Dampened Transient Actuation of Hydrogels Autonomously Controlled by pH-Responsive Bicontinuous Nanospheres

The fabrication of a soft actuator with a dampened actuation response is presented. This was achieved via the incorporation into an actuating hydrogel of urease-loaded pH-responsive bicontinuous nanospheres (BCNs), whose membrane was able to regulate the permeability and thus conversion of fuel urea into ammonia. The dampened response of these nanoreactors to the enzymatically induced pH change was translated to a pH-responsive soft actuator. In hydrogels composed of a pH-responsive and nonresponsive layer, the transient pH gradient yielded an asymmetric swelling behavior, which induced a bending response. The transient actuation profile could be controlled by varying the external fuel concentrations. Furthermore, we showed that the spatial organization of the BCNs within the actuator had a great influence on the actuation response. Embedding the urease-loaded nanoreactors within the active, pH-responsive layer resulted in a reduced response due to local substrate conversion in comparison to embedding them within the passive layer of the bilayer hydrogel. Finally, we were able to induce transient actuation in a hydrogel comprising two identical active layers by the immobilization of the BCNs within one specific layer. Upon addition of urea, a local pH gradient was generated, which caused accelerated swelling in the BCN layer and transient bending of the device before the pH gradient was attenuated over time.</p

Association between duration of early empiric antibiotics and necrotizing enterocolitis and late-onset sepsis in preterm infants:a multicenter cohort study

The threshold to initiate empiric antibiotics for suspicion of early-onset sepsis (EOS) is low in preterm infants. Antibiotics’ effects on short-term outcomes have recently been debated. We aimed at exploring the extent of early empiric antibiotic exposure (EEAE) in preterm infants and the association between the duration of EEAE with necrotizing enterocolitis (NEC) and late-onset sepsis (LOS) within different EEAE groups. EEAE practice for suspicion of EOS was evaluated in all included infants (gestational age 72 h). Infants with EEAE ≤ 72 h had a lower incidence of NEC compared to both infants without EEAE (adjusted odds ratio (aOR) 0.39; 95% confidence interval (CI) [0.19–0.80]; p = 0.01) and with prolonged EEAE (> 72 h) (aOR [95%CI]: 0.58 [0.35–0.96]; p = 0.03). With every additional day of EEAE, LOS incidence decreased (aOR [95%CI]: 0.90 [0.85–0.97]; p = 0.003). Conclusion: Almost 90% of preterm infants who have negative blood culture results in the first 72 h of life are exposed to EEAE under suspicion of EOS. One-fourth has prolonged EEAE. Duration of EEAE was differently associated with NEC and LOS incidence. The effects of antibiotics, and potentially induced microbial dysbiosis related to development of NEC and LOS, should further be explored.What is Known:• Preterm infants often receive antibiotics empirically directly after birth for suspicion of early-onset sepsis.• The effects of the duration of early empirical antibiotic exposure on the risk for necrotizing enterocolitis and late-onset sepsis are debated.What is New:• Almost 90% of preterm infants with a gestational age below 30 weeks are exposed to antibiotics empirically after birth despite negative culture results. In a quarter of these culture-negative infants, empirical antibiotics are prolonged.• A short course of empirical antibiotics (≤72h) is associated with decreased odds for necrotizing enterocolitis compared to both prolonged (>72h) or no empirical antibiotics after birth. Furthermore, every additional day of empirical antibiotic exposure is associated with decreased risk for late-onset sepsis in the first month of life

Metabolomic profiles predict individual multidisease outcomes

Publisher Copyright: © 2022, The Author(s).Risk stratification is critical for the early identification of high-risk individuals and disease prevention. Here we explored the potential of nuclear magnetic resonance (NMR) spectroscopy-derived metabolomic profiles to inform on multidisease risk beyond conventional clinical predictors for the onset of 24 common conditions, including metabolic, vascular, respiratory, musculoskeletal and neurological diseases and cancers. Specifically, we trained a neural network to learn disease-specific metabolomic states from 168 circulating metabolic markers measured in 117,981 participants with ~1.4 million person-years of follow-up from the UK Biobank and validated the model in four independent cohorts. We found metabolomic states to be associated with incident event rates in all the investigated conditions, except breast cancer. For 10-year outcome prediction for 15 endpoints, with and without established metabolic contribution, a combination of age and sex and the metabolomic state equaled or outperformed established predictors. Moreover, metabolomic state added predictive information over comprehensive clinical variables for eight common diseases, including type 2 diabetes, dementia and heart failure. Decision curve analyses showed that predictive improvements translated into clinical utility for a wide range of potential decision thresholds. Taken together, our study demonstrates both the potential and limitations of NMR-derived metabolomic profiles as a multidisease assay to inform on the risk of many common diseases simultaneously.Peer reviewe

Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2 total), and the proportion of heritability captured by known metabolite loci (h2 Metabolite-hits) for 309 lipids and

Genome-wide characterization of circulating metabolic biomarkers

Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1,2,3,4,5,6,7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases8,9,10,11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.</p