Paternal behaviours and adolescent development: Examining father-adolescent relationships and academic performance among Singaporean Chinese adolescents

Master'sMASTER OF SOCIAL SCIENCE

Sequential effects of a high-fat, calorie-dense diet or a high-fiber diet on gene expression, body weight and associated metabolic responses in C57/BL6J Mice

Ph.DDOCTOR OF PHILOSOPH

Reducing meat consumption in Central Asia through 3D printing of plant-based protein—enhanced alternatives—a mini review

3D food printing (3DFP) is emerging as a vital innovation in the food industry’s pursuit of sustainability. 3DFP has evolved to significantly impact food production, offering the capability to create customized, nutritionally balanced foods. Central Asia has a higher than global average level of meat consumption per capita, which might be influenced by its historical and cultural background of nomadism. This dietary trend might potentially result in negative impacts on both the environment and human health outcomes, as it leads to increased greenhouse gas emissions and increased risk of chronic diseases. Reducing meat consumption holds the potential to address these sustainability and health issues. A possible strategy to reduce meat consumption and promote plant-based foods is 3D Food Printing (3DFP), which can rely on plant-protein sources from the region to create appealing and tasty alternatives for these populations. This review summarizes recent studies on plant protein-rich materials for 3DFP as a substitute to meet the growing global demand for meat as well as the 3DFP printing parameters associated with the different plant-based proteins currently used (e.g., lentils, soybeans, peas, and buckwheat). The findings revealed that buckwheat, a dietary staple in Central Asia, can be a promising choice for 3DFP technology due to its widespread consumption in the region, gluten-free nature, and highly nutritious profile

Changes in plasma C1q, apelin and adropin concentrations in older adults after descending and ascending stair walking intervention

This study compared changes in plasma complement component 1q (C1q), apelin and adropin concentrations in older obese women after descending (DSW) and ascending stair walking (ASW) training (n = 15/group) performed twice a week for 12 weeks, with gradual increases in exercise time from 5 to 60 min. Fasting blood samples were collected 3 days before the first and 4 days after the last training session. The improvements in the maximal voluntary isometric contraction (MVIC) strength of the knee extensors, functional physical fitness [e.g., 30-s chair stand (CS) performance], resting systolic blood pressure (SBP), insulin sensitivity [e.g., oral glucose tolerance test (OGTT)] and blood lipid profiles [e.g., total cholesterol (TC)] were greater (p \u3c 0.05) in the DSW than ASW group. Plasma C1q decreased (− 51 ± 30%), and apelin (23 ± 15%) and adropin (127 ± 106%) increased (p ≤ .0.05) only after DSW. Significant (p ≤ 0.01) partial correlations were found between the pre- to post-DSW changes in C1q, apelin or adropin and changes in outcome measures [e.g., C1q and MVIC (r = − 0.837), apelin and SBP (r = − 0.854), and andropin and OGTT (r = − 0.729)]. These results showed that greater decreases in plasma C1q and greater increases in apelin and adropin concentrations were associated with greater improvements in outcome measures after DSW than after ASW

The Growing Up in Singapore Towards Healthy Outcomes Study

Objective Epidemiological studies relating maternal 25-hydroxyvitamin D (25OHD) with gestational diabetes mellitus (GDM) and mode of delivery have shown controversial results. We examined if maternal 25OHD status was associated with plasma glucose concentrations, risks of GDM and caesarean section in the Growing Up in Singapore Towards healthy Outcomes (GUSTO) study. Methods Plasma 25OHD concentrations, fasting glucose (FG) and 2-hour postprandial glucose (2HPPG) concentrations were measured in 940 women from a Singapore mother-offspring cohort study at 26–28 weeks’ gestation. 25OHD inadequacy and adequacy were defined based on concentrations of 25OHD ≤75nmol/l and >75nmol/l respectively. Mode of delivery was obtained from hospital records. Multiple linear regression was performed to examine the association between 25OHD status and glucose concentrations, while multiple logistic regression was performed to examine the association of 25OHD status with risks of GDM and caesarean section. Results In total, 388 (41.3%) women had 25OHD inadequacy. Of these, 131 (33.8%), 155 (39.9%) and 102 (26.3%) were Chinese, Malay and Indian respectively. After adjustment for confounders, maternal 25OHD inadequacy was associated with higher FG concentrations (β = 0.08mmol/l, 95% Confidence Interval (CI) = 0.01, 0.14), but not 2HPPG concentrations and risk of GDM. A trend between 25OHD inadequacy and higher likelihood of emergency caesarean section (Odds Ratio (OR) = 1.39, 95% CI = 0.95, 2.05) was observed. On stratification by ethnicity, the association with higher FG concentrations was significant in Malay women (β = 0.19mmol/l, 95% CI = 0.04, 0.33), while risk of emergency caesarean section was greater in Chinese (OR = 1.90, 95% CI = 1.06, 3.43) and Indian women (OR = 2.41, 95% CI = 1.01, 5.73). Conclusions 25OHD inadequacy is prevalent in pregnant Singaporean women, particularly among the Malay and Indian women. This is associated with higher FG concentrations in Malay women, and increased risk of emergency caesarean section in Chinese and Indian women

Metabolic health status and fecundability in a Singapore preconception cohort study

Background: Obesity compromises metabolic health and female fertility, yet not all obese women are similar in metabolic status. The extent to which fecundability is influenced by the metabolic health status of women who are overweight or obese before conception is unknown. Objective: This study aimed to: (1) determine the metabolic health status, and (2) examine the association between metabolic health status and fecundability of overweight and obese women trying to conceive in the Singapore PREconception Study of long-Term maternal and child Outcomes cohort study. Study Design: We conducted a prospective preconception cohort study of Asian women (Chinese, Malay, and Indian) aged 18 to 45 years trying to conceive who were treated from 2015 to 2017 in KK Women's and Children's Hospital in Singapore (n=834). We defined women to have metabolically unhealthy status if they: (1) met 3 or more modified Joint Interim Statement metabolic syndrome criteria; or (2) had homeostasis model assessment-insulin resistance index ≥2.5. Body mass index was categorized as normal (18.5–22.9 kg/m2), overweight (23–27.4 kg/m2), or obese (≥27.5 kg/m2) on the basis of cutoff points for Asian populations. Fecundability was measured by time to pregnancy in menstrual cycles within a year of enrolment. Discrete-time proportional hazards models were used to estimate fecundability odds ratios, with adjustment for confounders and accounting for left truncation and right censoring. Results: Of 232 overweight women, 28 (12.1%) and 25 (10.8%) were metabolically unhealthy by metabolic syndrome ≥3 criteria and homeostasis model assessment-insulin resistance ≥2.5, respectively. Of 175 obese women, 54 (30.9%) and 93 (53.1%) were metabolically unhealthy by metabolic syndrome ≥3 criteria and homeostasis model assessment-insulin resistance ≥2.5, respectively. Compared with metabolically healthy normal-weight women, lower fecundability was observed in metabolically unhealthy overweight women on the basis of metabolic syndrome criteria (fecundability odds ratios, 0.38 [95% confidence interval, 0.15–0.92]) and homeostasis model assessment-insulin resistance (fecundability odds ratios, 0.68 [95% confidence interval, 0.33–1.39]), with metabolic syndrome criteria showing a stronger association. Metabolically unhealthy obese women showed lower fecundability than the healthy normal-weight reference group by both metabolic syndrome (fecundability odds ratios, 0.35; 95% confidence interval, 0.17–0.72) and homeostasis model assessment-insulin resistance criteria (fecundability odds ratios, 0.43; 95% confidence interval, 0.26–0.71). Reduced fecundability was not observed in overweight or obese women who showed healthy metabolic profiles by either definition. Conclusion: Overweight or obesity was not synonymous with having metabolic syndrome or insulin resistance. In our preconception cohort, metabolically unhealthy overweight and obese women showed reduced fecundability, unlike their counterparts who were metabolically healthy. These findings suggest that metabolic health status, rather than simply being overweight and obese per se, plays an important role in fecundability.acceptedVersionPeer reviewe

Differentiating impacts of non‐pharmaceutical interventions on non‐coronavirus disease‐2019 respiratory viral infections: Hospital‐based retrospective observational study in Taiwan

Background Physical distancing and facemask use are worldwide recognized as effective non-pharmaceutical interventions (NPIs) against the coronavirus disease-2019 (COVID-19). Since January 2020, Taiwan has introduced both NPIs but their effectiveness on non-COVID-19 respiratory viruses (NCRVs) remain underexplored. Methods This retrospective observational study examined electronic records at a tertiary hospital in northern Taiwan from pre-COVID (January–December 2019) to post-COVID period (January–May 2020). Patients with respiratory syndromes were tested for both enveloped (eg, influenza virus and seasonal coronavirus) and non-enveloped RVs (eg, enterovirus and rhinovirus) using multiplex reverse transcription polymerase chain reaction assays. Monthly positivity rates of NCRVs among adult and pediatric patients were analyzed with comparison between pre- and post-COVID periods. Results A total of 9693 patients underwent 12 127 multiplex RT-PCR tests. The average positivity rate of NCRVs reduced by 11.2% (25.6% to 14.4%) after nationwide PHIs. Despite the COVID-19 pandemic, the most commonly identified enveloped and non-enveloped viruses were influenza virus and enterovirus/rhinovirus, respectively. Observed reduction in NCRV incidence was predominantly contributed by enveloped NCRVs including influenza viruses. We did not observe epidemiological impacts of NPIs on non-enveloped viruses but an increasing trend in enterovirus/rhinovirus test positivity rate among pediatric patients. Our data were validated using Taiwan's national notification database. Conclusions Our frontline investigation suggests that the current NPIs in Taiwan might not effectively control the transmission of non-enveloped respiratory viruses, despite their protective effects against influenza and seasonal coronavirus. Health authorities may consider using hydrogen peroxide or chloride-based disinfectants as additional preventative strategies against non-enveloped respiratory viruses in the post-COVID-19 era

Comparing feature selection and machine learning approaches for predicting CYP2D6 methylation from genetic variation

IntroductionPharmacogenetics currently supports clinical decision-making on the basis of a limited number of variants in a few genes and may benefit paediatric prescribing where there is a need for more precise dosing. Integrating genomic information such as methylation into pharmacogenetic models holds the potential to improve their accuracy and consequently prescribing decisions. Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene conventionally associated with the metabolism of commonly used drugs and endogenous substrates. We thus sought to predict epigenetic loci from single nucleotide polymorphisms (SNPs) related to CYP2D6 in children from the GUSTO cohort.MethodsBuffy coat DNA methylation was quantified using the Illumina Infinium Methylation EPIC beadchip. CpG sites associated with CYP2D6 were used as outcome variables in Linear Regression, Elastic Net and XGBoost models. We compared feature selection of SNPs from GWAS mQTLs, GTEx eQTLs and SNPs within 2 MB of the CYP2D6 gene and the impact of adding demographic data. The samples were split into training (75%) sets and test (25%) sets for validation. In Elastic Net model and XGBoost models, optimal hyperparameter search was done using 10-fold cross validation. Root Mean Square Error and R-squared values were obtained to investigate each models’ performance. When GWAS was performed to determine SNPs associated with CpG sites, a total of 15 SNPs were identified where several SNPs appeared to influence multiple CpG sites.ResultsOverall, Elastic Net models of genetic features appeared to perform marginally better than heritability estimates and substantially better than Linear Regression and XGBoost models. The addition of nongenetic features appeared to improve performance for some but not all feature sets and probes. The best feature set and Machine Learning (ML) approach differed substantially between CpG sites and a number of top variables were identified for each model.DiscussionThe development of SNP-based prediction models for CYP2D6 CpG methylation in Singaporean children of varying ethnicities in this study has clinical application. With further validation, they may add to the set of tools available to improve precision medicine and pharmacogenetics-based dosing