METHODS: C0 were retrieved from a large neonatal vancomycin dataset. Individual estimates of AUC0-24 were obtained from Bayesian post hoc estimation. Various ML algorithms were used for model building to C0 and AUC0-24. An external dataset was used for predictive performance evaluation.
RESULTS: Before starting treatment, C0 can be predicted a priori using the Catboost-based C0-ML model combined with dosing regimen and nine covariates. External validation results showed a 42.5% improvement in prediction accuracy by using the ML model compared with the population pharmacokinetic model. The virtual trial showed that using the ML optimized dose; 80.3% of the virtual neonates achieved the pharmacodynamic target (C0 in the range of 10-20 mg/L), much higher than the international standard dose (37.7-61.5%). Once therapeutic drug monitoring (TDM) measurements (C0) in patients have been obtained, AUC0-24 can be further predicted using the Catboost-based AUC-ML model combined with C0 and nine covariates. External validation results showed that the AUC-ML model can achieve an prediction accuracy of 80.3%.
CONCLUSION: C0-based and AUC0-24-based ML models were developed accurately and precisely. These can be used for individual dose recommendations of vancomycin in neonates before treatment and dose revision after the first TDM result is obtained, respectively.
OBJECTIVE: To investigate the associations of ACEs with changes in epigenetic age acceleration (EAA), a biomarker associated with various health outcomes in middle-aged adults, in a population with balanced race and sex demographics.
DESIGN, SETTING, AND PARTICIPANTS: Data for this cohort study were from the Coronary Artery Risk Development in Young Adults (CARDIA) study. Participants in CARDIA underwent 8 follow-up exams from baseline (year 0 [Y0]; 1985-1986) to Y30 (2015-2016), and participant blood DNA methylation information was obtained at Y15 (2000-2001) and Y20 (2005-2006). Individuals from Y15 and Y20 with available DNA methylation data and complete variables for ACEs and covariates were included. Data were analyzed from September 2021 to August 2022.
EXPOSURES: Participant ACEs (general negligence, emotional negligence, physical violence, physical negligence, household substance abuse, verbal and emotional abuse, and household dysfunction) were obtained at Y15.
MAIN OUTCOMES AND MEASURES: The primary outcome consisted of results from 5 DNA methylation-based EAA measurements known to be associated with biological aging and long-term health: intrinsic EAA (IEAA), extrinsic EAA (EEAA), PhenoAge acceleration (PhenoAA), GrimAge acceleration (GrimAA), and Dunedin Pace of Aging Calculated From the Epigenome (DunedinPACE), measured at Y15 and Y20. Linear regression and generalized estimating equations were used to assess associations of the burden of ACEs (≥4 vs <4 ACEs) with EAA adjusting for demographics, health-related behaviors, and early life and adult socioeconomic status.
RESULTS: A total of 895 participants for Y15 (mean [SD] age, 40.4 [3.5] years; 450 males [50.3%] and 445 females [49.7%]; 319 Black [35.6%] and 576 White [64.4%]) and 867 participants for Y20 (mean [SD] age, 45.4 [3.5] years; 432 males [49.8%] and 435 females [50.2%]; 306 Black [35.3%] and 561 White [64.7%]) were included after excluding participants with missing data. There were 185 participants with (20.7%) vs 710 participants without (79.3%) 4 or more ACEs at Y15 and 179 participants with (20.6%) vs 688 participants without (79.4%) 4 or more ACEs at Y20. Having 4 or more ACEs was positively associated with EAA in years at Y15 (EEAA: β = 0.60 years; 95% CI, 0.18-1.02 years; PhenoAA: β = 0.62 years; 95% CI = 0.13-1.11 years; GrimAA: β = 0.71 years; 95% CI, 0.42-1.00 years; DunedinPACE: β = 0.01; 95% CI, 0.01-0.02) and Y20 (IEAA: β = 0.41 years; 95% CI, 0.05-0.77 years; EEAA: β = 1.05 years; 95% CI, 0.66-1.44 years; PhenoAA: β = 0.57 years; 95% CI, 0.08-1.05 years; GrimAA: β = 0.57 years; 95% CI, 0.28-0.87 years; DunedinPACE: β = 0.01; 95% CI, 0.01-0.02) after adjusting for demographics, health-related behaviors, and socioeconomic status.
CONCLUSIONS AND RELEVANCE: In this cohort study, ACEs were associated with EAA among middle-aged adults after controlling for demographics, behavior, and socioeconomic status. These findings of the associations between early life experience and the biological aging process in midlife may contribute to health promotion in a life course perspective.
RESULTS: Heat and UHP treatments induced the unfolding of DLp to varied degrees, as revealed by fluorescence spectroscopy, ultraviolet-visible absorption, circular dichroism spectra and surface hydrophobicity measurements. Two types of heating-denatured states with varied unfolding degrees were obtained, while UHP at both levels of 100/500 MPa caused partial unfolding of DLp and the presence of a molten-globule state, which significantly enhanced the binding affinity between DLp and (E,E)-2,4-heptadienal. In particular, significantly modified secondary structures of DLp were observed in heating-denatured samples. Excessive denaturing and unfolding degrees resulted in no significant changes in the absorption behavior of the volatile ligand, as characterized by observations of fluorescence quenching and analysis of headspace concentrations.
CONCLUSION: Defining process-induced conformational transition behavior of matrix proteins could be a promising strategy to regulate food flavor attributes and, particularly, to produce DLp coextracted with limited off-flavor components by modifying their interaction during extraction processes. © 2023 Society of Chemical Industry.
METHODS: This review was conducted across the Android and iOS app stores in September-December 2022 to identify and describe all apps targeting stroke survivors. Apps were included if they were designed for stroke management and contained at least one of the following components: medication taking, risk management, blood pressure management, and stroke rehabilitation. Apps were excluded if they were unrelated to health, not in Chinese or English, or the targeted users were healthcare professionals. The included apps were downloaded, and their functionalities were investigated.
RESULTS: The initial search yielded 402 apps, with 115 eligible after title and description screening. Some apps were later excluded due to duplicates, registration problems, or installation failures. In total, 83 apps were included for full review and evaluated by three independent reviewers. Educational information was the most common function (36.1%), followed by rehabilitation guidance (34.9%), communication with healthcare providers (HCPs), and others (28.9%). The majority of these apps (50.6%) had only one functionality. A minority had contributions from an HCP or patients.
CONCLUSION: With the widespread accessibility and availability of smartphone apps across the mHealth landscape, an increasing number of apps targeting stroke survivors are being released. One of the most important findings is that the majority of the apps were not specifically geared toward older adults. Many of the currently available apps lack healthcare professionals' and patients' involvement in their development, and most offer limited functionality, thus requiring further attention to the development of customized apps.
METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).
RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.
CONCLUSION: PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.