Additive Manufacturable Materials for Electrochemical Biosensor Electrodes

With the impending Industrial Revolution 4.0, the information produced by sensors will be central in many applications. This includes the healthcare sector, where affordable healthcare and precision medicine are highly sought after. Electrochemical sensors have the potential to produce affordable, high sensitivity and specificity, intuitive, and rapid point‐of‐care diagnostics. Underpinning these achievements is the choice of material and the fabrication thereof. In this review, the different types of materials used in electrochemical biosensors are reported, with a focus on synthetic conductive materials. The review demonstrates that there is an abundance of materials to select from, and compositing different types of materials further widens their applicability in biosensors. In addition, the fabrication of such materials using the state‐of‐the‐art of fabrication technology, additive manufacturing (AM), is also detailed. The need for compositing is evident in AM, as the feedstock for certain AM technologies is inherently nonconductive. Both material choice and fabrication technologies limitations are also discussed to highlight opportunities for growth. The review highlights how recent technological advancements have the potential to drive the healthcare industry toward achieving its primary goals

Optical biosensors - Illuminating the path to personalized drug dosing

Optical biosensors are low-cost, sensitive and portable devices that are poised to revolutionize the medical industry. Healthcare monitoring has already been transformed by such devices, with notable recent applications including heart rate monitoring in smartwatches and COVID-19 lateral flow diagnostic test kits. The commercial success and impact of existing optical sensors has galvanized research in expanding its application in numerous disciplines. Drug detection and monitoring seeks to benefit from the fast-approaching wave of optical biosensors, with diverse applications ranging from illicit drug testing, clinical trials, monitoring in advanced drug delivery systems and personalized drug dosing. The latter has the potential to significantly improve patients' lives by minimizing toxicity and maximizing efficacy. To achieve this, the patient's serum drug levels must be frequently measured. Yet, the current method of obtaining such information, namely therapeutic drug monitoring (TDM), is not routinely practiced as it is invasive, expensive, time-consuming and skilled labor-intensive. Certainly, optical sensors possess the capabilities to challenge this convention. This review explores the current state of optical biosensors in personalized dosing with special emphasis on TDM, and provides an appraisal on recent strategies. The strengths and challenges of optical biosensors are critically evaluated, before concluding with perspectives on the future direction of these sensors

Electrochemical biosensors: a nexus for precision medicine

Precision medicine is a field with huge potential for improving a patient's quality of life, wherein therapeutic drug monitoring (TDM) can provide actionable insights. More importantly, incorrect drug dose is a common contributor to medical errors. However, current TDM practice is time-consuming and expensive, and requires specialised technicians. One solution is to use electrochemical biosensors (ECBs), which are inexpensive, portable, and highly sensitive. In this review, we explore the potential for ECBs as a technology for on-demand drug monitoring, including microneedles, continuous monitoring, synthetic biorecognition elements, and multi-material electrodes. We also highlight emerging strategies to achieve continuous drug monitoring, and conclude by appraising recent developments and providing an outlook for the field

Inkjet drug printing onto contact lenses: Deposition optimisation and non-invasive dose verification

Inkjet printing has the potential to advance the treatment of eye diseases by printing drugs on demand onto contact lenses for localised delivery and personalised dosing, while near-infrared (NIR) spectroscopy can further be used as a quality control method for quantifying the drug but has yet to be demonstrated with contact lenses. In this study, a glaucoma therapy drug, timolol maleate, was successfully printed onto contact lenses using a modified commercial inkjet printer. The drug-loaded ink prepared for the printer was designed to match the properties of commercial ink, whilst having maximal drug loading and avoiding ocular inflammation. This setup demonstrated personalised drug dosing by printing multiple passes. Light transmittance was found to be unaffected by drug loading on the contact lens. A novel dissolution model was built, and in vitro dissolution studies showed drug release over at least 3 h, significantly longer than eye drops. NIR was used as an external validation method to accurately quantify the drug dose. Overall, the combination of inkjet printing and NIR represent a novel method for point-of-care personalisation and quantification of drug-loaded contact lenses

Connected healthcare: Improving patient care using digital health technologies

Now more than ever, traditional healthcare models are being overhauled with digital technologies of Healthcare 4.0 being increasingly adopted. Worldwide, digital devices are improving every stage of the patient care pathway. For one, sensors are being used to monitor patient metrics 24/7, permitting swift diagnosis and interventions. At the treatment stage, 3D printers are currently being investigated for the concept of personalised medicine by allowing patients access to on-demand, customisable therapeutics. Robots are also being explored for treatment, by empowering precision surgery or targeted drug delivery. Within medical logistics, drones are being leveraged to deliver critical treatments to remote areas, collect samples, and even provide emergency aid. To enable seamless integration within healthcare, the Internet of Things technology is being exploited to form closed-loop systems that remotely communicate with one another. This review outlines the most promising healthcare technologies and devices, their strengths, drawbacks, and scopes for clinical adoption

Machine learning predicts 3D printing performance of over 900 drug delivery systems

Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy trial-and-error approach in optimization. Artificial intelligence (AI) is a technology that could revolutionize pharmaceutical 3DP through analyzing large datasets. Herein, literature-mined data for developing AI machine learning (ML) models was used to predict key aspects of the 3DP formulation pipeline and in vitro dissolution properties. A total of 968 formulations were mined and assessed from 114 articles. The ML techniques explored were able to learn and provide accuracies as high as 93% for values in the filament hot melt extrusion process. In addition, ML algorithms were able to use data from the composition of the formulations with additional input features to predict the drug release of 3D printed medicines. The best prediction was obtained by an artificial neural network that was able to predict drug release times of a formulation with a mean error of ±24.29 min. In addition, the most important variables were revealed, which could be leveraged in formulation development. Thus, it was concluded that ML proved to be a suitable approach to modelling the 3D printing workflow

Analysis of Human Accelerated DNA Regions Using Archaic Hominin Genomes

Several previous comparisons of the human genome with other primate and vertebrate genomes identified genomic regions that are highly conserved in vertebrate evolution but fast-evolving on the human lineage. These human accelerated regions (HARs) may be regions of past adaptive evolution in humans. Alternatively, they may be the result of non-adaptive processes, such as biased gene conversion. We captured and sequenced DNA from a collection of previously published HARs using DNA from an Iberian Neandertal. Combining these new data with shotgun sequence from the Neandertal and Denisova draft genomes, we determine at least one archaic hominin allele for 84% of all positions within HARs. We find that 8% of HAR substitutions are not observed in the archaic hominins and are thus recent in the sense that the derived allele had not come to fixation in the common ancestor of modern humans and archaic hominins. Further, we find that recent substitutions in HARs tend to have come to fixation faster than substitutions elsewhere in the genome and that substitutions in HARs tend to cluster in time, consistent with an episodic rather than a clock-like process underlying HAR evolution. Our catalog of sequence changes in HARs will help prioritize them for functional studies of genomic elements potentially responsible for modern human adaptations

The effect of a sports chiropractic manual therapy intervention on the prevention of back pain, hamstring and lower limb injuries in semi-elite Australian Rules footballers: a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Hamstring injuries are the most common injury in Australian Rules football. It was the aims to investigate whether a sports chiropractic manual therapy intervention protocol provided in addition to the current best practice management could prevent the occurrence of and weeks missed due to hamstring and other lower-limb injuries at the semi-elite level of Australian football.</p> <p>Methods</p> <p>Sixty male subjects were assessed for eligibility with 59 meeting entry requirements and randomly allocated to an intervention (n = 29) or control group (n = 30), being matched for age and hamstring injury history. Twenty-eight intervention and 29 control group participants completed the trial. Both groups received the current best practice medical and sports science management, which acted as the control. Additionally, the intervention group received a sports chiropractic intervention. Treatment for the intervention group was individually determined and could involve manipulation/mobilization and/or soft tissue therapies to the spine and extremity. Minimum scheduling was: 1 treatment per week for 6 weeks, 1 treatment per fortnight for 3 months, 1 treatment per month for the remainder of the season (3 months). The main outcome measure was an injury surveillance with a missed match injury definition.</p> <p>Results</p> <p>After 24 matches there was no statistical significant difference between the groups for the incidence of hamstring injury (OR:0.116, 95% CI:0.013-1.019, p = 0.051) and primary non-contact knee injury (OR:0.116, 95% CI:0.013-1.019, p = 0.051). The difference for primary lower-limb muscle strains was significant (OR:0.097, 95%CI:0.011-0.839, p = 0.025). There was no significant difference for weeks missed due to hamstring injury (4 v14, χ2:1.12, p = 0.29) and lower-limb muscle strains (4 v 21, χ2:2.66, p = 0.10). A significant difference in weeks missed due to non-contact knee injury was noted (1 v 24, χ2:6.70, p = 0.01).</p> <p>Conclusions</p> <p>This study demonstrated a trend towards lower limb injury prevention with a significant reduction in primary lower limb muscle strains and weeks missed due to non-contact knee injuries through the addition of a sports chiropractic intervention to the current best practice management.</p> <p>Trial registration</p> <p>The study was registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12608000533392).</p

Additive and multiplicative hazards modeling for recurrent event data analysis

<p>Abstract</p> <p>Background</p> <p>Sequentially ordered multivariate failure time or recurrent event duration data are commonly observed in biomedical longitudinal studies. In general, standard hazard regression methods cannot be applied because of correlation between recurrent failure times within a subject and induced dependent censoring. Multiplicative and additive hazards models provide the two principal frameworks for studying the association between risk factors and recurrent event durations for the analysis of multivariate failure time data.</p> <p>Methods</p> <p>Using emergency department visits data, we illustrated and compared the additive and multiplicative hazards models for analysis of recurrent event durations under (i) a varying baseline with a common coefficient effect and (ii) a varying baseline with an order-specific coefficient effect.</p> <p>Results</p> <p>The analysis showed that both additive and multiplicative hazards models, with varying baseline and common coefficient effects, gave similar results with regard to covariates selected to remain in the model of our real dataset. The confidence intervals of the multiplicative hazards model were wider than the additive hazards model for each of the recurrent events. In addition, in both models, the confidence interval gets wider as the revisit order increased because the risk set decreased as the order of visit increased.</p> <p>Conclusions</p> <p>Due to the frequency of multiple failure times or recurrent event duration data in clinical and epidemiologic studies, the multiplicative and additive hazards models are widely applicable and present different information. Hence, it seems desirable to use them, not as alternatives to each other, but together as complementary methods, to provide a more comprehensive understanding of data.</p

From the Killing Ground: digital approaches to conflict archaeology–a case study from Waterloo

Since 2015, Waterloo Uncovered has been conducting archaeological fieldwork on the famous 1815 battlefield in Belgium. This paper will focus on two aspects of this work that demonstrate how digital technologies have been used both to interpret the archaeology and to facilitate reconstruction. At Hougoumont, the farm which served as a strong point on Wellington’s right, metal detector survey has provided a visceral insight into the fighting, which has added much to what is already known from historical accounts. This interpretation has in part been facilitated through the use of a digital recording system known as ARK, which plots finds on a map of the site and allows artefacts to be viewed as groups and also as individual objects, which can be subject to detailed scrutiny. The archaeological results of the project have also been useful in informing a virtual reality reconstruction of Hougoumont, which although in an early stage of development will permit visitors to step back in time and experience the farm as it appeared in 1815