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Abstract Image-based deformation estimation is an important tool used in a variety of engineering problems, including crack propagation, fracture, and fatigue failure. These tools have been important in biomechanics research where measuring in vitro and in vivo tissue deformations are important for evaluating tissue health and disease progression. However, accurately measuring tissue deformation in vivo is particularly challenging due to limited image signal-to-noise ratio. Therefore, we created a novel deep-learning approach for measuring deformation from a sequence of images collected in vivo called StrainNet. Utilizing a training dataset that incorporates image artifacts, StrainNet was designed to maximize performance in challenging, in vivo settings. Artificially generated image sequences of human flexor tendons undergoing known deformations were used to compare benchmark StrainNet against two conventional image-based strain measurement techniques. StrainNet outperformed the traditional techniques by nearly 90%. High-frequency ultrasound imaging was then used to acquire images of the flexor tendons engaged during contraction. Only StrainNet was able to track tissue deformations under the in vivo test conditions. Findings revealed strong correlations between tendon deformation and applied forces, highlighting the potential for StrainNet to be a valuable tool for assessing rehabilitation strategies or disease progression. Additionally, by using real-world data to train our model, StrainNet was able to generalize and reveal important relationships between the effort exerted by the participant and tendon mechanics. Overall, StrainNet demonstrated the effectiveness of using deep learning for image-based strain analysis in vivo.

Mechanical testing is a valuable tool for assessing intervertebral disc health, but the wide range of testing protocols makes it difficult to compare results from different studies. Normalizing mechanical properties by disc geometry allows for such comparisons, but there is little consistency in the methods by which disc geometry is measured. As such, we hypothesized that methods used to measure disc geometry would impact reported mechanical properties. Disc height and area were measured using computed tomography (CT), digital calipers, and ImageJ to yield three different measurements for disc height and six for disc area. Disc heights measured by digital calipers ex situ were >30% less than disc heights measured in situ by CT, and disc areas measured ex situ using ImageJ were >30% larger than those measured by CT. This significantly affected reported mechanical properties, leading to a 65% reduction in normalized compressive stiffness in the most extreme case. Though we cannot quantitatively correct between methods, results presented in this study suggest that disc geometry measurement methods have a significant impact on normalized mechanical properties and should be accounted for when comparing results.

The intervertebral disc is a complex structure that experiences multiaxial stresses regularly. Disc failure through herniation is a common cause of lower back pain, which causes reduced mobility and debilitating pain, resulting in heavy socioeconomic burdens. Unfortunately, herniation etiology is not well understood, partially due to challenges in replicating herniation in vitro. Previous studies suggest that flexion elevated risks of herniation. Thus, the objective of this study was to use a multiscale and multiphasic finite element model to evaluate the risk of failure under torque- or muscle-driven flexion. Models were developed to represent torque-driven flexion with the instantaneous center of rotation (ICR) located on the disc, and the more physiologically representative muscle-driven flexion with the ICR located anterior of the disc. Model predictions highlighted disparate disc mechanics regarding bulk deformation, stress-bearing mechanisms, and intradiscal stress-strain distributions. Specifically, failure was predicted to initiate at the bone-disc boundary under torque-driven flexion, which may explain why endplate junction failure, instead of herniation, has been the more common failure mode observed in vitro. By contrast, failure was predicted to initiate in the posterolateral annulus fibrosus under muscle-driven flexion, resulting in consistent herniation. Our findings also suggested that muscle-driven flexion combined with axial compression could be sufficient for provoking herniation in vitro and in silico. In conclusion, this study provided a computational framework for designing in vitro testing protocols that can advance the assessment of disc failure behavior and the performance of engineered disc implants.

Abstract Background A precipitous decline in health status among people recently released from prison is common. In Victoria, Australia, opioid agonist treatment (OAT) in the community involves frequent contact with primary care, potentially facilitating broader use of primary healthcare services. Among a cohort of men who injected drugs regularly pre-imprisonment, we estimated differences in rates of primary healthcare use and medication dispensation between people who did and did not receive OAT post-release. Methods Data came from the Prison and Transition Health Cohort Study. Three-month post-release follow-up interviews were linked with primary care and medication dispensation records. Generalised linear models were fit with one exposure (OAT: none/partial/complete) for 13 outcomes relating to primary healthcare use, pathology testing, and medication dispensation, adjusted for other covariates. Coefficients were reported as adjusted incidence rate ratios (AIRR). Results Analyses included 255 participants. Compared to no OAT use, both partial and complete OAT use were associated with increased rates of standard (AIRR: 3.02, 95%CI: 1.88–4.86; AIRR: 3.66, 95%CI: 2.57–5.23), extended (AIRR: 2.56, 95%CI: 1.41–4.67; AIRR: 2.55, 95%CI: 1.60–4.07) and mental health-related (AIRR: 2.71, 95%CI: 1.42–5.20; AIRR: 2.27, 95%CI: 1.33–3.87) general practitioner (GP) consultations, total medication (AIRR: 1.88, 95%CI: 1.19–2.98; AIRR: 2.40, 95%CI: 1.71–3.37), benzodiazepine (AIRR: 4.99, 95%CI: 2.81–8.85; AIRR: 8.30, 95%CI: 5.28–13.04) and gabapentinoid (AIRR: 6.78, 95%CI: 3.34–13.77; AIRR: 4.34, 95%CI: 2.37–7.94) dispensations, respectively. Partial OAT use was also associated with increased after-hours GP consultations (AIRR: 4.61, 95%CI: 2.24–9.48) and complete OAT use? with increased pathology utilisation (e.g. haematological, chemical, microbiological or immunological tissue/sample testing; AIRR: 2.30, 95%CI: 1.52–3.48). Conclusion We observed higher rates of primary healthcare use and medication dispensation among people who reported partial and complete OAT use post-release. Findings suggest that access to OAT post-release may have a collateral benefit in supporting broader health service utilisation, underscoring the importance of retention in OAT after release from prison.

Abstract Background Australian needle and syringe distribution occurs via a mix of modalities, including syringe dispensing machines (SDMs). SDMs are electronic vending machines providing (often) 24-h access to needles/syringes and may attract greater numbers of people who are younger, female, and/or have limited connection to health care services compared to individuals accessing fixed-site needle and syringe programs (NSPs). However, validating the demographic characteristics of SDM clients has proven difficult in previous research. Methods In this paper, we analyse SDM order and client demographic data from four SDMs located in South-East Melbourne, Australia, and compare this against the managing fixed-site NSP between May 2017 and December 2020. SDM data were collected via a novel 0–9 numeric keypad input tool. Via the tool, SDM clients were requested to input their categorised age, gender and postcode. Given the novelty of the tool, we evaluate the feasibility of the data collection method. We analysed data according to: (1) total SDM orders made, (2) estimated ‘unique SDM presentations’ and (3) describing the demographics of unique SDM clients. Importantly, we noted substantial invalid demographic data, and consequently, severely restricted data for analysis. Results There were 180,989 SDM orders made across the four SDMs to an estimated 90,488 unique SDM presentations. There was little variation in unique presentations across days of the week, but 69% occurred out of NSP operating hours. Across the study period, the SDMs distributed 66% of the number of syringes distributed by the fixed-site NSP. Due to invalid demographic data, our restriction method provided only 10,914 (6% of all data) unique presentations for analysis. There were some demographic differences between SDM and NSP client, but these should be treated with caution. Conclusions The data collection tool provides a novel means of comparing SDM and fixed-site presentations, demonstrating the substantial expansion of service via the SDMs. However, the validity of the demographic data was highly questionable and requires significant data coding, meaning it is not feasible for community NSPs. While we recommend the inclusion of automatically collected SDM order data, the use of a 0–9 numeric keypad to collect demographic data—while an innovation—requires alteration to support NSP data.

Abstract Background Australian harm reduction services are provided via a mix of modalities, including fixed-site needle and syringe programmes (NSP) and syringe-dispensing machines (SDMs). SDMs are cost-effective and provide 24-h anonymous access to needles/syringes, often to underserved geographic areas, and can attract clientele who may choose not to use NSPs. The introduction of COVID-19 control measures saw disruptions and adaptations to the provision of harm reduction services. It is possible that SDMs filled the gap in otherwise disrupted harm reduction services in Melbourne. In this paper, we use data from four SDMs and an NSP to explore changes to harm reduction usage during periods of COVID-19 lockdowns in Melbourne, Australia, in 2020. Methods Our data span September 2017–December 2020. We analysed daily counts of SDM use and monthly counts of NSP use, according to unique presentations to both. Auto-regressive integrated moving average (ARIMA) time-series models were fitted to the data with the effects of lockdowns estimated via a step function. Results Across the study period, we estimated 85,851 SDM presentations and 29,051 NSP presentations. Usage across both the SDMs and the NSP declined during the COVID-19 lockdowns, but only the decline in SDM usage was significant in ARIMA analysis. Conclusions The slight, but significant decline in SDM use suggests barriers to access, though this may have been mitigated by SDM users acquiring needles/syringes from other sources. The decline, however, may be a concern if it led to lowered needle/syringe coverage and a subsequent increase in injecting risk. Further work is needed to properly explore potential changes in preference for needle/syringe acquisition site and associated barriers. Importantly, this work adds to the body of literature around the impacts of COVID-19 on harm reduction provision and potential areas of improvement.

Abstract Mechanical testing is a valuable tool for assessing intervertebral disc health, but the wide range of testing protocols makes it difficult to compare results from different studies. Normalizing mechanical properties by disc geometry allows for such comparisons, but there is little consistency in the methods by which disc geometry is measured. As such, we hypothesized that methods used to measure disc geometry would impact reported mechanical properties. Disc height and area were measured using computed tomography (CT), digital calipers, and ImageJ to yield three different measurements for disc height and six for disc area. Disc heights measured by digital calipers ex situ were >30% less than disc heights measured in situ by CT, and disc areas measured ex situ using ImageJ were >30% larger than those measured by CT. This significantly affected reported mechanical properties, leading to a 65% reduction in normalized compressive stiffness in the most extreme case. Though we cannot quantitatively correct between methods, results presented in this study suggest that disc geometry measurement methods have a significant impact on normalized mechanical properties and should be accounted for when comparing results.

Solid‐state emission is pivotal for the functionality of organic compounds in opto‐electronic applications. Yet, tailoring the emission characteristics of existing solid‐state emissive organic frameworks is a challenging task, primarily due to their intricate structure‐activity interplay. In this study, an innovative family of solid‐state luminogens, centered around the dibenzosuberenylidene core are introduced. These luminogens are characterized by a remarkable excited‐state aromatization‐induced structural planarization (ESAISP) behavior. This unique feature allows for the modulation of their fluorescence properties, including color and intensity, through simple structural alterations, opening new avenues in the development of organic advanced functional materials. [ABSTRACT FROM AUTHOR]

Image-based deformation estimation is an important tool used in a variety of engineering problems, including crack propagation, fracture, and fatigue failure. These tools have been important in biomechanics research where measuring in vitro and in vivo tissue deformations are important for evaluating tissue health and disease progression. However, accurately measuring tissue deformation in vivo is particularly challenging due to limited image signal-to-noise ratio. Therefore, we created a novel deep-learning approach for measuring deformation from a sequence of images collected in vivo called StrainNet. Utilizing a training dataset that incorporates image artifacts, StrainNet was designed to maximize performance in challenging, in vivo settings. Artificially generated image sequences of human flexor tendons undergoing known deformations were used to compare benchmark StrainNet against two conventional image-based strain measurement techniques. StrainNet outperformed the traditional techniques by nearly 90%. High-frequency ultrasound imaging was then used to acquire images of the flexor tendons engaged during contraction. Only StrainNet was able to track tissue deformations under the in vivo test conditions. Findings revealed strong correlations between tendon deformation and applied forces, highlighting the potential for StrainNet to be a valuable tool for assessing rehabilitation strategies or disease progression. Additionally, by using real-world data to train our model, StrainNet was able to generalize and reveal important relationships between the effort exerted by the participant and tendon mechanics. Overall, StrainNet demonstrated the effectiveness of using deep learning for image-based strain analysis in vivo. [ABSTRACT FROM AUTHOR]

Loot boxes are a popular mechanic within many video games, but it remains unclear if some forms of loot boxes can be seen of as gambling. However, the perspectives of players are often neglected, such as whether they see them as ‘fair’ game elements and how closely they feel this aligns with gambling. In this paper, we synthesise a conceptualisation for loot boxes through players’ actual experience and explore if there are any parallels with gambling. Twenty-one participants who played video games took part in the research through either an interview or online survey. Thematic analysis suggested that six themes were core to exploring loot boxes: Random Chance Effects, Attitudes Towards Content, Implementation, Parallels with Gambling, Game Design, and The Player. The results suggested both indirect and direct parallels with gambling from the players experiences. Implications of game design and classifying loot boxes as gambling are discussed in relation to game design and risk factors of gambling and purchasing behaviour.

Abstract Arid rangelands are degraded worldwide, suffering vegetation transformation, soil erosion, introductions, and extinctions. Wild deserts is restoring a desert ecosystem in Sturt National Park, New South Wales, Australia (35,000 ha), eradicating or controlling introduced animals, managing native herbivores, and reintroducing regionally extinct mammals. We describe a Strategic Adaptive Management Plan for restoration of this desert ecosystem, including a vision, model of ecosystem processes, stakeholder input, a hierarchy of objectives linked to triggers and their management actions, producing outcomes and outputs. Our management treatments included two “no restoration” areas and three “restoration” areas. The latter include two exclosures (each 2,000 ha), free of introduced animals (foxes, cats, rabbits), with previously abundant kangaroos removed and regionally extinct mammals to be reintroduced. The third management treatment is a Wild Training Zone (10,400 ha), with introduced animals and kangaroos managed at low levels, using innovative methods, improving survivorship and avoidance behavior of reintroduced mammals to introduced predators. These measures will allow populations of threatened animals to establish, initially in the exclosures, then the Wild Training Zone and potentially more widely. Our strategic adaptive management planning approach is generic and implementable for any natural resource management project, providing explicit steps and processes that track and report transparently on outcomes, fostering learning by doing.

The reliable production of carbon nanotubes and nanofibres is a relatively new development, and due to their unique structure, there has been much interest in filling their hollow interiors. In this review, we provide an overview of the most common approaches for filling these carbon nanostructures. We highlight that filled carbon nanostructures are an emerging material for biomedical applications.