Resilin and chitinous cuticle form a composite structure for energy storage in jumping by froghopper insects

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background Many insects jump by storing and releasing energy in elastic structures within their bodies. This allows them to release large amounts of energy in a very short time to jump at very high speeds. The fastest of the insect jumpers, the froghopper, uses a catapult-like elastic mechanism to achieve their jumping prowess in which energy, generated by the slow contraction of muscles, is released suddenly to power rapid and synchronous movements of the hind legs. How is this energy stored? Results The hind coxae of the froghopper are linked to the hinges of the ipsilateral hind wings by pleural arches, complex bow-shaped internal skeletal structures. They are built of chitinous cuticle and the rubber-like protein, resilin, which fluoresces bright blue when illuminated with ultra-violet light. The ventral and posterior end of this fluorescent region forms the thoracic part of the pivot with a hind coxa. No other structures in the thorax or hind legs show this blue fluorescence and it is not found in larvae which do not jump. Stimulating one trochanteral depressor muscle in a pattern that simulates its normal action, results in a distortion and forward movement of the posterior part of a pleural arch by 40 μm, but in natural jumping, the movement is at least 100 μm. Conclusion Calculations showed that the resilin itself could only store 1% to 2% of the energy required for jumping. The stiffer cuticular parts of the pleural arches could, however, easily meet all the energy storage needs. The composite structure therefore, combines the stiffness of the chitinous cuticle with the elasticity of resilin. Muscle contractions bend the chitinous cuticle with little deformation and therefore, store the energy needed for jumping, while the resilin rapidly returns its stored energy and thus restores the body to its original shape after a jump and allows repeated jumping

Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.

Background: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. Methods: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. Results: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. Conclusions: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. Trial registration: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.</p

Molecular similarity and diversity approaches in chemoinformatics

10.1002/ddr.20404Drug Development Research72174-84DDRE