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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.

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. Bees fly through complex environments in search of nectar from flowers. They are aided in this quest by excellent eyesight. Scientists have extensively studied the eyesight of honeybees to learn more about how such tiny eyes work and how they process and learn visual information. Less is known about the honeybee’s larger cousins, the bumblebees, which are also important pollinators. Bumblebees come in different sizes and one question scientists have is how eye size affects vision. Bigger bumblebees are known to have bigger eyes, and bigger eyes are usually better. But which aspects of vision are improved in larger eyes is not clear. For example, does the size of a bee’s eyes affect how large their field of view is, or how sensitive they are to light? Or does it impact their visual acuity, a measurement of the smallest objects the eye can see? Scaling up an eye would likely improve all these aspects of sight slightly, but changes in a small area of the eye might more drastically improve some parts of vision. Now, Taylor et al. show that larger bumblebees with bigger eyes have better vision than their smaller counterparts. In the experiments, a technique called microtomography was used to measure the 3D structure of bumblebee eyes. The measurements were then applied to build 3D models of the bumblebee eyes, and computational geometry was used to calculate the sensitivity, acuity, and viewing direction across the entire surface of each model eye. Taylor et al. found that larger bees had improved ability to see small objects in front or slightly above them. They had a bigger area of overlap between the sight in both eyes when they looked forward and up. They were also more sensitive to light across the eye. The experiments show that improvements in eyesight with larger size are very specific and likely help larger bees to adapt to their environment. Behavioral studies could help scientists better understand how these changes help bigger bees and how the traits evolved. These findings might also help engineers trying to design miniature cameras to help small, flying autonomous vehicles navigate. Bees fly through complex environments and face challenges similar to those small flying vehicles would face. Emulating the design of bee eyes and how they change with size might lead to the development of better cameras for these vehicles.

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.

In a recent article published in Viruses by Manna et al. [1], the authors estimate the resonant frequency of SARS-CoV-2 particles using elastic continuum theory of the vibrational modes of a sphere [2]. Unfortunately, the article provides an incorrect solution to the eigenvalue equation. Although this does not influence the validity of the experimental results, the error will be misleading if the solution is used to select frequencies for testing virus inactivation in other studies. This comment provides details on how to obtain a correct solution numerically.

Background Although evidence suggests that stage of disease may influence costs associated with non-small cell lung cancer (NSCLC), there remains a relative paucity of data on the financial burden incurred directly by patients and their informal caregivers as they progress through the disease course. As part of a large, cross-sectional study of the “real-world” humanistic and financial burden of advanced NSCLC in Europe, an analysis was conducted to quantify the cost burden of disease from a patient and caregiver perspective, and to evaluate how stage of disease impacts these costs. Methods Financial data were collected (May 2015–June 2016) during a multinational (France, Germany, and Italy) cross-sectional study of adults with advanced NSCLC (stage IIIB–IV) and their informal (unpaid) caregivers. Data were obtained via medical chart reviews and patient/caregiver self-completion forms. Costs were annualized and unadjusted or adjusted for government financial support. Statistical significance was assessed using Mann-Whitney U tests. Results One thousand thirty patients and 427 accompanying caregivers were recruited and asked to provide cost data. Mean total unadjusted direct and indirect out-of-pocket expenses were €5691 for patients and €4125 for caregivers; after adjusting for government financial support, values were €2644 and €3477. Mean wage losses were significantly higher for patients with stage IV vs IIIB NSCLC (€2282 vs €499; p  = 0.0135) as were unadjusted direct out-of-pocket expenses (€4020 vs €1546; p  = 0.0306). For caregivers, a similar but non-significant trend was observed. Mean total unadjusted direct and indirect out-of-pocket costs were numerically higher for stage IV vs IIIB NSCLC among patients (€5925 vs €3528) and caregivers (€4319 vs €2232); government financial support normalized patient costs, but they remained numerically higher for stage IV disease among caregivers. Conclusions The financial burden of advanced NSCLC is considerable and appears to be influenced by stage of disease, with direct and indirect costs increasing as the disease progresses. Government financial support programmes appear to mitigate additional cost burdens among patients, but not among caregivers.

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.

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.

Purpose Disease symptom management in patients with advanced non-small cell lung cancer (NSCLC) is a critical aspect of therapy. The main objective of our study was to assess patient-reported outcomes and the degree of concordance between physician and patient perceptions of symptom severity in advanced NSCLC in the USA. Methods Patients with advanced (stage IIIB/IV) NSCLC ( N  = 450) were recruited in a nationwide (USA) lung cancer study. Patients and their oncologists completed patient and physician versions of the Lung Cancer Symptom Scale (LCSS). Patient-reported lung cancer-specific quality of life was assessed with the Functional Assessment of Cancer Therapy—Lung (FACT-L). Concordance was assessed using the kappa-statistic. Regression analysis was performed with FACT-L total score as the dependent variable and patient-reported LCSS symptom scores as predictors. Results A high proportion of patients experienced lung cancer symptoms: fatigue (100 %), loss of appetite (97 %), shortness of breath (95 %), cough (93 %), pain (92 %), and blood in sputum (63 %). Concordance between physician and patients was lowest for loss of appetite (kappa 0.1701) and greatest for hemoptysis (kappa 0.4586). Loss of appetite ( β  = −0.204; p  < 0.001), cough ( β  = −0.145; p  < 0.01), pain ( β  = −0.265; p  < 0.001), and shortness of breath ( β  = −0.145; p  < 0.01) were found to be significant predictors of the quality of life. Conclusions Symptom burden in patients with advanced NSCLC is high and has a negative impact on the quality of life. Patient-reported outcomes data could help optimize disease outcomes and therapy management in NSCLC.

Understanding how ecological communities assemble in relation to natural and human‐induced environmental changes is critical, particularly for communities of pollinators that deliver essential ecosystem services. Despite widespread attention to interactions between functional traits and community responses to environmental changes, the importance of sensory traits has received little attention. To address this, we asked whether visual traits of bumblebee communities varied at large geographical scales along a habitat gradient of increased tree cover. Because trees generate challenging light conditions for flying insects, in particular a reduced light intensity, we hypothesised that differences in tree cover would correlate with shifts in the visual and taxonomical composition of bumblebee communities. We quantified 11 visual traits across 36 specimens from 20 species of bumblebees using micro‐CT and optical modelling of compound eyes and ocelli, and investigated how these traits scale with body size. Using an inventory of bumblebee communities across Sweden and our visual trait dataset, we then explored how visual traits (both absolute and relative to body size) differed in relation to tree cover. We found positive shifts of the community weighted means of visual traits along the increasingly forested habitat gradient (facet diameter, inter‐ommatidial angle, eye parameter of the compound eye and alignment of the three ocelli) that were consistent regardless of body size, while other traits decreased when more forest was present in the landscape (facet number). These functional patterns were associated with differences in the abundance of six common species that likely explains the community‐wide shift of visual traits along the habitat gradient. Our study demonstrates the interaction between vision, habitat and community assembly in bumblebees, while highlighting a promising research topic at the interface between sensory biology and landscape ecology. Do visual traits of bumblebee communities vary at large scales with increasing tree cover? We found shifts of visual traits along forested habitat gradient, suggesting that sensory properties not only of species, but also of whole communities interact with the optical constraints of their habitat niche.

Background Malignant pleural mesothelioma (MPM) is an aggressive and rare tumour with poor prognosis. Most patients are diagnosed with advanced disease and there is a paucity of data on the humanistic burden of MPM in terms of impact on health-related quality of life (HRQoL) and activity. This study examined real-world treatment patterns and humanistic disease burden of MPM in Europe. Methods Physicians abstracted demographic/clinical characteristics and treatment data from MPM-patient medical records; MPM patients self-completed a questionnaire including symptoms, 3-level-EQ-5D questionnaire and Visual Analogue Scale (VAS), Lung Cancer Symptom Scale for Mesothelioma (LCSS-Meso), and Work Productivity and Activity Impairment (WPAI) questionnaire. Results Physicians ( n  = 171) abstracted data of 1390 patients; 767/1390 patients self-completed questionnaires. Patients were elderly with advanced, unresectable MPM. Treatment patterns followed guidelines with most (81%) patients receiving platinum+antifolate chemotherapy at first line (1 L). Maintenance treatment use was high (51.1%) despite no recommended maintenance therapies. Symptom burden was high and health states and HRQoL were poor at 1; declining further with progression. Overall mean (SD): LCSS-Average Symptom Burden Index score was 48.8 (19.3; n  = 758); EQ-5D Utility Index score was 0.510 (0.349; n  = 763); EQ-5D VAS score was 54.2 (20.3; n  = 766); LCSS-3-Item Global Index score was 143.2 (64.5; n  = 762); LCSS-normal activities score was 51.9 (24.6; n  = 765); WPAI-activity impairment was 56.0% (23.2%; n  = 737). Conclusion The humanistic burden of MPM is high, despite treatments being prescribed as per available guidance. Treatments that delay progression and provide palliation of symptoms are most likely to improve/maintain HRQoL.