Comment on Manna et al. SARS-CoV-2 Inactivation in Aerosol by Means of Radiated Microwaves. Viruses 2023, 15, 1443.

In a recent article published in Viruses by Manna et al. [...].

Gradients of Orientation, Composition, and Hydration of Proteins for Efficient Light Collection by the Cornea of the Horseshoe Crab.

The lateral eyes of the horseshoe crab, Limulus polyphemus, are the largest compound eyes within recent Arthropoda. The cornea of these eyes contains hundreds of inward projecting elongated cuticular cones and concentrate light onto proximal photoreceptor cells. Although this visual system has been extensively studied before, the precise mechanism allowing vision has remained controversial. Correlating high-resolution quantitative refractive index (RI) mapping and structural analysis, it is demonstrated how gradients of RI in the cornea stem from structural and compositional gradients in the cornea. In particular, these RI variations result from the chitin-protein fibers architecture, heterogeneity in protein composition, and bromine doping, as well as spatial variation in water content resulting from matrix cross-linking on the one hand and cuticle porosity on the other hand. Combining the realistic cornea structure and measured RI gradients with full-wave optical modeling and ray tracing, it is revealed that the light collection mechanism switches from refraction-based graded index (GRIN) optics at normal light incidence to combined GRIN and total internal reflection mechanism at high incident angles. The optical properties of the cornea are governed by different mechanisms at different hierarchical levels, demonstrating the remarkable versatility of arthropod cuticle.

Allometric scaling of a superposition eye optimizes sensitivity and acuity in large and small hawkmoths.

Animals vary widely in body size within and across species. This has consequences for the function of organs and body parts in both large and small individuals. How these scale, in relation to body size, reveals evolutionary investment strategies, often resulting in trade-offs between functions. Eyes exemplify these trade-offs, as they are limited by their absolute size in two key performance features: sensitivity and spatial acuity. Due to their size polymorphism, insect compound eyes are ideal models for studying the allometric scaling of eye performance. Previous work on apposition compound eyes revealed that allometric scaling led to poorer spatial resolution and visual sensitivity in small individuals, across a range of insect species. Here, we used X-ray microtomography to investigate allometric scaling in superposition compound eyes-the second most common eye type in insects-for the first time. Our results reveal a novel strategy to cope with the trade-off between sensitivity and spatial acuity, as we show that the eyes of the hummingbird hawkmoth retain an optimal balance between these performance measures across all body sizes.

Developing a Smart Home Technology Innovation for People With Physical and Mental Health Problems: Considerations and Recommendations.

Smart home technologies present an unprecedented opportunity to improve health and health care by providing greater communication and connectivity with services and care providers and by supporting the daily activities of people managing both mental and physical health problems. Based on our experience from conducting smart technology health studies, including a smart home intervention, we provide guidance on developing and implementing such interventions. First, we describe the need for an overarching principle of security and privacy that must be attended to in all aspects of such a project. We then describe 4 key steps in developing a successful smart home innovation for people with mental and physical health conditions. These include (1) setting up the digital infrastructure, (2) ensuring the components of the system communicate, (3) ensuring that the system is designed for the intended population, and (4) engaging stakeholders. Recommendations on how to approach each of these steps are provided along with suggested literature that addresses additional considerations, guidelines, and equipment selection in more depth.

Characterisation of Grains and Flour Fractions from Field Grown Transgenic Oil-Accumulating Wheat Expressing Oat WRI1.

Wheat (Triticum aestivum L.) is one of the major staple crops in the world and is used to prepare a range of foods. The development of new varieties with wider variation in grain composition could broaden their use. We characterized grains and flours from oil-accumulating transgenic wheat expressing the oat (Avena sativa L.) endosperm WRINKLED1 (AsWRI1) grown under field conditions. Lipid and starch accumulation was determined in developing caryopses of AsWRI1-wheat and X-ray microtomography was used to study grain morphology. The developing caryopses of AsWRI1-wheat grains had increased triacylglycerol content and decreased starch content compared to the control. Mature AsWRI1-wheat grains also had reduced weight, were wrinkled and had a shrunken endosperm and X-ray tomography revealed that the proportion of endosperm was decreased while that of the aleurone was increased. Grains were milled to produce two white flours and one bran fraction. Mineral and lipid analyses showed that the flour fractions from the AsWRI1-wheat were contaminated with bran, due to the effects of the changed morphology on milling. This study gives a detailed analysis of grains from field grown transgenic wheat that expresses a gene that plays a central regulatory role in carbon allocation and significantly affects grain composition.

Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting.

Data-driven forecasts of air quality have recently achieved more accurate short-term predictions. However, despite their success, most of the current data-driven solutions lack proper quantifications of model uncertainty that communicate how much to trust the forecasts. Recently, several practical tools to estimate uncertainty have been developed in probabilistic deep learning. However, there have not been empirical applications and extensive comparisons of these tools in the domain of air quality forecasts. Therefore, this work applies state-of-the-art techniques of uncertainty quantification in a real-world setting of air quality forecasts. Through extensive experiments, we describe training probabilistic models and evaluate their predictive uncertainties based on empirical performance, reliability of confidence estimate, and practical applicability. We also propose improving these models using "free" adversarial training and exploiting temporal and spatial correlation inherent in air quality data. Our experiments demonstrate that the proposed models perform better than previous works in quantifying uncertainty in data-driven air quality forecasts. Overall, Bayesian neural networks provide a more reliable uncertainty estimate but can be challenging to implement and scale. Other scalable methods, such as deep ensemble, Monte Carlo (MC) dropout, and stochastic weight averaging-Gaussian (SWAG), can perform well if applied correctly but with different tradeoffs and slight variations in performance metrics. Finally, our results show the practical impact of uncertainty estimation and demonstrate that, indeed, probabilistic models are more suitable for making informed decisions.

Exploring the visual world of fossilized and modern fungus gnat eyes (Diptera: Keroplatidae) with X-ray microtomography.

Animal eyes typically possess specialized regions for guiding different behavioural tasks within their specific visual habitat. These specializations, and evolutionary changes to them, can be crucial for understanding an animal's ecology. Here, we explore how the visual systems of some of the smallest flying insects, fungus gnats, have adapted to different types of forest habitat over time (approx. 30 Myr to today). Unravelling how behavioural, environmental and phylogenetic factors influence the evolution of visual specializations is difficult, however, because standard quantitative techniques often require fresh tissue and/or provide data in eye-centric coordinates that prevent reliable comparisons between species with different eye morphologies. Here, we quantify the visual world of three gnats from different time periods and habitats using X-ray microtomography to create high-resolution three-dimensional models of the compound eyes of specimens in different preservation states-fossilized in amber, dried or stored in ethanol. We present a method for analysing the geometric details of individual corneal facets and for estimating and comparing the sensitivity, spatial resolution and field of view of species across geographical space and evolutionary time. Our results indicate that, despite their miniature size, fungus gnats do have variations in visual properties across their eyes. We also find some indication that these visual specializations vary across species and may represent adaptations to their different forest habitats. Overall, the findings demonstrate how such investigations can be used to study the evolution of visual specializations-and sensory ecology in general-across a range of insect taxa from different geographical locations and across time.

Outcome Measures for Acute Submassive Pulmonary Embolisms at a Community-Based Hospital Using Ultrasound-Facilitated, Catheter-Directed, Low-Dose Fibrinolysis.

PURPOSE: Ultrasound-facilitated, catheter-directed, low-dose fibrinolysis (USAT) appears to provide promising results for the management of acute submassive pulmonary embolisms (ASMPEs) at tertiary care centers. This study assessed outcome measures at a community-based hospital systems and compared results to known studies. MATERIALS AND METHODS: This is a single-center, retrospective study assessing clinical outcomes of the EkoSonic Endovascular System intervention for ASMPEs performed by three surgical 3 subspecialties (interventional radiology, interventional cardiology, and vascular surgery) part of a pulmonary embolism response team (PERT). We reviewed 146 PERT activations from June 2013 to December 2017. Eighty-three patients with ASMPEs underwent USAT. RESULTS: Our study showed greater differences (P = .01) between baseline and follow-up pulmonary artery systolic pressures (20.9 ± 9.8 mm Hg [n = 14]) compared to the ULTIMA study (12.3 ± 10 mm Hg [n = 30]). Our length-of-stay measures were shorter (6.1 ± 5.1 [n = 83]; P = .0001) compared to the SEATTLE II study (8.8 ± 5.0 [n = 150]). Preprocedure transthoracic echocardiograms (TTEs) were performed for 54 (65%) of 83 patients. Postprocedure TTEs at 48 hours was performed for 52 (62%) of 83 patients. Use of TTEs before and after intervention did not change outcomes. Intracranial hemorrhage was not observed in our patient population. There was no difference in outcomes between the three subspecialties in our study. CONCLUSIONS: Use of USAT in a community-based hospital PERT has similar outcomes to tertiary care centers. Furthermore, similar outcomes were observed between the three subspecialties suggesting development of a comprehensive care team for management of ASMPEs.

Using micro-CT techniques to explore the role of sex and hair in the functional morphology of bumblebee (Bombus terrestris) ocelli.

Many insects have triplets of camera type eyes, called ocelli, whose function remains unclear for most species. Here, we investigate the ocelli of the bumblebee, Bombus terrestris, using reconstructed 3D data from X-ray microtomography scans combined with computational ray-tracing simulations. This method enables us, not only to predict the visual fields of the ocelli, but to explore for the first time the effect that hair has on them as well as the difference between worker female and male ocelli. We find that bumblebee ocellar fields of view are directed forward and dorsally, incorporating the horizon as well as the sky. There is substantial binocular overlap between the median and lateral ocelli, but no overlap between the two lateral ocelli. Hairs in both workers and males occlude the ocellar field of view, mostly laterally in the worker median ocellus and dorsally in the lateral ocelli. There is little to no sexual dimorphism in the ocellar visual field, suggesting that in B. terrestris they confer no advantage to mating strategies. We compare our results with published observations for the visual fields of compound eyes in the same species as well as with the ocellar vision of other bee and insect species.

Bumblebee visual allometry results in locally improved resolution and globally improved sensitivity.

The quality of visual information that is available to an animal is limited by the size of its eyes. Differences in eye size can be observed even between closely related individuals, yet we understand little about how this affects vision. Insects are good models for exploring the effects of size on visual systems because many insect species exhibit size polymorphism. Previous work has been limited by difficulties in determining the 3D structure of eyes. We have developed a novel method based on x-ray microtomography to measure the 3D structure of insect eyes and to calculate predictions of their visual capabilities. We used our method to investigate visual allometry in the bumblebee Bombus terrestris and found that size affects specific aspects of vision, including binocular overlap, optical sensitivity, and dorsofrontal visual resolution. This reveals that differential scaling between eye areas provides flexibility that improves the visual capabilities of larger bumblebees.

The image-forming mirror in the eye of the scallop.

Scallops possess a visual system comprising up to 200 eyes, each containing a concave mirror rather than a lens to focus light. The hierarchical organization of the multilayered mirror is controlled for image formation, from the component guanine crystals at the nanoscale to the complex three-dimensional morphology at the millimeter level. The layered structure of the mirror is tuned to reflect the wavelengths of light penetrating the scallop's habitat and is tiled with a mosaic of square guanine crystals, which reduces optical aberrations. The mirror forms images on a double-layered retina used for separately imaging the peripheral and central fields of view. The tiled, off-axis mirror of the scallop eye bears a striking resemblance to the segmented mirrors of reflecting telescopes.

X-ray micro computed-tomography.

Emily Baird and Gavin Taylor describe how you can make three-dimensional models of biological samples using x-ray micro-computed tomography.

The Dual Function of Orchid Bee Ocelli as Revealed by X-Ray Microtomography.

Visually guided flight control in the rainforest is arguably one of the most complex insect behaviors: illumination varies dramatically depending on location [1], and the densely cluttered environment blocks out most of the sky [2]. What visual information do insects sample for flight control in this habitat? To begin answering this question, we determined the visual fields of the ocelli-thought to play a role in attitude stabilization of some flying insects [3-5]-of an orchid bee, Euglossa imperialis. High-resolution 3D models of the ocellar system from X-ray microtomography were used for optical ray tracing simulations. Surprisingly, these showed that each ocellus possesses two distinct visual fields-a focused monocular visual field suitable for detecting features elevated above the horizon and therefore assisting with flight stabilization [3-5] and, unlike other ocelli investigated to date [4, 6, 7], a large trinocular fronto-dorsal visual field shared by all ocelli. Histological analyses show that photoreceptors have similar orientations within each ocellus and are likely to be sensitive to polarized light, as in some other hymenopterans [7, 8]. We also found that the average receptor orientation is offset between the ocelli, each having different axes of polarization sensitivity relative to the head. Unlike the eyes of any other insect described to date, this ocellar system meets the requirements of a true polarization analyzer [9, 10]. The ocelli of E. imperialis could provide sensitive compass information for navigation in the rainforest and, additionally, provide cues for visual discrimination or flight control.

Using an abstract geometry in virtual reality to explore choice behaviour: visual flicker preferences in honeybees.

Closed-loop paradigms provide an effective approach for studying visual choice behaviour and attention in small animals. Different flying and walking paradigms have been developed to investigate behavioural and neuronal responses to competing stimuli in insects such as bees and flies. However, the variety of stimulus choices that can be presented over one experiment is often limited. Current choice paradigms are mostly constrained as single binary choice scenarios that are influenced by the linear structure of classical conditioning paradigms. Here, we present a novel behavioural choice paradigm that allows animals to explore a closed geometry of interconnected binary choices by repeatedly selecting among competing objects, thereby revealing stimulus preferences in an historical context. We used our novel paradigm to investigate visual flicker preferences in honeybees (Apis mellifera) and found significant preferences for 20-25 Hz flicker and avoidance of higher (50-100 Hz) and lower (2-4 Hz) flicker frequencies. Similar results were found when bees were presented with three simultaneous choices instead of two, and when they were given the chance to select previously rejected choices. Our results show that honeybees can discriminate among different flicker frequencies and that their visual preferences are persistent even under different experimental conditions. Interestingly, avoided stimuli were more attractive if they were novel, suggesting that novelty salience can override innate preferences. Our recursive virtual reality environment provides a new approach to studying visual discrimination and choice behaviour in animals.

Insects modify their behaviour depending on the feedback sensor used when walking on a trackball in virtual reality.

When using virtual-reality paradigms to study animal behaviour, careful attention must be paid to how the animal's actions are detected. This is particularly relevant in closed-loop experiments where the animal interacts with a stimulus. Many different sensor types have been used to measure aspects of behaviour, and although some sensors may be more accurate than others, few studies have examined whether, and how, such differences affect an animal's behaviour in a closed-loop experiment. To investigate this issue, we conducted experiments with tethered honeybees walking on an air-supported trackball and fixating a visual object in closed-loop. Bees walked faster and along straighter paths when the motion of the trackball was measured in the classical fashion - using optical motion sensors repurposed from computer mice - than when measured more accurately using a computer vision algorithm called 'FicTrac'. When computer mouse sensors were used to measure bees' behaviour, the bees modified their behaviour and achieved improved control of the stimulus. This behavioural change appears to be a response to a systematic error in the computer mouse sensor that reduces the sensitivity of this sensor system under certain conditions. Although the large perceived inertia and mass of the trackball relative to the honeybee is a limitation of tethered walking paradigms, observing differences depending on the sensor system used to measure bee behaviour was not expected. This study suggests that bees are capable of fine-tuning their motor control to improve the outcome of the task they are performing. Further, our findings show that caution is required when designing virtual-reality experiments, as animals can potentially respond to the artificial scenario in unexpected and unintended ways.

Selective attention in the honeybee optic lobes precedes behavioral choices.

Attention allows animals to respond selectively to competing stimuli, enabling some stimuli to evoke a behavioral response while others are ignored. How the brain does this remains mysterious, although it is increasingly evident that even animals with the smallest brains display this capacity. For example, insects respond selectively to salient visual stimuli, but it is unknown where such selectivity occurs in the insect brain, or whether neural correlates of attention might predict the visual choices made by an insect. Here, we investigate neural correlates of visual attention in behaving honeybees (Apis mellifera). Using a closed-loop paradigm that allows tethered, walking bees to actively control visual objects in a virtual reality arena, we show that behavioral fixation increases neuronal responses to flickering, frequency-tagged stimuli. Attention-like effects were reduced in the optic lobes during replay of the same visual sequences, when bees were not able to control the visual displays. When bees were presented with competing frequency-tagged visual stimuli, selectivity in the medulla (an optic ganglion) preceded behavioral selection of a stimulus, suggesting that modulation of early visual processing centers precedes eventual behavioral choices made by these insects.

FicTrac: a visual method for tracking spherical motion and generating fictive animal paths.

Studying how animals interface with a virtual reality can further our understanding of how attention, learning and memory, sensory processing, and navigation are handled by the brain, at both the neurophysiological and behavioural levels. To this end, we have developed a novel vision-based tracking system, FicTrac (Fictive path Tracking software), for estimating the path an animal makes whilst rotating an air-supported sphere using only input from a standard camera and computer vision techniques. We have found that the accuracy and robustness of FicTrac outperforms a low-cost implementation of a standard optical mouse-based approach for generating fictive paths. FicTrac is simple to implement for a wide variety of experimental configurations and, importantly, is fast to execute, enabling real-time sensory feedback for behaving animals. We have used FicTrac to record the behaviour of tethered honeybees, Apis mellifera, whilst presenting visual stimuli in both open-loop and closed-loop experimental paradigms. We found that FicTrac could accurately register the fictive paths of bees as they walked towards bright green vertical bars presented on an LED arena. Using FicTrac, we have demonstrated closed-loop visual fixation in both the honeybee and the fruit fly, Drosophila melanogaster, establishing the flexibility of this system. FicTrac provides the experimenter with a simple yet adaptable system that can be combined with electrophysiological recording techniques to study the neural mechanisms of behaviour in a variety of organisms, including walking vertebrates.

Vision and air flow combine to streamline flying honeybees.

Insects face the challenge of integrating multi-sensory information to control their flight. Here we study a 'streamlining' response in honeybees, whereby honeybees raise their abdomen to reduce drag. We find that this response, which was recently reported to be mediated by optic flow, is also strongly modulated by the presence of air flow simulating a head wind. The Johnston's organs in the antennae were found to play a role in the measurement of the air speed that is used to control the streamlining response. The response to a combination of visual motion and wind is complex and can be explained by a model that incorporates a non-linear combination of the two stimuli. The use of visual and mechanosensory cues increases the strength of the streamlining response when the stimuli are present concurrently. We propose this multisensory integration will make the response more robust to transient disturbances in either modality.

Cognitive Assessment and Rehabilitation Pathway for Stroke (CARPS).

Complex cognitive impairments are common after stroke and they can significantly impede individuals' progress in rehabilitation. Treatment strategies that allow patients to compensate for such deficits are therefore an important part of multidisciplinary rehabilitation, as acknowledged by various clinical guidelines. In part due to the heterogeneity of poststroke cognitive impairments, the evidence base for treatments in this area is often unclear or inconsistent. There are no straightforward clinical tools or guidelines available to facilitate poststroke cognitive rehabilitation across cognitive domains. The present article proposes a cognitive assessment and rehabilitation pathway for stroke (CARPS), which aims to provide a structure to guide stroke rehabilitation teams in this difficult area of clinical practice. Practical treatment strategies are also discussed in some detail. Finally, the limitations of the proposed pathway are acknowledged, as is the importance of further research.

Post-stroke emotional adjustment: a modified Social Cognitive Transition model.

Patients report a wide variety of emotional responses following stroke. Some individuals find the process of adjusting to their changed circumstances extremely difficult, while others cope well. Predicting and understanding patients' adjustment to stroke therefore poses challenges within rehabilitation settings. While research has revealed some of the variables associated with increased emotional distress (i.e., post-stroke depression) after stroke, a general model of post-stroke emotional adjustment has not yet been put forward. This article proposes that the Social Cognitive Transition model provides a sound theoretical basis upon which to build an understanding of post-stroke adjustment. The essential elements of a Social Cognitive Transition Model for Stroke are summarised, and clinical examples are used to discuss this model. The implications for psychological assessment, formulation and treatment are also discussed.