A scalable model for EPA and fatty acid production by Phaeodactylum tricornutum

Data availability statement: The data underpinning this publication can be accessed from Brunel University London's data repository, Brunelfigshare here under a CCBY licence: https://doi.org/10.17633/rd.brunel.21197263.v1.Copyright © 2022 Gu, Kavanagh and McClure.. Large-scale photoautotrophic production of microalgae has the potential to provide a sustainable supply of omega-3 fatty acids (eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)) for human and animal nutrition. This study presents a kinetic model for the EPA-producing microalga Phaeodactylum tricornutum in photoautotrophic conditions, with light and nitrogen being the growth limiting factors. The model was developed using a dataset obtained from bench-scale (5 L) cultures and was successfully validated against pilot-scale (50 L) cultures. This model is the first to predict the biomass and total fatty acid accumulation along with the EPA concentrations in the biomass and total fatty acid fraction for microalgae. The model was used to develop an optimized repeated-batch strategy; implementation of this led to increases in the biomass and EPA productivities of 50 and 20% respectively. This clearly indicates the potential of the model to be used as a tool in the design, optimization and scale-up of microalgal systems for EPA production.Australian Government Research Training Program Scholarshi

Process evaluation of appreciative inquiry to translate pain management evidence into pediatric nursing practice

Background Appreciative inquiry (AI) is an innovative knowledge translation (KT) intervention that is compatible with the Promoting Action on Research in Health Services (PARiHS) framework. This study explored the innovative use of AI as a theoretically based KT intervention applied to a clinical issue in an inpatient pediatric care setting. The implementation of AI was explored in terms of its acceptability, fidelity, and feasibility as a KT intervention in pain management. Methods A mixed-methods case study design was used. The case was a surgical unit in a pediatric academic-affiliated hospital. The sample consisted of nurses in leadership positions and staff nurses interested in the study. Data on the AI intervention implementation were collected by digitally recording the AI sessions, maintaining logs, and conducting individual semistructured interviews. Data were analysed using qualitative and quantitative content analyses and descriptive statistics. Findings were triangulated in the discussion. Results Three nurse leaders and nine staff members participated in the study. Participants were generally satisfied with the intervention, which consisted of four 3-hour, interactive AI sessions delivered over two weeks to promote change based on positive examples of pain management in the unit and staff implementation of an action plan. The AI sessions were delivered with high fidelity and 11 of 12 participants attended all four sessions, where they developed an action plan to enhance evidence-based pain assessment documentation. Participants labeled AI a 'refreshing approach to change' because it was positive, democratic, and built on existing practices. Several barriers affected their implementation of the action plan, including a context of change overload, logistics, busyness, and a lack of organised follow-up. Conclusions Results of this case study supported the acceptability, fidelity, and feasibility of AI as a KT intervention in pain management. The AI intervention requires minor refinements (e.g., incorporating continued follow-up meetings) to enhance its clinical utility and sustainability. The implementation process and effectiveness of the modified AI intervention require evaluation in a larger multisite study

Lower trunk motion and speed-dependence during walking

Abstract Background There is a limited understanding about how gait speed influences the control of upper body motion during walking. Therefore, the primary purpose of this study was to examine how gait speed influences healthy individual's lower trunk motion during overground walking. The secondary purpose was to assess if Principal Component Analysis (PCA) can be used to gain further insight into postural responses that occur at different walking speeds. Methods Thirteen healthy subjects (23 ± 3 years) performed 5 straight-line walking trials at self selected slow, preferred, and fast walking speeds. Accelerations of the lower trunk were measured in the anterior-posterior (AP), vertical (VT), and mediolateral (ML) directions using a triaxial accelerometer. Stride-to-stride acceleration amplitude, regularity and repeatability were examined with RMS acceleration, Approximate Entropy and Coefficient of Multiple determination respectively. Coupling between acceleration directions were calculated using Cross Approximate Entropy. PCA was used to reveal the dimensionality of trunk accelerations during walking at slow and preferred speeds, and preferred and fast speeds. Results RMS acceleration amplitude increased with gait speed in all directions. ML and VT trunk accelerations had less signal regularity and repeatability during the slow compared to preferred speed. However, stride-to-stride acceleration regularity and repeatability did not differ between the preferred and fast walking speed conditions, partly due to an increase in coupling between frontal plane accelerations. The percentage of variance accounted for by each trunk acceleration Principal Component (PC) did not differ between grouped slow and preferred, and preferred and fast walking speed acceleration data. Conclusion The main finding of this study was that walking at speeds slower than preferred primarily alters lower trunk accelerations in the frontal plane. Despite greater amplitudes of trunk acceleration at fast speeds, the lack of regularity and repeatability differences between preferred and fast speeds suggest that features of trunk motion are preserved between the same conditions. While PCA indicated that features of trunk motion are preserved between slow and preferred, and preferred and fast speeds, the discriminatory ability of PCA to detect speed-dependent differences in walking patterns is limited compared to measures of signal regularity, repeatability, and coupling.</p

A modelling workflow for quantification of photobioreactor performance

Data availability: Data has been uploaded to the Brunel figshare repository: https://doi.org/10.17633/rd.brunel.23905842Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S1385894723057637?via%3Dihub#s0065 .Copyright © 2023 The Authors. In this work we have developed a comprehensive modelling workflow for the quantification of photobioreactor performance. Computational Fluid Dynamics (CFD) modelling combined with Lagrangian particle tracking was used to characterise the flow field inside the reactor; this information was combined with a Monte-Carlo model of light attenuation and a kinetic growth model to predict the performance of the system over the duration of the entire batch. The CFD model was validated against measurements of the overall hold-up, local hold-up and mixing time for superficial velocities between 0.6 and 6 cm s−1 in a pilot-scale bubble column photobioreactor, with the CFD predictions agreeing with the experimental data. Comparison was also made between the predicted biomass concentration and experimental measurements using the diatom Phaeodactylum tricornutum, with the model predictions being in good agreement with the experimental results. The model was used to investigate a range of operating conditions and reactor designs, with the most promising predicted to give a 40 % increase in the biomass productivity. Results from this work can be used for the in-silico design and optimisation of photobioreactor systems, thereby enabling their wider use as a sustainable production technology

Development of dynamic compartment models for industrial aerobic fed-batch fermentation processes

Inhomogeneities in key cultivation variables (e.g., substrate and oxygen concentrations) have been shown to affect key process metrics in large-scale bioreactors. Being able to understand these gradients is hence of key interest from both an industrial and academic perspective. One of the main shortcomings of current modelling approaches is that volume change is not considered. Volume increase is a key feature of fed-batch fermentation processes. Existing models are restricted to simulating snapshots (hundreds of seconds) of industrial processes, which can last several weeks. This study presents a novel methodology that overcomes this limitation by constructing dynamic compartment models for the simulation of fed-batch fermentation processes. This strategy is applied to an industrial aerobic fed-batch fermentation process (40–90 m3) with Saccharomyces cerevisiae. First, it has been validated numerically that the compartmentalization strategy used captures the mixing performance and fluid dynamics. This was done by comparing the mixing times and the local concentration profiles of snapshot fermentation process simulations calculated with both CFD and compartment models. Subsequently, simulations of the entire process have been performed using the dynamic compartment model with kinetics. The simulation allows the spatio-temporal characterization of all process variables (e.g., glucose and DO concentrations), as well as the quantification of the metabolic regimes that the cells experience over time. This strategy enables the rapid characterization and assessment of the impact of gradients on process performance in industrial (aerobic) fed-batch fermentation processes and can be readily generalized to any type of bioreactor and microorganism.Technical University of Denmark; Novozymes A/S

Modelling of industrial-scale bioreactors using the particle lifeline approach

Data Availability: Data have been made available in a repository, details are in the data availability statement.Supplementary material is available online at https://www.sciencedirect.com/science/article/pii/S1369703X23001845?via%3Dihub#sec0030 .Copyright © 2023 The Author(s). A key factor in improving the performance of large-scale bioreactors is understanding the conditions experienced by the cells inside the reactor. This can be challenging due to the practical difficulties involved, hence there is increasing use of simulation to quantify the environmental conditions found in large-scale bioreactors. In this work we have used the particle lifeline approach to quantify the effect of the reactor design on the conditions experienced by two very commonly used industrial organisms (Escherichia coli and Saccharomyces cerevisiae). It was found that the cells in the stirred tank reactor tended to experience longer fluctuations of both starvation and overflow metabolism when compared with those in the bubble column, this behaviour being caused by differences in mixing between the two reactor designs. It was found that a significant (60%) fraction of the population in the stirred tank reactors experienced starvation conditions for a large fraction (>70%) of the time, with exposure to such conditions being likely to affect the cellular metabolism. Results from this work provide a detailed insight into the conditions experienced inside industrial-scale bioreactors operated at realistic conditions. Such data can be leveraged to optimise large-scale reactor designs as well as for the development of scale-down systems.Technical University of Denmark and Novozymes A/S

Bridging the data gaps in the epidemiology of hepatitis C virus infection in Malaysia using multi-parameter evidence synthesis

BACKGROUND: Collecting adequate information on key epidemiological indicators is a prerequisite to informing a public health response to reduce the impact of hepatitis C virus (HCV) infection in Malaysia. Our goal was to overcome the acute data shortage typical of low/middle income countries using statistical modelling to estimate the national HCV prevalence and the distribution over transmission pathways as of the end of 2009. METHODS: Multi-parameter evidence synthesis methods were applied to combine all available relevant data sources - both direct and indirect - that inform the epidemiological parameters of interest. RESULTS: An estimated 454,000 (95% credible interval [CrI]: 392,000 to 535,000) HCV antibody-positive individuals were living in Malaysia in 2009; this represents 2.5% (95% CrI: 2.2-3.0%) of the population aged 15-64 years. Among males of Malay ethnicity, for 77% (95% CrI: 69-85%) the route of probable transmission was active or a previous history of injecting drugs. The corresponding proportions were smaller for male Chinese and Indian/other ethnic groups (40% and 71%, respectively). The estimated prevalence in females of all ethnicities was 1% (95% CrI: 0.6 to 1.4%); 92% (95% CrI: 88 to 95%) of infections were attributable to non-drug injecting routes of transmission. CONCLUSIONS: The prevalent number of persons living with HCV infection in Malaysia is estimated to be very high. Low/middle income countries often lack a comprehensive evidence base; however, evidence synthesis methods can assist in filling the data gaps required for the development of effective policy to address the future public health and economic burden due to HCV. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-014-0564-6) contains supplementary material, which is available to authorized users

Experimental investigations of Per- and Poly-fluoroalkyl substances (PFAS) degradation by non-thermal plasma in aqueous solutions

Data Availability: Data will be made available on request.Supplementary material is available online at: https://www.sciencedirect.com/science/article/pii/S2213343723023278?via%3Dihub#sec0100 .The treatability of perfluorocarboxylic acids (PFCA) (perfluorobutanoic acid (PFBA), perfluorohexanoic acid (PFHxA), perfluorooctanoic acid (PFOA) and perfluorodecanoic acid (PFDA)) and perfluorosulfonic acids (PFSA) (PFBS, Perfluorooctanesulfonic acid PFHxS and Perfluorooctanesulfonic acid (PFOS)) via a bubble column with non-thermal plasma discharges in the argon headspace were investigated in individual solutions and from surface water sourced from a contaminated site. High degradation (>90%) could be achieved for PFOA, PFHxS and PFOS within 40 min treating the contaminated surface water. Overall, treatability correlated with the length of the perfluorinated carbon chain, with a decrease in treatability associated with a reduction of the length of the perfluorinated backbone. Experiments with prepared PFAS solutions at initial concentrations of 10, 25 and 50 μg/L found higher initial concentrations of PFCA and PFSA were associated with faster degradation rates suggesting the treatment efficiency was limited by mass transfer of PFAS. Negligible breakdown was observed for PFBA at any of the concentrations trialled, indicating limitations when treating more hydrophilic PFAS, which may require combining this treatment approach with a polishing step, such as nanofiltration.This work was funded by the Australian Research Council’s Special Research Initiative on PFAS (SR180200046). Additionally, we acknowledge the support by the Australian Government Research Training Program (RTP) scholarship and David Cook (Ventia, formerly ICD Asia Pacific) for providing the contaminated surface water samples, Dr. Trevor Walker (Ventia, formerly ICD Asia Pacific) for his technical support and Charles Grimison (Ventia) for his time and technical input reviewing this manuscript. This research was facilitated by access to Sydney Mass Spectrometry, a core research facility at the University of Sydney

Impact of partial bivalent HPV vaccination on vaccine-type infection; a population-based analysis

Background: Data on the effectiveness of 1 dose of HPV vaccine are lacking, particularly in population-based settings. Data from a national HPV immunisation catch-up programme of 14-18 year old girls were used to assess the effectiveness of < 3 doses of the bivalent vaccine on vaccine-type and cross reactive-type HPV infection. Methods: Cervical samples from women attending for their first cervical smear which had been genotyped for HPV as part of a longitudinal HPV surveillance programme were linked to immunisation records to establish the number of vaccine doses (0,1,2,3) administered. Vaccine effectiveness (VE) adjusted for deprivation and age at first dose, was assessed for prevalent HPV 16/18 and HPV 31/33/45 infection.Results: VE for prevalent HPV 16/18 infection associated with 1, 2 and 3 doses was 48.2% (95% CI 16.8-68.9), 54.8% (95% CI 30.7-70.8) and 72.8% (95% CI 62.8-80.3). Equivalent VE for prevalent HPV 31/33/45 infection was -1.62% (95% CI -85.1 – 45.3), 48.3 % (95% CI 7.6 -71.8) and 55.2 % (95% CI 32.6-70.2).Conclusion: Consistent with recent aggregated trial data, we demonstrate the potential effectiveness of even one dose of HPV vaccine on vaccine type infection. Given that these women were immunised as part of a catch-up campaign, the VE observed in this study is likely to be an underestimate of what will occur in girls vaccinated at younger ages. Further population-based studies which look at the clinical efficacy of one dose schedules arewarranted