers to offspring by utilizing machine learning techniques to differentiate between true mother–child dyads and randomly paired non-dyads. Employing random forests (RF), light gradient boosting machine (LGBM), and logistic regression (Elasticnet) models, we analyzed metabolite concentration discrepancies in mother–child pairs, with maternal plasma sampled at 24 weeks of gestation and children’s plasma at 6 months. The propensity of vertical transfer was quantified, reflecting the likelihood of accurate mother–child matching. Our findings were substantiated against an external test set and further verified through statistical tests, while the models were explained using permutation importance and SHapley Additive exPlanations (SHAP). The best model was achieved using RF, while xenobiotics were shown to be highly relevant in transfer. The study reaffirms the transmission of certain metabolites, such as perfluorooctanoic acid (PFOA), but also reveals additional insights into the maternal influence on the child’s metabolome. We also discuss the multifaceted nature of vertical transfer. These machine learning-driven insights complement conventional epidemiological findings and offer a novel perspective on using machine learning as a methodology for understanding metabolic interactions.