Activity and stability of immobilized Candida rugosa lipase on chitosan coated Fe3O4 nanoparticles in aqueous and organic media

Fe3O4 (magnetite) nanoparticles were prepared by coprecipitation method, coated by chitosan and functionalized by glutaraldehyde. Lipase enzyme from Candida rugosa was immobilized on the prepared particles via cross linking reaction. Synthesis steps and characterization were examined by XRD, TEM, and FTIR.  The immobilization conditions were 10 mL of phosphate buffer (0.1 M, pH 6.5) containing 30 mg of  functionalized magnetic chitosan nanoparticles and 2.0 mg·mL-1 of lipase, immobilization temperature of 4 ℃ and immobilization time of 1 h. Under these conditions, lipase was successfully immobilized with loading capacity of 87 mg/g. The immobilized enzyme showed good operational and storage stability, where it remained stable after 30 days of storage at 4â—¦C.and retained about 61% of its initial activity after twenty repeated uses. Finally enzymatic catalyze synthesis of butyl and hexyl oleate at 40 â—¦C with shaking (200 rpm) was realized in n-hexane and confirmed by GC analysis

Age at puberty and accelerometer-measured physical activity:findings from two independent UK cohorts

Background It is unclear if puberty timing influences future physical activity (PA). Aim To investigate the association of puberty timing with PA across adolescence and adulthood. Subjects and methods Data were from two British cohorts. Participants from an adolescent birth cohort (females = 2349, males = 1720) prospectively reported age at menarche and voice break and had PA recorded by Actigraph accelerometers at ages 14 years and 16 years. A cohort of middle-aged and older adults (40–70 years; females = 48,282; males = 36,112) recalled their age at puberty and had PA (mean acceleration; mg) measured by AxivityAX3 accelerometers. Results After adjustment for age, education, smoking and BMI, per 1-year older age at menarche was associated with higher mean counts/minute at age 14 years (0.07 SD counts/minute; 95% CI = 0.04–0.11) with associations attenuated at age 16 years (0.02; −0.03–0.07). Differences in mean acceleration per older year at menarche were close to the null in women aged 40–49 years (0.02 mg; 0.01–0.03), 50–59 years (0.01; 0.00–0.02) and 60–70 years (0.01; 0.00–0.01). Age at voice break and PA associations were close to the null in both cohorts. Conclusion We found a positive association between puberty timing and PA in females which weakened at older ages and limited evidence of an association at any age in males

Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies

BACKGROUND: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. METHODS: This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5-40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. RESULTS: Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. CONCLUSIONS: LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software

Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies

BACKGROUND: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. METHODS: This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5–40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. RESULTS: Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. CONCLUSIONS: LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01542-8

Hip and spine bone mineral density are greater in master sprinters, but not endurance runners compared with non-athletic controls

Summary: We examined bone density in older athletes and controls. Sprinters had greater hip and spine bone density than endurance athletes and controls, whereas values were similar in the latter two groups. These results could not be explained by differences in impact, muscle size or power between sprint and endurance athletes. Purpose: We examined the relationship between prolonged participation in regular sprint or endurance running and skeletal health at key clinical sites in older age, and the factors responsible for any associations which we observed. Methods: We recruited 38 master sprint runners (28 males, 10 females, mean age 71 ± 7 years), 149 master endurance runners (111 males, 38 females, mean age 70 ± 6 years) and 59 non-athletic controls (29 males, 30 females, mean age 74 ± 5 years). Dual X-ray absorptiometry was used to assess hip and spine bone mineral density (BMD), body composition (lean and fat mass), whilst jump power was assessed with jumping mechanography. In athletes, vertical impacts were recorded over 7 days from a waist-worn accelerometer, and details of starting age, age-graded performance and training hours were recorded. Results: In ANOVA models adjusted for sex, age, height, body composition, and jump power, sprinter hip BMD was 10 and 14% greater than that of endurance runners and controls respectively. Sprinter spine BMD was also greater than that of both endurance runners and controls. There were no differences in hip or spine BMD between endurance runners and controls. Stepwise regression showed only discipline (sprint/endurance), sex, and age as predictors of athlete spine BMD, whilst these variables and starting age were predictive of hip BMD. Conclusions: Regular running is associated with greater BMD at the fracture-prone hip and spine sites in master sprinters but not endurance runners. These benefits cannot be explained by indicators of mechanical loading measured in this study including vertical impacts, body composition or muscular output

Sleep duration in preschool age and later behavioral and cognitive outcomes:an individual participant data meta-analysis in five European cohorts

Data de publicació electrònica: 07-02-2023Short sleep duration has been linked to adverse behavioral and cognitive outcomes in schoolchildren, but few studies examined this relation in preschoolers. We aimed to investigate the association between parent-reported sleep duration at 3.5 years and behavioral and cognitive outcomes at 5 years in European children. We used harmonized data from five cohorts of the European Union Child Cohort Network: ALSPAC, SWS (UK); EDEN, ELFE (France); INMA (Spain). Associations were estimated through DataSHIELD using adjusted generalized linear regression models fitted separately for each cohort and pooled with random-effects meta-analysis. Behavior was measured with the Strengths and Difficulties Questionnaire. Language and non-verbal intelligence were assessed by the Wechsler Preschool and Primary Scale of Intelligence or the McCarthy Scales of Children's Abilities. Behavioral and cognitive analyses included 11,920 and 2981 children, respectively (34.0%/13.4% of the original sample). In meta-analysis, longer mean sleep duration per day at 3.5 years was associated with lower mean internalizing and externalizing behavior percentile scores at 5 years (adjusted mean difference: - 1.27, 95% CI [- 2.22, - 0.32] / - 2.39, 95% CI [- 3.04, - 1.75]). Sleep duration and language or non-verbal intelligence showed trends of inverse associations, however, with imprecise estimates (adjusted mean difference: - 0.28, 95% CI [- 0.83, 0.27] / - 0.42, 95% CI [- 0.99, 0.15]). This individual participant data meta-analysis suggests that longer sleep duration in preschool age may be important for children's later behavior and highlight the need for larger samples for robust analyses of cognitive outcomes. Findings could be influenced by confounding or reverse causality and require replication.Open Access funding enabled and organized by Projekt DEAL. This research (LifeCycle Project ID: ECCNLC201914) was funded by the European Union’s Horizon 2020 research and innovation programme under Grant Agreement N: 733206, LifeCycle project. Kathrin Guerlich was granted a LifeCycle Fellowship (Grant Agreement N: 733206, LifeCycle project). Berthold Koletzko is the Else Kröner Seniorprofessor of Paediatrics at LMU – University of Munich, financially supported by Else Kröner-Fresenius-Foundation, LMU Medical Faculty and LMU University Hospital. Deborah A Lawlor and Ahmed Elhakeem work in a Unit that receives support from the University of Bristol and UK Medical Research Council (MC_UU_00011/6). Deborah A Lawlor is a British Heart Foundation Chair (CH/F/20/90003) and a National Institute of Health Research Senior Investigator (NF-0616–10102). Mònica Guxens is funded by a Miguel Servet II fellowship (CPII18/00018) awarded by the Spanish Institute of Health Carlos III. Jordi Julvez holds Miguel Servet-II contract (CPII19/00015) awarded by the Instituto de Salud Carlos III (Co-funded by European Social Fund "Investing in your future"). Tim Cadman was funded a Marie Sklodowska-Curie Individual Fellowship. Funding details for each cohort are provided in Online Resource 1. No funder had any influence on the study design, data collection, statistical analyses or interpretation of findings. The views expressed in this paper are those of the authors and not necessarily of any funders

Prenatal urban environment and blood pressure trajectories from childhood to early adulthood

Background: Prenatal urban environmental exposures have been associated with blood pressure in children. The dynamic of these associations across childhood and later ages is unknown. Objectives: The purpose of this study was to assess associations of prenatal urban environmental exposures with blood pressure trajectories from childhood to early adulthood. Methods: Repeated measures of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were collected in up to 7,454 participants from a UK birth cohort. Prenatal urban exposures (n = 43) covered measures of noise, air pollution, built environment, natural spaces, traffic, meteorology, and food environment. An exposome-wide association study approach was used. Linear spline mixed-effects models were used to model associations of each exposure with trajectories of blood pressure. Replication was sought in 4 independent European cohorts (up to 9,261). Results: In discovery analyses, higher humidity was associated with a faster increase (mean yearly change in SBP for an interquartile range increase in humidity: 0.29 mm Hg/y, 95% CI: 0.20-0.39) and higher temperature with a slower increase (mean yearly change in SBP per interquartile range increase in temperature: −0.17 mm Hg/y, 95% CI: −0.28 to −0.07) in SBP in childhood. Higher levels of humidity and air pollution were associated with faster increase in DBP in childhood and slower increase in adolescence. There was little evidence of an association of other exposures with change in SBP or DBP. Results for humidity and temperature, but not for air pollution, were replicated in other cohorts. Conclusions: Replicated findings suggest that higher prenatal humidity and temperature could modulate blood pressure changes across childhood.</p