Modelling and palaeoclimate evidence suggest that rapidly increasing temperatures in the Arctic can trigger positive feedback mechanisms for the GrIS, leading to self-sustained melting4, and the GrIS has been shown to permit several stable states5. Critical transitions are expected when the global mean temperature (GMT) crosses specific thresholds, with substantial hysteresis between the stable states6. Here we use two independent ice-sheet models to investigate the impact of different overshoot scenarios with varying peak and convergence temperatures for a broad range of warming and subsequent cooling rates. Our results show that the maximum GMT and the time span of overshooting given GMT targets are critical in determining GrIS stability. We find a threshold GMT between 1.7 °C and 2.3 °C above preindustrial levels for an abrupt ice-sheet loss. GrIS loss can be substantially mitigated, even for maximum GMTs of 6 °C or more above preindustrial levels, if the GMT is subsequently reduced to less than 1.5 °C above preindustrial levels within a few centuries. However, our results also show that even temporarily overshooting the temperature threshold, without a transition to a new ice-sheet state, still leads to a peak in SLR of up to several metres.Melting of the Greenland ice sheet (GrIS) in response to anthropogenic global warming poses a severe threat in terms of global sea-level rise (SLR) Simulations using two state-of-the-art ice-sheet models show that abrupt melting of the Greenland ice sheet following overshooting of the global mean temperature critical threshold can be mitigated by subsequent cooling to below 1.5 °C. Modelling results indicate that the GrIS exhibits several stable states, with critical transitions between them when the GMT exceeds a critical threshold8. With further global warming, a partial to complete loss of the ice sheet is expected, implying an increase of the global sea level by up to 7 m (refs. 9). The land-ice contribution to SLR until the year ad 2100 is expected to be in the range of several decimetres, with the GrIS being one of the main contributors12. As well as the direct impacts on coastal ecosystems and populations, the North Atlantic freshening resulting from a melting GrIS might contribute to a weakening or even destabilization of the Atlantic Meridional Overturning Circulation (AMOC), which would have global-scale impacts, including disruptions of the African and Asian monsoon systems16.Melting of the GrIS has contributed more than 20% to the observed SLR since 17 and there are precursor signals of an impending critical transition detectable in ice cores from the central-western GrIS18. There is, therefore, a need to explore the future trajectories of the GrIS under different emission scenarios. Furthermore, it is important to understand what is required to prevent a runaway effect. The so-far insufficient efforts to reduce global emissions make it necessary to investigate scenarios in which we do not achieve current warming targets, such as those defined in the Paris Agreement, by the end of the twenty-first century21. Different options to remove CO2 from the atmosphere, including carbon capture and storage technologies and large-scale reforestation, could make it possible to maintain such temperature goals in the long term, even if a temporary overshoot occurs22. These subsequent efforts to reduce GMTs after ad 2100 could have a substantial mitigating effect because many of the large-scale components of the climate system change slowly compared with the current rate of global warming. In the following, we refer to temporary exceedances of temperature targets or critical temperature thresholds as overshoots and to the equilibrium temperatures that will be reached in the long term as convergence temperatures.In recent decades, meltwater runoff from the GrIS has accelerated relative to global surface temperatures23. Thus, the temperature threshold of the GrIS could be surpassed without committing to total mass loss, if later on, yet within a specific time frame, actions are taken that reduce the temperature back under the critical threshold.Owing to the effect of inertia, crossing a critical threshold in a dynamical system with several stable states does not necessarily imply that a transition to an alternative state is realized. It is possible to temporarily overshoot the tipping threshold of a system without triggering a transition to a new system stateThe overshoot phenomenon is particularly relevant for the GrIS because the timescales for mass loss are long compared with changes in anthropogenic greenhouse emissions. The separation of timescales could make it possible to reverse ice loss if global surface temperatures decrease sufficiently quickly after an initial overshoot. However, because of the complexity of the ice sheet and the various physical processes that play a role, including ice flow and surface processes, it is intrinsically challenging to determine the temperature thresholds and required cooling rates that will prevent a substantial loss of the GrIS.1. Subsequently, we apply different idealized carbon-removal scenarios that lead to a temperature decrease on timescales varying from one hundred to tens of thousands of years  model27. Both approaches have been extensively tested and validated and have been used to simulate the past, present-day and future evolution of ice sheets32.We investigate the behaviour of the GrIS using two independent, state-of-the-art ice-sheet models: a new version of the Parallel Ice Sheet Model (PISM) with a modified version of the diurnal Energy Balance Model (dEBM-simple) for the surface mass balanceWe force the two models, PISM-dEBM-simple (hereafter PISM-dEBM) and Yelmo-REMBO, by a prescribed change in regional summer temperature relative to present day and apply a scaling factor of 1.61 between regional winter and summer surface temperature to obtain the temperature forcing over the seasonal cycle. This forcing can then be translated into GMT above preindustrial through a linear scaling that accounts for higher warming rates in the Arctic region relative to the global mean (see ad 2000 (present day) to ad 2100 to a maximum summer temperature anomaly of ΔTmax,JJA , that is, the time needed to reach the convergence temperature, with Δtconv spanning from 100 years to several millennia for various convergence temperatures. We then investigate the behaviour of the GrIS for these different cooling scenarios.In a first set of experiments, we force the models with a prescribed linear summer ) temperature increase from year JJA Fig. . Thereafad 2100, the temperature increase during the twenty-first century leads to at least some further melting of the GrIS for every prescribed positive temperature anomaly  by ad 2200 or lower leads to a stable ice sheet, with the equivalent of less than 1 m long-term SLR contribution in simulations with both models , the models show very similar SLR contributions and the maximum ice-volume loss before ice-sheet regrowth is in the range of 50 cm SLR equivalent  to capture surface albedo feedbacks. This improves on the more conventional positive degree-day parameterization, which might fail for past and future climate conditions34. However, the timescale of this feedback is still debated41 and is often neglected on sub-millennial timescales3. The fluctuations of the ice sheet on a decamillennial timescale simulated by PISM-dEBM are believed to be the consequence of an interplay between bedrock uplift and melt-elevation feedback42. We find that the intermediate GrIS states found with PISM-dEBM are at least partially caused by the interplay between the glacial isostatic adjustment and melt-elevation feedback and we find fewer intermediate states without bedrock uplifting  and the glacial isostatic rebound and should certainly be studied with more models in future work.It has recently been shown that, to some extent, glacial isostatic adjustment can counteract the positive feedbacks that are believed to cause a hysteresis of the GrIS with global warming, such as the melt-elevation feedback and albedo feedback45 and agree with the general consensus that limiting global warming below the range of 1.5–2.5 °C above preindustrial levels can prevent the most severe consequences8. However, we do not aim to give a precise threshold value for the safe zone but rather to show that it is possible to mitigate a critical loss of the GrIS and the associated SLR contribution if efforts are made to (1) prevent extreme warming by ad 2100 and (2) reduce the temperature after a reasonable time, that is, centuries. Failing in either of these efforts can result in large SLR contributions from the GrIS even for convergence temperatures of between 0 and 1.5 °C above preindustrial.Our temperature thresholds are in accordance with previous work11. Yet, we find qualitatively remarkably similar behaviour with both models used here. A coordinated model intercomparison following an experimental setup such as the one used here would help to constrain the uncertainty in potential critical thresholds and the long-term future ice-sheet evolution.Notably, in the warming-only experiments, we find that several intermediate stable states of the GrIS are accessible with PISM-dEBM as temperatures increase before the remaining ice sheet is lost abruptly, but not with Yelmo-REMBO. This seems, therefore, to be a model-dependent behaviour that is a result of applying different ice dynamics, climatic forcing and interactions within the system. It is clear that the existence of the intermediate states facilitates reversibility of the ice loss before the final threshold is crossed with PISM-dEBM. In previous studies that investigate the short-term response of the GrIS to global warming, it has been shown that future projections can differ substantially across models3, so we expect that our conclusions are robust. Nonetheless, this should be a target for future work.Our simulations are restricted to horizontal resolutions of 16–20 km, which means that small-scale processes are not well represented. The choice of this resolution was because of computational constraints and the large number of simulations. However, we are mostly interested in the large-scale evolution of the GrIS on decamillennial timescales. Previous work has shown that the chosen resolutions give similar results to higher-spatial-resolution simulationsad 2100 (ref. 46). Although we based our estimate of Arctic amplification on Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) models, there is considerable uncertainty about the extent of future warming in the Arctic. Recently, it has been shown that the Arctic warms four times faster than the global average and thus substantially exceeds previous estimates and projections from climate models47. Arctic amplification of this magnitude would reduce the safe space for the GrIS substantially. However, surface temperatures around Greenland might not increase that severely in the future48. On multimillennial timescales, there may be substantial changes in global climate, atmosphere and ocean circulation that are hard to quantify today. For example, a weakening AMOC leads to decreasing Greenland temperatures49, which could help to restabilize the ice sheet. However, at the same time, a weakening of the AMOC is expected to decrease precipitation over Greenland49, which could lead to the opposite effect and destabilize the GrIS even more. These further interactions should be tackled in the future by Earth system models with interactive ice-sheet components.Long-term climate projections for Greenland remain uncertain, as most Earth-system-model simulations typically end by the year 50. Our results show that mitigation of an ice-sheet loss is possible if temperatures are reduced relatively quickly after a temporary overshoot. We find several stable intermediate ice-sheet configurations with PISM-dEBM that return to the present-day state if the climate returns to present-day conditions. However, if longer time spans are needed to cool down to a relatively safe convergence GMT of, for example, 1.0 °C, the SLR contribution from the GrIS can still exceed several metres for thousands of years. With Yelmo-REMBO, there is a temperature range of 0.5 °C below the threshold that shows irreversibility; even if the convergence temperature is below the critical threshold after an initial overshoot, the GrIS does not regrow. This emphasizes the risk of an irreversible ice-sheet loss for long-term overshoot scenarios. Moreover, total runoff amounts would still be substantial even for a reversible ice-sheet loss, with possibly severe consequences for the AMOC51. Remarkably, the timescale of ice loss relative to their respective thresholds agrees very well across the two models used here. It should be emphasized nevertheless that quantitative differences between the two ice-sheet models are present and should be investigated in the future.The potential irreversibility of a loss of the GrIS is an important concern45. We show that a transition to an ice-free GrIS state can be avoided in scenarios that overshoot this critical temperature threshold, as long as the temperature anomaly is subsequently reduced sufficiently quickly. Our results highlight the critical role of warming and cooling rates as well as the maximum and convergence temperatures. In our simulations, southwestern Greenland is most sensitive to temperature changes and primarily determines the spatial extent of the potential intermediate states. However, even without an irreversible transition to a new stable ice-sheet state, the intermediate SLR contribution from the GrIS can exceed several metres, depending on the warming and cooling rate, as well on as the convergence temperature.We find a threshold for an abrupt, complete loss of the GrIS around 2.3 °C GMT above preindustrial level with PISM-dEBM and 1.7 °C GMT above preindustrial level with Yelmo-REMBO, which is in agreement with previously reported critical temperatures for the GrIS24. The ice rheology is based on the Glen–Paterson–Budd–Lliboutry–Duval flow law53 with an exponent of n = 3 with the enhancement factors ESSA = 1 and ESIA = 3 for the SSA and SIA flow, respectively.We use the open-source, state-of-the-art PISM version v1.2-41-g53a9818 with the dEBM-simple surface mass balance module and parameterized climate forcing. PISM is a three-dimensional, thermomechanically coupled ice-sheet/ice-shelf model that combines the shallow-ice approximation (SIA) and shallow-shelf approximation (SSA) of the non-Newtonian Stokes model. This hybrid SSA + SIA approach permits modelling of the whole domain from the ice-sheet flow zone with grounded ice to the ice-shelf flow zones in an appropriate manner54 of the formτb, basal sliding velocity u, yield stress τc and a threshold velocity u0. We chose q = 0.5 and a threshold velocity of u0 = 100 m year−1 for our simulations.We use a pseudo-plastic sliding law55Ntill, a material property field ϕ (till friction angle) and the till cohesion c0. The effective pressure Ntill is determined by the subglacial hydrology model, the till friction angle ϕ is a piecewise linear function of bed elevation56 and the till cohesion c0 is set to 0.The yield stress is determined by the Mohr–Coulomb criterion58. The model is described by a purely elastic lithosphere with a flexural rigidity of 5 × 1024 N m−1 and the upper mantle is represented as a three-dimensional viscous half-space with a viscosity of 1021 Pa s−1. The model uses a time-dependent partial differential equation that generalizes and improves on the standard elastic plate lithosphere model (ELRA)58.We model the deformation of the Earth owing to the changes in the ice load using the Lingle–Clark model25. The dEBM-simple is a modified version of the earlier introduced full dEBM39. We use the standard parameters used by Zeitz et al.25, except for the coefficients c1 and c2, which calibrate the energy balance of the snowpack in the melt equation. These we set to c1 = 20 W m−2 K and c2 = −50 W m−2, based on an optimization of the product of temporal and spatial root-mean-square error of the surface mass balance with regards to the MARv3.12 regional climate model surface mass balance from 1980 to 2000 (ref. 59). We keep the orbital parameters fixed to the present-day values25. The transmissivity of the atmosphere is given by a linear function and assumed not to change in future climate. For an extensive description of the dEBM and the implementation in PISM, see refs. 39.To calculate the surface mass balance, we use a recently developed dEBM-simple59). We apply an elevation-dependent correction of the surface temperature and precipitation, imposing a lapse rate of Γ = 6 K km−1. The precipitation P changes 3.6% per degree of temperature change. The change of precipitation with increasing temperature is derived from a linear fit of the mean annual precipitation against surface air temperature from 37 CMIP6 SSP585 runs  from the regional climate model MARv3.12 (ref. 60), and basal heat flux61, as well as climatological mean (monthly 1980–2000) surface temperature and precipitation taken from the regional climate model MARv3.12 (ref. 59). We run the model until an equilibrium state is reached, but for at least 50,000 years. All simulations were performed on a regular rectangular grid with a horizontal resolution of 20 km and an equally spaced grid in the vertical direction with a resolution of 40 m.Our simulations are initialized from a reference equilibrium state of the GrIS that resembles the present-day configuration. We show the ice-surface elevation and ice-surface velocity deviation from observational data in Extended Data Fig. 56.We normalize the ice volume such that the initial volume corresponds to the observed ice volume of 7.42 m sea-level equivalent in all plots26 resolves ice dynamics by means of the higher-order DIVA solver62. Thermodynamics are linked to dynamics by means of effective viscosity, which is determined with a Glen’s flow law formulation (n = 3) and enhancement factors in the shearing, streaming and floating regimes of 3, 1 and 0.7, respectively. The basal friction is determined with a regularized Coulomb law63 of the formu0 = 100 m year−1 and q = 0.2. Ntill is the effective pressure at the base and ϕ represents the material strength of the bed as a till friction angle. As in PISM, c0 = 0 and ϕ is set as a piecewise linear function of bedrock elevation with ϕmin = 0.5° at bedrock elevations at or below −700 m and ϕmax = 40° at or above 700 m. Effective pressure at the base of the ice sheet is modelled following ref. 64. When ice is frozen at the base, then the effective pressure equals the overburden pressure (Ntill = ρgH), and when a saturated water layer is present for temperate ice, the effective pressure reduces to 2% of the overburden pressure value. To determine the basal water layer thickness, basal hydrology is resolved locally , depending on water production from melting/freezing the base of the ice sheet and a constant till drainage rate of 1 mm year−1. The water layer is limited to 2 m, at which point the till below the ice sheet is considered saturated. Geothermal heat flux is imposed using the reconstruction in ref. 61. Glacial isostatic adjustment of the bedrock is determined using the Lingle–Clark model, as with PISM, and the same parameter values are used. Yelmo is run at 16-km horizontal resolution, with ten terrain-following coordinates in the vertical dimension. The ice-sheet model is coupled bidirectionally to the regional climate model REMBO27. REMBO is a two-dimensional energy–moisture balance model in the atmosphere. At the ice-sheet surface, the snowpack is modelled as a single layer. The surface energy balance is approximated through the insolation–temperature melt equation, which accounts for changes in insolation and temperature, as well as surface albedo, but ignores other components. The snowpack and atmosphere evolves with a daily time step over the year and provides the mean annual surface temperature and surface mass balance to the ice-sheet model. At the domain boundaries, the climatological near-surface temperature is imposed, along with desired temperature anomalies. REMBO resolves the snowpack and surface energy balance on the ice-sheet-model grid and resolves the atmospheric dynamics at 120-km resolution. To reduce biases in the simulated present-day ice sheet, an extra 4 m year−1 of melt is included in the surface mass balance for areas in which there is no ice present in Greenland today. A simple oceanic anomaly method is used to determine the basal mass balance for marine ice at the grounding line: κ = 10 m year−1 K−1 and Tocn = 0.25T2m,ann.The ice-sheet model Yelmo55.Yelmo-REMBO is initialized with the present-day topography and ice-sheet thickness and a semi-analytical solution for the ice-temperature profile at each grid point. The model is then run for 25 kyr to equilibrate the ice sheet with the climatic forcing from REMBO. This is not long enough to reach full thermodynamic equilibrium, but the ice sheet becomes stable by this point with a well-defined thermodynamic distribution. As with PISM-dEBM, we normalize the ice volume such that the initial volume corresponds to the observed ice volume of 7.42 m sea-level equivalent in all plots67. To translate the increase in GMT to the warming rate of Greenland and vice versa, we fit the historical (1850–2014) and SSP585 (2015–2100) global mean surface temperature to the mean surface temperature anomaly around Greenland for summer (JJA) from the first available run of the 37 different CMIP6 models to get a scaling factor between regional temperature and GMT increase46  compared with preindustrial levels (1850–1900) and is derived from HadCRUT5 observational data68. The factor The Arctic region is experiencing the most rapid regional warming around the globestorical 850–2014 69 (Extended Data Fig. For the future scenarios, we a apply a spatially constant temperature anomaly with a temperature-dependent seasonal amplitude. We use the scaling factor of 1.61 between regional winter and summer temperature (Extended Data Table We address both possible structural and parametric uncertainties of our results. Here structural uncertainties are those associated with the model mechanisms and the structure of the model, whereas parametric uncertainties refer to those that are because of incomplete knowledge of the optimal values for the parameters of a given model.We account for structural uncertainties by carrying out our experiments with two independent ice-sheet models, PISM-dEBM and Yelmo-REMBO. We show all our results obtained with both models side by side in the figures and conclude that our results are remarkably robust for both models; they are thus unlikely to be affected by structural uncertainties in general, although important differences do arise in the details.Also, we investigate the parametric uncertainties potentially associated with our results by performing further sensitivity analyses with PISM-dEBM, varying critical parameters that influence the ice dynamics, surface mass balance and further climatic factors (Extended Data Fig. Although the exact ice-volume loss differs slightly for each combination of the parameters, the qualitative behaviour remains the same. Only the simulation without an Earth deformation model shows a qualitatively different behaviour without a recovery of the ice sheet after an initial loss for some temperature anomalies. This is because of the missing glacial isostatic adjustment. The critical threshold of the ice sheet is not greatly influenced by the ice dynamics parameterization. The melt equation parameterization and precipitation scaling influence the critical temperature threshold to some extent, yet within the range set by the two independent models. However, the qualitative behaviour does not change and a recovery after an initial loss is seen for all combinations for small temperature anomalies.TJJA = 2.2 °C, although the other simulations show a recovery to a mostly glaciated Greenland (Fig. TJJA = 1.5 °C, but it eventually transitions to the ice-free state. We attribute this to computational errors that can influence the simulations for temperatures very close to the threshold temperature.It should be noted that, in both models, the ice-sheet response is very sensitive when temperatures are close to the critical thresholds. For example, two simulations with PISM-dEBM show an ice-free state at the temperature of Δand Fig. . SimilarAny methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41586-023-06503-9.Peer Review File


Culicoides hypersensitivity, we compared the transcriptome of IgE-binding monocytes in allergic and non-allergic horses at two seasonal timepoints: (i) when allergic animals were clinical healthy, in the winter “Remission Phase”, and (ii) during chronic disease, in the summer “Clinical Phase”. Most transcriptional differences between allergic and non-allergic horses occurred only during the “Remission Phase”, suggesting principal differences in monocyte function even in the absence of allergen exposure. F13A1, a subunit of fibrinoligase, was significantly upregulated at both timepoints in allergic horses. This suggested a role for increased fibrin deposition in the coagulation cascade to promote allergic inflammation. IgE-binding monocytes also downregulated CCR10 expression in allergic horses during the “Clinical Phase”, suggesting a defect in maintenance of skin homeostasis, which further promotes allergic inflammation. Together, this transcriptional analysis provides valuable clues into the mechanisms used by IgE-binding monocytes in allergic individuals.IgE-binding monocytes are a rare peripheral immune cell type involved in the allergic response through binding of IgE on their surface. IgE-binding monocytes are present in both healthy and allergic individuals. We performed RNA sequencing to ask how the function of IgE-binding monocytes differs in the context of allergy. Using a large animal model of allergy, equine  IgE-mediated allergies are caused by the binding of allergen-specific IgE to receptors on basophils and mast cells, which degranulate when exposed to allergen , 2. IgE-Monocytes are a heterogenous cell population that can adopt a wide range of functions, depending on distinct developmental pathways . MonocytCulicoides (Cul) hypersensitivity [Cul hypersensitivity is an IgE-mediated allergy in horses [Cul midges [Cul are present in the environment only during warm and humid months, resulting in a seasonal disease where allergic individuals have signs of allergy in the summer and appear clinically healthy in the winter. This model allows comparison of immune cells when the horses have clinical allergy or are in remission to determine how cells are programmed to remember and maintain allergy.In order to better understand the role of IgE-binding monocytes in allergy, we used a large animal model affected by an allergy called equine sitivity –18, whicsitivity , 20. Culn horses , 21–27 cl midges –31. Cul In this article, we purified IgE-binding monocytes from allergic and healthy individuals at two seasonal timepoints, the “Remission Phase” in the winter and the “Clinical Phase” in the summer. We performed RNA sequencing (RNA-seq) on IgE-binding monocytes from each phase to ask how the IgE-binding monocyte transcriptome differs between allergic and healthy horses. We also asked if certain pathways were more activated in IgE-binding monocytes from allergic horses, and whether these genes were always activated or only activated during one or the other seasonal timepoint. To our knowledge, this is the first transcriptional analysis of IgE-binding monocytes and comparison between allergic and healthy individuals.All animals included in this study were Icelandic horses with heterogenous genetic backgrounds, as determined previously by MHC haplotype . All horCul midges from mid-May to mid-October, and no exposure to midges during the winter months. Horses were either clinically healthy (n = 5) or had naturally occurring, seasonal Cul hypersensitivity (n = 7). The sample size was selected based on the previously reported prevalence of allergic disease for Icelandic horses that are exported from Iceland as adults  [V. jugularis venipuncture using a vacutainer system . Blood samples were used for peripheral blood mononuclear cell (PBMC) isolation followed by IgE-binding monocyte cell sorting and RNA-seq. Two-four horses were sampled each day over 7-weeks in January–February and 3-weeks in August-September. In January (“Remission Phase”), all horses were clinically healthy. In August , allergic horses had chronic, severe clinical signs of allergy, while healthy horses had no clinical signs  , 33, 34 ns Table .Table 1SCul hypersensitivity was diagnosed by clinical signs and confirmed by intradermal skin testing with Cul whole body extract  where allergic horses had immediate skin reactions and healthy horses did not. Histamine and saline intradermal injections served as positive and negative controls, respectively. As previously described [escribed , all horAll animal procedures were carried out in accordance with the recommendation in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The animal protocol was approved by the Institutional Animal Care and Use Committee at Cornell University (protocol #2011–0011). The study also followed the Guide for Care and Use of Animals in Agricultural Research and Teaching.PBMC were isolated from cell-rich plasma of whole blood by density gradient centrifugation, as previously described , 7. Brie8 PBMC were sorted in parallel for each horse and CD14+ fractions were pooled after collection. For fluorescence-activated cell sorting (FACS), CD14+ cells were further stained with antibodies against equine MHCII  [Following PBMC isolation, cells were immediately prepared for sorting as previously described . Brieflyrythrin) , IgE (clrythrin) , CD16 (crythrin) , CD163 (rythrin) , and a vrythrin) , 21, 24.low/IgE + /MHCIIhigh/CD16-/CD163- cells) were collected into cell culture medium (DMEM supplemented with 1%(v/v) non-essential amino acids, 2mM L-glutamine, 50 µM 2-mercaptoethanol, 50 µg/ml gentamicin, 100 U/ml penicillin, 100 µg/ml streptomycin, all from ThermoFisher Scientific, Waltham, MA, USA, and 10% FCS from Atlanta Biological, Flowery Branch, GA, USA) at room temperature (RT) and viability was confirmed by trypan blue exclusion .FACS was performed on a BD FACS Aria Fusion sorter at Cornell University’s Biotechnology Resource Center (BRC) Flow Cytometry core through an 85 µm nozzle at 25 psi. Live IgE-binding monocytes  at RT. Cells were pelleted at 100 x g, 5 min, RT and washed once in 1 ml PBS-FCS. Cells were resuspended in 250 µl PBS-FCS and 750 µl Trizol LS solution . Then, 200 µl chloroform  was added. Tubes were vigorously shaken for 15 s and centrifuged at 16,000 x g, 15 min, 4 °C. The aqueous phase was collected and added to an additional 600 µl chloroform in Phase Lock Gel tubes . To improve RNA recovery, 2 µl of a glycogen carrier  was added. Last, 500 µl isopropanol was added and incubated on ice for 1 h, then washed three times in 75% ice-cold ethanol. All wash spins were performed at 16,000 x g, 10 min, 4 °C. Extracted RNA was air dried in a laminar flow hood at RT, then resuspended in 20 µl RNase-free water , and stored at −80 °C until submitted for sequencing.RNA concentration was determined by High Sensitivity RNA Qubit assay  and RNA integrity was measured with a Fragment Analyzer . All samples were of good quality  and had a median RNA concentration of 36 ng/µl (range 22–49.3 ng/µl)  Facility prepared RNA libraries for Illumina® Sequencing. RNA was first poly-A selected with the NEBNext Poly(A) mRNA Magnetic Isolation Module  and TruSeq-barcoded RNA-seq libraries were generated using the NEBNext® Ultra™ II Directional RNA Library Prep kit . Libraries were sequenced on an Illumina instrument with a read length of 75 bp single end reads at a depth of 20 million reads per sample.Raw sequencing reads were initially processed by Cornell’s TREx Facility using pipelines built around ENCODE standards and practices. First, raw fastq files were processed with TrimGalore v0.6.0 to remove low quality bases and adaptor sequences. Reads were then mapped to the EquCab3.0 genome using STAR v2.7.0e . Read cop-value (p) throughout, and 39 genes had an adjusted p-value (FDR) < 0.05 at one or both timepoints. These genes were mapped in a heatmap using heatmap.2 and ggplot2 functions. Data was centered by subtracting the average expression level for each gene. Hierarchical clustering of genes was performed with Euclidean distance and average linkage. Samples were clustered by seasonal timepoint and allergy group.Differentially expressed genes (DEGs) between allergic and healthy horses were identified by DESeq2  and foldP-values < 0.05 were considered significant. Graphs were generated with GraphPad Prism software version 9.0.0 .The data were not normally distributed as confirmed by D’Agostino and Pearson tests. Therefore, non-parametric tests were used for analysis. A Holm-Sidak multiple comparisons test compared clinical scores and sorting purities. RNA-seq counts data statistics were calculated by a Wald test in DESeq2 . Investin = 7) and healthy (n = 5) horses. IgE-binding monocytes in equine peripheral blood are characterized as CD14low/IgE + /MHCIIhigh/CD16-/CD163- cells  were further purified by FACS  when horses were constantly exposed to environmental allergen and allergic horses experienced chronic clinical signs  in allergic horses and 8.96  in healthy horses. During the “Clinical Phase”, the normalized median counts distribution was 7.94  in allergic horses and 7.92  in healthy horses. Principal component analysis revealed that IgE-binding monocytes from allergic and healthy horses had more distinct transcriptomes during the “Remission Phase” than the “Clinical Phase”  for CCR10 transcripts while allergic horses had 0.1 CPM (n = 3), 0.2 CPM (n = 1) or no expression (n = 3) of CCR10 transcripts. During the “Remission Phase”, CCR10 was almost entirely unexpressed. Two healthy horses had 0.2–0.4 CPM and one allergic horse had 0.1 CPM of CCR10 transcripts, but the remaining healthy (n = 3) and allergic (n = 6) horses had no CCR10 expression during this phase. The counts values during the “Remission Phase” did not pass the threshold of 0.5 CPM during normalization and therefore CCR10 was excluded from the “Remission Phase” analysis  and “Clinical Phase”  , SERPINE1  and C1R   Fig. . Three g39) Fig. . During 39) Fig. , there wIGF2BP3 was downregulated during the “Remission Phase”    Fig.  with onl24) Fig. . IgE-binTogether these differentially expressed immune system and mitochondrial genes suggest that IgE-binding monocytes exhibit different cell functions and regulatory capacities depending on the allergy status  and the phase of allergy .IgE-binding monocytes bridge innate and adaptive immune responses by responding to a broad range of molecular patterns and, through IgE, to specific allergens. We previously showed that IgE-binding monocytes exist at similar frequencies in healthy and allergic individuals , but proCul hypersensitivity is a naturally occurring, seasonal allergy in horses caused by Cul midge bites [Cul allergens at the same time and it was therefore possible to compare immune cell function during both allergy phases.To find further evidence for the role of IgE-binding monocytes in allergy, we compared transcriptional profiles of these cells in allergic and healthy horses. ge bites , 28, 29.ge bites , 19, 20.While IgE-binding monocytes exhibited multiple up- and downregulated genes in allergic horses at both seasonal timepoints, most of the differential gene expression occurred in the winter. During the “Remission Phase”, horses were clinically healthy and had not been exposed to allergens in at least three months. Therefore, transcriptional differences at this timepoint were sustained in IgE-binding monocytes of allergic horses, regardless of allergen exposure and clinical disease, suggesting an altered baseline expression profile of IgE-binding monocytes in allergic individuals.CD14, FcεRI alpha and gamma subunits, and IL10.To validate the gene expression profile of our IgE-binding monocyte transcriptome dataset, we compared gene expression of cell-specific proteins that we previously characterized in horse IgE-binding monocytes. As expected , both alDuring the “Clinical Phase”, transcriptomes were similar between healthy and allergic horses, with only nine DEGs. This suggests that IgE-binding monocytes are remarkably similar in function and activation status in allergic and healthy horses during the summer. IgE-binding monocytes respond both to allergen, through IgE, and to pathogen-associated molecular patterns which are abundant in the saliva of many biting insects, through CD14 and other pattern recognition receptors . As a reF13A1, was significantly upregulated in allergic horse IgE-binding monocytes at both timepoints. F13A1 encodes for coagulation factor XIIIa, a subunit of fibrinoligase. Fibrinoligase is a tetramer of two enzymatically active A subunits, encoded by F13A1, and two inhibitory B subunits [F13A1 by alternatively activated macrophages, important for tissue remodeling and repair [F13A1 upregulation leads to increased fibrin in nasal polyps, thereby increasing disease severity [Cul hypersensitivity is dermatitis at sites of allergen exposure. Therefore, F13A1 overexpression by IgE-binding monocytes of allergic individuals could induce excess fibrin buildup, as monocytes home to skin tissues to heal allergen-induced wounds, leading to dermatitis and scar tissue build-up typically seen in Cul hypersensitivity. Measuring F13A1 expression in monocyte-derived cells in the skin of allergic horses will further support this hypothesis.One gene, subunits , providid repair , 45, incseverity . One of F13A1 helps in causing allergic skin inflammation, or is upregulated in response to allergic wounds, also remains to be explored. F13A1 in humans is upregulated by IL-4 or IL-13 stimulation [F13A1 expression in IgE-binding monocytes could be induced in allergic individuals shortly after, or simultaneously with, the first development of allergen-specific IgE, when IL-4 and IL-13 are abundant [F13A1 in IgE-binding monocytes, setting up their elevated baseline expression in allergic horses , that inhibits fibrinolysis [C1R is a proteolytic subunit of the classical complement system [C1R, along with other complement subunits, was found to be a substrate for F13A1 [F13A1, SERPINE1, and C1R, or vis versa, is worth exploring.Similar to inolysis , 52, theinolysis . C1R is t system , and is or F13A1 . TogetheCCR10. This gene was downregulated in IgE-binding monocytes from allergic horses in the summer and hardly expressed by any horse in the winter. CCR10 is a critical regulator of skin immune homeostasis through binding of chemokine CCL27, produced by skin keratinocytes [CCL27 transcripts following stimulation with Cul allergens [CCR10 expression in IgE-binding monocytes during allergen exposure. CCR10 expression by IgE-binding monocytes requires further confirmation and may play a role in homing of these cells to the affected skin areas during allergen exposure. The role of this receptor on IgE-binding monocytes of healthy individuals will also be worth exploring.Another gene that may be important in the allergy-associated role of IgE-binding monocytes is inocytes . The CCLinocytes –59. In allergens . HoweverCCR10 by IgE-binding monocytes in allergic individuals may also reduce skin homing and consequently reduce their contribution to skin homeostasis. Future work needs to address the differences in CCR10 expression and skin homing of IgE-binding monocytes and skin tissue-associate macrophages in healthy and allergic individuals. Whether allergic inflammation induces the downregulation of CCR10, or IgE-binding monocytes in allergic individuals are preprogrammed to express less CCR10, remains to be explored.CCR10 has been shown to be preferentially expressed by skin-resident T-cells for their maintenance of skin homeostasis . It is tF13A1, SERPINE1 and C1R, and the CCR10/CCL27 axis, as candidate pathways used by IgE-binding monocytes in the mechanism of allergy. Significant upregulation of F13A1 in allergic horses both during clinical allergy and during remission suggests that IgE-binding monocytes may deposit excess fibrin, enhancing allergic dermatitis and skin inflammation. Downregulation of CCR10 in allergic horses during clinical allergy suggests an impaired ability of IgE-binding monocytes to home to the skin and maintain skin homeostasis. These results highlight specific transcriptional differences that begin to describe the role IgE-binding monocytes play in maintaining allergy, even in the absence of allergen exposure.Together we report both the coagulation cascade, specifically the genes Supplemental Material


Pikialasorsuaq (West Greenlandic for ‘great upwelling’) forms at the Strait’s southern end. There is evidence that a warming climate and the concomitant thinning of Arctic sea ice is weakening the arches and it has been proposed that this may impact the stability of NOW and the complex ecosystem that it sustains. Here we employ a categorization of recent winters with respect to the presence or absence of ice arches to explore their impact on sea ice along the Strait and over the NOW. We find that winters during which a southern ice arch is absent are associated with a reduced and thinner ice cover along the Strait with ice conditions over the NOW similar to that during winters with a southern arch. In winters, without a southern arch, there is also an acceleration of the winds along the Strait that contributes to the presence of reduced ice cover. Ocean color remote sensing data suggests that current levels of primary productivity over the NOW are independent of the presence or absence of an ice arch. The results suggest more research is needed to assess the stability of the NOW, with respect to reduced ice cover and primary productivity, in a future where ice arches cease to form along Nares Strait.Nares Strait, the waterway that separates northwest Greenland from Ellesmere Island, is a major pathway along which sea ice leaves the Arctic, including the planet’s oldest and thickest sea ice that is experiencing an accelerated loss. Ice arches that develop during the winter at the Strait’s northern or southern terminus can remain stable for months at a time during which the transport of sea ice ceases. The Arctic’s most productive polynya, the North Water (NOW) or  The planet’s oldest and thickest sea ice is situated to the north of Nares Strait in a region known as the Last Ice Area that is predicted to be the last region in the Arctic to lose its perennial ice cover6. The export of this ice, that has seen an accelerated loss in recent years7, occurs along the Strait8.Nares Strait is the waterway that separates northwest Greenland from Ellesmere Island Fig. . Along w10. Typically, the arches form in December or January and remain stable until July or August with their presence eliminating the export of sea ice along Nares Strait8. Arches can form either at the northern end of the Strait, to the north of Robeson Channel10, or in the vicinity of Smith Sound at its southern end1. Southern arches are more common during the satellite record11. The uniaxial compressive strength of sea ice is a function of its thickness9 and so there is concern that observed thinning of Arctic sea ice in the region to the north of Nares Strait may be impacting the arch’s stability14.The narrowness of the Strait when combined with the mechanical properties of sea ice, most notably its high uniaxial compressive strength, results in the frequent formation of arch-like features that can remain stable for months at a timePikialasorsuaq is a recurring polynya situated just south of Smith Sound  or und Fig. . It has 22. The reduction in ice cover along with the nutrients provided by upwelling contribute to its productivity23. The ice free waters support early blooms of phytoplankton that are the basis of a productive ecosystem that supports important species that include: Arctic cod, seabirds, as well as seals, walruses, narwals, beluga and polar bears24. There is evidence that the NOW is expanding in size as a result of warming air and sea surface temperatures in the region26. In addition, ocean color remote sensing of chlorophyll-a (Chl-a) indicate that phytoplankton blooms over the NOW typically start in late April and early May, reach peak amplitudes in late May and June before declining through July to September28. In addition, the bloom duration is positively correlated with the period of open water27. During the winter of 2009, a northern ice arch formed and this lead to low ice cover over the NOW and a particularly early bloom27. The amplitude of the bloom, defined as the peak value of Chl-a, has a negative trend that may be related to changes in sea surface conditions, increases in sea surface temperatures and decreases in sea surface salinity, as well as changes in wind driven upwelling of nutrients28. There is also concern that the weakening of the ice arches along Nares Strait may impact the stability of the NOW, its high level of productivity and its role as a traditional food source for nearby Inuit communities24. In this regard, a modelling study29 suggests that changes to the ocean, including an increase in sea surface temperatures through the upwelling of Atlantic Water, a shallowing of the mixed layer and an increase in stratification as well as an increase in ice flux, will fundamentally alter the nature of the NOW with potential impacts on its productivity. Indeed, the warming of Atlantic Water has been argued to contribute to a recent delay in ice growth in the region during the fall30.The NOW is the Arctic’s largest and most productive polynya31 provide a way to document the ice transport along the Strait8. With this technique it was noted that no arches formed along Nares Strait during the winter of 20071. This absence allowed for ice transport throughout the winter and as a consequence annual ice area and volume fluxes were twice as large as the mean over 1997–20091. Using SAR imagery, 2019 was also identified as a winter in which ice transport continued throughout the winter and as a consequence, no ice arches formed along the Strait8.Satellite-based synthetic aperture radar (SAR) imagery together with feature tracking algorithms32. In June 1854 during the Second Grinnell Expedition, Kane observed the presence of open water in Kennedy Channel that he that he assumed was the start of the Open Polar Sea33. Subsequent expeditions such as Hall’s Polaris Expedition of 1871–1873 and Nares’ British Arctic Expedition of 1875–1876 were able to navigate through sea ice all along Nares Strait up to the Lincoln Sea where thick ice blocked further progress35. Bessels, the Chief Scientist on the Polaris Expedition, noted that Nares Strait was never entirely frozen over including Hall Basin where open water and wind-driven mobile ice were observed during their overwintering34.Variability of sea ice along Nares Strait has not been extensively studied. However there is significant body of historical knowledge regarding this variability that is related to expeditions during the nineteenth century that attempted to reach the North Pole via the Nares Strait10. A similar polynya was observed to develop to the south of a northern ice arch during the winter of 201736. Examples using daily infra-red satellite imagery37 indicate that during May there was open water along Nares Strait during a winter when no southern ice arch formed, i.e. either a northern ice arch or no ice arch, that was in contrast to the extensive ice cover along the Strait during a winter in which a southern ice arch formed. This result was extended in a study8 that showed monthly mean sea ice concentration maps for June 2018 and 2019. During the winter of 2018, a southern ice arch formed; while during the winter of 2019 no arches formed. During June 2018, Nares Strait had close to 100% ice cover north of Smith Sound. In contrast during June 2019, the Strait had open water as far north as 81° N.More recently, a polynya was observed to form to the south of a northern ice arch during the winter of 198938. In addition, ICESat-2 freeboard data has been used to show that sea ice was thinner during the winter of 2019, when no southern arch formed, as compared to the winter of 2020, when a southern arch formed38. Warming subsurface waters of Atlantic and Pacific origin have been argued to contribute to a reduction in thermodynamic ice growth throughout the winter along Nares Strait thereby contributing to the observed weakening of arches along Nares Strait39.It has been shown that southern arches along Nares Strait tend to form during periods of cold surface air temperatures around low tide and during a cessation or even a reversal of the prevailing southerly winds along the StraitAs we will show in this paper, the winter of 2022 was another year in which ice motion continued throughout the winter along Nares Strait and as a result, no arches formed. We will use recent winters in which: a southern arch formed, a northern arch formed or no arches formed to assess the impact that ice arches have on the distribution of sea ice along Nares Strait and the NOW. We find that the absence of a southern ice arch results in the presence of open water and thin ice along Kennedy Channel. While over the NOW in the absence of a southern ice arch, there is a similar distribution of sea ice as well as similar levels of primary productivity as occurs when a southern ice arch is present.8 to include the winters of 2020, 2021 and 2022. The presence of an ice arch is indicated by a marked reduction in the IAF8. In addition to the previously identified cessation of this flux during 2017 and 20188, there was also a cessation during 2020 and 2021. There was variability in the nature of the IAF during these 4 winters that ranges from a complete cessation of the IAF during the winter of 2020 to continued small magnitude fluctuations during the remaining 3 winters that speaks to an underlying variability in the stability of the arches that will be the subject of a future investigation. As was the case during 2019, the IAF remained large during the winter of 2022 indicating the absence of an arch along the Strait.Figure 37 as well the first month of the year in which there is significant primary production in the NOW27. It is evident that the sea ice concentration along Nares Strait north of Smith Sound is close to 100% with reduced ice cover over the NOW during winters with a southern ice arch  along Nares Strait was calculated using a flux gate situated within the southern Lincoln Sea  as to the presence or absence of an arch. Table The IAF flux data in Fig. 40 were used. The primary payload on the CryoSat-2 satellite50 is a radar altimeter that retrieves sea ice thickness through measurements of sea ice freeboard with a spatial footprint of ~ 0.3 km by 1.7 km52. The primary payload of the Soil Moisture and Ocean Salinity (SMOS) satellite is a passive microwave radiometer operating at 1.4 GHz53 that is able to retrieve sea ice thickness up to ~ 1 m at a spatial resolution of 12.5 km54. CryoSat-2 retrievals of thin ice have a greater uncertainty as compared to thick ice; while SMOS exhibits greater sensitivity to retrievals of thin ice55. As a result, the merging of the two products results in an improved retrieval of ice thickness with lower rms errors and higher correlation as compared to in-situ observations55. The data is available where the sea ice concentration is non-zero on a weekly basis, updated daily, at a spatial resolution of 25 km during the cool season (October–April) from 2010/2011 to 2021/202240.Sea ice thickness data from the merged CryoSat-2/SMOS40. Supplementary Figure 40. As a result, the percent uncertainty during May (SF1c) is largest over the thin ice of the NOW, in excess of 60%, while it is less than 30% along Nares Strait.The merged CryoSat-2/SMOS dataset provides an estimate of the uncertainty in the thickness retrieval56. As a result, we use the 10 m meridional wind from the western domain, that includes Nares Strait and northern Baffin Bay, of the Copernicus Arctic Regional Reanalysis (CARRA). It is available on a Lambert Conformal grid with a horizontal resolution of 2.5 km and a temporal resolution of 3 h57. The CARRA is based on the mesoscale Numerical Weather Prediction (NWP) system known as HARMONIE-AROME58 with some modifications and extensions that are described in Yang57. Boundary conditions for CARRA are provided by the ERA5 reanalysis59. We used data for the period of overlap with the AMSR-E/2 dataset, 2002–2022. Sea ice in the CARRA is assumed to a uniform thickness of 0.75 m60. Within the Nares Strait region, a comparison with in-situ wind data suggests an uncertainty of ± 2.5 m/s42.There is evidence that the narrowness of the Strait combined with its steep topography requires high spatial resolution to represent the local wind climate61. Ocean color remote sensing has proven to be an important tool for monitoring oceanic primary productivity as it provides high spatial and temporal resolution information on biochemical proxies, such as chlorophyll-a (Chl-a), in remote regions with harsh climates62. As with any remotely sensed products, there are challenges in using the data. The presence of clouds can limit the availability of data63, as does sea ice cover that also introduces complications in the retrival of estimates of Chl-a. Despite these complexities, Chl-a data has been used in a number of studies to assist in the characterization of the NOW’s primary productivity66. Here we use monthly mean retrievals of Chl-a from the MODIS instruments on the Terra and AQUA satellites as well as the VIIRS instrument on the Suomi NPP satellite for the period 2002–2022 as processed by Ocean Biology Processing Group at NASA’s Goddard Space Flight Center (https://oceancolor.gsfc.nasa.gov).Space-based ocean color data provides a remotely sensed estimate of primary productivityTo provide information on the variability in the various datasets along Nares Strait, we used a latitudinal averaging process. The centerline along Nares Strait was determined from the GEBCO digital elevation model Fig. . For fixSupplementary Figure S1.


Introduction: Revision total hip arthroplasty in the setting of acetabular bone loss remains a challenging clinical entity. Deficiencies of the acetabular rim, walls, and/or columns may limit the bony surface area and initial acetabular construct stability necessary for osseointegration of cementless components. Press-fit acetabular components with supplemental acetabular screw fixation represent a common technique aimed to minimize implant micromotion and allow for definitive osseointegration. Although acetabular screw fixation is commonly practiced in revision hip arthroplasty, few studies to date have examined the screw properties associated with maximal acetabular construct stability. The purpose of the present report is to examine acetabular screw fixation in a pelvis model mimicking Paprosky IIB acetabular bone loss.Methods: Measuring bone-implant interface micromotion as a surrogate for initial implant stability, experimental models assessed the effect of screw number, screw length, and screw position on construct stability subject to a cyclic loading protocol designed to replicate joint reaction forces of two common daily activities.Results: Trends towards increasing stability were demonstrated with increasing screw number, increasing screw length, and concentrating screws in the supra-acetabular dome. All experimental constructs yielded micromotion levels sufficient for bone ingrowth, except when screws in the dome were moved to the pubis and ischium.Conclusions: When using a porous coated revision acetabular implant to treat Paprosky IIB defects, screws should be used, and furthermore, increasing number, length, and position within the acetabular dome may help further stabilize the construct. Porous-coated total hip acetabular components offer the advantage of stable, long-term fixation in primary and revision total hip arthroplasty. Osseointegration, the process of host subchondral bone incorporating into a porous metal surface, is required to establish enduring fixation of cementless acetabular implants. Successful osseointegration demands both intimate contact of the porous acetabular implant surface with host bone of sufficient quality and quantity as well as initial acetabular implant stability historically defined as micromotion of less than 150 µm . AcetabuUnfortunately, the use of supplemental acetabular screw fixation in the setting of acetabular bone loss does not eliminate aseptic cup loosening from the aftermath of surgery. This persistent threat of mechanical acetabular failure motivates orthopaedic surgeons to think critically about screw placement during the time of revision arthroplasty in order to optimize initial implant stability. The Paprosky type IIB acetabular defect, characterized by substantial loss of the superolateral acetabular rim with intact and supportive acetabular columns, is considered the most common yet severe bone defect in which an uncemented revision acetabular component can be utilized with strictly acetabular screw supplemental fixation . In an eIn this study, we used Sawbones fourth Generation Composite hemi-pelvis models  that were fashioned to simulate acetabular bone loss consistent with Paprosky type IIB acetabular defects. Models were created by sequentially over reaming the acetabulum, and removing the posterior-superior aspect of the acetabular rim with a sagittal saw Figure . A revisA two-by-two grid was drawn in the acetabular cavity using anatomic landmarks to map screw position safe zones Figure . Screw pHemi-pelvis specimens were then mounted into a linear load cell  using two custom machined mounts that were each fabricated to simulate an applied force vector consistent with previously defined joint reaction forces for two common daily activities: walking on flat ground, and descending stairs Figure . These fThe primary endpoint, micromotion at the bone-implant interface, was measured using a motion capture system  with a manufacturer’s reported precision of 5-10 mm. Motion capture reference markers were positioned on the rim of the component and on the acetabular bone to determine motion of the component in three planes: posterolateral rotation (XY) into the rim defect, anteromedial rotation (YZ), and horizontal rotation (XZ) around the rim equator of the component. Displacement over time was recorded in these three planes of motion using a custom MatLab equation, and force-displacement curves were created. After determining the displacement per load cycle in each of the three defined planes of motion, the total motion of a point on the spherical surface of the implant was estimated using a calculation for motion of a point on a sphere.Experimental specimens were divided into groups based on three screw variables: number, length, and position. Additionally, a control group in which no screws were implanted was created to assess motion without screw supplementation. Screw number was varied between two, three, and four 25 mm length screws in the supra-acetabular position. Screw length was varied utilizing two screws of 25- and 50-mm lengths used in the supra-acetabular position. Screw position was varied between three screws used in supra-acetabular, anterior (pubic), and posterior  positions. Three specimens were tested in each control and experimental group. Micromotion per load cycle was recorded in each plane of motion, and from these measurements, the total motion was calculated for each specimen.ANOVA comparative statistics were then run between each control and experimental group to establish statistical significance between differences in displacement, with a p<0.05. As previously defined and referenced in several studies, a threshold of >150 µm of motion was established as the point over which, fibrous ingrowth would be expected. A priori power analysis was not performed as no study has been published using this method of measurement of micromotion on the surface of an acetabular component, and therefore benchmark effect sizes are not available.With three specimens in each control and experimental group, a total of 36 models were tested. Table There was a trend towards decreased cup motion as screw number increased. This trend was observed in both the XY plane of motion and when total motion was calculated Figure ; howeverThere was a trend towards increased cup motion when screws were moved from the supra-acetabular position to either an anterior or posterior position. Again, this trend was observed in both the XY plane of motion and when total motion was calculated Figure . This trThere was a trend towards decreased cup motion as screw length was increased. In general, this trend was observed in both the XY plane and total motion; however, there was an unusually high average motion in the group with a 50 mm screw designated A and 25 mm screw designated P in the YZ plane, and this led to a higher total calculated motion in this group Figure . Once agWhile the trends observed in the experimental groups were not statistically significant between the experimental groups, there was a statistically significant decrease in micromotion from the control group with no screws to each of the experimental screw groups.Stable arthroplasty component fixation is paramount for the long-term survivorship of cementless implants in primary and revision hip arthroplasty. During hip arthroplasty, the absence of supportive acetabular bone secondary to osteolysis, overaggressive acetabular reaming, dysplastic acetabular morphology, previous acetabular fracture, and/or advanced avascular necrosis may jeopardize the surgeon’s ability to achieve stable non-augmented acetabular fixation. When full intrinsic stability of the acetabular shell cannot be obtained, options for supplemental fixation include acetabular screws, porous metal augments, allograft/autograft bone, cement, reconstruction cages, and custom triflange devices. Utilization of increasingly sophisticated reconstruction devices is not only costly but frequently requires larger surgical exposures and increased operative times, two variables that are undoubtedly associated with an increased risk of periprosthetic joint infection. Thus, multi-hole acetabular shells in combination with acetabular screws remain an attractive technique within the surgeon armamentarium. A paucity of objective evidence exists to guide surgeon placement of acetabular screws. Several previous studies have demonstrated the long-term reliability of porous coated implants using a press-fit technique and supplemental screw fixation in the revision setting as an alternative to implants with pegs, spikes, and dual geometries ,8-11. InIn this study, we were able to identify trends in decreasing micromotion, and therefore, increased initial stability of a cementless component with increasing screw length, screw number, and concentrating screws in a superior location within the acetabulum. Changing screw position , led to a decrease in stability, despite prior evidence to suggest that screw divergence can increase construct stability . Given oThe threshold of micromotion, which allows for ossoeintegration of the porous coated implant, varies by published historical report. In one of the earliest studies, Pilliar et al., evaluated the effect of micromotion on ingrowth of porous metal in a linear displacement model. This nascent report demonstrated that excess movement (>150 µm) results in fibrous ingrowth rather than bone ingrowth . ConsequSeveral weaknesses of our report are acknowledged. First, we elected to use sawbones models, as opposed to cadaveric specimens, in an effort to maximize the number of specimens and standardize experimental groups. While the biomechanical composite Sawbones models may provide a basis for better understanding bone implant interactions, sawbones models fail to replicate the pathologic state of acetabular bone frequently encountered during revision arthroplasty in the setting of bone loss and therefore these results may differ if studied in vivo. Additionally, although we focused on one acetabular bone loss pattern, understanding that in vivo bone loss patterns are neither predictable nor identical. Further study of additional bone loss patterns may further elucidate screw locations, which more effectively counter motion vectors corresponding to specific regions of acetabular bone deficiency. Second, our applied loading protocol established by Bergmann et al., relies upon simplified linear vectors, which may not accurately represent the physiologic joint reactive forces transmitted through the acetabular component-bone interface ,15. ThirThe data presented in this study supports the widely held belief that porous coated acetabular implants inserted with the press-fit technique in combination with supplemental screw fixation generate the initial stability necessary for long-term stability via osseointegration in Paprosky IIB acetabular defects. Furthermore, increasing the screw number, length, and position within the acetabular dome may help further stabilize the construct. Together, these findings warrant surgeon consideration during real-time placement of acetabular screws in Paprosky IIB defects.


Fear learning and memory rely on dynamic interactions between the excitatory and inhibitory neuronal populations that make up the prefrontal cortical, amygdala, and hippocampal circuits. Whereas inhibition of excitatory principal cells (PCs) by GABAergic neurons restrains their excitation, inhibition of GABAergic neurons promotes the excitation of PCs through a process called disinhibition. Specifically, GABAergic interneurons that express parvalbumin (PV+) and somatostatin (SOM+) provide inhibition to different subcellular domains of PCs, whereas those that express the vasoactive intestinal polypeptide (VIP+) facilitate disinhibition of PCs by inhibiting PV+ and SOM+ interneurons. Importantly, although the main connectivity motifs and the underlying network functions of PV+, SOM+, and VIP+ interneurons are replicated across cortical and limbic areas, these inhibitory populations play region-specific roles in fear learning and memory. Here, we provide an overview of the fear processing in the amygdala, hippocampus, and prefrontal cortex based on the evidence obtained in human and animal studies. Moreover, focusing on recent findings obtained using genetically defined imaging and intervention strategies, we discuss the population-specific functions of PV+, SOM+, and VIP+ interneurons in fear circuits. Last, we review current insights that integrate the region-specific inhibitory and disinhibitory network patterns into fear memory acquisition and fear-related disorders. Fear memories are associated with distressing emotions caused by anticipation of danger. Although essential for survival, when these memories persist even in the absence of threatful cues, it might lead to the development of post-traumatic stress disorder (PTSD). PTSD is a serious mental health condition that promotes reckless and self-destructive behavior due to disturbed activity within neuronal networks  that provide spatio-temporal coordination of the activity of principal cells (PCs) via the inhibition of specific subcellular domains of PCs, such as soma and dendrites , and neurogliaform cells, as well as VIP+ cells, providing synaptic inhibition with target-specific properties -expressing neurons projecting to the CeM, cause disinhibition of the CeM-to-PAG pathway, leading to the expression of the fear response by the PAG  clusters in orchestrating the transitions between the high- and low-fear states and fear extinction  has been considered as a robust behavioral paradigm to investigate the role of the hippocampus in fear learning  is primarily involved in spatial learning and episodic memory, whereas the ventral hippocampus (vHPC) receives inputs from the amygdala and the hypothalamus, and is involved in the regulation of stress and emotional responses  cells) are excited by cholinergic projections that arrive at the CA1 from the medial septum, which in turn leads to enhanced distal dendritic inhibition onto CA1 PCs and restricts the activation of these cells by foot-shock-evoked excitation  and VIP+ cells that inhibit other interneurons and are therefore considered as VIP+ interneuron-specific (IS) cells  and muscimol selectively into the PL-PFC followed by fear conditioning reduced both the cued and contextual fear expression  PCs, thus highlighting the circuit disinhibition as an important mechanism in associative learning (The primary auditory cortex (A1) is also involved in fear learning. The role of this region has been studied using the local administration of muscimol prior to fear conditioning, which resulted in a decrease in the fear-conditioned response  PCs. This population comprises Martinotti and non-Martinotti cell types that are distributed in layer 2 to layer 6  in SOM+ cells, rather than in PV+ interneurons (Cummings and Clem, rneurons . Collectvia their excitatory projection to the BLA and GABAergic ITC clusters, which can limit the activation of the CeM output (Milad and Quirk, via feed-forward inhibition (Sotres-Bayon et al., via PL-PFC PV+ interneurons (Sotres-Bayon et al., Furthermore, the IL-PFC was involved in the suppression of fear memory via selective recruitment of the VIP+ cells, therefore resulting in the perisomatic and dendritic disinhibition of PCs (Lee et al., Finally, during fear learning, the US can activate frontal VIP+ cells, thereby promoting the disinhibition of PCs necessary to facilitate the processing of the noxious signals. In this scenario, the US presentation can limit the activation of PV+ and SOM+ interneurons Although the data available thus far provide important insights regarding the structure and function of the neuronal circuits involved in fear memory, our understanding of how behavioral learning is implemented at the network level remains still limited. Several points need to be addressed to understand the mechanisms that contribute to the formation and regulation of fear circuitry. In particular, the extinction of fear memory that involves both the erasure and extinction-induced inhibition within fear circuits and allows to regulate the stability of fear memories (Herry et al., via inhibitory circuit mechanisms. The PV+, SOM+ and VIP+ interneurons in the amygdala received more attention than in the other fear circuits. In BLA, perisomatic inhibition provided to PCs by the PV+ cells, and likely VIP-BCs (Rhomberg et al., In this regard, over the last few decades, the field has moved to exploring the contributions of different neuronal populations to animal behavior, thanks to rapidly developing gene targeting technologies. An increasing number of studies have investigated the functional role of inhibitory interneurons in different memory paradigms thereby revealing that interneurons are important players in diverse learning tasks. In relation to fear learning, these cells not only shaped the circuit response during fear conditioning but also showed changes in their properties during fear consolidation. Therefore, across different fear circuits, the network function appears to be tightly regulated Circuit disinhibition has recently emerged as an important mechanism that participates widely in memory-related paradigms by limiting the firing of the GABAergic interneuronal populations and providing additional ways for the modulation of network activity. Disinhibition phenomenon appears to be critical in fear conditioning and related long-term changes that take place in different neural circuits (Letzkus et al., via the phenomena of inhibition and disinhibition, respectively. As such, whereas some PCs are excluded from memory engrams because of active inhibition, the others become linked to engrams because of increased intrinsic and synaptic excitability facilitated by disinhibition. The changes in inhibitory connections can also shift the network balance, thus altering the coding of the fear experience. Therefore, inhibitory neuronal populations responsible for local circuit inhibition and disinhibition are currently considered as a powerful component in the creation of mental fear representations. Further studies are required to establish the role of specific inhibitory and disinhibitory patterns in complex fear-related behavioral adaptations and a direct link between a stressful event and the functional plasticity of specific circuit elements.In summary, a working model of fear learning can be proposed in which traumatic events recruit specific interneuronal populations that control PCs and other interneurons to create the representative PC ensembles, or memory engrams, SS wrote the first version of the manuscript and prepared the figures. LT prepared the final version of the manuscript. All authors contributed to the article and approved the submitted version.


The BioFire® FilmArray® Gastrointestinal Pathogen Panel (GIPP) tests for 22 potential pathogens in stool, including Clostridioides difficile. C. difficile nucleic acid is detected via nested polymerase chain reaction (PCR) targeting toxin A (TcdA) and/or toxin B (TcdB) genes. While PCR-based diagnostic methods are highly sensitive, they lack specificity to differentiate colonization from C. difficile infection (CDI). Mayo Clinic Arizona (MCA) uses enzyme immunoassay (EIA) testing for toxin A/B and glutamate dehydrogenase antigens with reflex to PCR for discordance as the primary algorithm for diagnosing CDI; however, GIPP PCR testing circumvents this algorithm. When used in patients with low pretest probability for CDI, clinical false positives can lead to inappropriate diagnosis and treatment of colonization.GIPA Results in the Electronic Medical Record Pre-InterventionMCA Standalone C. difficile Testing AlgorithmAbbreviations – EIA, enzyme immunoassay; GDH, glutamate dehydrogenase; NAAT, nucleic acid amplification testWe convened a multidisciplinary quality improvement team to reduce the detection and treatment of C. difficile colonization secondary to GIPP test results. Surveys were sent to providers and nurses as part of a formal gap analysis and included questions around ordering patterns, knowledge of appropriate tests, and associated costs. Baseline data was compiled from GIPP orders in MCA from 1/1/2022-9/30/2022.There were 1978 GIPP orders for 1694 patients during the study period (∼7 GIPPs/day). Most orders (65%) originated from ambulatory settings. The most common positive target was C. difficile , which resulted in treatment for suspected CDI in 94.9% (337/355) of cases. Of the 49 providers who responded to the survey, 86% ordered the GIPP at least monthly. Testing for C. difficile was the 2nd most common reason for ordering the GIPP. Most providers underestimated the cost of the panel and were unfamiliar with the differences between the GIPP and EIA testing algorithm. Nurses sought clarification on stool samples suitable for GIPP testing. Following education and modifications to ordering in the electronic health record, the decision was made to remove the C. difficile target from the GIPP.Provider Understanding of C. difficile Testing MethodsGIPA Results in the Electronic Medical Record Post-InterventionMultiplex PCR panels are comprehensive but require careful implementation to facilitate diagnostic stewardship. Facilities with robust standalone C. difficile testing algorithms may consider removing the C. difficile target from the GIPP.All Authors: No reported disclosures


It is well established that immunoglobulin E (IgE) plays a crucial role in atopy by binding to two types of Fcε receptors . The cross-linking of FcεRI-bound IgE on effector cells, such as basophils and mast cells, initiates the allergic response. Conversely, the binding of IgE to CD23 modulates IgE serum levels and antigen presentation. In addition to binding to FcεRs, IgE can also interact with other receptors, such as certain galectins and, in mice, some FcγRs. The binding strength of IgE to its receptors is affected by its valency and glycosylation. While FcεRI shows reduced binding to IgE immune complexes (IgE-ICs), the binding to CD23 is enhanced. There is no evidence that galectins bind IgE-ICs. On the other hand, IgE glycosylation plays a crucial role in the binding to FcεRI and galectins, whereas the binding to CD23 seems to be independent of glycosylation. In this review, we will focus on receptors that bind to IgE and examine how the glycosylation and complexation of IgE impact their binding. Immunoglobulin E (IgE) is a crucial molecule in the development of allergic disorders. It interacts with various receptors, with the FcεRI receptor being the most important and well-studied of these. Free IgE preferentially binds to FcεRI due to its high affinity for this receptor. The cross-linking of FcεRI by IgE and allergen triggers intracellular signaling, leading to the degranulation of effector cells such as basophils and mast cells. The mediators released in this process are responsible for the characteristic symptoms of allergies.The second IgE receptor is CD23 (FcεRII), whose function has long been overlooked as important in the field of allergy. This is because CD23 binds IgE with lower affinity and is involved in different immunological processes , 2. HoweGalectin 3 and 9 are also receptors for IgE, and both are expressed in humans and mice –14. Besiγ receptors. However, recent research performed in mice suggests that FcγII, FcγIII, and FcγIV, which correspond to FcεRI (αγγ) in humans, only bind IgE in a complexed form, such as when it is bound to an allergen or IgG  region and a constant (C) region. The C region of the IgE heavy chain contains four Ig domains (Cε1-Cε4) and one V domain (VH). The C region allows for interaction with its two main receptors, FcεRI and FcεRII (CD23). Compared to IgG, the IgE-Fc has an additional pair of domains (Cε2), and the Cε3-Cε4 domains of IgE are most homologous to the Cγ2-Cγ3 domains of IgG-Fc .IgE is unique because it lacks a hinge region, and its flexible constant region can adopt either an open or closed conformation . The cloFurthermore, IgE is the most glycosylated immunoglobulin, with about 12% of its molecular weight resulting from glycosylation , containSeven asparagine N-linked glycosylation sites for human IgE  and nineIgE antibodies bind to FcεRI on the surface of mast cells and basophils, which in turn leads to the release of inflammatory mediators such as histamine, prostaglandins, and leukotrienes upon cross-linking of cell-bound IgE with allergens. This process can result in a range of allergic symptoms, including the most severe form of allergic reaction, anaphylaxis.In mice, FcεRI is expressed only as a tetrameric structure, consisting of the IgE-binding α-chain, two γ-chains responsible for signaling, and the β-chain which amplifies signaling of FcεRI , 43.via IgE, which is then transported to endo/lysosomal compartments for loading and presentation on MHC class II molecules  most IgE remains bound to the receptor on the cell surface for several weeks, leaving only a small amount of free, short-lived IgE in the plasma  decreases the ability of IgE to bind to FcεRI. At the present time the reason for this is not yet understood . One posin vivo has not yet been characterized, but in vitro data with human cells shows that it can be generated after IgE-mediated cross-linking of the trimeric form of surface-expressed FcεRI  molecules are formed by the proteolytic cleavage of the transmembrane form of CD23. These cleavage products are produced by intracellular proteolytic processing, metalloproteases of the ADAM family and the house dust mite allergen Der p1 –96. sCD2sCD23 also promotes proliferation and differentiation of various immune cells and enhances production of inflammatory cytokines by binding to various receptors on monocytes and macrophages , 99, 100Galectins are a large and evolutionarily conserved group of lectins that bind to beta-galactosides . They arGalectin-3  has been identified as an IgE-binding receptor that can also interact with FcεRI and activate mast cells –13. Gal-The role of Gal-3 in allergic reactions is complex and depends primarily on whether it is located intracellularly or extracellularly. Extracellularly, Gal-3 has been shown to promote allergic inflammation by facilitating the migration of eosinophils to the airways , 22 and in vivo and in vitro studies indicate that Gal-3 is mostly pro-inflammatory , Bambouskova et al. found that intracellular Gal-3 impairs degranulation and mediator release by decreasing phosphorylation of signaling molecules and calcium response, as well as by promoting internalization of IgE-FcεRI complexes upon antigen triggering . Additioammatory .Since the binding of Gal-3 to IgE is glycan-dependent, it is not surprising that differentially glycosylated IgE antibodies show unique Gal-3 binding capabilities , 114. HoThe impact of IgE complexation on its binding to Gal-3 remains uncertain. While complexed IgE retains its glycans, a reduced binding may be attributed to changes in conformation or steric hindrance that prevent binding to Gal-3. For FcεRI, IgE glycosylation is essential for binding, although the sugars are not directly involved in binding . This isGalectin-9  is also known to bind to IgE . It is p5 M−1 and 4.8 × 105 M−1 for FcγRIII  with an affinity comparable to that of IgG . The ass FcγRIII . Further FcγRIII .A 2.9 × 107 M−1 and 1.7 × 107 M−1, respectively  bind to IgE or IgE-allergen immune complexes (IC). However, it may be postulated that IgE-anti-IgE IgG complexes with or without allergen may bind to FcγR like IgE-omalizumab complexes . AdditioThe regulation of IgE half-life in serum depends strongly on whether it is present as IgE or as an IgE-immune complex (IgE-IC). Monomeric IgE can bind to both FcεRI and CD23. Since the affinity of FcεRI for IgE is exceptionally high, IgE binds quickly and remains bound to the receptor for a relatively long time  , 125. InAs discussed above, the binding of an allergen may influence the conformation of IgE, with an open conformation preferentially binding to FcεRI, and a closed conformation preferentially binding to CD23  after binding to the receptor CD23 is determined by the type of cells that binds the complexes. Interestingly, B cell take up IgE-ICs ive form . This al T cells , 127. Hoferation , 9.It is still not clear how B cells transfer antigens to other cell types. It might be contact-dependent or contact-independent mechanisms such as exosomes . StudiesAdministration of IgE-IC in mice results in the induction of anti-IgE IgG antibodies , 29. SurThe mechanism by which human auto-anti-IgE IgG antibodies are generated remains unresolved, as there is currently no evidence of human FcγRs binding to IgE-IC complexes.H2 response and thus may be responsible for initiating allergic reactions  on APCs may also play a role in humans. The role of antigen presentation by the FcεRI in allergy is not clear. Some studies show that antigen uptake by the FcεRI leads to a Teactions , 59. In eactions , 136. Hovia their IgE-specific B cell receptor, they will automatically process the complexed part  for MHC class II presentation. Hence, the IgE-IC receptor for B cells is the B cell receptor specific for IgE, which also mediates uptake and subsequent allergen processing. For APCs, IgE-IC uptake may be facilitated by the receptors mentioned above. However, in allergic individuals, there will be pre-existing allergen-specific help, rendering the role of APCs for priming T help less important. Hence, the role of IgE receptors in driving anti-IgE IgG responses may vary with pre-existing T help.From an immunological point of view, B cells and APCs may handle IgE-ICs differently. B cells are needed to make the antibodies, and APCs are needed to induce T help. As B cells will take up IgE-ICs The structure, flexibility, and glycosylation of IgE have a significant impact on its fate. The main inflammatory pathway for IgE, FcεRI, preferentially binds monomeric  and glycGalectins, specifically Gal-3 and Gal-9, also interact with monomeric IgE , 12, 14.In mice, some FcγRs, such as FcγRII, FcγRIII, and FcγRIV, have been found to bind IgE-ICs, activating mast cells and inducing the production of auto-anti-IgE IgG antibodies –28. The The bigger picture of the interplay between all IgE-binding receptors is still unresolved. More studies are needed analyzing the interplay between IgE, IgE-IC, IgE glycosylation, and their receptors to gain a clearer understanding. A deeper understanding of this will aid in the development of appropriate therapies against IgE-based diseases.