Tyto alba; tawny owl, Strix aluco, and goshawk, Accipiter gentilis). Wing shapes were highly repeatable and shoulder actuation was a key component of reconfiguring the overall planform and controlling angle of attack. The three birds shared common spanwise patterns of wing twist, an inverse relationship between twist and peak camber, and held their wings depressed below their shoulder in an anhedral configuration. With increased speed, all three birds tended to reduce camber throughout the wing, and their wings bent in a saddle-shape pattern. A number of morphing features suggest that the coordinated movements of the wing and tail support efficient flight, and that the tail may act to modulate wing camber through indirect aeroelastic control.In gliding flight, birds morph their wings and tails to control their flight trajectory and speed. Using high-resolution videogrammetry, we reconstructed accurate and detailed three-dimensional geometries of gliding flights for three raptors (barn owl,  At their fastest glide speeds, birds fold and sweep back their wings, and fully contract their tail . At slowDespite limitations in our knowledge of avian wing morphing, each of the effects identified are broadly consistent with achieving efficient flight. Wing sweep alone, with minimal area change, allows wings to operate at high lift-to-drag ratios over a wide range of speeds . When chThe morphing described above can be broadly categorized as rigid-body rotations of a lifting surface, and changes in its shape. Wing sweep and tail pitch describe rotations, while tail spread, wing area or wing camber describe changes in shape. The latter can be further refined into changes within the plane of the lifting surface, such as area, or out of the plane, such as camber. As bird wings are highly coupled by passive mechanisms constraining the elbow, wrist and flight feathers to move in unison, shape change will generally be small and multi-dimensional, and result in a smooth aerofoil –15 as opHere, we seek to understand how birds morph their wing and tail configuration over a range of self-selected gliding speeds, while also maintaining approximate weight support and moment balance. We use this conceptual framework for morphing to assess better the contributions of aeroelastic deflection of the feathers, planform shape change by the forelimb muscles, and articulation between the body and wings or tail; such parameters are critical for minimizing drag, changing the forces and moments produced by wings, and modifying stability ,17–19.Tyto alba, a tawny owl, Strix aluco, and a goshawk, Accipiter gentilis. The gliding flights occurred indoors in quiescent air. We describe only steady glides and within each glide, a single instance in time, for 13–15 glides for each bird. We measured wing shape and posture using photogrammetric methods , tawny owl  and goshawk (A. gentilis) were captive-bred and trained to fly between handlers on command and they received a food reward after each flight. The birds weighed 333 ± 7 g, 366 ± 2 g and 966 ± 2 g, respectively .The barn owl (. 2.2a). In each flight, the birds flapped to build speed before entering a smooth glide, during which the measurements were taken. They subsequently entered a deceleration phase and finally perched 3–5 m beyond the measurement region. We only report on ‘steady’ glides where wing movements relative to the body could not be readily perceived in the reconstructions.Flight measurements were conducted in a 17 m-long indoor flight corridor at the Royal Veterinary College . The corridor was 2 m wide, bounded by a structural wall on one side and framed mesh on the other, with a suspended floor to elevate the flight path of the bird and permit camera views from above and below a. In eac−1, arranged in upper and lower sets  intrinsic calibration; (ii) individual extrinsic calibration of upper and lower cameras sets and (iii) alignment of both sets' coordinate systems to the corridor reference frame. (i) The intrinsic properties of each camera–lens pair, including optical distortion, were calculated from 50 to 100 images of a flat, 1.2 × 0.7 m checkerboard that filled the field of view of each camera. To fill the view and achieve a sharp image, we increased sharpness over a larger depth of field by further closing the aperture; changing aperture has a negligible effect on the pin-hole calibration model. (ii) The extrinsic parameters of each camera set—position, orientation and scale—were calculated from images of a visually textured board with corner markers at known distances from each other to define scale. (iii) As the pattern on the board could only be seen from a single set of cameras at once, we aligned the upper and lower sets of cameras using a T-shaped wand with spherical reference points. Finally, a coordinate system was defined using an L-shaped wand whose axes pointed along and across the flight corridor, in the plane normal to gravity.. 2.4Reconstruction error has two sources: camera calibration and point matching. To estimate camera calibration error, we compared our reconstruction of a fibreglass bird model to a high-accuracy laser scan of the model . Model wingspan was 1.3 m, slightly greater than the goshawk's wingspan of approximately 1.1 m. The point cloud surfaces were generated with the model placed within the measurement volume at glide height. Point matching is dependent upon each object's visual features or visual ‘texture'. For the model, visual texture was added using a marker to make small dots of varying size, which enhanced effective point matching.. 2.5Three-dimensional surface points of the birds were reconstructed using commercial photogrammetry software  and custom Python scripting. To accelerate processing, this was conducted using the Bluecrystal Phase 3 high-power computing facility at the University of Bristol. First, common image features were identified and matched between multiple views, providing an initial sparse reconstruction when combined with camera calibrations. The sparse reconstruction served as a foundation for disparity-map calculations between camera pairs. The detailed three-dimensional point cloud was then reconstructed from the disparity maps and camera calibrations. Each cloud point was assigned a greyscale value, based on the matched image pixels from which it was obtained.. 2.6We wrote custom graphical user interfaces in order to remove spurious points from the point cloud and identify whether the point belonged to the wing, tail or ‘body' . We tracked the movement of each segment using an ‘iterative-closest-point' algorithm in MATLAB , which estimated the rigid-body transform, consisting of rotations and translations, that minimized the distance between two different point clouds of the same segment. For further details, see electronic supplementary material.. 2.7T. alba, S. Aluco and A. gentilis, respectively, once we removed glides with observable unsteadiness. As the birds glided steadily, we selected a single instance in time, in the centre of the measurement volume, to describe the properties of the glide. To compute time derivatives, we aligned the body and wings for a 50 ms window centred about the measurement instant and fitted a second-order polynomial to the data.We described 15, 14 and 13 glides for . 2.8We deconstructed our alignment transforms into Euler angles and global translations. The order of rotations used to decompose the rotation matrices differed for the body and wings but were fundamentally similar. We calculated the rotations about the body in the order of yaw, pitch and then roll. Then, because long-axis rotation of the body—roll—is similar to long-axis rotation of the wing—pitch—we adjusted the rotation order for the wings to be sweep, elevation angle/dihedral and then pitch. This adjustment makes the axes order the same, if the long axes for the reference postures of the wing and body are parallel.. 2.9a); rotations about each axis described roll, pitch up and yaw, respectively . We used the coordinate system to quantify the body's angle of attack using its pitch relative to the flow, the body's glide angle.We created a coordinate system for the body to describe its gross movement. The axes of the body ran from: the base of the tail to the head, the body out to the right and the body out downward a; rotatia); rotations about each axis describe wing elevation, pitch up and forward sweep. We defined the axis aligned with the wing chord based on the average flow orientation relative to the wings—and not based on wing morphology—this resulted in the average wing sweep equalling zero .After smoothing the chord profile, we processed the parameters of the wing chords by first computing the chord line, and then the mean line of the chord. We computed the chord line by identifying the leading edge as the point along the wing surface with greatest curvature occurring within the anterior half of the section. We then used a curvilinear-coordinate system to identify the mean line between the upper and lower surfaces, by using the proportional distance travelled along both surfaces from the leading edge to the trailing edge. From the chord line and mean line, we computed chord pitch, quarter-chord position, and the chordwise thickness and camber distribution.. 3T. alba, S. aluco and A. gentilis. To refrain from frequently repeating each species, when all three birds are described together, we will maintain this order, and only repeat the species names once for each section. We report mean ± s.e.m. unless stated otherwise, and we will repeat this once for each section.Throughout the results, we will quantify flight parameters and wing morphology metrics for . 3.1b). The average signed error was 0.022 ± 0.002 mm (mean ± s.e.m.).We estimated reconstruction error attributable to camera calibration by comparing a high-accuracy laser scan of a bird-shaped physical model (scan accuracy = 0.063 mm) to its point cloud reconstruction. The median absolute error was 0.6 mm; 72% of all points were within 1 mm from the laser scan, and 95% of all points were within 2.2 mm b. The av. 3.2T. alba, S. aluco and A. gentilis, respectively. The details we highlight focus on parameters consistent across the three birds. A more detailed description of the average morphology and configuration can be found in the electronic supplementary material.While our focus is on the changes in wing, body and tail morphing that occurred with changing flight speed, we begin by highlighting a few features of the average flight morphology for reference. The average was constructed from 15, 14 and 13 gliding flights for −1 (mean ± s.e.m.). Wing protraction, here, describes the forward translational movement of the quarter-chord points (b–d). At these speeds, the fitted line along the wingspan through these quarter-chord points was angled forward by 4.5 ± 0.2°, 7.9 ± 0.4° and 0.8 ± 0.2°, and the tail spread so its feathers covered an arc of 35.8 ± 2.7°, 51.2 ± 2.6° and 90.7 ± 5.9°; well above the minimum observed arcs of 20.7°, 30.8° and 38.9°.The configuration of the birds suggested that these flights were not near maximum speed, as the wings were protracted forward and the tails spread wide. The average flight speeds were 7.7 ± 0.1, 6.1 ± 0.1 and 7.3 ± 0.2 m sd points b–d. At tb).The wings and tail operated at steep angles to the relative flow produced by the glide. The bodies' angles of attack relative to the wind (coordinate system in figure 3b). However, the distal wing was less cambered than the proximal wing (figure 3c). The maximum wing camber across the entire wing was on average 7.0 ± 0.1, 9.4 ± 0.1 and 11.1 ± 0.1% of the chord length, and occurred proximal to the body at 33, 15 and 10% of wing length. Camber in the distal quarter of the wing was only 0.5–3.0% of the chord length.Across the wingspan, the mean chord pitch and peak camber changed inversely . Wing twfigure 3Other notable features were the interface between wing and body, wing anhedral, spanwise curvature and the absence of negative camber across the chords. The wing root intersected with the torso at the shoulder and formed a smooth dorsal surface . The pla. 3.3−1, in T. alba, S. aluco and A. gentilis, respectively. For each, their fastest speed was 23, 33 and 36% greater than their slowest speed. The speed range of T. alba was substantially extended by a single slower flight, and with that flight excluded the fastest speed was only 10% greater than the slowest speed.We describe the wing and tail morphing over the flight speed range of 6.6–8.1, 5.2–6.9 and 6.3–8.6 m s−1’, and the mean ± s.e.m. of the slope. Some of the analysed metrics are expected to scale linearly with the lift coefficient, and, therefore, might scale better with inverse dynamic pressure, but over the observed ranges of flight speeds, the differences in quality of fit between speed and inverse dynamic pressure were small and regressing against inverse dynamic pressure did not affect our conclusions. We treated each bird independently in the regressions against speed, as their differing morphology should result in different scaling relationships with speed.To determine changes with flight speed, we linearly regressed our measurements against speed. We report the slope of the linear relationship with flight speed as ‘units per m s. 3.3.1−1), −22.1 ± 5.9°/(m s−1) and −29.3 ± 4.7°/(m s−1) in T. alba, S. aluco and A. gentilis, respectively . While each of the three birds contracted their tail by relatively similar amounts with increased speed, the larger tail of A. gentilis resulted in a threefold greater proportional change in its ventrally projected area. The proportion of the area represented by the tail against that of the whole bird decreased by −1.3 ± 0.4%/(m s−1), −1.8 ± 0.5%/(m s−1) and −6.0 ± 0.7%/(m s−1) (a).The tail contracted significantly with increased speed in all three birds. The arc angle covered by the tail feathers contracted by −28.1 ± 11.2°/(m s/(m s−1) a.FigureS. aluco and A. gentilis. Relative to each bird's largest observed wingspan, wingspan decreased by −2.3 ± 1.0%/(m s−1) and −2.0 ± 0.7%/(m s−1), in S. aluco (p = 0.04) and A. gentilis (p = 0.02), respectively, and wingspan varied by 0.8 ± 1.1%/(m s−1) in T. alba (p = 0.48). With both wings and tail contracting, the ventrally projected area decreased with speed. Relative to each bird's largest observed area, area decreased by −3.5 ± 1.3%/(m s−1) and −7.0 ± 1.6%/(m s−1), in S. aluco (p = 0.02) and A. gentilis (p = 0.001), respectively, and area varied by −0.2 ± 1.4%/(m s−1) in T. alba (p = 0.91). The decrease in area was largely attributable to tail contraction: in T. alba, the tail was responsible for the overall decrease in projected area with increased speed, as planform area excluding the tail slightly increased; and in S. aluco and A. gentilis, the tail was responsible for 52% and 77% of the decrease in area with increased speed, respectively.With increased speed, the wings also contracted in both . 3.3.2a); the linear relationships with speed were: 0.5 ± 0.8°/(m s−1), 1.1 ± 0.7°/(m s−1) and −3.6 ± 1.9°/(m s−1)  for T. alba, S. aluco and A. gentilis, respectively.When speed is varied, birds must compensate to maintain support for body weight. As area changes relatively little, either the glide angle must change dramatically or angle of attack must change inversely with speed in the whole bird, or its body, wings or tail. Change in the glide angle with increased speed was not statistically different from zero for any bird a; the lib,d) in T. alba (p = 9 × 10−6), S. aluco (p = 0.001) and A. gentilis (p = 4 × 10−6). While the body's angle of attack decreased with speed significantly only in S. aluco by −3.6 ± 0.7°/(m s−1) (p = 3 × 10−4) and varied by −0.6 ± 0.7°/(m s−1) and −2.5 ± 1.6°/(m s−1) in T. alba (p = 0.38) and A. gentilis, respectively (p = 0.16), the tail's angle of attack decreased significantly with speed in all three birds, decreasing by −5.6 ± 1.5°/(m s−1), −9.1 ± 2.5°/(m s−1) and −13.3 ± 2.3° (m s−1) .The pitch of the tail changed with flight speed and not solely because of changes in the angle of attack of the body. If the whole bird's angle of attack changed, the angle-of-attack relationships with speed for the body, wings and tail would be equal. Instead, the tail's angle of attack decreased significantly more with speed than that of the body b,d in T.p = 0.36, 0.91 and 0.38). The wings' angles of attack decreased significantly with speed by −2.5 ± 0.8°/(m s−1) and −3.0 ± 1.0°/(m s−1), in S. aluco (p = 0.02) and A. gentilis (p = 0.01), respectively; and varied by −1.3 ± 0.7°/(m s−1) in T. alba (p = 0.11).By contrast, the relationships between the plane of the wing's angle of attack and speed were not significantly different from the bodies' relationships in any bird . This was not the case with the wing, which compensated for deviations from the body's expected angle of attack. Wing-angle-of-attack residuals scaled by 0.11 ± 0.12° for every degree of body deviation, significantly different from one to one scaling , the shallow slope indicating substantial wing pitch compensation at the shoulder.If the wing and body can maintain a constant angle of attack relationship with speed, then shoulder pitch actuation is unnecessary for modulating angle of attack at different speeds; however, an important role for shoulder actuation may be to compensate for the body when it is pitched improperly for a given flight speed. Without compensation, deviations in the body's angle of attack from its predicted linear relationships with speed  would lead to similar deviations for the wing and tail. Indeed, for the tail, when the residuals across all three birds were combined, tail-angle-of-attack residuals scaled by 1.10 ± 0.26° for every degree of body deviation, a relationship not significantly different from 1 to 1   and varied by 4.0 ± 2.8°/(m s−1) and 2.0 ± 1.1°/(m s−1) in T. alba (p = 0.18) and A. gentilis (p = 0.08), respectively (a). The wings swept backwards with speed significantly only in A. gentilis by −4.6 ± 0.7°/(m s−1) (p = 5 × 10−5) and varied by −0.3 ± 1.4°/(m s−1) and −1.0 ± 0.8°/(m s−1) in T. alba (p = 0.84) and S. aluco (p = 0.23), respectively (b). The consistency in wing-sweep posture of the two owls was also evident from the projections of the whole bird onto a ventral plane , significantly only in ectively a. The wiectively b. The coal plane .Figure . 3.3.4T. alba, the planforms changed in a manner consistent with the second digit actuating and abducting the 10th primary feather anteriorly [a); extension of the distal leading edge in T. alba did not exhibit a relationship with speed (p = 0.82).The wings maintained a similarly sized and shaped planform across all speeds, once aligned to a common coordinate system. The region of the planform with greatest change was the distal portion of the wing . In T. ateriorly , extendi. 3.3.5S. aluco and A. gentilis twisted significantly with increased speed  across 24%, 36% and 49% of the planform area in T. alba, S. aluco and A. gentilis, respectively. If we only examine wing regions with at least moderate coefficients of determination (r2 > 0.25), then camber decreased by more than −0.5% chord/(m s−1) across 64, 75 and 78% of the remaining planform. The small regions where wing camber increased were generally at the tips of the distal feathers, and, in S. aluco, near the wrist ; we excluded changes in thickness . Among all three birds, we observed four consistent regions. Two regions depressed and two regions rose in height . These four regions form a saddle pattern across the wing, with one axis along the wing depressing (labels 2 and 4) and the perpendicular axis rising (labels 1 and 3). Each of these wing domains exhibited relatively high coefficients of determination when regressed against speed (r2); although coefficients of determination were generally low across the whole wing in T. alba.All three birds exhibited similar patterns of out-of-plane wing movement with increased speed . Out-of-n height b,c. Thes. 3.4T. alba and A. gentilis  were consistent with drag minimization [We established the detailed in-flight wing morphology of three gliding raptors. We observed consistent patterns with speed in angle of attack, wing posture, wing and tail planform, and out-of-plane changes in the wing. With these details, we can better approach avian gliding flight integratively and comprehensively. Among our findings, we highlight how (i) the shoulder allows the wings to maintain a consistent angle of attack relationship with speed figures  and 8, a6mization ; (iii) r. 4.1c and 8b). The shoulder, therefore, either compensated for the body's deviations in pitch, or allowed the aerofoil of the body [The shoulder decouples wing pitch from body pitch, but pitch actuation may be relatively simple. Unlike the wing with its many linkages that impose and facilitate coordinated movement , the bod7the body  to modul. 4.2a) and its angle of attack (d), consistent with drag minimization [T. alba geometry with artificial manipulation of the tail demonstrated that slower flight required both greater tail pitch and tail spread to adopt the minimum drag configuration while providing body weight support, which is consistent with our observations of all three birds [With decreased speed, all three birds increased both the size of the tail a and itsf attack d, consismization . If weigmization . When moee birds .. 4.3b) as has been observed in other birds [T. alba, S. aluco and A. gentilis, but accounted for 24%, 39%, and 72% of the contraction in area.In-plane morphing of the wing was relatively subtle compared to that of the tail. The wing planforms varied among the flights , but aftfigure 6er birds ,4,23, bu. 4.4b).In studies of camber-morphing wings, increased camber is consistently beneficial at low speeds or high angles of attack, but, as speed increases and the lift coefficient requirement reduces, camber should decrease for efficient flight ,24,25. Afigure 7Aeroelasticity can modulate the wing camber of flexible aerofoils through changes in the pressure difference between the upper and lower wing surfaces. Increased pressure differential increases the deflection of the trailing edge and reduces camber . A changT. alba, whose tail is smallest proportionally, the differential pressure between the upper and lower tail surfaces accounts for only 3% of body weight, however, decreasing tail pitch by merely 5° decreases total aerodynamic force generation by 5%, more than what is supported solely by the tail [a).The effect of tail morphing is to predominantly change the effectiveness of the body as an aerofoil . For exathe tail . In othea), decreasing its lift production [T. alba geometry suggest that the change in total lift with increased speed would have decreased by approximately 10% from tail action (spread: −28°/(m s−1); pitch: −5°/(m s−1)) [−1) for each bird). This would suggest that tail action improves flight efficiency both by actively and directly modifying the geometry of the bird, and by passively and indirectly influencing wing camber through changing the pressure distribution acting on the wings .The geometries provided will help to address questions of raptor flight at and around the observed speeds. Morphing the geometries and examining their aerodynamic performance will elucidate whether the morphology supports efficiency, maximal loading, stability or may be a comprised design borne of evolutionary trade-offs with other requirements. Simulation of unloaded wings suggests optimization for maximal loading , but whe. 5We presented accurate and detailed reconstructions of the body, wing and tail morphology during gliding flight. The three birds shared common spanwise patterns of wing twist, an inverse relationship between twist and peak camber, and held their wings depressed below their shoulder in an anhedral configuration. Shoulder elevation and sweep controlled much of the planform, and after aligning the wing to a common coordinate system, the wing's in-plane configuration was remarkably similar. Shoulder pitch was critical to maintaining control over the wing's angle of attack.Tail morphing supports minimizing drag, both by modulating aerodynamic performance and, we postulate, through actively manipulating the aeroelastic behaviour of the wing. The tail pitched up and contracted with increased speed, matching the predicted behaviour from computational studies. Further, the same tail movements also likely increased loading on the wings, changing wing camber through aeroelastic deflection. The birds reduced camber with increased speed, which is the expected pattern based on studies of efficient flight with variable-camber wings. This would suggest that through solely tail control, birds control multiple portions of their morphology through coupling and reduce the need for actuators in their wing.T. alba and A. gentilis should provide a strong foundation and powerful initial tool to accelerate our understanding of avian wing morphology and morphing, as a reference for bioinspired engineering.We have described an array of aerodynamic traits that as a whole form a complex and dynamic solution for flight. Further, unlike traditional fixed-wing aircraft, these traits change with speed, all of which will require substantial analytical studies. Our provided geometries of


Qingshu 168’) growth, photosynthesis, yield, water use efficiency, and quality were examined from 2017 to 2019 in cold and arid northwestern China. In the four stages of potato growth , eight treatments were designed, with a mild deficit was in treatments WD1 (seedling), WD2 (tuber initiation), WD3 (tuber bulking), and WD4 (starch accumulation); and a moderate deficit in WD5 (seedling), WD6 (tuber initiation), WD7 (tuber bulking), and WD8 (starch accumulation). The net photosynthetic rate, stomatal conductance, and transpiration rate decreased significantly under water deficit in the tuber formation and starch accumulation stages. Although water deficit reduced potato yields, a mild deficit in the seedling stage resulted in the highest yield and water use efficiency at 43,961.91 kg ha−1 and 8.67 kg m−3, respectively. The highest overall quality was in potatoes subjected to mild and moderate water deficit in the seedling stage. Principal component analysis identified mild water stress in the seedling stage as the optimum regulated deficit irrigation regime. The results of this study provide theoretical and technical references for efficient water-saving cultivation and industrialization of potato in northwestern China.The effects of the amount and timing of regulated deficit drip irrigation under plastic film on potato (‘ Solanum tuberosum L. is also known as the white or Irish potato and is rich in nutrients and starch. It is a popular food with the reputation of being a “lost treasure”, with medicinal and health care properties that include neutralizing the stomach, tonifying the spleen and qi, detoxifying, and relieving inflammation. Moreover, potato is the world’s fourth largest food crop after wheat, rice and corn1. The United Nations declared 2008 as the International Year of the Potato, which further demonstrated the status of the potato as the world’s number one non-cereal food in global food security. As of 2018, the world's potato planting area and total output were 1.8 × 107 hm2 and 3.7 × 108 t, respectively, while China's potato planting area and total output accounted for 27% and 24% of the world's total, respectively, ranking first in the world2. In recent years in the Hexi Corridor Oasis Irrigation Area in the Hexi Oasis, potato has been a popular crop because of its strong adaptability, simple cultivation, suitability for storage, ease of transportation, and long supply period. However, with scaled-up cultivation, irrigation systems that use water inefficiently have led to a continuous increase in demand for irrigation water. Therefore, the design of irrigation systems that increase irrigation water use efficiency is an important approach to optimize water use. Regulated deficit irrigation is an advanced irrigation technology that was first proposed and practically implemented by the Australian Sustainable Irrigation Agricultural Research Institute when studying methods to improve the productivity of densely planted orchards (mainly those with peach trees) in the 1970s3. With this technology, a crop experiences a regulated water deficit at different amounts according to the characteristics of water consumption for that crop, thereby saving water and increasing water use efficiency. Regulated deficit irrigation has been widely applied, including with corn5, tomatoes6, wheat7, onions9, Isatis tinctoria11, grapes13, persimmons14, cherries16, garlic17, watermelons18, and peppers19. The technology is effective at increasing yields and water conservation. In potato, Xue et al.20 studied the effects of regulated deficit irrigation with film in different growth stages on yield and water use efficiency in a desert oasis. They found that the highest indices of potato water sensitivity were in the starch accumulation stage, followed the tuber enlargement stage, with lower indices in the seedling and tuber formation stages. Thus, regulated deficit irrigation increased water use efficiency at the seedling and tuber formation stages while stabilizing yield. By comparison, the decrease in output caused by regulated deficit irrigation was from 28.30 to 44.32% in the starch accumulation stage and from 20.13 to 27.92% in the tuber enlargement stage. Martínez-Romero et al.21 found that a timely and moderate irrigation quota deficit improved potato yield, potato commodity rate, and water use efficiency in an experiment with regulated deficit irrigation in Basque, Spain. In addition, Zhang and Li22, Li et al.23, and Du et al.24 further developed the technology of regulated deficit drip irrigation under film for potato in arid areas by examining water use, growth, yield, and quality.Various modifications of regulated deficit drip irrigation under film for potato in arid inland oases have been proposed in previous studies, which are highly instructive for the development of potato cultivation and water conservation. Current research primarily focuses on the effects of regulated deficit drip irrigation under film on potato yield and water use efficiency. However, less attention is paid to the effects on photosynthesis in potatoes, and reports on the effects on potato quality are rare. Soil and climatic conditions in different regions can affect the application of irrigation and cultivation technologies. Therefore, research to improve the cultivation system of regulated deficit drip irrigation under film in arid oasis areas is a long-term task. In this study, in the light loam soil of the Hexi Oasis, the effects of regulated deficit drip irrigation under film on potato growth, photosynthetic properties, quality, output, and water use efficiency were examined in a field experiment. The aim of this work was to study the sensitivity of each phenological stage of potato to different degrees of water deficit, for the application of regulated deficit irrigation strategies. The research results provide a theoretical basis for the establishment of a drought-resistant (water-saving) potato planting technology system.P > 0.05). In the moderate deficit treatments WD6 and WD7, plant height decreased significantly (P < 0.05). Stem diameter decreased in all treatments to various degrees but the smallest decrease was in WD1 and WD5 with the water deficit in the seedling stage. Compared with that in CK, the diameter decreased by 3.37% in WD1 and by 5.62% in WD5. However, when the deficit occurred in the tuber initiation and tuber bulking stages, the diameter decreased by 3.93–8.99% and by 6.74–10.64%, respectively, indicating that a water deficit in those two stages reduced potato stem growth.Irrigation with different levels of regulated deficit in different growth stages significantly affected the biological characteristics of potato Table . CompareCompared with CK, all treatments caused the leaf area index to decrease to varying degrees, ranging from 4.14 to 22.07%. The greatest decreases in leaf area index were in WD6 and WD8, with significant decreases of 11.72% and 22.07%, respectively. The leaf area index was least affected in WD5, with a decrease of only 4.14%. This result showed that mild water deficit at the seedling stage did not significantly affect leaf growth. By contrast, water deficit in the other stages hindered leaf growth. Both the longitudinal and transverse lengths of the potato tubers decreased, to different degrees. The greatest effect was in WD8, with significant decreases ranging from 11.51 to 14.28%. In WD1, WD2, WD5, and WD6, the decreases in both diameters were slight and not significant.−2 s−1 in WD2 (mild deficit) and to 0.337 μmol m−2 s−1 in WD6 (moderate deficit), decreases of 19.28% (WD2) and 33.70% (WD6) compared with that in CK. The Pn was not significantly affected in the other treatments in this stage.The net photosynthetic rate (Pn) of potato leaf from seedling to starch accumulation stage increased first and then decreased, showing a single-peak in CK and all treatments Fig. . Mild re−2 s−1. In the starch accumulation stage, the absolute value of the Pn was lower than that at tuber initiation and expansion stages, with a mean value between 0.227 and 0.348 μmol m−2 s−1. However, the Pn was significantly higher than that in the seedling stage. The Pn decreased by 15.12% in WD4 (mild deficit) and by 33.46% in WD8 (moderate deficit), compared with that in CK, indicating that a regulated deficit at the starch accumulation stage negatively affected the net photosynthetic rate.In the tuber bulking stage, the Pn decreased by 8.31% in WD3 (mild deficit) and by 29.37% in WD7 (moderate deficit), compared with that in CK. The compensation effect in WD2 after rehydration was greater than that in WD6, but neither rate was significantly different from that in CK. The Pn did not decrease from the tuber initiation stage to the tuber expansion stage, and the mean value in the bulking stage was between 0.323 and 0.463 μmol m−2 s−1. In WD1 (mild deficit) and WD5 (moderate deficit), Gs decreased significantly by 7.29% and 11.09%, respectively, compared with that in CK. The Gs in the seedling stage was not affected in the other treatments. The Gs increased in the tuber initiation stage in all treatments except WD2 and WD6, with values increasing to between 12.68 and 14.70 mol m−2 s−1. The Gs in WD2 decreased by 13.70% and that in WD6 decreased by 14.83%. In the tuber bulking stage, Gs increased to the highest levels of the entire growth period, ranging from 14.73 to 17.00 mmol m−2 s−1, although it was lower in regulated deficit treatments than in CK. Compared with that in CK, the Gs decreased significantly in WD3 by 8.96% and in WD7 by 13.34%, which showed that regulated deficit in the tuber initiation and expansion stages did not favor stomatal opening. The Gs decreased significantly from the tuber bulking stage to the starch accumulation stage. With sufficient irrigation in this period, Gs was not significantly different from that in CK, whereas in WD4 (mild deficit) and WD8 (moderate deficit), it decreased significantly by 17.22% and 25.05%, respectively. This result demonstrated that regulated deficit during starch accumulation affected stomatal conductance.Throughout the growth period, the stomatal conductance (Gs) increased successively from the seedling stage to the tuber initiation stage and then tuber bulking stage; however, the Gs decreased at the starch accumulation stage. There were differences in the range of decrease among the treatments Fig. . The low−1 s−1 in WD2 (mild deficit) and 4.84 μmol mol−1 s−1 in WD6 (moderate deficit), decreasing by 10.68% in WD2 and by 20.63% in WD6 compared with that in CK.In all treatments, the transpiration rate (Tr) first increased as growth progressed and then decreased, with a peak at the tuber expansion stage Fig. . In the −1 s−1 in WD4 (mild deficit) and 4.53 μmol mol−1 s−1 in WD8 (moderate deficit), decreasing by 15.58% in WD4 and by 16.64% in WD8 compared with that in CK, although the decreases were not significant. After rehydration, the Tr in WD3 and WD7 decreased, but it was not significantly different from that in CK.In the tuber bulking stage, the Tr in WD1, WD2, WD5, and WD6 was not significantly different from that in CK after rehydration, showing evidence of a compensation effect. Compared with the tuber initiation stage, the Tr showed a large increase in all treatments. The Tr in WD7 (moderate deficit) decreased significantly by 10.28% compared with that in CK, whereas in WD3 (mild deficit), the Tr decreased by 5.25%, but it was not significantly different from that in CK. In the tuber initiation and tuber bulking stages, the Tr was higher than that in the seedling stage. In the starch accumulation stage, the Tr was 4.59 μmol mol3 ha−1 in CK, water consumption decreased to 4977 m3 ha−1 in WD3: 4952 m3 ha−1 in WD5: 4769 m3 ha−1 in WD6, and 4724 m3 ha−1 in WD8, which were decreases of 14.73% (WD3), 15.16% (WD5), 18.30% (WD6), and 19.08% (WD8) compared with that in CK. In WD2 (mild deficit) and WD7 (moderate deficit), the decrease was slight. The regulated deficit treatments caused decreases in potato yield to different degrees. The water deficit in the seedling stage in WD1 caused the smallest decrease in yield to 43,962 kg ha−1, a decrease of only 4.50% compared with that in CK. Water deficit in the tuber bulking stage in WD7 (moderate deficit) caused the greatest decrease in yield to 33,835 kg ha−1, a decrease of 26.50% compared with that in CK. The decreases in yield under moderate regulated deficit treatment were greater than those under mild treatment, indicating that the larger decrease in irrigation had a greater negative effect on potato yield. Affected by yield, the output values showed similar trends by treatment. Output value per cubic water was the lowest in WD7 (moderate deficit), decreasing by 15.56% compared with that in CK. By contrast, the values increased in the other treatments by 0.07–50.93%, compared with that in CK.Regulated deficit in all growth stages significantly affected water consumption, yield, water use efficiency, and irrigation water use efficiency Table . Water d−1, an increase of 0.77% compared with that in CK. The protein contents decreased by 4.46–32.46% in the other treatments. The greatest reductions compared with the protein content in CK were in WD3 (18.31%), WD7 (21.85%), and WD8 (32.46%). With the deficit in the seedling stage, the starch content reached 36.06% in WD1 (mild deficit), a 3.34% increase compared with that in CK. In the other mild deficit treatments, although the starch content decreased, it was not significantly different from that in CK. In the moderate deficit treatments, the starch content decreased significantly by 10.66% in WD6, by 20.41% in WD7, and by 27.55% in WD8. With the deficit in the seedling stage, vitamin C and calcium contents decreased significantly by 9.21% in WD1 (mild deficit), compared with the contents in CK. However, the vitamin C content increased in the other mild and moderate deficit treatments, with the values increasing by 11.55–55.35% compared with that in CK. In addition, the vitamin C content tended to increase with the delay in deficit treatment, and the greatest increase was in WD8, with the content increasing significantly by 55.35% compared with that in CK.Regulated deficit treatment had different effects on the characteristics of potato quality Table . Compare−3, an increase of 50.93% compared with that in CK. Water use efficiency was the highest in WD1 at 8.67 kg m−3, followed by WD5, WD4, and WD8, representing increases of 10.87% (WD1), 5.84% (WD5), 4.60% (WD4), and 4.99% (WD8) compared with that in CK. By contrast, WUE decreased by 6.39% in WD3 and by 12.92% in WD7 (6.81 kg m−3) compared with that in CK. The lowest IWUE was in WD7 at only 15.66 kg m−3, a decrease of 13.45% compared with that in CK. By contrast, IWUE increased in the other treatments by 2.52–30.13%. The highest IWUE was in WD5 at 23.54 kg m−3, followed by WD8 at 22.79 kg m−3, increases of 30.13% and 25.98%, respectively, compared with that in CK.With water deficit in the starch accumulation stage, water use efficiency increased most significantly in WD4 by 13.49 yuan mHexi Oasis  and moderate (WD7) regulated deficits in the tuber enlargement stage significantly decreased the output by 20.86% and 26.50%, respectively. Consistent with this study, Mustafa Ünlü et al.40, Hassan et al.41, Nagaz et al.42, and Im et al.43 also found that water deficit at the tuber enlargement stage reduces production by approximately 20% compared with that with a sufficient water supply. As tubers begin to divide and expand in the tuber enlargement stage, potatoes transition from the reproductive stage to the vegetative growth stage. Water deficit decreases potato transpiration and photosynthesis, and compensation and recovery with rehydration are difficult. As a result, yield is severely reduced, decreasing economic benefits. Compared with the output of potatoes in CK, the output a with mild regulated deficit in the seedling stage (WD1) decreased by only 4.50%, likely because root activity and absorption were low in the early growth stage. During the seedling stage, the water deficit likely promoted deep root penetration. With the irrigation deficit in the seedling stage, potato had a longer time to recover following the subsequent rehydration, and thus, water deficit had little effect on yield and economic benefits.In this study, regulated deficit irrigation decreased potato yield and output values to different extents, ranging from 4.50 to 26.50%, which reduced production benefits. Enciso et al.−3, which was a decrease of 12.92% compared with that in CK. The highest IWUE was in WD5, reaching 23.54 kg m−3, followed by that in WD8 (22.79 kg m−3), which increased by 30.13% and 25.98%, respectively, compared with that in CK. The lowest IWUE was in WD7 (15.66 kg m−3), which was a decrease of 13.45% compared with that in CK. The IWUE of the other treatments increased to different degrees, with increases ranging from 2.52 to 30.13%. Therefore, moderate water deficit at the seedling and starch accumulation stages helped to improve the WUE and IWUE of potato, consistent with the findings of Li et al.44 and Liuyang et al.45. However, an unreasonable water deficit can cause significant yield reduction and thus reduce output and benefits.The highest WUE was in WD1, followed by that in WD5, WD4, and WD8, which increased by 10.87% (WD1), 5.84% (WD5), 4.60% (WD4), and 4.99% (WD8) compared with that in CK. The lowest WUE was in WD7 at only 6.81 kg m48. In this study, a moderate regulated deficit increased protein, starch, vitamin C, potassium, and calcium contents in potato. Mild regulated deficit in the seedling stage increased starch and potassium contents without reducing total sugar content. By comparison, moderate regulated deficit increased protein, vitamin C, and calcium contents. Regulated deficit irrigation in the other growth stages did not lead to the accumulation of total sugar, protein, starch, and potassium. Guizani et al.49 found that water deficit in the seedling stage can improve potato quality, which is consistent with the conclusion in this study. However, Zhang50 found that a regulated deficit had no significant effect on starch content during potato growth stages. In contrast, the results of in this study showed that a regulated deficit significantly reduced potato starch content. The inconsistency between studies might be due to differences in factors such as soil type and potato variety. Because there are few comprehensive reports on how the amount of regulated deficit and the stages in which the deficit occurs affect potato yield and quality, additional experiments are needed to explore the effects of regulated deficit irrigation on yield and quality with different varieties and in different regions.While maintaining yield, timely and moderate water deficit can increase WUE and the quality of productsYimin Irrigation Experimental Station  of the Hongshui River Administrative Office, Minle County, Gansu Province, China, from March to September in 2017, 2018, and 2019. The area has a typical continental arid climate, with abundant sunshine and large differences between day and night temperatures, which are conditions conducive to photosynthesis, nutrient accumulation, and yield formation in crops. The average annual temperature is 6.0 °C. The thermal integral exceeding 0 °C is 3,500 °C day, whereas the thermal integral over 10 °C is 2985 °C day”. The average annual sunshine time is 3000 h, and the average frost-free period is 136 days. According to meteorological data from 2000 to 2018, the average annual rainfall in the area is 328 mm, and the evaporation is 1900 mm. Soil in the experimental site is light loam with medium fertility and a pH of 7.22. The field capacity of tilled soil is 24.0%, the wilting point of the soil is 8.2%, and the soil bulk density is 1.48 t/m3. The 0 to 20 cm of topsoil contained 12.8 g/kg organic matter, 63.5 mg/kg alkali-hydrolyzable nitrogen, 13.1 mg/kg available phosphorus, and 192.7 mg/kg available potassium. The salinization effect was mild because of the deep source of groundwater. The rainfall and temperature for the three potato seasons are shown in Fig. The experiment was conducted at the Qinghai Agricultural Science Research Institute of China Qinghai Agricultural Research Institute. In 2017, potatoes were sown on April 17 and harvested on September 27; in 2018, they were sown on April 11 and harvested on September 28; and in 2019, they were sown on April 14 and harvested on October 9. The row spacing was 40 cm, and the plant spacing was 20 cm  covered two rows of potatoes with a planting density of 77,000 plants/ha. Drip irrigation was applied under the film with the irrigation pipe placed between two rows. Each treatment and control were repeated three times, and 140 potato plants were sown in each test plot. Each section covered 33.6 m2 (7 m × 4.8 m). There were two levels of water deficit: mild with soil moisture at 55–65% of field capacity and moderate with soil moisture at 45–55% of field capacity. The soil moisture with conventional irrigation (CK) was 65–75% of field capacity. Each level of deficit was applied in each of four growth stages of potato: seedling, tuber initiation, tuber bulking, and starch accumulation stages. Thus, there were eight total treatments: WD1: mild, seedling; WD2: mild, tuber initiation; WD3: mild, tuber bulking; WD4: mild, starch accumulation; WD5: moderate, seedling; WD6: moderate, tuber initiation; WD7: tuber bulking; WD8: starch accumulation  at 400 kg/ha and western compound fertilizer  at 750 kg/ha were applied as base fertilizers one time at sowing.To ensure crop yield, the experimental section was tilled to 30 cm 10 days before sowing. Weeds were cleared manually. Diammonium phosphate  from 9:30 to 11:00 a.m. Photosynthetic indicators measured included net photosynthetic rate (Pn), stomatal conductance (Gs), and transpiration rate (Tr).After potatoes ripened, the potatoes in each section were harvested and measured. There were three plots in each experiment, and the average value of the three plots was taken for analysis in each experiment. In other words, the average value of three replicate plots was the output of each treatment. An electronic scale (accuracy to 0.01 g) was used to weigh the potatoes, and the yield was converted to kg/ha. In addition, 20 potato plants were harvested separately in each section, and the tubers were cut off and washed. The transverse and longitudinal diameters of the tubers were measured with vernier calipers that were accurate to 0.01 mm. The average value of each treatment was determined.50:3) and IWUE (kg/m3) are the water use efficiency and the irrigated water use efficiency, respectively, in all growth stages; Y (kg/ha) is the yield per unit area; ETa (m3/ha) is the actual water consumption per unit area in all growth stages; and I (m3/ha) is the irrigation amount per unit area in all growth stages.Water use efficiency (WUE) and irrigation water use efficiency (IWUE) were calculated using the following formulas51ρb(g/cm3)is the soil bulk density of the planned wet layer. H (cm) is the depth of the soil plan wet layer, βi is the target moisture content (field water holding capacity multiplied by the upper limit of the design target relative moisture content), and βj is the soil moisture content before irrigation.The experiment used PVC pipe water delivery and drip irrigation under the film to irrigate water. All gate valves and water meters were installed in each treatment area, and the corresponding irrigation volume was quantitatively controlled by the water meter. When the soil water content dropped to the lower limit of the design value, irrigation was should be carried out in time, and the required irrigation amount was calculated by the irrigation quota formula:52.In the four growth periods of potatoes, for each treatment plot, three uniformly growing potatoes, were randomly selected. All the leaves, were cut from each potato in order to measure the maximum length and maximum width of the leaves and calculate the area of all the leaves. The total leaf area of a single plant was derived from the sum of all leaf areas, the leaf area was corrected with a coefficient of 0.76, and the average leaf area was finally taken51The test mainly followed the traditional soil drilling and soil drying weighing method to determine the soil moisture in each treatment plot. According to previous research results, the root activity range of potato is mainly concentrated in the 0–40 cm of the soil layer. Therefore, the soil was sampled every 7 days during the whole growth period of the potato, and the sampled soil depth was 80 cm, which was divided into five parts: 0–10 cm, 10–20 cm, 20–40 cm, 40–60 cm, and 60–80 cm. The soil water content (SWC) is calculated as follows:53ETI–II (mm) is the water consumption in the potato stage; i is the serial number of the soil layer; n is the total number of soil layers; ri (g·cm−3) is the dry bulk density of the ith layer of soil; Hi (cm) is the thickness of the ith layer of soil; M (mm) is the amount of irrigation water during the growth period; P (mm) is the rainfall during the growth period; and K (mm) is the amount of groundwater replenishment in the growth period. The groundwater depth in the test area is greater than 20 m, so K = 0. D (mm) is the drainage volume within the stage, and there is no runoff drainage in the test area, so D = 0.Evapotranspiration was calculated using the water balance method:The Coomassie Brilliant Blue G-250 method was used to determine protein content, and anthrone colorimetry was used to determine total sugar content. The content of starch was determined by enzymatic hydrolysis, vitamin C by 2, 6-dichloroindophenol titration, potassium by the potassium tetraphenylborate gravimetric method, and calcium by the gravimetric titration method.Excel 2017 (Microsoft 365) was used to perform calculations, and Duncan’s multiple comparison method in SPASS 19.0 (Stanford University) software was used to determine significant differences between means. Origin 8.0 (Origin lab) was used prepare the diagrams of average values. All analyses were performed using 3-year  averages.Hexi Corridor Oasis Irrigation Area, due to low rainfall, high evaporation intensity, water shortage, serious irrigation water waste and other factors, the development of local agriculture has been severely restricted. To minimize these negative impacts, we tested a novel planting method: regulated deficit drip irrigation under film mulching. The experiment found that different levels of water deficit in different growth periods of potatoes will affect the growth and development of their potatoes, and the degree of impact will continue to increase as the growth period advances. The analysis showed that the best water regulation scheme was mild water stress in the seedling stage. However, there was no significant difference in plant water content among potato treatments after harvest, the values of the water status of the plant is 74.10–79.70%. Therefore, the relative water content in soil should be maintained between 55 and 65% in the seedling stage, whereas in the other growth stages, it should range from 65 to 75%. The irrigation method proposed in this study can simultaneously stabilize output and maintain good quality, which is significant for yield improvement, water conservation, quality adjustment, and industrialization of potatoes cultivated in the Hexi Corridor Oasis Irrigation Area.In the Supplementary Information.


Rose canina fruit represents a rich source of bioactive compounds such as minerals, phenolic compounds, vitamins, carotenoids, folate, and antioxidant activity that still needs to be further exploited. Thus, this study aimed to use wild Rosa canina fruit encapsulated powder with different biopolymers aiming to manufacture ready-to-eat products, such as corn extrudates. To achieve this goal, extrudate physicochemical characteristics, such as water content (xw), water activity (aw), water absorption index (WAI), water solubility index (WSI), swelling index (SWE), hygroscopicity (Hy), expansion index (SEI), bulk density (ρb), porosity (ε), textural, optical; nutritional; and functional analysis  were determined. Results highlighted that 4 and 8% addition of wild Rose canina fruit encapsulated powder could be successfully used in the corn extrudates, showing the positive influence on its nutritional and functional value. Strong positive Pearson correlations were identified between antioxidant capacity and total flavonoids, carotenoids, folates, and vitamin C of mixtures and extrudates Minerals increased their amount during the extrusion process, reaching the highest values at an addition of 8% rosehip encapsulated with pea protein biopolymer. Furthermore, from the biopolymers used in the present study, pea protein powder exhibited the highest protection on the analyzed bioactive compounds against the extrusion process.Wild  The market for ready-to-eat products is constantly developing in the context of the social habits of the modern consumer. Furthermore, because of their sensorial features such as taste, texture, palatability, and appearance, ready-to-eat products are attractive to consumers ,2.The most common technique of producing ready-to-eat foods is extrusion cooking, the process of pressing the powder mixture through a die with a specific shape, which causes the material . A wide Rosa canina L.) is a native shrub that belongs to the Rosaceae family and is widespread in northern Europe, Asia, Middle East, and North America. For centuries, the pseudo-fruits of Rosa canina (rose hips) are recognized as valuable food and medicine constituents due to their notable content of pro-health compounds [Wild rose , rutin (>99% HPLC), gallic acid (>99% HPLC), and Multi-elemental solutions of 1000 mg L−1 ICP Standard Certipur® were achieved from Merk, . All other chemicals were purchased from the same supplier. A Millipore Direct-Q UV system from Merck  was used to purified water.Acid ascorbic standard, carotene, and folic acid standards were purchased from Sigma-Aldrich  with a purity level ≥99.9%. HR. canina) fruits were manually harvested in Aldehuela  in September 2020. Maltodextrin (GLUCIDEX® 12) (MD), pea protein powder  (PP), and beta-cyclodextrin (KLEPTOSE®) (CD) were supplied by Roquette S.L. . Resistant maltodextrin (Fibersol-2®) (RMD) was purchased from ADM/Matsutani, LLC .Corn grits (CM) were supplied by Maicerías Españolas S.L. . Rosehip (Rose hips (1000 g) were washed with distilled water and homogenized in a Thermomix  for 1 min at 5200 rpm. Then, distilled water (1000 g) was added and newly re-homogenized for 5 min at 5200 rpm. The mixture was filtered using a sieve . Four different formulations were prepared by adding 10 g of MD, RMD, PP, or CD to 90 g of the filtered mixture. Moreover, a control sample (R) without biopolymers was prepared. The formulated rosehip and control purees were then freeze-dried. A puree layer (0.5 cm thickness) was placed in a standardized aluminum plate with the following dimensions: 15 cm diameter and 5 cm height. Consecutively, samples were stored at −45 °C  for 24 h before being dried in a Lioalfa-6 Lyophyliser  at 2600 Pa and −56.6 °C for 48 h. The freeze-dried samples were ground in a grinder  to obtain a free-flowing powder. Therefore, the powdered products obtained from rosehip were R (rosehip), MDR , RMDR , PPR (pea protein rosehip), and CDR (cyclodextrin rosehip).CM was mixed manually using a whisk, with two quantities  of obtained rosehip powders  to produce the extrusion mixtures . The extrudates were coded as follows: R4M—extrudate with 4% rosehip addition, MDR4M—extrudate with maltodextrin rosehip 4% addition, RMDR4M—extrudate with resistant maltodextrin 4% rosehip addition, PPR4M—extrudate with pea protein 4% rosehip addition, CDR4M—extrudate with cyclodextrin 4% rosehip addition, R8M—extrudate with 8% rosehip addition, MDR8M—extrudate with maltodextrin rosehip 8% addition, RMDR8M—extrudate with resistant maltodextrin 8% rosehip addition, PPR8M—extrudate with pea protein 4% rosehip addition and CDR8M—extrudate with cyclodextrin 8% rosehip addition).A single-screw laboratory extruder  was used for extrusion process. The total material extrusion amount was 200 g. The operating conditions were: 3:1 compression ratio; 18 rpm of dosing speed (3.4 kg/h); 150 rpm screw rotation; 25, 70, 170, and 175 °C of temperature in barrel sections and 3 mm of the nozzle. The calculated specific mechanical energy of the corn extrusion ranged from 950 to 1100 kJ/kg. The pressure measured on the extruder head ranged between 92 and 127 bar. Extrudates were cooled at ambient temperature and sealed in plastic bags for further analysis. The extrudates obtained were: R4E, MDR4E, RMDR4E, PPR4E, CDR4E, R8E, MDR8E, RMDR8E, PPR8E, and CDR8E.w) (g water/100 g sample) of mixtures and extruded was determined according to AOAC [w) of the extruded samples was measured by the AquaLab PRE LabFerrer equipment .Water content  and then their weight was measured [The diameter of samples was measured for each sample with an electronic Vernier caliper . The surface expansion index of the die (SEI) was calculated as the quotient between the square of the measured diameters and the square of the die diameter . ρb was measured . The pormeasured . WAI and WSI were determined by the method of Singh and Smith  and calc2SO4 saturated solution (81% relative humidity). Initially and after 7 days each sample was weighed and the Hy was expressed as g of water gained per 100 g dry solids [Samples were placed in a petri dish at 25 °C, in an airtight plastic container containing Nap), the average specific force of structural ruptures (Fs), the spatial frequency of structural ruptures (Nsr), and crispness work (Wc), and the number of peaks (No) were obtained from the force–time curve of puncture test [The average puncturing force  were calculated for the control sample. To evaluate the color changes of the mixtures because of extrusion, the total color difference (ΔE2) was calculated between each mixture and extruded at the same encapsulated rosehip powder addition. Both translucency  and CIE*a et al. , consideg for 10 min) with a centrifuge Eppendorf 5804 . Afterward, samples were filtered through a 0.45 µm nylon filter  and injected into the HPLC system, according to our previous work, Igual et al. [For the phenolic compounds, a total amount of 0.5 g of each sample was homogenized with 2 mL of methanol and 1% HCl. The samples were mixed for 1 min with a vortex . Furthermore, the samples were sonicated for 30 min in an ultrasonic bath  and centrifugated (4000× v/v/v), sonicated, and centrifuged  using Eppendorf 5804 centrifuge . After, a separation funnel was used for the supernatant collection. To obtain the sample’s complete discoloration, the pellet was re-extracted three more times, following the same procedure. Sodium chloride solution (15%) was used to wash the collected extracts; then the organic phase was dried, and the solvent was eliminated by using an evaporator .Ultrasound-assisted extraction for carotenoids was made according to Szabo et al. . Shortly3PO4 and 8% acetic acid in an aqueous solution, sonicated for 30 min at 20 °C (Elmasonic E15H) and centrifugated at 4000× g, 10 min, 4 °C (Eppendorf). Afterward, after filtration, 20 μL of each sample was injected into an HPLC system, according to our previous work [Ascorbic (AA) and dehydroascorbic (DHA) acids were analyzed by using ultrasound-assisted extraction. Shortly, 0.5 g of sample was mixed with 3 mL of 3% Hg, for 10 min and 24 °C, filtered, and injected in the HPLC system, according to Igual et al. [For the folate extraction, 1 g of sample was mixed with 5 mL phosphate buffer (pH = 7), sonicated in the ultrasonic bath for 30 min, centrifuged at 4000× v/v) and (B) acetonitrile acidified by acetic acid 0.1%  with the flow rate was 0.5 mL/min, following the elution program described by Dulf et al. [m/z. The method described in our previous work Igual et al.  was usedf et al. . The ESIWavelengths of λ = 254, 280, and 340 nm were used for recording the chromatograms, and data acquisition was registered with the Agilent ChemStation software . The phenolics identification was based on UV-visible spectra, time retention, mass spectra, and chromatography with authentic standards (when available). 2 = 0.9981) with a concentration ranged between 10–100 μg/mL and expressed as equivalents of rutin (µg rutin/gdry weight), hydroxybenzoic acid was quantified using the calibration curve performed with gallic acid  on the concentration range of 1–100 μg/mL and expressed as gallic acid equivalents , and hydroxycinnamic acids  were quantified on the chlorogenic acid calibration curve  with a minimum and maximum concentration of 10 to 50 μg/mL chlorogenic acid and expressed as chlorogenic equivalents (µg chlorogenic acid/gdry weight). All the analyses were made in triplicate and are presented as means ± standard deviations. The samples limit of quantification (LOQ) was 1 μg/mL and the limit of detection (LOD) was 0.125 μg/mL.The quantification of flavonoids (flavones and isoflavones) was realized based on the rutin standard calibration curve  with 0.25% triethylamine (A) and ethyl acetate with 0.25% triethylamine (B) with the elution program detailed described by Szabo et al. [2 = 0.9931), with a minimum and a maximum concentration of 1 µg/mL and 25 µg/mL, respectively. The analysis was carried out in triplicate and presented as means ± standard deviations.An Agilent 1200 HPLC system coupled to a diode array detector , was used for the identification of carotenoids, as described by Szabo et al. . Reverseo et al. . The flov/v) (A) and 1% formic acid in acetonitrile (B); the flow rate was 0.5 mL/min at a temperature of 25 ± 0.5 °C. A scanning range of 100–600 m/z in the ESI (+) mode was performed for the MS fragmentation and the capillary voltage was set at 3000 V, temperature 300 °C, with a nitrogen flow of 7 L/min. The spectral absorbance values were registered in the range 200–400 nm and the chromatograms were recorded at λ 240 nm. To acquire and analyze the samples, an Agilent ChemStation software  was used. Acid ascorbic standard was used for identification and quantification . All samples were analyzed in triplicate and expressed as means ± standard deviations.Ascorbic and dehydroascorbic acids were performed on an HPLC-DAD-ESI-MS system, composed of an Agilent 1200 HPLC equipped with a quaternary pump, autosampler, DAD detector, coupled to an MS-detector single-quadrupole Agilent 6110 . The compounds separation was made on an XDB C18 Eclipse column  with the following binary gradients: 1% formic acid:acetonitrile (95:5) in distilled water (v/v) in the isocratic system, a flow rate of 0.5 mL/min, and temperature of 25 ± 0.5 °C. A scanning range of 120–600 m/z in the ESI (+) mode was applied for the MS fragmentation and the following parameters were set for the capillary voltage: 3000 V, temperature 350 °C, and nitrogen flow at 7 L/min. Chromatograms were registered at wavelength λ = 280 nm and data acquisition was done by using Agilent ChemStation software (Rev B.04.02 SP1) as described in our previous work [2 = 0.9945) with a minimum and maximum concentration of 1 µg/mL to 30 µg/mL was used. All the samples were analyzed in triplicate and the results were expressed as means ± standard deviations.The same HPLC-DAD-ESI-MS system described above was used for the folate determination. Briefly, the separation was performed on the XDB C18 Eclipse column  with a mobile phase with acetonitrile:acetic acid 1% at a ratio of 20:80  following Agudelo et al.  methodol3 65% and 3 mL H2O2, and mineralized in a Berghof MWS-2 , following the program parameters described by Mihăiescu et al. [Sample mineralization was conducted according to Mihăiescu et al. . Brieflyu et al. . After, u et al.  the indu®  were used.For analysis, s spectrometer Optima 5300DV , with a dual viewing inductively coupled plasma optical emission coupled with CETAC 6000AT+  ultrasonic nebulizer. The following parameters were used: 1300 W RF power, 15 L/min plasma flow, 2.0 L/min auxiliary flow, 0.8 L/min nebulizer flow, and the sample uptake rate was 1.5 mL/min. The delay time for washing between each sample and signal measurement was 180 s and high-purity argon was used to sustain plasma as a carrier gas. For calibration, multi-elemental solutions of 1000 mg/L ICP Standard Certipurp < 0.05). The differences between means were evaluated through the Fisher test. Using Statgraphics Centurion XVII software  a high correlation analysis with a 95% significance level was applied between the extrusion parameters and textual characteristics of extrudates. Pearson correlation was used to better explain the relationship between antioxidant activity and other bioactive compounds. All samples were analyzed in triplicate and the final results were reported as means ± standard deviations.To evaluate the data analysis of mixtures and extrudates, an ANOVA (Statgraphics Centurion XVII software) test with a confidence level of 95% was used, . When some of the rosehip powdered product was added xw, aw, and ρb decreased significantly (p < 0.05), therefore, there are more hygroscopic and more easily soluble. The control sample presented 5.62 (0.05) gw/100 g, like other studies of corn extrudates [w/100 g. Extrusion moisture loss in the control was 10%, like other studies [w were similar to the other corn snacks obtained by García-Segovia et al. and Uribe-Wandurraga et al. [w values were obtained in PPR4E and CDR4E.Mean values of xtrudates ,30 and t studies  it seemsa et al. ,23. The p < 0.05). Furthermore, according to the soluble nature of these biopolymers, extrudates with MD, RMD, and CD presented water solubilized components that make them vulnerable to molecular damage. Samples with PP or without biopolymers presented WSI values lower than the other extruded samples. Thus, R4E, R8E, PPR4E, and PPR8E could be more stable samples. SWE mean values expressed as mLswollen/gdry solid are also shown in p < 0.05), probably for the hydration of the protein structure. However, extrudates with CD in the formulation presented the lowest values; the control SWE was like other studies [WAI and WSI properties exhibit the interaction of extrudates with water. . WAI sho studies ,30. Addip < 0.05). Other studies have reported the same link between these parameters [Typical extrudate structures are due to the sudden expansion—at the exit—of the molten mass from the restricted die, from high pressure to atmospheric pressure . Adding rameters ,30. Highb and ε of extrudates. Density is defined as a general extrudate property, that could indicate changes in material parameters such as cell structure, pores, and voids developed during the extrusion process; a porous structure is characterized by highly expanded extruded materials [p < 0.05) differences in ρb values between control and enriched samples, with the values of the control ρb being higher. ρb was related to xw by significant Pearson correlation  as also shown by García-Segovia et al. [p < 0.05). ρb and ε values of the control sample were like other corn extrudates [Finally, aterials . This poa et al. . ε valuetrudates ,30.c is described as the force applied on the first bite to break the sample [Texture characteristics are included in e sample  and coule sample .p and Fs of extruded products. Hardness is defined as the necessary force to compress a solid substance between the molar teeth [sr describes the number of fracture events during puncture [0 corresponds to the number of fractures throughout the test [c values except to RMDR4E. The significantly lowest Wc value was found in R8E. Samples with rosehip powders required less force in the first bite to break the extrudate. All extrudates with rosehip powders showed lower Fp values than control and lower Fs values too, except to RMDR4E which presented similar Fs than control. N0 was significantly higher in extrudates with rosehip powders in comparison with control. Nsr and N0 are associated with the crunchiness of extruded snacks [sr and N0 could be influenced by the pore size, and furthermore, could be related to the interface fractures propagation, according to Chanvrier et al. [Hardness and chewing are usually associated with Far teeth . Nsr despuncture  and N0 cthe test . Adding d snacks ; in thisr et al. .c was positively correlated with xw  and Fp with xw and ρb presenting values of Pearson correlation of 0.7870 (p < 0.05) and 0.6315 (p < 0.05), respectively. Other works with corn snacks also detected a significant positive correlation between Fp and ρb [Correlation analysis was applied in order to better explain the relationship between texture parameters of extruded products and typical extrudate parameters; Wp and ρb .L*, a*, b*, C*, h*, ΔE1, and ΔE2). Both mixtures and extrudates with or without R did not show differences in the measurements taken on white and black backgrounds; therefore, they were not translucent and color coordinates CIE*L*a*b* and the values of chroma (C*) and tone (h*) were obtained directly from the equipment used for color measurement. This has also been observed in corn snacks previously [L* and h* parameters (p < 0.05) but a positive one regarding the a* value.Mixtures and extrudates optical properties are showed in eviously . In conteviously ,28 have p < 0.05) redder than CE. R8M showed the highest a* and the lowest L*. The lowest values of b* and C* were in PPR4M and the highest values were in RMDR8M. After extrusion, L*, a* b*, and C* decreased significantly (p < 0.05). R8E presented the significantly (p < 0.05) highest values of a*, b*, and C*; however, the lowest h* was for PPR8. Moreover, CDR8E showed the significantly (p < 0.05) lowest value of L*. These differences can be observed in All mixtures were redder by the addition of rosehip or encapsulated rosehip. Moreover, these extrudates were also significantly (1) ranged between 4.4 and 13.5, higher than 3 units; therefore, humanly perceptible [2 represents the total color difference between extrudates and mixtures. According to Dogan et al. [2 ranged between 26.6 and 37.1. These ΔE2 values were significantly higher in CDR4E than in the other extrudates and lower in R8E compared to the rest.Total color differences between samples with rosehip and the control  of the mixture with increasing rose hip addition is remarkable. Moreover, extrudates lost the reddish color compared to mixtures, as observed in ΔE2. The appearance of the extrudates is adequate and in the same trend as these products., 42.52, and 29.34 µg/g, respectively, whereas caffeic and syringic acids registered smaller values, 17.27 and 12.82 µg/g, respectively. The rosehip total phenolic amount was low compared with the corn flour and exhibited a value of only 27.09 µg/g, from which only ferulic and p-Coumaric acids were identified with values of 9.03 and 18.06 µg/g, respectively. The small amount of rosehip phenolic acids could be explained by rosehip being rich in chlorogenic acids and catechin, as previously shown by Tabaszewska et al. [The mixtures and extrudate phenolic acids content are presented in p < 0.05). However, in all samples with polymers, ferulic and Di-caffeic acids significantly increased their values through extrusion (p < 0.05) compared to the mixtures  and ten flavonols were identified, as presented in p < 0.05). For instance, the extrudates with 4% rosehip registered a 60% loss for the MDR4M sample, whereas PPR4E registered a loss of 39% . The carotenoids extrusion losses are illustrated in Adding rose hip increased the mixture’s content, leading to significant differences between samples with 4% and 8% addition, as presented in Adding rosehip in different percentages in mixtures had a positive influence on AA and DHAA, vitamin C, folate content, and AC, as presented in The AC mixtures values increased with rosehip addition, mainly because of its high antioxidant activity (19.23 μg TE/g). A large body of literature emphasized the AC rosehip high content ,50,55, aAC extrudates and vitamin C values decrease during extrusion, even if polymers were used a. The reThe samples folate content is presented in The mixtures levels of AA and DHAA registered a linear increase with the addition of rosehip , reachinp < 0.05)) were identified between folates, AA, vitamin C and AC mixtures and extrudates. Total flavonoids and total carotenoids also showed high positive Pearson’s correlations of 0.9870 and 0.9615 (p < 0.05), respectively. Some authors have reported that the main contributing AC factor was vitamin C or AA [p < 0.05), probably because of the stabilizing effect of AA on carotenoids [To better explain the relationship between vitamin C, AA, folates, total phenolic acids, total flavonoids, and total carotenoids, correlation statistical analyses were used. Positive strong Pearson’s correlation coefficients , K (Potassium), and Mg (Magnesium) with 7367.09, 6785.77, and 1558.9 µg/g values, meanwhile the micromineral values for Mn (Manganese), Fe (Iron) and Zn (Zinc) were 127.56, 98.36, and 20.56 µg/g, respectively.According to the scientific literature, rosehip represents a rich source of minerals, such as K, Ca, Mg, Na, Mn, Fe, and Zn, as reported by a large body of literature ,54,67,68Adding rose hip increased the mineral content in the mixtures , probablGulati et al.  showed tKamau et al.  reportedR. canina) powder led to significant changes in physicochemical characteristics of extrudates compared to a control sample. xw, aw, and ρb showed significant decreases (p < 0.05) in all samples, whereas WSI and Hy increased significantly (p < 0.05). Extrudates with 4 or 8% rosehip encapsulated with pea protein registered the lowest WSI values, showing more sample stability. However, mixtures’ optical properties, such as reddish color a* increased with increasing rose hip content, but in line with the color of these types of products. Nutritionally, PPR8E registered the highest content of AC, vitamin C, and total flavonoids content such as Quercetin-glucoside, Quercetin-glucosyl-glucosyl-rhamnoside, Isorhamnetin-glucoside, and Isorhamnetin-acetyl-glucosyl-glucoside. PPR8E, R8E, and CDR8E exhibited the highest values of total carotenoid content, and macrominerals were identified in larger amounts in PPR8E, RMDR8E, and CDR8E.The addition of rosehip (Rosa canina encapsulated with pea protein biopolymers could be successfully used in corn extrudates manufacturing.To conclude, we can assess that the addition of 8%


The 7th Cardiovascular Outcome Trial (CVOT) Summit on Cardiovascular, Renal, and Glycemic Outcomes, was held virtually on November 18–19, 2021. Pursuing the tradition of the previous summits, this reference congress served as a platform for in-depth discussion and exchange on recently completed CVOTs. This year’s focus was placed on the outcomes of EMPEROR-Preserved, FIGARO-DKD, AMPLITUDE-O, SURPASS 1–5, and STEP 1–5. Trial implications for diabetes and obesity management and the impact on new treatment algorithms were highlighted for endocrinologists, diabetologists, cardiologists, nephrologists, and general practitioners. Discussions evolved from outcome trials using SGLT2 inhibitors as therapy for heart failure, to CVOTs with nonsteroidal mineralocorticoid receptor antagonists and GLP-1 receptor agonists. Furthermore, trials for glycemic and overweight/obesity management, challenges in diabetes management in COVID-19, and novel guidelines and treatment strategies were discussed.Trial registration The 8th Cardiovascular Outcome Trial Summit will be held virtually on November 10–11, 2022 (http://www.cvot.org) Diabetes mellitus is on the rise across the globe. Prevalence estimates in the 20–79-year age group have increased from 463 million (9.3% of the world population) in 2019 to 537 million (10.5%) in 2021 ; p < 0.001). The results of other prespecified analyses are presented in Table Empagliflozin showed a significant improvement of the primary composite outcome with a reduced combined risk for CV death or HHF (hazard ratio (HR) 0.79 [95% confidence interval (CI) 0.69–0.90]; p < 0.001). This result was mainly related to a lower risk of HHF (HR 0.71 [95% CI 0.60–0.83]) and a slight decrease in CV death risk (HR 0.91 [95% CI 0.76–1.09]). Subgroup analysis showed consistent benefit of empagliflozin on the primary composite outcome in patients with diabetes (HR 0.79 [95% CI 0.67–0.94]) or without diabetes (HR 0.78 [95% CI 0.64–0.95]). Regarding the first secondary outcome, a significant 27% relative reduction in the total number of HHF was reported (HR 0.79 [95% CI 0.69–0.90]). In addition, the decline rate in the eGFR (second secondary outcome) was slower in the empagliflozin-treated group compared to placebo  ). There was no significant decrease in the risk of the secondary composite outcome (occurrence in 9.5% in the finerenone group N = 3686) and 10.8% in the placebo group (N = 3666); HR 0.87 [95% CI 0.76–1.01]). Also, no significant reduction in the risk for the secondary outcomes  was observable. The kidney secondary composite outcome  occurred in 2.9% in the finerenone group and 3.8% in the placebo group . In. In40]. In SURPASS-4, tirzepatide’s comparator was insulin glargine (100 U/ml). Participants in each group remained on currently prescribed treatment with metformin, SGLT2is, and/or sulfonylureas. All three doses of tirzepatide led to a significant reduction of HbA1c (− 2.24% 5 mg), − 2.43% (10 mg), and − 2.58% (15 mg) vs. − 1.44% insulin glargine) and body weight  from baseline. Significantly more patients achieved the HbA1c targets < 7.0% and < 5.7%. No increase in adjusted MACE-4 events  was noticeable on tirzepatide compared with insulin glargine (HR 0.74 [95% CI 0.51–1.08]). Further results are shown in Table  mg, − 2.In SURPASS-5, tirzepatide was compared with placebo. Participants received insulin glargine (U100), once daily with or without metformin as background medication Table . TirzepaThe most common adverse effects in all SURPASS 1–5 trials of the tirzepatide-treated groups were gastrointestinal . Their severity was generally mild to moderate and mainly dose-dependent. They occurred more frequently in the tirzepatide-treated groups than in the comparator groups. The incidence of severe hypoglycemia and blood glucose concentrations less than 54 mg/dl was lower with tirzepatide compared to insulin degludec and insulin glargine respectively (SURPASS-3 and 4) or did not differ between the tirzepatide and the comparator groups  –42.The SURPASS-CVOT, whose estimated completion date is October 2024, aims to investigate the cardiovascular safety of tirzepatide compared to dulaglutide 1.5 mg. The primary endpoint is a composite of MI, stroke, and CV death over 52 weeks. In SURMOUNT-1 the effect of tirzepatide primarily on weight loss in people with diabetes and obesity is being investigated. Primary outcomes are body reduction from baseline and the percentage of participants achieving ≥ 5% body weight reduction by week 72.The STEP trial 1 to 5 investigated the effect of semaglutide 2.4 mg as adjunctive therapy to lifestyle intervention on weight loss in adults with obesity or overweight –46, 58.2 or ≥ 27 kg/m2 and one or more treated or untreated weight-related comorbidities  were included. An exception was the STEP 2 trial, which explicitly included patients with T2D and BMI ≥ 30 kg/m2 or ≥ 27 kg/m2.In these randomized, double-blind trials, ≥ 18 years old participants without T2D and with a BMI ≥ 30 kg/mThe primary endpoints were the percentage change in body weight from baseline to the end of treatment (STEP 4: from week 20 to week 68) and the proportion of participants achieving ≥ 5% weight loss from baseline after the end of treatment (except for STEP 4)  compared to placebo (− 2.4%). Moreover, significantly more participants achieved a weight loss ≥ 5% with semaglutide than with placebo (86.4% vs. 31.5%).In STEP 2, which included participants with T2D, the percentage change in mean body weight was − 9.6% with semaglutide 2.4 mg and − 3.4% with placebo. At week 68, significantly more participants achieved a weight loss of ≥ 5% with semaglutide than with placebo (68.8% vs. 28.5%).In the STEP 3 trial, the lifestyle intervention was more intensive than STEP 1 . The mean body weight change from baseline was 16.0% for semaglutide 2.4 mg and 5.7% for placebo. Compared with placebo, significantly more participants treated with semaglutide lost ≥ 5% body weight.In STEP 4, all the participants received semaglutide 2.4 mg for 20 weeks (run-in period). They were then randomized to continue the semaglutide treatment or to switch to placebo for 48 weeks. The weight loss effect of continuing semaglutide treatment versus switching to placebo from week 20 to week 68 was investigated. After completion of the run-in period, participants achieved a mean weight loss of 10.6%. The mean body change from week 20 to week 68 was − 7.9% for semaglutide and + 6.9% for placebo, indicating a maintained weight loss effect for the treatment with semaglutide 2.4 mg .In the STEP 5 trial, the long-term weight loss effect of semaglutide was evaluated [semaglutide 2.4 mg vs. placebo for 2 years (104 weeks)]. The participants treated with semaglutide had, on average, a significant and sustained weight loss compared to those treated with placebo (15.2% vs. 2.6%) and were more likely to achieve a weight loss ≥ 5%  Guidelines for the diagnosis and treatment of acute and chronic heart failure , the defMore than 660,000 publications and 5300 registered or ongoing trials related to COVID-19 have been recorded. In the light of constantly and rapidly emerging new research evidence, the publication of systematic reviews including the latest evidence can become a complicated and resource-demanding task that affects the timely update of guidelines. The “living guidelines” approach, meaning the continuous update of the guideline recommendations and sustained by advances in evidence-based medicine and digitalization technology, was developed to tackle this challenge and create trustworthy, timely, and accessible guidelines , 62. TheIn 2019, an interdisciplinary experts’ panel (Taskforce of the Guideline Workshop) convened to develop strategies to optimize guideline processes in diabetes, CVD, and kidney diseases . In 2020One of the Taskforce’s conclusions from this successful pilot was to move towards living guidelines for cardiorenal outcomes in diabetes, as demonstrated in the COVID-19 pandemic. The Taskforce will now be included in an update of the above-mentioned systematic review and network meta-analysis. The addition of new CVOT trials, and in particular determining the relative effectiveness of finerenone, can help the societies update their respective guidelines. The next goal would be for the professional societies to move to living guidelines, based on living systematic reviews with network meta-analysis to inform dynamic and rapid updates of recommendations.FIDELITY was designed as a prespecified individual meta-analysis of the trials FIDELIO-DKD and FIGARO-DKD  , 36, 74.2, T1D, and prior diabetic ketoacidosis. The participants were randomized to receive dapagliflozin (10 mg/day) or a placebo for 30 days. The trial had dual composite primary endpoints: a prevention endpoint (time to new or worsened organ dysfunction or death from any cause) and a hierarchical recovery endpoint . Safety outcomes (in patients who received ≥ 1 study medication dose) included serious adverse events, adverse events leading to discontinuation, and adverse events of interest. The prevention endpoint (time to organ dysfunction or death) occurred in 70 patients (11.2%) in the dapagliflozin group, and 86 (13.8%) in the placebo group . The primary outcome of recovery  was numerically in favor of the dapagliflozin group than the placebo group [n = 547 (87.5%) vs. n = 532 (85.1%)]; however, this was statistically not significant . Serious adverse events occurred in 65 (10.6%) of 613 dapagliflozin-treated participants and in 82 (13.3%) of 616 patients who received a placebo [Since COVID-19 may impair multiple organs, through among others vascular damage, endothelial dysfunction, and inflammation resulting in thrombosis and potential organ damage  and know placebo . Althoug placebo , 78, the placebo .The World Health Organization (WHO), the FDA, and the European Medicines Agency (EMA) define biosimilars as biotherapeutic/biological products/medicines that are highly similar to already approved biotherapeutic/biological products/medicines –82. BiosThe prospective trial ORIGIN, which involves people with CV risk factors and impaired fasting glucose, impaired glucose tolerance, or T2D, showed a neutral effect of insulin glargine on CV outcomes  and cancer compared to standard-care . In addiMajor clinical trials conducted in the last decades regarding diabetes management used the surrogate, long-term marker HbA1c to assess the efficacy of diabetes care in routine clinical care for both T1D and T2D , 95. Imphttps://www.cvot.org).The 7th Cardiovascular Outcome Trial (CVOT) Summit on Cardiovascular, Renal and Glycemic Outcomes offered an interactive and multi-disciplinary platform to discuss key results of recently published trials. The virtual format enabled attendants from 88 countries to participate. The summit covered two CVOTs (FIGARO-DKD and AMPLITUDE-O) and one HF trial (EMPEROR-Preserved). In addition, glycemic (SURPASS 1–5) and overweight/obesity outcome trials (STEP 1–5) were discussed. The meeting provided novel data, insights, strategies, and guidelines for specialists and primary care for the management of diabetes, obesity, HF, CV, and kidney disease. In-depth discussions and presentations of upcoming CV, kidney, HF, glycemic, and obesity trials will be resumed at the 8th edition of the CVOT Summit, which will be held virtually on November 10–11, 2022 (


To evaluate the effects of pretreatment for dry eye disease (DED) on the accuracy of intraocular lens (IOL) power calculation.Patients who underwent uneventful cataract surgery were included in the study. IOL power was determined using the SRK/T and Barrett Universal II (Barrett) formulas. The patients were divided into non-pretreatment and pretreatment groups, and those in the pretreatment group were treated with topical 0.5% loteprednol etabonate and 0.05% cyclosporin A for 2 weeks prior to cataract surgery. Ocular biometry was performed in all groups within 2 days before surgery. The mean prediction error, mean absolute error (MAE), and proportions of refractive surprise were compared between the non-pretreatment and pretreatment groups at 1 month postoperatively. Refractive surprise was defined as MAE ≥ 0.75D.p < 0.001/=0.008). The number of refractive surprises was also significantly lower in the pretreatment group. . Pretreatment of DED was related to a reduction in postoperative refractive surprise. .In a total of 105 patients, 52 (52 eyes) were in the non-pretreatment group and 53 (53 eyes) in the pretreatment group. The MAE was 0.42 ± 0.33, 0.38 ± 0.34  and 0.23 ± 0.19, 0.24 ± 0.19 in the non-pretreatment and pretreatment groups, respectively (The accuracy of IOL power prediction can be increased by actively treating DED prior to cataract surgery. The number of cataract surgeries has grown significantly in recent years due to an increase in lifespan in the elderly population . There iDry eye disease (DED) is one of the most common ocular diseases affecting millions of people worldwide. It is mainly associated with tear film instability, tear hyperosmolarity, and inflammation of the ocular surface , 6. It iHovanesian et al. showed that treatment with lifitegrast for 1 month prior to cataract surgery increased the accuracy of IOL power prediction, thereby highlighting the importance of preoperative treatment of DED , 12. In This retrospective observational study was conducted in accordance with the tenets of the Declaration of Helsinki, and ethical approval was obtained from the Institutional Review Board of Gachon University Gil Medical Center, Korea (IRB number: GCIRB 2021–170). Patients who underwent uneventful cataract surgeries between January 2018 and May 2020 were enrolled in this study. Exclusion criteria were patients with corneal opacity, history of corneal refractive surgery, intraoperative posterior capsular rent, and a history of ocular trauma affecting zonular damage. Patients who were unable to calculate IOL power using IOLMaster 500  due to severe cataract or poor cooperation were also excluded. When the SNR value was greater than 2 and the standard deviation of the K value was less than 0.01D, the ocular biometry was measured once with IOLMaster500. The right eye was enrolled if the patient underwent cataract surgery in both eyes.To manage preoperative DED, patients in the pretreatment group were administered 0.5% LE  four times a day and 0.05% CsA  twice a day for 2 weeks prior to surgery Fig. . Eyelid All cataract surgeries (phacoemulsification and posterior chamber lens implantation) were performed by a single surgeon (DH Kim) under topical anesthesia, with a superior corneal incision of 2.2 mm. A one-piece aspheric monofocal IOL  was used in all surgeries. The A-constant in SRK/T formula was 119.3 for Tecnis ZCB00, and this A-constant of ZCB00 was optimized from previous 500 operated eyes by DH Kim. Optimized A-constant were applied in both the non-pretreatment and pretreatment groups. When calculating the IOL power using the Barrett Universal II formula, the recommended A-constant of 119.39 in APACRS web was used. Ocular biometry was performed within 2 days before surgery in all groups.p-value of < 0.05. We compared the accuracy of intraocular power calculation between the non-pretreatment and pretreatment group for DED before cataract surgery, and analyzed which factors influence on the refractive surprise.Manifest refraction was measured 1 month after surgery, and the spherical equivalent (SE) was calculated. Prediction error was calculated by subtracting the preoperative predicted IOL power using the SRK/T and Barrett Universal II formulas from the postoperative actual SE. The absolute value of prediction error was used to prevent mathematical errors. The mean error (ME) and mean absolute error (MAE) of each formula were compared between the non-pretreatment and pretreatment groups. MAE was categorized into four range groups: MAE < 0.25D, 0.25D ≤ MAE < 0.5D, 0.5D ≤ MAE < 0.75D, and 0.75D ≤ MAE. Postoperative refractive surprise was defined as an MAE ≥ 0.75 D. Other clinical variables such as age, sex, axial length (AL), and keratometric (K) values were considered together to assess the effects of DED pretreatment on the accuracy of IOL power. Statistical analysis was performed using the SPSS Statistics . Independent t-test, chi-squared test, and logistic regression were used for analyses. Statistical significance was defined as a p > 0.05, Table A total of 105 eyes of 105 patients were analyzed. The mean age of the patients was 67.9 ± 11.8 years. Among the 105 patients, 53 (53 eyes) received pretreatment for DED while 52 (52 eyes) did not. The baseline characteristics of the patients are summarized in Table p = 0.828/0.529, Table p < 0.001/=0.008, Table p = 0.024/0.016; Table p = 0.001/0.020 and MAE ≤ 0.5D; p = 0.002/0.154 for SRK/T and Barrett Universal II, respectively).The ME at 1 month after surgery was 0.10 ± 0.53D, − 0.06 ± 0.51D  in the non-pretreatment group and 0.09 ± 0.28D, − 0.01 ± 0.30D in the pretreatment group. There were no significant differences between the two groups ; Table p > 0.05). In the subgroup analysis in the pretreatment group, pretreatment was more effective on the reduction of refractive surprise in the elderly (> 60 years), men, and patients with a normal range of AL /0.040/0.018/0.041]. The pretreatment also showed the effectiveness on the reduction of refractive surprise in the abnormal range of K values with marginally significance. [p = 0.063(SRK/T)/0.054].In univariate and multivariate logistic regression analysis, the pretreatment of DED significantly lowered the proportion of refractive surprise [univariate: odds ratio (OR) = 0.19/0.11, 95% confidence interval (CI): 0.04–0.91/0.01–0.88, There were no adverse effects, such as elevation of intraocular pressure and ocular infection, in the pretreatment group before and after surgery.This study showed that short-term treatment of DED prior to cataract surgery improved the accuracy of IOL power calculation. Pretreatment protocols of DED for 2 weeks comprised topical LE and CsA and eyelid scrub with warm compression. In our previous study, we have shown excellent effects of short-term topical corticosteroids in patients with refractory DED . In thisThe prevalence of DED tends to increase with age . The preIn our subgroup analysis Table , pretreaDetailed screening procedures for DED and selective treatment prior to cataract surgery are definitely beneficial. However, it may be time-consuming and difficult to perform in clinical settings. In fact, more than 80% of preoperative patients showed signs of DED and 75% showed MGD, both of which are well-known factors that aggravate postoperative DED , 31. HenThis study has several limitations. First, the study was retrospective in nature. Second, the sample size was small. Third, detailed ocular biometry examinations (AL and K) were not evaluated before and after DED pretreatment. Fourth, we did not classify the severity of DED and MGD. Nevertheless, the short-term DED pretreatment group showed a marked improvement in postoperative IOL power prediction compared to the non-pretreatment group. Since this was our first study about effects of the pretreatment of DED on postoperative IOL power accuracy, we wanted to maximize the treatment effects by using topical LE and CsA simultaneously. We have a plan to compare the pretreatment effects of only LE, LE + CsA, and no pretreatment in the future prospective study.In conclusion, short-term preoperative management of DED using topical LE, CsA and eyelid scrubs with warm compression can improve the accuracy of IOL power calculation. Our pretreatment protocol for DED before cataract surgery can reduce the probability of refractive surprise. Thus, we believe that this protocol may be helpful before cataract surgery, as it is easily applicable and safe, with no adverse effects.