Ghrelin expression in the brain was higher in T-NP compared to NP-FM and NP-PP, while in the gut it was reduced in both NP-PP and T-NP groups. Cholecystokinin expression showed an opposite trend to ghrelin. The brain neuropeptide Y expression was lower in NP-PP compared to PP but not different with NP-FM and T-NP groups. The highest villus length to width ratio in the middle intestine was found in T-NP compared to all other groups. The study suggests that NP induced during juvenile stages improves zebrafish growth and affects digestive hormone regulation and morphology of the intestinal lining–possible mechanisms behind the improved PP utilization in pre-adult zebrafish stages.Nutritional Programming (NP) has been shown to counteract the negative effects of dietary plant protein (PP) by introducing PP at an early age towards enhancement of PP utilization during later life stages. This study explored the effect of NP and its induction time on growth, expression of appetite-stimulating hormones, and any morphological changes in the gut possibly responsible for improved dietary PP utilization. At 3 days post-hatch (dph) zebrafish were distributed into 12 (3 L) tanks, 100 larvae per tank. This study included four groups: 1) The control (NP-FM) group received fishmeal (FM)-based diet from 13–36 dph and was challenged with PP-based diet during 36–66 dph; 2) The NP-PP group received NP with dietary PP in larval stage via live food enrichment during 3–13 dph followed by FM diet during 13–36 dph and PP diet during 36–66 dph; 3) The T-NP group received NP between 13–23 dph through PP diet followed by FM diet during 23–36 dph and PP diet during 36–66 dph; and 4) The PP group received PP diet from 13–66 dph. During the PP challenge the T-NP group achieved the highest weight gain compared to control and PP.  Replacement of fishmeal (FM) in fish diets with plant protein (PP) has been an ongoing challenge in the aquaculture industry. High-quality PP sources such as soy or pea protein concentrates and wheat or corn gluten have been widely used by the feed industry since their digestibility in some species is comparable to FM. However, their price can often exceed the cost of marine raw materials. Although some progress with utilization of lower-quality PP, such as soybean meal, has been made, a number of concerns must still be overcome including a presence of anti-nutritional factors responsible for inducing intestinal inflammation, to maintain acceptable growth rates and feed efficiency values at high FM substitution levels.Oncorhynchus mykiss subjected to PP-based diet during the first three weeks of life showed improved acceptance and utilization of the same dietary PP-based diet when given during later life stages. Furthermore, two other studies reported that early exposure of young European seabass Dicentrarchus labrax to diets deficient in long-chain polyunsaturated fatty acids induced higher expression of delta-6 desaturase mRNA levels in juveniles–the rate-limiting enzyme involved in biosynthesis of highly unsaturated fatty acids  + 159.In vitro transcription was performed using T3 RNA polymerase and other reagents supplied in the RiboProbe In Vitro Transcription System kit  according to the manufacturer’s protocol. The concentration of the mRNAs thus obtained was measured by reading the absorbance at 260 nm by means of NanoDrop ™ 2000c (Thermo Scientific). By knowing the molecular weight and the concentration of each mRNA it was possible to determine the number of molecules/μL for each target gene.® Green quantitative real-time RT-PCR, in the same plate with defined amounts of synthetic mRNAs at 10-fold dilutions, using iTaq™ Universal SYBR® Green One-Step kit . The sequences of primers used for target gene amplification are shown in ® Green PCR reactions were performed on a Bio-Rad® CFX96™ System.The synthetic mRNAs of each gene were used as quantitative standards in the analysis of biological samples. For this, one hundred nanograms of total RNA extracted from fish samples were amplified via One-step SYBR™ Software. The Ct values of the standard mRNAs amplification were used to create standard curves, which were then used for the calculation of the copies of mRNAs in the biologic samples.Data from the real time PCR runs were collected with CFXThe intestines previously fixed in 10% neutral buffered formalin were processed to paraffin using a Sakura enclosed automated tissue processor (Netherlands). The three representative areas of zebrafish intestines were orientated for cross sections embedded together in the same block. Five micrometer serial sections were cut with a Leica manual microtome  and placed on water bath at 44°C. Sections were placed on positive charged slides. After drying, the slides were stained with hematoxylin and eosin and cover-slipped using acrylic mounting media. The histological analysis of the mid-gut portions of fish digestive tract focused on the tissue sections of medium diameter. Pictures of the samples were taken at 100x magnification using a microscope  and a camera .To obtain villus length and width, pictures of each slide were obtained using a microscope (Leica DMI 300B) and camera (Leica DMC 290) combination, with the software LAS V4.4 . From these pictures, individual lengths and widths were taken of intact villi using ImageJ . Length and width data were measured according to Karimi and Zhandi  in the tp values <.05 were considered significant.Results are presented as means ± standard deviation. One-way ANOVA was used followed by Tukey’s test using the software R. Differences with At the end of the study the lowest average weight was achieved by the PP group compared to all other groups. No differences were detected in average weight between NP-FM, NP-PP, or T-NP groups .During the PP challenge the T-NP group achieved the highest weight gain compared to both control groups NP-FM and PP. The NP-PP group achieved higher weight gain compared to the negative control; however, no differences were detected with NP-FM or T-NP groups. No differences in the feed intake were detected during NP phase, control feeding phase, or PP challenge. Similarly, no differences were found in the survival  between the different dietary regimes.Ghrelin expression in the brain was significantly higher in the T-NP group compared to NP-FM and NP-PP groups but not different with the PP group. Ghrelin expression in the gut was significantly reduced in both NP-PP and T-NP groups compared to the other groups. No differences were detected in the gut ghrelin expression between NP-PP and T-NP nor between NP-FM and PP groups . A similar trend was also seen in the gut but no significant differences were actually detected  that stimulates body weight gain and adiposity in mammals. In the present study, fish brain and whole digestive tract samples were taken 3- and 24-hours after feeding. In T-NP fish 3-hours after feeding the level of ghrelin in the brain was higher compared to NP-PP and control fish. In the gut however, the level of ghrelin in both “programmed” groups was lower compared to control (NP-FM) and PP groups. Moreover, the level of ghrelin mRNA expression in NP-PP and T-NP groups 3-hours after feeding was lower compared to fish sampled 24-hours after feeding. Ghrelin in zebrafish is mainly expressed in endocrine pancreatic cells [ghrelin expression level in the gut observed in our study might possibly indicate fish in “programmed” (NP-PP and T-NP) groups to be in a satiated (fed) state compared to both controls. In rainbow trout Oncorhynchus mykiss ghrelin was shown to have an anorexigenic effect that leads to suppression of food intake. However, in cyprinids such as goldfish Carassius auratus, ghrelin was reported to increase food intake through stimulation of NPY and orexin neurons in the brain and a potential feedback of orexin on ghrelin expression, which might help explain the elevated ghrelin levels in the T-NP fish in zebrafish brain in our study. Orexin has been found to stimulate appetite and food consumption after fasting in different fish species including zebrafish [orexin expression levels in both brain and gut not significantly different among groups. However, there was a trend for higher levels of orexin in T-NP and PP groups compared to the other groups, particularly in the brain, possibly supporting the aforementioned assumption about the orexin-related increased ghrelin levels in T-NP group in the brain.Flavor experiences during early life stages have been shown to be a driver for life-long flavor acceptance in adults’ life. For example, citric acid, which has a sour/bitter taste, is known to be an instinctively aversive substance for rats. However, rats exposed/programmed to citric acid during nursing showed increased voluntary ingestion of citric acid compared to rats that were not exposed to citric acid at all . We hypoic cells . The lowebrafish –29. We fNPY in feed regulation in fish has not been studied extensively but the available literature indicates that NPY in fish has orexigenic effects similar to those observed in mammals. More specifically, higher levels of NPY have been associated with increased food intake in zebrafish [NPY brain expression levels have been reported higher around feeding time and lower post-prandially in Chinook salmon Oncorhynchus tshawytscha, Coho salmon Oncorhynchus kisutchand [NPY as an appetite stimulator consequently being widely considered as one of the most highly conserved neuropeptides in vertebrates [NPY expression to be higher in the PP group compared to NP-PP and not different with T-NP and NP-FM groups, suggesting that perhaps fish in the PP group were in an “unfed” state 3-hours after feeding. Valen et al. [NPY mRNA levels in fed Atlantic salmon Salmo salar compared to unfed fish 1.5 and 9-hours after feeding. The authors argued, however, that the increased NPY expression was probably a result of digestive tract feedback since after 9 hours the feed had likely been evacuated from the digestive tract rendering the fish to be in “unfed” state again.The role of ebrafish . The NPYsutchand , and in sutchand ,33 furthtebrates . Our stun et al.  observedLeptin—an antagonist of ghrelin, is an anorexigenic hormone released mostly by adipose tissue in mammals. In fish, leptin has been found in liver, brain, muscle, gonads, kidneys, and other tissues [leptin expression have been observed in common carp Cyprinus carpio [Epinephelus coioides [leptin at a dose of 10 ng/g/h using implanted micro-osmotic pump over a three-week period. However, leptin response to feeding status varies between species and salmonids show an opposite trend to the mammalian model in which fasting or feed restriction actually leads to decreased leptin levels. Trombley et al. [leptin and 2.3 times higher plasma leptin levels in Atlantic salmon in the feed-restricted group  compared to the control group . Similar results were obtained by Kling et al. [leptin levels to be higher in fasted rainbow trout compared to fed trout throughout 21 days of the experimental period. In our study, leptin expression in the brain was not significantly different among groups. Leptin expression in the gut was not different between groups 3-hours after feeding suggesting that either a longer time is required for the leptin signal to take effect or the link between diet and leptin regulation in zebrafish is not significant if all the fish receive similar food rations across groups as opposed to feeding versus starving. This first assumption can be consolidated by the observed rise in leptin mRNA levels in T-NP group 24-hours after feeding compared to 3-hour sampled fish potentially suggesting fish in T-NP group to be in a satiated state 24-hours after the last meal compared to all other groups. The second assumption is supported by results obtained by Oka et al. [leptin mRNA expression between overfed and control  zebrafish. Huising et al. [leptin expression levels corresponded to increase in plasma glucose levels 3-hours and 6-hours after feeding in common carp Cyprinus carpio. Yet, leptin expression was not affected by short-term fasting (six days) nor long-term-fasting (21 days) even though the latter fish lost 30% of their initial weight towards the end of the third week. Leptin’s role in satiety is supplemented by the actions of both ghrelin and CCK. Volkoff et al. [CCK might affect actions of leptin in goldfish. Interestingly, although in our study no differences were detected in leptin expression level among groups 3-hours after feeding, CCK expression level was significantly lower in both programmed groups compared to control and negative control in the brain. Similar trend was observed in the gut. CCK has been linked to stimulation of pancreatic enzyme secretion, gallbladder contraction, and intestinal peristalsis. In the brain CCK acts as a neurotransmitter involved in control of appetite as a satiation signal from the gut. In goldfish, CCK has been found to inhibit feed intake [CCK expression in programmed groups potentially led to enhanced digestion and nutrient absorption and therefore better growth of fish in those two groups. However, CCK expression in the gut seemed to present a similar trend to ghrelin expression contradicting previous evidence on involvement of ghrelin in suppression of CCK anorexic effect in goldfish [CCK expression in the gut [CCK response to fasting/feeding is species-, tissue-, and time-dependent [CCK expression in the gut after two weeks of fasting in winter skate Raja ocellata but no effect was detected in the brain. CCK has also been shown to differ between gastric and agastric fish species such as ballan wrasse Labrus bergylta [CCK in NP-PP and T-NP groups could also indicate these fish were actually in “starvation” compared to both control groups—an alternative scenario to the earlier statement on CCK status in our experiment. However, this speculation contradicts previous results presented for ghrelin, orexin, NPY, and leptin and therefore the results remain perplexing and suggest further investigation on the effects of nutritional status on the expression of CCK in zebrafish. tissues ,35–37 ancoioides  confirmicoioides  showed ry et al.  reporteda et al.  who founf et al.  found thd intake . Consequgoldfish . Althoug the gut –50 the rependent . For exaependent  showed abergylta . The decSoybean meal is the most commonly used PP source in aquaculture feeds, but its use has been limited due to its negative effects at higher dietary inclusion rates that lead to reduced growth and an intestinal inflammation . TypicalOur study found that zebrafish is able to utilize PP-based diets more efficiently for growth when exposed to the same PP source early in life. This study also proposes that NP should probably be induced when fish are already in a juvenile stage when all the organs and systems are fully present to be able to respond to this early nutritional trigger more effectively. Furthermore, this study found that early exposure to PP affects gut responses on both molecular and histological level. The expression of three out of five genes coding for appetite-controlling hormones was significantly affected including ghrelin, cholecystokinin, and neuropeptide Y. The “programmed” fish group was also characterized by improved intestinal lining with the highest villus length to width ratio in the middle intestine. Taken together these results suggest that the mechanism behind NP might be associated with endocrine and morphological adaptation of the digestive system that leads to enhanced digestion and absorption capacity ultimately reflected by improved growth performance.S1 FileThis file contains the raw data for the histological and gene expression analysis of the zebrafish intestines.(XLSX)Click here for additional data file.


Adoptive immunotherapy with gene-engineered T cells has provided new treatment options for cancer patients. The most successful strategies have involved the engineering of T cells expressing chimeric antigen receptors (CARs) directed against differentiation antigens expressed in haematological malignancies. To date, clinical trials with TCR gene-engineered T cells have not yet demonstrated the clinical efficacy seen with CAR-T cells directed against CD19-positive blood cancers. However, this Special Issue demonstrates some of the advantages of TCR engineering of T cells to target cancer antigens, including mutated neoantigens, that cannot be reached by the CAR technology. In this issue, the authors provide insights into the nature of cancer proteins that can be targeted by TCR engineering, demonstrate that virus-driven human cancers can be targeted with TCR gene therapy, explore the role of CD4+ helper T cells and CD8+ cytotoxic T cells, show how TCRs from CD8+ T cells can be functional in CD4+ T cells, and finally discuss how targeting of the tumour microenvironment may enhance the efficacy of TCR gene therapy of solid cancer. This Special Issue provides detailed insight into the opportunities of TCR gene therapy and how it may enable the development of highly specific immunotherapies for the treatment of solid cancer.The paper by Crowther and colleagues provides an excellent comparison of the CAR and TCR technology platforms that are used to redirect the specificity of patient T cells against selected target proteins present in cancer cells . Over reGaissmaier and colleagues provide an excellent overview of the challenges and bottlenecks of TCR gene therapy . A majorThere is currently much effort to generate “off the shelf” cell products that could be used in multiple patients. Moving from autologous T-cell products that are unique for each individual patient to a generic T-cell product that can be utilised in many patients would be a major step towards providing engineered T-cell therapy at a large scale and mitigating current prohibitive costs. Mornadi et al. discuss the advantages of engineering γ/δ T cells and NKT cells for therapy in the allogeneic setting . The majThree papers in the Special Issue have explored the use of TCR-redirected CD4+ T cells for adoptive T-cell therapy. Klobuch et al. have isolated TCRs specific for the human HLA-DPB1 antigen . This MHThe importance of TCR affinity and T-cell avidity is addressed in the paper by Campillo-Davo et al. . AffinitTo date, TCR transgenic T cells most often express the introduced TCR in addition to the endogenous TCR. The expression of two TCRs in the same T cells has two major disadvantages; mispairing between introduced and endogenous TCR chains can produce unknown specificities and toxicity, as evidenced in mouse models when T cells are adoptively transferred in vivo . SecondlThe paper by Rath et al. provides a comprehensive overview of the clinical trial experience with TCR-engineered T cells, while also reviewing how synthetic biology approaches may further enhance the efficacy of TCR gene therapy . SynthetTwo papers illustrate how TCR gene therapy can be utilised as a treatment option for malignancies associated with infection by Epstein–Barr Virus (EBV) and hepatitis virus. Healy et al. provide a summary of currently known peptide epitopes in HBV, HCV, and HEV that can be targeted by TCRs . The autThe contribution by Munz covers the therapeutic options to treat EBV infection and EBV-driven cancer . A TCR gThis Special Issue provides a comprehensive cutting-edge overview of current and future immunotherapy of cancer with TCR-engineered patient T cells. The TCR gene therapy approach is not in competition with CAR–T-cell therapy, but instead, it extends the scope of T-cell engineering to include intracellular proteins and mutated cancer neoantigens that are difficult to target with the conventional CAR technology platform.


Drosophila compound eye. Since defects can provide insight into cell-cell interactions responsible for pattern formation, here we characterize the arrangement of cones in individual Y-Junction cores as well as the spatial distribution of Y-junctions across entire retinae. We find that for individual Y-junctions, the distribution of cones near the core corresponds closely to structures observed in physical crystals. In addition, Y-Junctions are organized into lines, called grain boundaries, from the retinal center to the periphery. In physical crystals, regardless of the initial distribution of defects, defects can coalesce into grain boundaries via the mobility of individual particles. By imaging in live fish, we demonstrate that grain boundaries in the cone mosaic instead appear during initial mosaic formation, without requiring defect motion. Motivated by this observation, we show that a computational model of repulsive cell-cell interactions generates a mosaic with grain boundaries. In contrast to paradigmatic models of fate specification in mostly motionless cell packings, this finding emphasizes the role of cell motion, guided by cell-cell interactions during differentiation, in forming biological crystals. Such a route to the formation of regular patterns may be especially valuable in situations, like growth on a curved surface, where the resulting long-ranged, elastic, effective interactions between defects can help to group them into grain boundaries.The outer epithelial layer of zebrafish retinae contains a crystalline array of cone photoreceptors, called the cone mosaic. As this mosaic grows by mitotic addition of new photoreceptors at the rim of the hemispheric retina, topological defects, called “Y-Junctions”, form to maintain approximately constant cell spacing. The generation of topological defects due to growth on a curved surface is a distinct feature of the cone mosaic not seen in other well-studied biological patterns like the R8 photoreceptor array in the  i.e., defects) are inserted to maintain constant spacing between sensory cells. We study the spatial distribution of these defects to gain insight into how the cone pattern forms. By imaging retinae in live fish, we find that as differentiating cones are incorporated into the mosaic, defects form lines (grain boundaries) that separate mostly defect-free domains. Then, we show that a computational model based on repulsion between mobile cells during their incorporation into the mosaic generates similar grain boundaries. This study thus suggests that cell motion governed by repulsive cell-cell interactions can play an important role in establishing regular patterns in living systems.From hair cells in the mammalian inner ear to the bristles on a fly’s back, sensory cells often form precise arrays, ensuring that these cells are evenly spread out on the tissue’s surface. Here we consider the zebrafish cone mosaic, a crystal of cone photoreceptors in the outer retinal layer. Because the cone mosaic grows from the rim of the curved retinal surface, new rows of cones ( In epithelial sheets that sense an external stimulus, the sensory function often depends on the spatial ordering of the constituent cells. In several examples –7, the pFour spectral subtypes form the zebrafish cone mosaic: Red, Green, Blue, and Ultraviolet (UV) ,15. The The retinal hemisphere grows outward from the rim by mitotic addition of new photoreceptors   16–19].–19.16–19As new cells are incorporated at the rim, the circumference of the retinal hemisphere enlarges, and the spacing between the original rows necessarily increases . To mainDrosophila .–68.61–68a priori reason that the dynamics of a biological system should be governed by a free energy, we expect that many models with symmetric, pairwise, repulsive interactions between unpolarized cells can be mapped onto an effective free energy of the phase-field crystal form.)The phase-field crystal model assumes that the density field evolves to minimize a free energy functional while conserving the total number of particles. This dynamical law can be derived from a microscopic model of individual particles whose pairwise interactions include a short-ranged repulsion and that are subject to frictional damping and thermal noise; the approximations involved in the derivation amount in essence to assuming that higher-order correlations relax quickly compared to two-body correlations and that the crystal structure can be described by keeping only Fourier modes in the particle density of the dominant wavelength . The exiTo model the growth of the cone mosaic, we initialize the phase-field to be entirely uniform except near the center of the simulation domain .i.e., the liquid is “undercooled”), the density field is unstable to the formation of periodic structures; otherwise, only the liquid phase is stable. As there is no clear analogue to temperature in our system, we interpret this parameter as quantifying the strength of the interactions relative to the random noise in cone cell motion. The second parameter is the mean of the cone density field, which is conserved by the dynamics.For a fixed anisotropy of the lattice spacing , the simThe values of these two free parameters, the interaction strength and the mean of the density modulation field, determine which phase (or phases) are stable. Depending on these parameters, this model can generate three phases: a constant (“liquid”) phase, a striped phase, and a triangular phase ,64. We cad hoc parameters). Thus, this model, for which there is supportive evidence in embryonic retinae ) fish. Blue cones express a fluorescent reporter (pseudo-colored blue) under control of the Blue opsin promoter sws2, and Red cones express a fluorescent reporter (pseudo-colored red) under control of the trβ2 promoter. All cones express an additional fluorescent reporter under control of the gnat2 promoter. Although UV and Green cones do not express different fluorescent reporters, these two cone subtypes are morphologically distinguishable. (B) Nodes of graph are Red cones from panel A, and edges connect nearest neighbors in honeycomb lattice. Note the existence of a heptagon-pentagon pair  in both defect cores. (C) Nodes of the graph are Green cones from panel A, and edges connect nearest neighbors in honeycomb lattice. Note the existence of an octagon  in both defect cores. (D-F) Another example of a Y-Junction from a flat-mount retinal preparation from the same triple transgenic line (akin to panels A-C).(A) Two Y-Junctions (asterisks) in a flat-mount retinal preparation from an adult, triple transgenic (Tg[(TIF)Click here for additional data file.S4 Fig(A-C) For each of three flat-mounted retinae, image on the left-hand side is of all identified Y-junctions (yellow dots). Central image is all Y-junctions that our algorithm identified as in a grain boundary (with cutoff of twelve degrees). Image on the right-hand side is all Y-junctions that our algorithm identified as in a grain boundary (with cutoff of fourteen degrees). Panel A is fish 5 . Panel B is fish 4 . Panel C is fish 8 , the retina in Figs (TIF)Click here for additional data file.S5 Figi.e., move perpendicular to the Burgers vector). The lattice in panel 1 has a dislocation. Photoconverted UV cones are magenta, and non-photoconverted UV cones are yellow. Panel 2 is triangulation in panel 1 with a new vacancy. Gray arrow is where the vacancy will hop, to create the distribution in Panel 3. Gray arrow in Panel 3 is where the vacancy will hop, to create distribution in Panel 4. As the vacancy hops, the defect core moves perpendicular to the Burgers vector. (B) Vacancy in the cone mosaic  can be destroyed. Red cone in Panel 1 must move as indicated by gray arrow to create distribution in Panel 2. Movements denoted by gray arrows in Panel 2 allow for the vacancy to close and for the defect to move. Panel 3 corresponds to the distribution of cones after destruction of the vacancy. We never observe a vacancy  in the cone mosaic, and thus consider climb motion irrelevant for our system.(A) The creation of a vacancy allows a dislocation to climb ((TIF)Click here for additional data file.S6 Fig(A) We trace rows of UV cones (white dashed lines) near Y-Junctions. Yellow dots: Y-Junctions observed immediately after photoconversion. White dots: Y-Junctions that are incorporated during the two days after photoconversion. Double-sided black arrow: newly incorporated UV cone columns. This is grain boundary 1 in (PDF)Click here for additional data file.S7 Figtrβ2 mutant retinae. (B) Flat-mount retinal preparation of trβ2 mutant immunostained for ZO1 (green). Profiles of UV cone are large and rounded (see (A) Immunocytochemistry for cone-subtype-specific opsins, including Red opsin (red), Green opsin (green), Blue opsin (blue), and UV opsin (yellow) in wild-type and nded see . White d(PDF)Click here for additional data file.S8 Figψ0 is the mean of the density modulation field and where R is the undercooling parameter. The number of initial rows on the cone frustum is two hundred. Approximately ninety-five columns exist from the top of the cone frustum to the bottom. About two row insertions per added column are necessary to maintain constant cell-cell spacing. The degree of anisotropy is constrained by We take a one-dimensional cut of the two-dimensional phase diagram of the phase-field crystal model ((TIF)Click here for additional data file.S9 Fig(A) Positions of all Y-Junctions (yellow dots). (B) Positions of all Y-Junctions (yellow dots) which coincide with a row orientation change of more than ten degrees. (C) Positions of all Y-Junctions (yellow dots) which coincide with a row orientation change of more than twelve degrees. (D) Positions of all Y-Junctions (yellow dots) which coincide with a row orientation change of more than fourteen degrees. See Detection of grain boundaries in simulated cone mosaic.(TIF)Click here for additional data file.S10 Figi.e., in the phase-field crystal free energy) selects and maintains the orientation during growth (in contrast with panel A). Even when a domain forms with improper orientation , the domain rotates to the proper orientation during growth. (C) Zoomed-in snapshot of an anisotropic phase-field crystal simulation on the surface of a cone. Note that near grain boundaries , there is a lag in proper positioning of UV cones  relative to growth of neighboring domains. This results in a characteristic V-shape.(A) Example of isotropic crystal growth on cone frustum with an initial column as prepattern. Yellow dots: seven-coordinated particles . Note the lines of seven-coordinated particles that do not radiate from the center of the cone to the periphery . These non-radiating lines of seven-coordinated particles result from a rotation of crystallographic orientation during growth of the isotropic crystal, not observed in zebrafish retinae. (B) Example of anisotropic crystal growth on cone frustum with no initial column as prepattern. With only white noise at the top of the cone in initial conditions, the anisotropy of the crystal ((TIF)Click here for additional data file.S11 Figu≈1 cells forms on a square packing of 20000 cells with periodic boundary conditions. Defects  in triangular lattice of u≈1 cells are yellow dots. Initially, all cells are in state (u = 0) because an external inhibiting signal is provided to all cells. Starting at t = 0, a wave of de-inhibition moves from left to right . The wave moves at a speed τ is the timescale of cell differentiation, and l is the range of cell-cell signaling. In each panel, the black arrow is the direction of wave propagation. (A) The signaling range is A0 is the mean cell area. This signaling range results in seven to eight u≈0 cells between each pair of neighboring u≈1 cells in the final pattern. Note that some defects are generated early in pattern formation , but the right side of the packing contains no defects. (B) The signaling range is u≈0 cells between each pair of neighboring u≈1 cells in the final pattern. The entire packing contains defects. (C) The signaling range is u≈0 cells between each pair of neighboring u≈1 cells in the final pattern. The entire packing contains defects. This image is enlarged relative to panels A and B for the sake of clarity.Triangular lattice of (PDF)Click here for additional data file.S12 FigThe simulations analyzed here are the same simulations as in (TIF)Click here for additional data file.S1 TableThe same fish numbers are used in (PDF)Click here for additional data file.S2 TableSee Detection of grain boundaries in flat-mounted, row-traced retinae. Note that the percentage of Y-Junctions in grain boundaries depends strongly on the cutoff on the row orientation’s change; this threshold determines whether or not a Y-Junction is within a grain boundary. The percentage of Y-Junctions in grain boundaries depends only weakly on the size of the boxes over which we average row orientation .(PDF)Click here for additional data file.S3 Tablee.g., 4 and 8). These two samples have grain boundaries in neighboring non-photoconverted regions, but do not have defects within the photoconverted region itself. For each sample, we fit the positions of UV cone nuclei in the photoconverted region to a plane in order to compute a triangulation. Because the photoconverted region is small relative to the radius of curvature of the retina, the positions of UV cone nuclei are well fit (as quantified by RMSE) by a plane at both imaging times. In the UV cone triangulations, we check for bond flips near the defect core between photoconversion and later imaging (see Tracking UV cone positions in photoconverted regions and measuring glide motion). If a Y-Junction glides by one row, we denote that with a 1, and if a Y-Junction does not glide, we denote that with a 0.Here we quantify the motion of Y-Junctions within photoconverted regions. The fish labels are the same as in (PDF)Click here for additional data file.S4 Tablei.e., along the margin axis) between a new Y-Junction and its nearest grain boundary if each new Y-Junction’s position is uncorrelated with positions of existing grain boundaries. We, then, list the actual distances  between each newly incorporated Y-Junction and its nearest existing grain boundary in the image. Fish 8 is omitted because, within the image, no new Y-Junctions are added between photoconversion and later imaging. Note that whether a collection of defects is a grain boundary or not depends on how strongly the row orientation changes from one side of that collection of defects to the other side. We systematically change the cutoff in the angle of rotation of the row orientation that defines grain boundaries to see how our results depend on that cutoff.The fish labels are the same as in (PDF)Click here for additional data file.S5 TableR. Within each table, the noise in the initial conditions is varied. Note that each simulation has a unique ID, which we list in the same column as the simulation parameters. For each simulation, we list the total number of Y-Junctions and the number of Y-Junctions in grain boundaries. We find that the results depend weakly on the size of the boxes over which we average row orientation (see Detection of grain boundaries in simulated cone mosaic) but depend strongly on the cutoff in row orientation used to define whether a Y-Junction is in a grain boundary.We group the simulations into distinct tables based on the value of the undercooling parameter (PDF)Click here for additional data file.S6 TableSee Alternative method for detection of grain boundaries for a description of the alternative method for grain boundary detection. These retinae correspond to the same retinae in (PDF)Click here for additional data file.S1 VideoThe top and bottom (y) boundaries are periodic; the left and right (x) boundaries are no-flux. There are one hundred rows and one hundred columns.(ZIP)Click here for additional data file.S2 VideoThe cone is mapped to a flat plane here. The inner boundary (closest to origin) and the outer boundary (farthest from origin) are no-flux boundaries. The remaining two boundaries are periodic. There are two hundred initial rows.(ZIP)Click here for additional data file.S3 VideoThe cone is mapped to a flat plane here. The inner boundary (closest to origin) and the outer boundary (farthest from origin) are no-flux boundaries. The remaining two boundaries are periodic. There are two hundred initial rows. Note that the dimensions of this simulation domain are different than that of (ZIP)Click here for additional data file.S4 VideoThe cone is mapped to a flat plane here. The inner boundary (closest to origin) and the outer boundary (farthest from origin) are no-flux boundaries. The remaining two boundaries are periodic. The dimensions of the simulation domain are the same as in (ZIP)Click here for additional data file.S5 VideoThe cone is mapped to a flat plane here. The inner boundary (closest to origin) and the outer boundary (farthest from origin) are no-flux boundaries. The remaining two boundaries are periodic. The dimensions of the simulation domain are the same as in (ZIP)Click here for additional data file.S6 VideoThis simulation is of an anisotropic triangular lattice on a cone frustum with a couple of initial columns (masked with white noise). The cone is mapped to a flat plane here. The inner boundary (closest to origin) and the outer boundary (farthest from origin) are no-flux boundaries. The remaining two boundaries are periodic. There are two hundred fifty initial rows and approximately one hundred fifty columns.(ZIP)Click here for additional data file.


The outbreak of the SARS-CoV-2 virus in early 2020, known as COVID-19, spread to more than 200 countries and negatively affected the global economic output. Financial activities were primarily depressed, and investors were reluctant to start new financial investments while ongoing projects further declined due to the global lockdown to curb the disease. This study analyzes the money supply reaction to the COVID-19 pandemic using a cross-sectional panel of 115 countries. The study used robust least square regression and innovation accounting techniques to get sound parameter estimates. The results show that COVID-19 infected cases are the main contributing factor that obstructs financial activities and decrease money supply. In contrast, an increasing number of recovered cases and COVID-19 testing capabilities gave investors confidence to increase stock trade across countries. The overall forecast trend shows that COVID-19 infected cases and recovered cases followed the U-shaped trend, while COVID-19 critical cases and reported deaths showed a decreasing trend. Finally, the money supply and testing capacity show a positive trend over a period. The study concludes that financial development can be expanded by increasing the testing capacity and functional labs to identify suspected coronavirus cases globally. The control of excess money supply and credit creations through bank rates is considered one of the oldest instruments for monetary policy adoption by the central bank to re-settle economic issues Auclert . The advFigure (i)To examine the impact of coronavirus infected cases, reported deaths, critical cases, and recovered cases on money supply in a cross-sectional panel of 115 countries.(ii)To evaluate the role of coronavirus testing capacity in improving financial development across countries, and(iii)To analyze the forecast evaluation of the candidate variables over a time horizon.This study used four main factors for analyzing the COVID-19 pandemic  and the money supply, while earlier studies were limited to a few variables  as a proxy variable for financial development served as a “regressand variable.” In comparison, the counts of coronavirus registered cases (denoted by CASES), death cases (denoted by DEATHS), recovered cases (denoted by RECOVERED), critical cases (denoted by CRITICAL), and coronavirus testing (denoted by TEST) served as “regressors.” The available data for the M2 variable is taken from World Bank , whereasThe study used the following equation to assess the effects of COVID-19 pandemic on money supply during increased testing capacity and reported critical cases:Equation  shows th.COVID-19 registered cases, critical cases, and reported deaths will negatively impact money supply across countriesMoney supply is expected to have a positive response to increased COVID-19 recovered cases, and.An increase in testing capacity for COVID-19 will positively impact the money supply.These hypotheses are essential to analyze and devise strong global financial policies. The study used sequential steps for statistical analysis.The RLS estimator is the extended version of the simple least square regression, which addresses possible outliers of the dependent variable (by M-estimation technique), independent variables (by S- estimation technique) and simultaneously handle outliers from the regressand and regressors (by MM-estimation technique) from the model. The study used the M-estimation technique, as the money supply widely fluctuated during the COVID-19 pandemic. The M-estimation is abbreviated to "maximum likelihood estimator-like," magnifying the possible outliers in the regressand. This estimator is also known as the Huber-M estimator, as Huber  proposedi-th variable has translated into other system endogenous variables via the dynamic lag structure. The function traces the i-th shock of innovations on present and future endogenous variables during the VAR system. The VDA innovation technique is somehow different from the IRF estimates, as IRF estimates mark out the system shock one to other endogenous variables. At the same time, VDA provides the importance of the components shocks that separate it from the endogenous variable in random innovation in the VAR system.The innovation accounting matrix (IAM) procedure is based on the Vector autoregression (VAR) system's two innovation techniques, that is, impulse response function (IRF) and variance decomposition analysis (VDA). The IRF estimates show that systematic shocks about the "Root Mean Square Error (RMSE),""Mean Absolute Error (MAE),""Mean Absolute Percentage Error (MAPE)," and"Theil inequality coefficient."The study further moves towards the forecast evaluation by four methods:These methods predict future deviation in individual variables where one can assess the candidate variables' direction over a time horizon.Table Table The results of the study further connected with the findings of the subsequent studies that concluded that financial trading is affected due to increase COVID-19 infected cases (see, Erdem Table Table Table Figure This study assessed the financial volatility in global stock trading during the COVID-19 pandemic, and at the same time, the role of coronavirus testing and operational labs in building investors’ confidence through ex-ante and ex-post analysis, using cross-sectional data from 115 countries. The earlier studies were limited to either ex-post analysis or simulation to show ex-ante analysis. The study results found that coronavirus infected cases are considered the main factor that has impeded financial activities, while recovered cases and increased testing capacity together with functional labs, support financial development across countries. The innovation accounting matrix suggested that an increase in the coronavirus critical cases and reported deaths are likely to negatively impact financial development which can be improved by increased testing capacity and functional labs. The U-shaped forecast trends are visible in the coronavirus infected cases and recovered cases, while the substantial decline is likely to exhibit in the critical cases and reported deaths. Money supply and testing capacity both are likely to increase over a period of time.The COVID-19 pandemic unprecedented increase in healthcare expenditures negatively impacted global economic activities. The nationwide lockdown, social distancing, transport and travel restrictions imposed many adverse effects on countries' economic growth, leading to a financial crisis. The low financial returns, high volatility in financial instruments, and stock market performance decrease caused many unprecedented challenges that has led the world economies into a global depression. The importance of supply chain in business operations and economic process remains viable in supporting financial trading. Organizational performance can be improved through buyer engagement in sustainable production to achieve social and environmental sustainability (Awan et al. The study has the following limitations that open the door for future studies to work on the stated theme to fill it with relevant factors. Firstly, the study used a single factor for assessing financial development, while it may add two to three more economic modeling factors for getting insights into financial sector reaction to the COVID-19 pandemic. Secondly, a list of a few other exogenous factors can be added, i.e., population density, per capita income, and real exchange rate, that create new empirical insights of the statistical inferences. Finally, the quantile regression technique can use for empirical testing that may show variations in the parameter estimates at different quantiles distribution. Hence, the greater need to study the risk of the COVID-19 pandemic on the global supply chain process can be projected in future studies.


There are limited data regarding the impact of bioresorbable polymer drug eluting stent (BP-DES) compared to durable polymer drug eluting stent (DP-DES) in patients treated with percutaneous coronary intervention using ultrathin stents in left main or bifurcations.In the RAIN registry  patients with a ULM or bifurcation stenosis treated with PCI using ultrathin stents (struts thinner than 81 μm) were enrolled. The primary endpoint was the rate of target lesion revascularization (TLR); major adverse cardiovascular events  and its components, along with target vessel revascularization (TVR) were the secondary ones. A propensity score with matching analysis to compare patients treated with BP-DES versus DP-DES was also assessed.p = 0.22) and MACE were similar  as well as for the other endpoints. Sensitivity analysis of outcomes after a two-stents strategy, showed better outcome in term of MACE  and TVR  and a trend towards lower TLR in patients treated with BP-DES.From 3001 enrolled patients, after propensity score analysis 1400 patients (700 for each group) were selected. Among them, 352 had ULM disease and 1048 had non-LM bifurcations. At 16 months (12–22), rates of TLR (3.7% vs 2.9%, In patients with bifurcations or ULM treated with ultrathin stents BP-DES seems to perform similarly to DP-DES: the trends toward improved clinical outcomes in patients treated with the BP-DES might potentially be of value for speculating the stent choice in selected high-risk subgroups of patients at increased risk of ischemic events.NCT03544294. Retrospectively registered June 1, 2018.ClinicalTrials.gov Identifier:  The treatment of unprotected left main and of coronary bifurcation still represents a challenge for interventional cardiologists due to both procedural complications and higher restenosis rates compared with non-bifurcation lesions –4.milieu is rooted into the unique flow patterns that characterized them, with local low and oscillatory endothelial shear stress along the lateral walls of the main vessel and of the side branch, whereas high endothelial shear stress develops at the carina. This ultimatey leads to a prothrombotic and atherogenic flow-pattern, and even after treatment with percutaneous coronary intervention (PCI), it may increase the failure rate wit need for subsequent revascularization on the target lesion (TLR) and an increased risk of stent thrombosis (ST) [The complexity of the bifurcation sis (ST) –6.In the last years, BP-DES (Bioresorbable polymer drug eluting stents) have been introduced with the rationale to potentially decrease ST. Differently from durable polymer stents (DP), after the elution of the antiproliferative drug the bioreabsorbable polymer is going to dissolve leaving behind a bare metal stent, thus reducing the local inflammatory reactions and therefore the risk of thrombosis related to a permanent polymer. Clinically, this translated into lower rates of TLR for BP-DESs implanted in coronary bifurcations in the LEADER-FREE , althougIn light of the intrinsic limitations of the above studies, the RAIN study  was designed to evaluate the clinical performance of ultrathin stents in everyday clinical practice. We here present an analysis of the RAIN study aimed to evaluate the safety and efficacy of BP-DES in the bifurcation setting.The RAIN is a large multicenter retrospective observational registry , Optical Coherence Tomography (OCT) and Fractional Flow Reserve (FFR) were recorded, along with the characteristics of the implanted stents. IVUS or OCT was used prior to stent implantation to assess the severity of the stenosis and side branch involvement, and post stent implantation to evaluate dissection and the requirement for stent optimisation. The decision to post-dilate, to perform final kissing balloon (FKB), to assess intracoronary imaging and the choice of the stenting technique , was at the discretion of the treating physician.http://www.cardiogroup.org/RAIN/index.php?cat=home).The above data were derived from electronic patient records at each center, while follow-up data were obtained from clinical assessment, telephonic consultations or via primary care physicians and then recorded online  and its components, along with TVR were the secondary endpoints. The analyses were performed according to PCI strategy .chi-square test for categorical variables and Fisher’s exact test for 2 × 2 tables. The a priori statistical significance level was set at α = 0.05. To account for clustered data among centres we used a normal regression (ANOVA) approach with a fixed effect for cluster and an effect for group when data were normally distributed. For non-normal data, we used the Wilcoxon rank sum test modified to account for clustering. For propensity score, first logistic regression analysis was done for all baseline features that differed between BP-DES and DP-DES, matching was computed after division into quintiles and methods of the 1:1 nearest neighbor on the estimated propensity score [Categorical variables are reported as count and percentages, whereas continuous variables as mean and standard deviations or interquartile range (IQR). Gaussian or not Gaussian distribution was evaluated by Kolmogorov-Smirnoff test. The t-test has been used to assess differences between parametric continuous variables, Mann-Whitney U test for non parametric variables, the ty score . CalibraAt the end of the enrolling period 3001 patients had been recorded: 2120 were treated with DP-DES ad 881 with BP-DES , with a higher rate of previous MI  and they were more often admitted due to STEMI . On the other side, patients with DP-DES were more often hyperlipidemic , and with true bifurcation involvement . They were less frequently treated with two-stent technique . Finally, there was a similar rate of total ULM disease   and true bifurcation involvement . Provisional strategy was successfully performed in both groups in the majority of patients  and MACE were similar , without significant differences among all the secondary endpoint  months, rates of TLR  and TVR .At sensitivity analysis for patients treated with two stents strategy, patients treated with BP-DES showed a better outcome in term of MACE  in patients with a ULM stenosis treated with PCI using newer-generation abluminal BP- DES as compared to the DP-DES.BP-DES have been developed to combine the best of both family of metallic stents, i.e. the efficacy of DES and the late safety associated with BMS. However, the available evidences on cardiac death, MI, or stent thrombosis are still scarce –17: netwThe principal finding of our current analysis is that BP-DES actually showed a similar safety and efficacy profile at 5 years compared with the DP-DES. Notably - apart from ST - event rates in our study were low keeping into account the clinical and anatomical complexity of the enrolled patients, and similar to previous studies on new-generation DES , 17. TheThe second interesting result is the trend towards better outcome in term of MACE and TVR in patients treated with BP-DES and a two stents strategy. The higher risk of subsequent events in this challenging anatomical subset is well known, and it is related either to patient either to technique drawbacks , 24. DesAs regard the percentage of stent thrombosis we found, we should not forget that such high numbers are actually in line with other real life reports with comparable follow-up . FurtherThere are several limitations to this study. First, this was not a randomized controlled study: with the use of propensity score we could not adjust for variables which were not possible to collect (e.g. the experience of the physicians performing PCI) or others among multiple factors that might be implicated in DES acute thrombogenicity and long-term vascular healing The main message is that BP-DES look as safe as DP-DES even in high anatomical risk setting like LM disease. Furthermore, the provisional approach confirms itself as the safer on the long term. Finally, when a two-stent strategy is absolutely needed, the trends toward improved clinical outcomes with respect to MACE and TVR we found with BP-DES might potentially be of value to speculate about the stent choice in selected high-risk subgroups of patients at increased risk of ischemic events.Additional file 1 Supplementary Methods. List of leading and participating study centres. Lists of stents used in the study. Supplementary Table 1. Baseline and interventional characteristics before the propensity score.


M) was suggested as a statistical measure of physiological dysregulation in aging individuals. We constructed DM variants using sets of biomarkers collected at the two visits of the Long Life Family Study (LLFS) and performed joint analyses of longitudinal observations of DM and follow-up mortality in LLFS using joint models. We found that DM is significantly associated with mortality  after controlling for age and other covariates. GWAS of random intercepts and slopes of DM estimated from joint models found a genome-wide significant SNP  in the TRIO gene associated with the slope of DM constructed from biomarkers declining in late life. Review of biological effects of genes corresponding to top SNPs from GWAS of DM slopes revealed that these genes are broadly involved in cancer prognosis and axon guidance/synapse function. Although axon growth is mainly observed during early development, the axon guidance genes can function in adults and contribute to maintenance of neural circuits and synaptic plasticity. Our results indicate that decline in axons’ ability to maintain complex regulatory networks may potentially play an important role in the increase in physiological dysregulation during aging.Recently, Mahalanobis distance (D Cross-sectional measurements of such biomarkers correspond to the instantaneous profile of the current physiological state of an organism which provides valuable information about the current aging status of the body. Numerous studies show that such biomarkers are associated with risks of death and aging-related diseases . Howeviews in . To inveAnalyses of longitudinal studies of aging present special methodological challenges due to inherent complexities that need to be taken into account to avoid biased inference. An essential assumption of such analyses is that the longitudinal outcomes  can be related to the risk of death so that the probability of having a missing value because of death depends on an unobserved value, which is missing not at random (MNAR) . This meM)  in whites, according to the NIH-supported online tool LDlink,https://ldlink.nci.nih.gov) that are associated with -5) with M variants . To check whether the signals observed in the analyses of -8; this SNP is located near GRM3, a glutamate receptor gene involved in brain functioning). The D-8 to p=9.7×10-9; p-values for the second-ranked SNP rs16903264 varied from p=3.3×10-8 to p=1.4×10-8). However, the genome-wide significant signal for grip strength found in the analyses with 20 PCs Hazard ratios (HR) of all-cause mortality risk for DM variables are per standard deviation: We also performed sensitivity analyses running the models with different numbers of principal components . The top two signals for -8 for the model with 2 PCs). In addition, we performed analyses of DM variants constructed using different sets of biomarkers selected according to other thresholds for correlation with age  which did not produce any genome-wide significant signals. We also ran the model with time-interaction terms for all covariates (except age) in the fixed effects part of the longitudinal sub-model in JM. All interactions were non-significant except that for country . The GWAS results for -9 for rs12652543 and p = 7.4×10-9 for rs16903264). did not M) using multiple biomarkers collected at two visits in the LLFS using the original approach from , the association of DM with mortality in LLFS is significant and effect sizes are substantial . Comparisons of joint models with the Cox regression model with DM considered as a time-dependent covariate indicated that the values of the association parameter for DM in the hazard are underestimated in the Cox model, as expected  processes, KEGG, BioCarta and Reactome pathway collections, among other. We also run the enrichment analysis using a commercial MetaCore platform for the functional analyses, by Clarivate Analytics (https://clarivate.com/products/metacore/), which uses custom-made manually curated libraries of pathways and processes, along with open-access ontologies, such as the GO and other /no [0]), medication use  , and fasting . The groups of medications indicated above were constructed by the LLFS investigators in a separate study from original medications records using the corresponding Anatomical Therapeutic Chemical Classification System codes. We note that this list of medications does not include all possible groups of medications that might be relevant for this analysis . The time-to-event outcome  was modeled as the standard relative risk form [M . See also sensitivity analyses with other specifications of JM described in Results.In our applications, the longitudinal trajectories of Disk form  with theub-model ) includeub-model  was chosM-related traits constructed using the output of the joint models estimation procedure for the respective DM variants specified above: random intercept (DM-RI) and random slope (DM-RS). These characteristics were computed for each study participant and define how the baseline value of DM (DM-RI) and the age dynamics of DM (DM-RS) in the particular individual differed from the average values in the study sample .We performed GWAS of two D-5. The resulting sample after QC contained 4,608 individuals of European ancestry  and 1,464,300 autosomal SNPs which passed the QC procedure.The QC procedure was performed according to the protocol described in  before rThe R-package GENESIS (Bioconductor)  was usedM variants computed from biomarkers selected using different thresholds for correlation with age, GWAS for separate biomarkers constituting the specific DM variant, and analyses with different number of PCs, as described in Results.We also performed sensitivity analyses to test the sensitivity of our results to various aspects of the analytic procedures. This included running GWAS for DSupplementary FiguresSupplementary Tables 1 and 2Supplementary Table 3Supplementary References


Climate is an important driver of changes in animal population size, but its effect on the underlying demographic rates remains insufficiently understood. This is particularly true for avian long-distance migrants which are exposed to different climatic factors at different phases of their annual cycle. To fill this knowledge gap, we used data collected by a national-wide bird ringing scheme for eight migratory species wintering in sub-Saharan Africa and investigated the impact of climate variability on their breeding productivity and adult survival. While temperature at the breeding grounds could relate to the breeding productivity either positively (higher food availability in warmer springs) or negatively (food scarcity in warmer springs due to trophic mismatch), water availability at the non-breeding should limit the adult survival and the breeding productivity. Consistent with the prediction of the trophic mismatch hypothesis, we found that warmer springs at the breeding grounds were linked with lower breeding productivity, explaining 29% of temporal variance across all species. Higher water availability at the sub-Saharan non-breeding grounds was related to higher adult survival  but did not carry-over to breeding productivity. Our results show that climate variability at both breeding and non-breeding grounds shapes different demographic rates of long-distance migrants. Despite the widespread influence of climatic conditions on animal populations3, their impacts on species’ demographic rates are still insufficiently known in many organisms. This is particularly true for long-distance migratory birds. Study of climatic impacts on their demographic rates is challenging because these species travel for thousands of kilometres and visit different regions where they are exposed to various drivers6. Therefore, simultaneous assessments of climatic factors acting on demographic rates in different phases of migrants’ annual cycle are needed7. For this purpose, we focused on two important demographic rates reflecting the influence of climatic factors at the breeding and the non-breeding grounds—breeding productivity and adult survival, in Afro-palearctic migratory birds.Climate is a key driver governing the spatial distribution of biodiversity8, climate change alters suitability of their habitats with consequences for their demography9. At the breeding grounds, migrants’ demography may be shaped by spring temperature acting upon breeding productivity11. Theoretically, two different relationships between temperature and breeding productivity are possible. In the first scenario, birds may benefit from higher temperatures due to earlier breeding enabling more breeding attempts per season resulting in higher number of juveniles produced per female12. In addition, higher temperatures result in higher amount of environmental energy, higher ecosystem productivity and thus more food resources available for birds during the breeding season13. The second scenario predicts the opposite pattern, i.e. a negative relationship between spring temperature and breeding productivity of long-distance migrants. Under this scenario, higher spring temperature results in altered interspecific interactions with the most influential trophic mismatch hypothesis in predator–prey interaction14. According to this hypothesis, warmer spring results in phenology shifts differing among trophic levels: since lower trophic levels typically shift faster16, a time lag between the peak of food supply for birds  and food demand of rearing nestlings occurs17. Consequently, nestlings have lower body condition resulting in reduced number of fledged juveniles and thus lower breeding productivity19.As each species is adapted to a specific range of climatic conditions20, temperature in late spring reflects conditions during breeding of long-distance migrants3 and may control the number of breeding attempts21. In addition, temperature may affect food availability22. It is thus interesting to study the relationships between the breeding productivity of long-distance migrants and spring advancement using different descriptors containing both early and late spring temperature, as well as variables describing ecosystem responses to weather conditions: growing degree days (accumulated temperatures above certain threshold) and dates of leaf unfolding25. One could expect that such variables describing the ecosystem responses will have stronger relationships to the breeding productivity than temperature per se.The influence of spring temperature on birds’ breeding may be complex. While early spring temperature shapes the environment before or during the arrival of long-distance migrants and controls bud burst and invertebrate phenology3. The water availability may affect populations of long-distance migrants by its influence on adult survival and subsequent breeding productivity. Higher water availability increases both primary and secondary productivity, providing more food resources for birds1. Therefore, adult survival of Afro-palearctic migrants should be higher in years when more water is available in the ecosystems at their non-breeding grounds28. Climate variability at non-breeding grounds may also carry-over to affect the breeding performance29. For instance, a lower water availability in Africa may delay migrants’ arrival to breeding grounds31, reduce body condition after arrival32, and affect recruitment, brood size and number of fledglings33. However, non-breeding grounds of the Afro-palearctic migrants cover very large areas, ranging from highly arid Sahel zone to the humid rainforests in equatorial regions34. We can expect that the potential positive effect of higher water availability on adult survival and subsequent breeding productivity may be larger in regions with more severe water limitation1.At the Afrotropical non-breeding grounds, climatic factors shaping long-distance migrants’ demographic rates are mainly represented by the water availability in ecosystems35 for review). In this study, we aim to overcome these limitations by exploiting data collected for multiple species within a nation-wide citizen science programme based on constant effort long-term mist-netting of breeding birds. We assessed the influence of climate variability on migrants’ breeding productivity and adult survival. Specifically, we tested (1) whether the breeding productivity is higher in warmer or in colder springs; (2) whether the early spring or late spring temperature have stronger relationship to the breeding productivity; (3) whether the variables describing climate variability directly (i.e. temperatures) show stronger relationships to the breeding productivity than the measures related to resources (i.e. woody plant phenology) because we can expect that the endotherm organisms like birds will respond to the resources rather than to the temperatures per se; (4) whether adult survival and breeding productivity are positively related to higher water availability in sub-Saharan non-breeding areas.The majority of previous studies linking climate variability with demographic rates of long-distance migratory birds faced one or more of the following limitations: they focused on a single demographic parameter (e.g. productivity), did not consider both breeding and non-breeding grounds, studied a single species or even a single population, or covered only a few sampling sites  only in a few models  in the sub-Saharan non-breeding grounds on long-distance migrants’ breeding productivity was weak Table b,c. Althels Fig. . Finallyels Fig.  and S3.We repeated the analyses with short-distance migrants, partial migrants, and residents  in the Sahelian part of sub-Saharan non-breeding grounds Fig. . In the When performing the analysis for each species separately Table , higher Our study aimed to assess links between climate variability and two key demographic rates, productivity and adult survival, in avian long-distance migrants. We found that migrants’ breeding productivity was lower in warmer springs. Our models indicated that the early spring temperature performed better than the late spring temperature and that the temperature per se had lower explanatory power than the variables describing advancement of the ecosystems (i.e. growing degree days and date of woody plants’ leaf unfolding) explaining up to 29% of variability in the breeding productivity. In addition, the breeding productivity was negatively related to population density. Higher water availability at the sub-Saharan non-breeding grounds was positively related to migrants’ adult survival, explaining up to 18% of variability, and the positive effect of water availability was higher when considering the Sahel zone than when considering the southern part of the non-breeding grounds. In contrast, the carry-over effects of water availability at the non-breeding grounds on breeding productivity were weak.37. When considering potential mechanisms, this result is consistent with the hypothesis of trophic mismatch14. It predicts that long-distance migrants suffer from fitness costs due to the spring advancement because they are unable to adjust timing of their breeding adequately38. Although the lower breeding productivity may be viewed as an obvious cost of warmer weather to long-distance migrants’ fitness, studies showing such a relationship are surprisingly infrequent. Negative relationship between productivity and spring temperature has been only seen in pied flycatcher in Poland and Spain41, barn swallow in Denmark23, seabirds44 and snow goose45 and Baird’s sandpiper46 in the Arctic. Many other studies on productivity show no such relationship47. This suggests that the warmer spring translates into population-level fitness costs only under certain circumstances and if these conditions are not met, no consequences of trophic mismatch are observed.Breeding productivity was negatively related to warmer springs, supporting the hypothesis that the more rapid spring advancement results in lower fitness of long-distance migrants, with population-level consequences48. This is particularly the case for residents or short-distance migrants, species with more flexible phenology than the long-distance migrants49. Such species may even benefit from warmer springs, as our data imply for the short-distance migrants  than to the late spring temperature . This result implies that breeding productivity is more affected by the weather conditions during or even before the species’ arrival to the breeding grounds than by the conditions the birds face during more advanced breeding phases. It may be caused by decisive impacts of the early spring phenology on food availability for birds in ecosystems27 and studies have tested their effects using single species69 or inferred their influence on migrants’ population dynamics without a specific test for relationships to adult survival70. However, broader formal assessments of the general validity of these relationships were lacking (but see28). Here we show that the influence of water availability at sub-Saharan non-breeding grounds was important when considering the northern (Sahelian) part, but less so in the southern part of the non-breeding ranges.The influence of climatic conditions at the non-breeding grounds on migrants’ survival has been discussed for decades71. In addition, trans-Saharan migrants frequently stopover in the Sahel to restore the reserves after and before crossing the Sahara Desert72. Drought events in the Sahel thus have serious consequences even for species spending the winter further south72. However, in our study the importance of different non-breeding regions differed at the species level. Together with previous studies, we found that conditions in the Sahel were important for sedge warbler and common whitethroat27, whereas willow warbler and reed warbler were more affected by water availability in southern parts of their non-breeding ranges.The key importance of moisture in the Sahel can be explained by the relatively low water availability and thus its stronger limiting effect on organisms in the northern part of sub-Saharan Africa compared to more southern regions73.). It can be explained by rather indirect causal pathways that act in these relationships when other factors affecting the breeding productivity can balance the adverse effects of water stress at the non-breeding grounds. For example, limited water availability results in increased migrant mortality during winter, but the individuals which do arrive successfully to the breeding grounds enjoy weaker intraspecific competition74. In turn, their body condition can improve and no adverse consequences on breeding performance may be observed. Indeed, the importance of intraspecific competition for breeding performance has been frequently reported (e.g.73.).In contrast to the importance of the non-breeding grounds’ climate variability for adult survival, we did not detect any significant carry-over effects of the water availability at the non-breeding grounds on the breeding productivity. Previous studies also reported a weak carry-over effect  affected both the breeding productivity and adult survival of long-distance migratory birds. Regression slopes and explained variability show that the relationships between spring advancement at the breeding grounds and the breeding productivity were stronger than the relationships between water availability at the non-breeding grounds and adult survival. However, it is difficult to correctly compare the importance of conditions at breeding and non-breeding grounds. As there are great uncertainties in locations of species’ non-breeding grounds77. For the present study, we used data from a total of 42 sites scattered throughout the country. At each site, birds were mist-netted during 9 visits in ca. 10-day intervals covering the advanced breeding season (May–July). We used data on all species available, except for species with less than 30 inter-annual recaptures and species recorded at less than 7 sites in any of the years, as these captures could not be used to get reliable estimates of demographic rates. In the end, we used data on eight long-distance migratory species (Supplementary Table 78.Bird population data were collected within the Constant Effort Sites (CES) mist-netting scheme in the Czech Republic during 2004–2014. The CES scheme focuses on the annual collection of capture-mark-recapture data for birds using a network of skilled volunteers using a standard protocolhttps://datazone.birdlife.org/species/search). To identify non-breeding grounds of Czech long-distance migrant populations, we intersected these ranges with those of77. In77, the ranges were defined based on all ringing recoveries collected in the Czech Republic . Because the number of ringing recoveries from sub-Saharan Africa was too low for the exact location of the migrants’ non-breeding grounds, the authors of77 divided sub-Saharan Africa into four large geographic regions and matched the non-breeding range of each species with one or more of these four regions , we further split the species’ non-breeding ranges into a Sahelian part and a part south of the Sahel , which reflects conditions during the breeding of long-distance migrants; growing degree-days in March and April ; date anomaly of 10% leaf unfolding of three tree species —these woody plant species reflect in a wide range of ecological conditions (from humid to dry habitats and from lowlands to highlands) and they are well-represented in sites where the focal bird species breed. The phenophase of 10% unfolding means that 10% of the plant leaves have started to unfold, having the whole midrib visible already, but the leaf is still partially folded80. We expressed the date anomaly of 10% leaf unfolding as a number of days before the long-term mean to reconcile the direction of all variables describing spring advancement  facilitating comparison of their performance. Temperatures and GDD5 were calculated as the average from 18 meteorological stations situated in proximity to the monitored area; the 10% leaf unfolding date anomaly was calculated as the median date from all 26–27 meteorological stations across the Czech Republic where these data were available .To describe spring advancement at the breeding grounds, we used the following variables provided on an annual basis from 2004 to 2014 by the Czech Hydrometeorological Institute: mean temperature in early spring (March and April), which shapes environmental conditions preceding or during the arrival of long-distance migrants and controls bud burst and invertebrate phenology81 and is reported to be better predictor of bird distribution82. The monthly data on AET/PET were obtained from MODIS MOD 1683, in particular MOD16A2 monthly data in the GeoTIFF raster format with 0.5 degree resolution. We considered three variants of non-breeding ranges . Unlike commonly used measures like rainfall, which is a measure of water income, or indirect measures like NDVI, AET/PET much more directly quantifies the amount of water available in the ecosystemges Fig. b: (1) th86 in R87. We fitted species-level models (separate model for every species), as well as cross-species models , and also to account for the breeding productivity difference between sites, we included random effects ‘species:year’ and ‘species:site’, respectively (year and site in species-level models). We also included a random intercept effect for species in cross-species models. It would have been beneficial to include a random slope effects of the covariates as well, but some of those models resulted in singular fit, suggesting they were too complex, so we did not use it in order to keep models comparable. We only used the random slope effect to evaluate the proportion of temporal variance explained by climatic covariates  because the explanatory power of these covariates would be underestimated without the species-specific component of the slope. To calculate the proportion of explained temporal variance (R2_var), we adopted the method proposed in88, their chapter 5.7, and in89, their p. 378, Eq. 7, generalized to cross-species model: R2_var was computed as (To relate the breeding productivity to the spring conditions at the breeding grounds and to the carry-over effect of water availability (AET/PET) in the sub-Saharan non-breeding grounds, we employed logistic regression using generalised linear mixed models (GLMM), using the glmer function in ‘lme4’ packageIn the productivity analysis, we excluded the year 2013 because of extreme weather conditions during late spring, with abnormally heavy rain and floods in May and June resulting in extraordinary low productivity clearly unrelated to our focal effect of spring advancement.To assess the impact of water availability in sub-Saharan Africa on the survival of adult birds of each long-distance migrant species, we used the Cormack–Jolly–Seber (CJS) survival model. Inter-annual survival between two consecutive years was modelled as a linear function (after logit transformation) of AET/PET in a given non-breeding season  if captured in two different occasions (regardless if they occur in the same breeding season or not). Transience, i.e. the probability that an individual is transient, was modelled as constant. We tested the temporal trend in transience by modelling it as a linear function of year, but it was not significant for any of the species. Models were computed in the program MARK ran within the R-package ‘RMark’91.Estimates of adult survival are often biased due to the presence of transient individuals, i.e. those being captured, but not being residents at a site, in the focal population2_dev) using the ANODEV method88 . Then, to assess the overall impact across species, we computed the mean of all AET/PET coefficients across all species, taking also their standard errors into account using the meta-analytic Bayesian approach described in88. This model was fit in JAGS, with 3 chains, 200 000 iterations and disposing the first half as burn-in.Next, we computed the percentage of deviance explained by the climate variable . All explanatory variables describing spring advancement at the breeding grounds and water availability at the non-breeding grounds were standardized to zero mean and unit variance before the analysis.All Bayesian models were fitted with uninformative priors. Convergence was tested using a potential scale reduction factorCES programme is organized by the Czech Bird Ringing Centre of the National Museum, Prague, with all voluntary ringers being attested by the Czech Bird Ringing Centre to conform the regulation no. 152/2006 of the Ministry of Environment of the Czech Republic on The Exception of Bird Capturing for Ringing Purposes based on the law no. 114/1992 on The Nature and Landscape Protection. The experimental protocol of CES was approved by the National Museum, Prague. The study was performed in accordance with relevant guidelines and regulations.Supplementary Information.Supplementary Table S2.Supplementary Table S3.Supplementary Table S4.Supplementary Table S5.