Multiscale modelling of biomolecular corona formation on metallic surfaces.

In the realm of food industry, the choice of non-consumable materials used plays a crucial role in ensuring consumer safety and product quality. Aluminum is widely used in food packaging and food processing applications, including dairy products. However, the interaction between aluminum and milk content requires further investigation to understand its implications. In this work, we present the results of multiscale modelling of the interaction between various surfaces, that is (100), (110), and (111), of fcc aluminum with the most abundant milk proteins and lactose. Our approach combines atomistic molecular dynamics, a coarse-grained model of protein adsorption, and kinetic Monte Carlo simulations to predict the protein corona composition in the deposited milk layer on aluminum surfaces. We consider a simplified model of milk, which is composed of the six most abundant milk proteins found in natural cow milk and lactose, which is the most abundant sugar found in dairy. Through our study, we ranked selected proteins and lactose adsorption affinities based on their corresponding interaction strength with aluminum surfaces and predicted the content of the naturally forming biomolecular corona. Our comprehensive investigation sheds light on the implications of aluminum in food processing and packaging, particularly concerning its interaction with the most abundant milk proteins and lactose. By employing a multiscale modelling approach, we simulated the interaction between metallic aluminum surfaces and the proteins and lactose, considering different crystallographic orientations. The results of our study provide valuable insights into the mechanisms of lactose and protein deposition on aluminum surfaces, which can aid in the general understanding of protein corona formation.

In silico prediction of protein binding affinities onto core-shell PEGylated noble metal nanoparticles for rational design of drug nanocarriers.

Polymer-coated nanoparticles (NP) are commonly used as drug carriers or theranostic agents. Their uptake rates are modulated by the interactions with essential serum proteins such as transferrin and albumin. Understanding the control parameters of these interactions is crucial for improving the efficiency of these nanoscale devices. In this work, we perform a multiscale computational study of protein adsorption onto polyethylene glycol (PEG) coated gold and silver NPs, producing protein-NP adsorption rankings as a function of PEG grafting density, which are validated against previously reported experimental protein-NP binding constants. Furthermore, the applied nano-docking method provides information on the preferred orientation of proteins immobilised on the surface of NPs. We propose a method of construction of model core-shell NPs in silico. The presented protocol can provide molecular level insights for the experimental development of biosensors, nanocarriers, or other nanoplatforms where information on the preferred orientation of protein at the bio-nano interface is crucial, and enables fast in silico prescreening of assays of various nanocarriers, i.e., combinations of proteins, NPs, and coatings.

Machine-learning based prediction of small molecule-surface interaction potentials.

Predicting the adsorption affinity of a small molecule to a target surface is of importance to a range of fields, from catalysis to drug delivery and human safety, but a complex task to perform computationally when taking into account the effects of the surrounding medium. We present a flexible machine-learning approach to predict potentials of mean force (PMFs) and adsorption energies for chemical-surface pairs from the separate interaction potentials of each partner with a set of probe atoms. We use a pre-existing library of PMFs obtained via atomistic molecular dynamics simulations for a variety of inorganic materials and molecules to train the model. We find good agreement between original and predicted PMFs in both training and validation groups, confirming the predictive power of this approach, and demonstrate the flexibility of the model by producing PMFs for molecules and surfaces outside the training set.

Innovations to maximise impact of a data for decision-making training programme in the Federated States of Micronesia.

Accurate and timely health information is an essential foundation for strengthening health systems. Data for decision making (DDM) is a training curriculum designed to enhance capacity of health department staff to capture and use high-quality data to address priority health issues. In 2013, the Pacific Public Health Surveillance Network adapted and piloted the DDM curriculum as an 'at work, from work, for work' field epidemiology training programme component for low-income and middle-income Pacific Island jurisdictions. Based on lessons learned from the pilot, we made several innovations, including delivery on-site at each district (rather than bringing trainees to a central location), conducting pre-DDM consultations and ongoing contact with health leaders across the programme, taking more care in selecting trainees and enrolling a larger cohort of students from within each health department. The decentralised programme was delivered in-country at four sites (both at national and state levels) in the Federated States of Micronesia. Following delivery, we performed an external evaluation of the programme to assess student outcomes, benefits to the health department and general programme effectiveness. Of the 48 trainees who completed all four classroom modules, 40 trainees participated in the evaluation. Thirty-two of these trainees completed the programme's capstone field project. Eighteen of these projects directly contributed to changes in legislation, revised programme budgets, changes in programme strategy to augment outreach and to target disease and risk factor 'hot spots'.

A hard-sphere model of protein corona formation on spherical and cylindrical nanoparticles.

A nanoparticle (NP) immersed in biological media rapidly forms a corona of adsorbed proteins, which later controls the eventual fate of the particle and the route through which adverse outcomes may occur. The composition and timescale for the formation of this corona are both highly dependent on both the NP and its environment. The deposition of proteins on the surface of the NP can be imitated by a process of random sequential adsorption, and, based on this model, we develop a rate-equation treatment for the formation of a corona represented by hard spheres on spherical and cylindrical NPs. We find that the geometry of the NP significantly alters the composition of the corona through a process independent of the rate constants assumed for adsorption and desorption of proteins, with the radius and shape of the NP both influencing the corona. We further investigate the roles of protein mobility on the surface of the NP and changes in the concentration of proteins.

First principles characterisation of bio-nano interface.

Nanomaterials possess a wide range of potential applications due to their novel properties and exceptionally high activity as a result of their large surface to volume ratios compared to bulk matter. The active surface may present both advantage and risk when the nanomaterials interact with living organisms. As the overall biological impact of nanomaterials is triggered and mediated by interactions at the bio-nano interface, an ability to predict those from the atomistic descriptors, especially before the material is produced, can present enormous advantage for the development of nanotechnology. Fast screening of nanomaterials and their variations for specific biological effects can be enabled using computational materials modelling. The challenge lies in the range of scales that needs to be crossed from the material-specific atomistic representation to the relevant length scales covering typical biomolecules (proteins and lipids). In this work, we present a systematic multiscale approach that allows one to evaluate crucial interactions at the bionano interface from the first principles without any prior information about the material and thus establish links between the details of the nanomaterials structure to protein-nanoparticle interactions. As an example, an advanced computational characterization of titanium dioxide nanoparticles (6 different surfaces of rutile and anatase polymorphs) has been performed. We computed characteristics of the titanium dioxide interface with water using density functional theory for electronic density, used these parameters to derive an atomistic force field, and calculated adsorption energies for essential biomolecules on the surface of titania nanoparticles via direct atomistic simulations and coarse-grained molecular dynamics. Hydration energies, as well as adsorption energies for a set of 40 blood proteins are reported.

A cross-sectional study exploring obesity and pregnancy planning among women attending an antenatal clinic in Suva, Fiji.

BACKGROUND: Pregnancy planning enables maternal health optimisation which is particularly important for women who have obesity and are at increased risk of adverse perinatal outcomes. AIMS: The prevalence of pregnancy planning and its relationship to body mass index (BMI) was investigated in a cohort of women attending antenatal clinics in the main referral hospital in Suva, Fiji. MATERIALS AND METHODS: The questionnaire captured health and socio-demographic data, anthropometry and asked about pregnancy planning. RESULTS: Two thousand, two hundred and three pregnant women presenting for their first booking at the antenatal clinic were enrolled; 721 (37.4%) out of 1926 women with complete data reported they did not plan their pregnancy. A third of women (n = 633, 32.8%) had overweight and 805 (41.7%) had obesity. In multivariable analyses parity, employment status, marital status, and BMI were significantly associated with pregnancy planning. Compared to women of a healthy weight or underweight, women who have obesity were less likely to plan their pregnancy (adjusted odds ratio 0.742; 95% CI 0.569-0.967). CONCLUSION: Tackling the cycle of obesity will require attention to preconception care and optimising weight before pregnancy.

In Silico Prediction of Protein Adsorption Energy on Titanium Dioxide and Gold Nanoparticles.

The free energy of adsorption of proteins onto nanoparticles offers an insight into the biological activity of these particles in the body, but calculating these energies is challenging at the atomistic resolution. In addition, structural information of the proteins may not be readily available. In this work, we demonstrate how information about adsorption affinity of proteins onto nanoparticles can be obtained from first principles with minimum experimental input. We use a multiscale model of protein-nanoparticle interaction to evaluate adsorption energies for a set of 59 human blood serum proteins on gold and titanium dioxide (anatase) nanoparticles of various sizes. For each protein, we compare the results for 3D structures derived from experiments to those predicted computationally from amino acid sequences using the I-TASSER methodology and software. Based on these calculations and 2D and 3D protein descriptors, we develop statistical models for predicting the binding energy of proteins, enabling the rapid characterization of the affinity of nanoparticles to a wide range of proteins.

A decade of data linkage in Western Australia: strategic design, applications and benefits of the WA data linkage system.

OBJECTIVES: The report describes the strategic design, steps to full implementation and outcomes achieved by the Western Australian Data Linkage System (WADLS), instigated in 1995 to link up to 40 years of data from over 30 collections for an historical population of 3.7 million. Staged development has seen its expansion, initially from a linkage key to local health data sets, to encompass links to national and local health and welfare data sets, genealogical links and spatial references for mapping applications. APPLICATIONS: The WADLS has supported over 400 studies with over 250 journal publications and 35 graduate research degrees. Applications have occurred in health services utilisation and outcomes, aetiologic research, disease surveillance and needs analysis, and in methodologic research. BENEFITS: Longitudinal studies have become cheaper and more complete; deletion of duplicate records and correction of data artifacts have enhanced the quality of information assets; data linkage has conserved patient privacy; community machinery necessary for organised responses to health and social problems has been exercised; and the commercial return on research infrastructure investment has exceeded 1000%. Most importantly, there have been unbiased contributions to medical knowledge and identifiable advances in population health arising from the research.

Compliance with advice and appropriateness of emergency presentation following contact with the HealthDirect telephone triage service.

OBJECTIVE: Evaluation of compliance with advice and appropriateness of emergency presentation following contact with a telephone triage service (HealthDirect). METHODS: Compliance rates, triage distributions and admission rates were determined using linked HealthDirect and ED records for patients living within 2 km of an ED that presented during 2000. RESULTS: Of 13 019 presentations, 842 (6.5%) were HealthDirect contacts. In the HealthDirect group there were a greater proportion of patients under the age of 15 (290, 34% vs 1598, 13.1%) and women (481, 57% vs 5610, 46%). The triage distributions and admission rates for HealthDirect contacts and other patients were similar (HealthDirect 37.6% admitted, 95% CI 34-41, others 38.4% admitted, 95% CI 38-39, Pchi2 = 0.67). Of 3996 callers to HealthDirect, 3167 (79%) complied with advice with 963 (61%) complying with advice to present and 212 (9%, 95% CI 8-10%) presenting despite advice to defer presentation. Triage distributions and admission rates for compliers and non-compliers were similar (compliers 38% admitted, 95% CI 34-41, non-compliers, 37% admitted, 95% CI 30-44, Pchi2 = 0.89). CONCLUSIONS: HealthDirect contacts were of similar appropriateness to non-HealthDirect presenters and appear to attend the ED independent of HealthDirect advice. HealthDirect has a limited capacity to influence ED utilization or workload.

Talipes equinovarus in Western Australia.

In Western Australia (WA), talipes equinovarus is a notifiable birth defect and, since 1980, has been ascertained by the population-based Birth Defects Registry (BDR). Talipes equinovarus deformities were classified as two distinct and distinguishable types, viz. isolated talipes equinovarus (no other birth defects present) and associated talipes equinovarus (other birth defects present). The birth prevalence of associated talipes in WA between 1980 and 1994 was 0.90 per 1000 births, and of isolated talipes was 1.25 per 1000 births. The rate of the isolated deformity was higher in Aboriginal infants (3.49 per 1000 births) than in Caucasian infants (1.11 per 1000 births) and non-Aboriginal non-Caucasian infants (0.73 per 1000 births). The sex differential in the rate of the isolated deformity was greatest among Aboriginal infants, with the rate in males being almost four times that in females. The birth prevalence of both types of the deformity remained stable over the 15-year study period. The rate of caesarean and breech deliveries and the proportion of bilaterally affected feet was greater among infants with associated talipes equinovarus deformity. An accurate and complete identification of cases of isolated talipes equinovarus in the 1980-94 WA birth cohort provides a basis for furthering the understanding of the epidemiology and hence the aetiology of the deformity.