A novel post-processing technique for correcting symmetric implant ambiguity in measuring total knee arthroplasty kinematics from single-plane fluoroscopy.

Recent advancements in computer vision and machine learning enable autonomous measurement of total knee arthroplasty kinematics through single-plane fluoroscopy. However, symmetric components present challenges in optimization routines, causing "symmetry traps" and ambiguous poses. Achieving clinically robust kinematics measurement requires addressing this issue. We devised an algorithm that converts a "true" pose to its corresponding "symmetry trap" orientation. From a dataset of nearly 13,000 human supervised kinematics, this algorithm constructs an augmented dataset of "true" and "symmetry trap" kinematics, used to train eight classification machine learning algorithms. The outputs from the highest-performing algorithm classify kinematics sequences as 'obviously true' or 'potentially ambiguous.' We construct a spline through 'obviously true' poses, and 'ambiguous' poses are compared to the spline to determine correct orientation. The machine learning algorithms achieved 88-94% accuracy on our internal test set and 91-93% on our external test set. Applying our spline algorithm to kinematics sequences yielded 91.1% accuracy, 94% specificity, but 67% sensitivity. The accuracy of standard ML algorithms for implants within 5 degrees of a pure-lateral view was 71%, rising to 88% beyond 5 degrees. This pioneering study systematizes addressing model-image registration issues with symmetric tibial implants. High accuracy suggests potential use of ML algorithms to mitigate shape-ambiguity errors in pose measurements from single-plane fluoroscopy. Our results also suggest an imaging protocol for measuring kinematics that favors more oblique viewing angles, which could further disambiguate "true" and "symmetry trap" poses.

Evaluating the Electromagnetic Shielding of Continuous Carbon Fiber Parts Produced by Additive Manufacturing.

Electronic devices are sensitive to electromagnetic (EM) emissions, and require electromagnetic shielding protection to ensure good operation, and prevent noise, malfunctioning, or even burning. To ensure protection, it is important to develop suitable material and design solutions for electronic enclosures. Most common enclosures are made with metal alloys using traditional manufacturing methods. However, using thermoplastic composites combined with additive manufacturing (AM) technologies emerges as an alternative that enables the fabrication of complex parts that are lightweight, consolidated, and oxidation- and corrosion-resistant. In this research, an AM technique based on material extrusion was used to print 2 mm-thick specimens with a multi-material made of micro-carbon fiber (CF)-filled polyamide that was reinforced at specific layers using continuous carbon fibers stacked with a 90° rotation to each other. The specimens' electromagnetic shielding effectiveness (EMSE) was evaluated in the frequency band of 0.03-3 GHz using the coaxial transmission line method. Depending on the number of CF layers, the EM shielding obtained can be up to 70 dB, with a specific shielding up to 60 dB.cm3/g, predominantly by the absorption mechanism, being 22 times higher than without the CF layers. These findings promote this innovative approach to lightweight customizable solutions for EM shielding applications.

Global warming overrides physiological anti-predatory mechanisms in intertidal rock pool fish Gobius paganellus.

In nature, a multitude of factors influences the fitness of an organism at a given time, which makes single stressor assessments far from ecologically relevant scenarios. This study focused on the effects of water temperature and predation stress on the metabolism and body mass gain of a common intertidal rock pool fish, Gobius paganellus, addressing the following hypotheses: (1) the energy metabolism of G. paganellus under predation stress is reduced; (2) G. paganellus shows thermal compensation under heat stress; and (3) thermal stress is the dominant stressor that may override predation stress responses. Individuals were exposed to simulated predation stress and temperature increase from 20 °C to 29 °C, and both stressors combined. Physiological effects were addressed using biochemical biomarkers related with energy metabolism (isocitrate dehydrogenase, lactate dehydrogenase, energy available, energy consumption rates), oxidative stress (superoxide dismutase, catalase, DNA damage, lipid peroxidation), and biotransformation (glutathione-S-transferase). The results of this study revealed that predation stress reduced the cellular metabolism of G. paganellus, and enhanced storage of protein reserves. As hypothesized, hyperthermia decreased the aerobic mitochondrial metabolism, indicating thermal compensation mechanisms to resist against unfavourable temperatures. Hyperthermia was the dominant stressor overriding the physiological responses to predation stress. Both stressors combined might further have synergistically activated detoxification pathways, even though not strong enough to counteract lipid peroxidation and DNA damage completely. The synergistic effect of combined thermal and predation stress thus may not only increase the risk of being preyed upon, but also may indicate extra energy trade-off for the basal metabolism, which in turn may have ecologically relevant consequences for general body functions such as somatic growth and reproduction. The present findings clearly underline the ecological importance of multi-stressor assessments to provide a better and holistic picture of physiological responses towards more realistic evaluations of climate change consequences for intertidal populations.

Sand smelt ability to cope and recover from ocean's elevated CO2 levels.

Considered a major environmental concern, ocean acidification has induced a recent research boost into effects on marine biodiversity and possible ecological, physiological, and behavioural impacts. Although the majority of literature indicate negative effects of future acidification scenarios, most studies are conducted for just a few days or weeks, which may be insufficient to detect the capacity of an organism to adjust to environmental changes through phenotypic plasticity. Here, the effects and the capacity of sand smelt larvae Atherina presbyter to cope and recover (through a treatment combination strategy) from short (15 days) and long-term exposure (45 days) to increasing pCO2 levels (control: ~515 µatm, pH = 8.07; medium: ~940 µatm, pH = 7.84; high: ~1500 µatm, pH = 7.66) were measured, addressing larval development traits, behavioural lateralization, and biochemical biomarkers related with oxidative stress and damage, and energy metabolism and reserves. Although behavioural lateralization was not affected by high pCO2 exposure, morphometric changes, energetic costs, and oxidative stress damage were impacted differently through different exposures periods. Generally, short-time exposures led to different responses to either medium or high pCO2 levels (e.g. development, cellular metabolism, or damage), while on the long-term the response patterns tend to become similar between them, with both acidification scenarios inducing DNA damage and tending to lower growth rates. Additionally, when organisms were transferred to lower acidified condition, they were not able to recover from the mentioned DNA damage impacts. Overall, results suggest that exposure to future ocean acidification scenarios can induce sublethal effects on early life-stages of fish, but effects are dependent on duration of exposure, and are likely not reversible. Furthermore, to improve our understanding on species sensitivity and adaptation strategies, results reinforce the need to use multiple biological endpoints when assessing the effects of ocean acidification on marine organisms.

Effects of ocean acidification on the swimming ability, development and biochemical responses of sand smelt larvae.

Ocean acidification, recognized as a major threat to marine ecosystems, has developed into one of the fastest growing fields of research in marine sciences. Several studies on fish larval stages point to abnormal behaviours, malformations and increased mortality rates as a result of exposure to increased levels of CO2. However, other studies fail to recognize any consequence, suggesting species-specific sensitivity to increased levels of CO2, highlighting the need of further research. In this study we investigated the effects of exposure to elevated pCO2 on behaviour, development, oxidative stress and energy metabolism of sand smelt larvae, Atherina presbyter. Larvae were caught at Arrábida Marine Park (Portugal) and exposed to different pCO2 levels (control: ~600µatm, pH=8.03; medium: ~1000µatm, pH=7.85; high: ~1800µatm, pH=7.64) up to 15days, after which critical swimming speed (Ucrit), morphometric traits and biochemical biomarkers were determined. Measured biomarkers were related with: 1) oxidative stress - superoxide dismutase and catalase enzyme activities, levels of lipid peroxidation and DNA damage, and levels of superoxide anion production; 2) energy metabolism - total carbohydrate levels, electron transport system activity, lactate dehydrogenase and isocitrate dehydrogenase enzyme activities. Swimming speed was not affected by treatment, but exposure to increasing levels of pCO2 leads to higher energetic costs and morphometric changes, with larger larvae in high pCO2 treatment and smaller larvae in medium pCO2 treatment. The efficient antioxidant response capacity and increase in energetic metabolism only registered at the medium pCO2 treatment may indicate that at higher pCO2 levels the capacity of larvae to restore their internal balance can be impaired. Our findings illustrate the need of using multiple approaches to explore the consequences of future pCO2 levels on organisms.

Quantification of neural functional connectivity during an active avoidance task.

Many behavioral and cognitive processes are associated with spatiotemporal dynamic communication between brain areas. Thus, the quantification of functional connectivity with high temporal resolution is highly desirable for capturing in vivo brain function. However, brain functional network quantification from EEG recordings has been commonly used in a qualitative manner. In this paper, we consider pairwise dependence measures as random variables and estimate the pdf for each electrode of the arrangement. A metric imposed by the quadratic Cauchy-Schwartz Mutual Information quantifies these pdfs. We present the results by brain regions simplifying the analysis and visualization drastically. The proposed metric of functional connectivity quantification is addressed for temporal dependencies of the brain network that can be related to the task.