The prognosis for pancreatic ductal adenocarcinoma (PDAC) patients has not significantly improved in the past 3 decades, highlighting the need for more effective treatment approaches. Poor patient ...outcomes and lack of response to therapy can be attributed, in part, to a lack of uptake of perfusion of systemically administered chemotherapeutic drugs into the tumour. Wet-spun alginate fibres loaded with the chemotherapeutic agent gemcitabine have been developed as a potential tool for overcoming the barriers in delivery of systemically administrated drugs to the PDAC tumour microenvironment by delivering high concentrations of drug to the tumour directly over an extended period. While exciting, the practicality, safety, and effectiveness of these devices in a clinical setting requires further investigation. Furthermore, an in-depth assessment of the drug-release rate from these devices needs to be undertaken to determine whether an optimal release profile exists. Using a hybrid computational model (agent-based model and partial differential equation system), we developed a simulation of pancreatic tumour growth and response to treatment with gemcitabine loaded alginate fibres. The model was calibrated using in vitro and in vivo data and simulated using a finite volume method discretisation. We then used the model to compare different intratumoural implantation protocols and gemcitabine-release rates. In our model, the primary driver of pancreatic tumour growth was the rate of tumour cell division. We were able to demonstrate that intratumoural placement of gemcitabine loaded fibres was more effective than peritumoural placement. Additionally, we quantified the efficacy of different release profiles from the implanted fibres that have not yet been tested experimentally. Altogether, the model developed here is a tool that can be used to investigate other drug delivery devices to improve the arsenal of treatments available for PDAC and other difficult-to-treat cancers in the future.
Drug resistance has profoundly limited the success of cancer treatment, driving relapse, metastasis, and mortality. Nearly all anticancer drugs and even novel immunotherapies, which recalibrate the ...immune system for tumor recognition and destruction, have succumbed to resistance development. Engineers have emerged across mechanical, physical, chemical, mathematical, and biological disciplines to address the challenge of drug resistance using a combination of interdisciplinary tools and skill sets. This review explores the developing, complex, and under-recognized role of engineering in medicine to address the multitude of challenges in cancer drug resistance. Looking through the “lens” of intrinsic, extrinsic, and drug-induced resistance (also referred to as “tolerance”), we will discuss three specific areas where active innovation is driving novel treatment paradigms: (1) nanotechnology, which has revolutionized drug delivery in desmoplastic tissues, harnessing physiochemical characteristics to destroy tumors through photothermal therapy and rationally designed nanostructures to circumvent cancer immunotherapy failures, (2) bioengineered tumor models, which have benefitted from microfluidics and mechanical engineering, creating a paradigm shift in physiologically relevant environments to predict clinical refractoriness and enabling platforms for screening drug combinations to thwart resistance at the individual patient level, and (3) computational and mathematical modeling, which blends in silico simulations with molecular and evolutionary principles to map mutational patterns and model interactions between cells that promote resistance. On the basis that engineering in medicine has resulted in discoveries in resistance biology and successfully translated to clinical strategies that improve outcomes, we suggest the proliferation of multidisciplinary science that embraces engineering.
To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and ...virtual patient cohort. Our results suggest that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings suggest biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.
: to develop sport-specific and effective dietary advice, it is important to understand the dietary intakes of team sport athletes. This systematic literature review aims to (1) assess the dietary ...intakes of professional and semi-professional team sport athletes and (2) to identify priority areas for dietetic intervention.
an extensive search of MEDLINE, Sports DISCUS, CINAHL, Web of Science, and Scopus databases in April-May 2018 was conducted and identified 646 studies. Included studies recruited team sport, competitive (i.e. professional or semi-professional) athletes over the age of 18 years. An assessment of dietary intake in studies was required and due to the variability of data (i.e. nutrient and food group data) a meta-analysis was not undertaken. Two independent authors extracted data using a standardised process.
21 (
= 511) studies that assessed dietary intake of team sport athletes met the inclusion criteria. Most reported that professional and semi-professional athletes' dietary intakes met or exceeded recommendations during training and competition for protein and/or fat, but not energy and carbohydrate. Limitations in articles include small sample sizes, heterogeneity of data and existence of underreporting.
this review highlights the need for sport-specific dietary recommendations that focus on energy and carbohydrate intake. Further exploration of factors influencing athletes' dietary intakes including why athletes' dietary intakes do not meet energy and/or carbohydrate recommendations is required.
Heterogeneity is a dominant factor in the behaviour of many biological processes. Despite this, it is common for mathematical and statistical analyses to ignore biological heterogeneity as a source ...of variability in experimental data. Therefore, methods for exploring the identifiability of models that explicitly incorporate heterogeneity through variability in model parameters are relatively underdeveloped. We develop a new likelihood-based framework, based on moment matching, for inference and identifiability analysis of differential equation models that capture biological heterogeneity through parameters that vary according to probability distributions. As our novel method is based on an approximate likelihood function, it is highly flexible; we demonstrate identifiability analysis using both a frequentist approach based on profile likelihood, and a Bayesian approach based on Markov-chain Monte Carlo. Through three case studies, we demonstrate our method by providing a didactic guide to inference and identifiability analysis of hyperparameters that relate to the statistical moments of model parameters from independent observed data. Our approach has a computational cost comparable to analysis of models that neglect heterogeneity, a significant improvement over many existing alternatives. We demonstrate how analysis of random parameter models can aid better understanding of the sources of heterogeneity from biological data.
Relatively little is known about social cognition in people with intellectual disability (ID), and how this may support understanding of co-occurring autism. A limitation of previous research is that ...traditional social-cognitive tasks place a demand on domain-general cognition and language abilities. These tasks are not suitable for people with ID and lack the sensitivity to detect subtle social-cognitive processes. In autism research, eye-tracking technology has offered an effective method of evaluating social cognition-indicating associations between visual social attention and autism characteristics. The present systematic review synthesised research which has used eye-tracking technology to study social cognition in ID. A meta-analysis was used to explore whether visual attention on socially salient regions (SSRs) of stimuli during these tasks correlated with degree of autism characteristics presented on clinical assessment tools.
Searches were conducted using four databases, research mailing lists, and citation tracking. Following in-depth screening and exclusion of studies with low methodological quality, 49 articles were included in the review. A correlational meta-analysis was run on Pearson's r values obtained from twelve studies, reporting the relationship between visual attention on SSRs and autism characteristics.
Eye-tracking technology was used to measure different social-cognitive abilities across a range of syndromic and non-syndromic ID groups. Restricted scan paths and eye-region avoidance appeared to impact people's ability to make explicit inferences about mental states and social cues. Readiness to attend to social stimuli also varied depending on social content and degree of familiarity. A meta-analysis using a random effects model revealed a significant negative correlation (r = -.28, 95% CI -.47, -.08) between visual attention on SSRs and autism characteristics across ID groups. Together, these findings highlight how eye-tracking can be used as an accessible tool to measure more subtle social-cognitive processes, which appear to reflect variability in observable behaviour. Further research is needed to be able to explore additional covariates (e.g. ID severity, ADHD, anxiety) which may be related to visual attention on SSRs, to different degrees within syndromic and non-syndromic ID groups, in order to determine the specificity of the association with autism characteristics.
Abstract
Background: Mandatory induction for foundation year 1 trainees (F1s) was introduced in 2012 to ease the transition from student to doctor. The aims of this national study were to assess ...anxiety levels and preparedness in the 2012 F1 cohort and whether these varied according to medical school of graduation and foundation school of practice.
Methods: Online surveys were completed anonymously and voluntarily by F1s and F1 supervisors from participating foundation schools. Questions assessed how prepared F1s were for practice and how well they coped with the transition from medical school. A validated screening tool was used to assess anxiety levels.
Results: 1829 F1s and 1145 supervisors participated. 27.8% of F1s screened positive for pathological anxiety. Increased time spent in a 'shadowing' type role during medical school and each additional day of induction reduced anxiety levels. How prepared F1s were for different aspects of their jobs varied according to medical and foundation school, from both the F1 and supervisor perspective.
Conclusions: How prepared F1s feel can vary according to the medical school of graduation and foundation school of practice. F1 anxiety may be reduced with a prolonged F1 induction programme and an extended shadowing period during the final year of medical school.
We report the design and synthesis of two novel indigo donor-acceptor (D-A) polymers,
PIDG-T-C20
and
PIDG-BT-C20
, comprising an indigo moiety that has intramolecular hydrogen-bonds as the acceptor ...building block and thiophene (T) and bithiophene (BT) as the donor building block, respectively.
PIDG-T-C20
and
PIDG-BT-C20
exhibited characteristic p-type semiconductor performance, achieving hole mobilities of up to 0.016 and 0.028 cm
2
V
−1
s
−1
, respectively, which are highest values reported for indigo-based polymers. The better performing
PIDG-BT-C20
was used for the fabrication of water-gated organic field-effect transistors (WGOFETs), which showed excellent stability at ambient conditions. The
PIDG-BT-C20
-based WGOFETs exhibited rapid response when fluoride ions were introduced to the water gate dielectric, achieving a limit of detection (LOD) of 0.40 mM. On the other hand, the devices showed much lower sensitivities towards other halide ions with the order of relative response: F
−
> Cl
−
> Br
−
> I
−
. The high sensitivity and selectivity of
PIDG-BT-C20
to fluoride over other halides is considered to be realized through the strong interaction of the hydrogen atoms of the N-H groups in the indigo unit with fluoride ions, which alters the intramolecular hydrogen-bonding arrangement, the electronic structures, and thus the charge transport properties of the polymer.
A p-type indigo polymer semiconductor is developed for water-gated organic field-effect transistors (WGOFET) for sensing fluoride ions.
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