This paper examines the interpretation that northwest India’s settlement density increased as Indus cities declined by developing an integrated site location database and using this pilot database to conduct large-scale geographical information systems (GIS) analyses. It finds that settlement density in northwestern India may have increased in particular areas after ca. 1900 b.c., and that the resulting landscape of de-urbanization may have emerged at the expense of other processes. Investigating the Indus Civilization’s landscapes has the potential to reveal broader dynamics of social complexity across extensive and varied environments.Survey data play a fundamental role in studies of social complexity. Integrating the results from multiple projects into large-scale analyses encourages the reconsideration of existing interpretations. This approach is essential to understanding changes in the Indus Civilization’s settlement distributions (ca Investigating transformations in the distribution and density of past settlements is crucial to the identification of “signature landscapes,” which are those generated by specific social, cultural, and economic processes within specific physical environments . It hasLandscape archaeology provides the approaches necessary to frame research on past social processes. It has been foundational to modeling social complexity in ancient Mesopotamia Adams , 2017, aWilkinson : 4–9 argb.c.), which were the largest of thousands of settlements across areas that today lie in western India and Pakistan , so there is a degree of imprecision in the reported site location coordinates  project produced two complementary site location datasets that can anchor data assembly projects: the Rakhigarhi Hinterland Survey and the Ghaggar Hinterland Survey. LWS focused on rural life in northwestern India, and expanded and refined a subset of site location datasets from this region , which facilitated the speedy examination of attributes from non-corresponding tables prior to developing related fields through comparison. After importing the selected tables, each site location was given a unique identifying value: the Pilot TwoRains Identification Number (ptr_id). The resulting ptr_id list was initially extensive, including over 10,000 entries. Moreover, overlap between the original tables resulted in significant duplication of entries. To reduce the ptr_id list, entries that shared a common location were reclassified, which reduced the number of ptr_ids. As records based on the same site location were linked to the same key ptr_id, it became possible to query information about the same location derived from multiple sources. Duplicates were then assigned the same ptr_ids by projecting the site table in a GIS (ArcGIS v10.4.1) and examining each location against ESRI’s World Imagery.2 and includes 695 reported site locations.While the resulting ptr_id table allowed the querying of related fields across multiple tables, standardizing the information available for each site location and reconstructing its history and characteristics required the review of each record. To evaluate settlement density in northwest India, ptr_ids from a sample area were selected for more detailed assessment. The sample area consists of a projected rectangle that encloses both LWS survey areas that was automatically generated figure 2.supplemental material 1).Bibliographic information was assembled for each site location and cross-referenced with the original publications to the extent that primary sources were available, and assessments of site location accuracy and precision were included in the resulting table. Outright errors, reported locations that lacked complete geographical information, were located outside of South Asia, or were unlikely to be related to a specific location in the landscape, were flagged with the assistance of GIS analyses undertaken using ArcGIS 10.4.1 and QGIS v2.18.2. The apparent precision of site location reports was noted . Reported periodization for each site location was also compiled and included in the resulting table. The pilot database compiled the history of study for each site location, along with its earliest likely discovery date, and the tabulated results of this compilation are presented in the supplement accompanying this paper  through further fieldwork, it will be possible to identify further gradations of certainty in site location data, and test hypotheses at larger scales.The study reveals the necessity of examining the silos in which archaeological survey data are generated and analyzed. Projecting site locations merely as dots on a map can lure researchers into thinking they understand previous settlement patterns better than they do, while site locations that remain more or less unmoved after multiple on the ground surveys are of particular value. The Indus Civilization in northwestern India is particularly different in this regard, as it takes many different survey datasets to understand the Indus Civilization’s settlement distribution, incorporating some areas that have been surveyed again and again. This very fact means that certain trends in settlement are surer than others. Further investigation of the Indus Civilization’s signature landscapes also has the potential to enhance alternative models of social complexity, revealing how heterarchical social relations may have materialized and supported social relations across vast and varied environments.Archaeological survey data are essential for understanding the dynamics of social complexity. Identifying the signature landscapes that materialized the prevailing social processes that underpinned these dynamics requires large scale analysis that exceed the boundaries of most individual field survey projects. By integrating site location data from multiple projects, this paper offers new support for the interpretation that northwestern India comprised one or more of the Indus Civilization’s signature landscapes, where settlement densities chart trajectories of urbanization and de-urbanization, involving agglomeration and dispersal into areas with suitably favorable environmental conditions. Site location concentrations appear to generally correspond to previous survey coverage, and there has been an overall underestimation of northwestern India’s settlement density across both time and space. There remain many areas where systematic surveys are needed, such as the broad area between the LWS surveys, and many areas would benefit from re-visitation and re-evaluation, such as the site locations reported in the northeastern quadrant of the study area. An extensively occupied landscape appears to have emerged during the Early Harappan period and was largely re-occupied during the Late Harappan period, as there appears to have been a displacement of settlement into specific parts of the plain. It remains necessary to test the veracity of this re-occupation by reassessing sites located in the northeastern corner of the surveyed area and closing gaps in survey coverage. Engaging in such reassessment will contribute to research on the signature landscapes that inform scholarly understanding of urbanization and de-urbanization and the impact of variable and changing environments on settlement distributions in the past.Click here for additional data file.


Young sea ice composed of grease and pancake ice (GPI), as well as thin floes, considered to be the most common form of sea ice fringing Antarctica, is now becoming the “new normal” also in the Arctic. A study of the rheological properties of GPI is carried out by comparing the predictions of two viscous wave propagation models: the Keller model and the close-packing (CP) model, with the observed wave attenuation obtained by SAR image techniques. In order to fit observations, it is shown that describing GPI as a viscous medium requires the adoption of an ice viscosity which increases with the ice thickness. The consequences regarding the possibility of ice thickness retrieval from remote sensing data of wave attenuation are discussed. We provide examples of GPI thickness retrievals from a Sentinel-1 C band SAR image taken in the Beaufort Sea on 1 November 2015, and three CosmoSkyMed X band SAR images taken in the Weddell Sea on March 2019. The estimated GPI thicknesses are consistent with concurrent SMOS measurements and available local samplings. In these conditions, water freezes to form a thin slurry of frazil ice, called grease ice, with thicknesses up to 10–30 cm depending on the windy conditions5. As the freezing process continues, it leads to a further stage of development of the grease ice layer, which consolidates into pancake-shaped ice bodies, called pancake ice7. Grease and pancakes ice (GPI) have always been relatively ubiquitous in the Antarctic MIZ8, and extensive GPI formation has recently been observed also in the western Arctic, as documented during the field campaign in fall 20159.Climate change has led in the last decade to a dramatic reduction in the extent and the thickness of sea ice in the Arctic region during the summer season. As a result, the marginal ice zone (MIZ), which is the dynamic transition region separating the ice pack from the open ocean, has become increasingly exposed to the wind and the wave actionsInvestigations to determine how an increase in GPI may affect the climate, possibly leading to local warming in the far north, are ongoing. These studies and their implementation in climate models clearly require some tools to monitor the GPI’s properties, especially as regards its thickness.11. Validation and calibration of any GPI wave model are tasks that cannot be entrusted to in situ activities, due to the vast extent of the GPI fields, their intrinsic dynamic nature, and the harsh environment where they develop. A systematic and extensive characterization of the spatio–temporal distribution of GPI can however be carried out through remote sensing by exploiting the capability of SAR imaging techniques to measure the full ocean wave directional spectrum12. By tracking the SAR observed ocean wave spectrum , from open sea throughout the GPI cover, it is indeed possible to measure wave dispersion and attenuation. A dedicated GPI wave model can then be used to relate the modifications in the wave propagation with GPI properties such as its thickness and mechanical properties.As the extent of GPI fields is controlled by the presence of waves that usually come from the open ocean, the relationship between wave attenuation rates and GPI rheology is a key factor to understand and model the evolution of the ice cover. Given the large scale separation between pancakes and the typical wavelength, a good approximation to describe the interaction with ocean waves is to represent GPI as a continuum17, the GPI thickness was estimated by a adopting a mass-loading scheme, in which GPI is represented as a continuum of non-interacting point-like mass loads on the sea surface10. However, the success of the approach was limited by the excessively high values of the thickness resulting from SAR inversion.The literature on the application of SAR spectral inversion techniques to GPI thickness retrieval dates back at least to 1997. In earlier papers20 abandoned the mass-loading approach for the more realistic representation of GPI proposed by Keller11. The Keller’s model pictures the GPI layer as a viscous fluid of given thickness h and effective viscosity 21, without a clear relationship with the GPI layer thickness.Later papers22, and the viscoelastic model, which treats the ice layer as a viscoelastic medium23. All these generalizations of the Keller’s model, however, seem unable to significantly reduce the variability of the effective ice viscosity25.Other viscous layer models have been proposed to describe wave propagation in ice/water systems. We can mention the two-layer viscous model (TLV), which assumes the water underneath the ice cover to have a finite viscosity, possibly due to turbulent effects26 makes a first attempt to explicitly take into account the inhomogeneity of GPI, by assuming that pancakes are confined to a fictitious layer of infinitesimal thickness, lying on top of the grease ice layer and modifying the wave stress at the upper surface. The CP model was tested on field data from the Arctic and the Antarctic, along with Keller’s and TLV models25. Fitting of the field data was possible with all the models considered, but only the CP model produced GPI effective viscosities in a range consistent with that of grease ice in laboratory experiments  model12 and later modified for the SAR image cross-spectral transform28.Estimation of the directional open ocean wave spectrum 29: Simulation of the ocean wave spectrum in sea ice 12,Transformation of the simulated wave spectrum to a SAR image spectrum Comparison of the modeled and the observed SAR spectrum, The SAR inversion procedure consists of the following four steps:25. The present study is therefore limited to the Keller’s and the CP model. An outline of the models is presented in the “The procedure is therefore characterized by the choice of the viscous wave propagation model to predict the wave damping. Predictions on 25. The valleys follow power-law curves In the former SAR inversion schemes, the couple 30. Both in the case of the Keller’s and the CP model, calibration produces an effective viscosity which is a monotonically increasing function of the ice thickness.We perform such calibration thanks to a study conducted in the Odden Ice Tongue, Greenland Sea. The Odden Ice Tongue developed in 1996/1997 and was characterized by massive presence of GPI. The process was extensively documented by SAR imagery, and GPI thickness maps obtained from a specifically developed model were availableThe proposed calibration technique is eventually tested on four different SAR images gathered by Sentinel-1A and COSMO-SkyMed, representing case studies for the Arctic and for the Antarctic MIZ, respectively. The SAR retrieved GPI thicknesses result in good agreement with the concurrent SMOS measurements and the available local samplings.21C and h are respectively the concentration and thickness of grease (gr) and pancake (p) ice. The relation is physically sound, as it states a proportionality between wave decay and ice volume per unit area of the region of the sea traveled by the waves. We point out that the effective ice thickness is the quantity most relevant to the overall changes in ice volume, and is used in numerical dynamic-thermodynamic sea ice models31. Hereafter we will refer to the GPI thickness as the effective ice thickness of the GPI layer.The analysis of a set of wave buoy data gathered in the advancing MIZ of the Weddell Sea covered by GPI clearly revealed that the GPI wave attenuation rates scale with the “equivalent solid ice thickness”h and 25. On the contrary, the parameter h dependence of 18. From a broader perspective, this suggests that if one uses a viscous layer model to describe wave propagation in a GPI field, a viscosity dependent on the ice thickness is required to reproduce the attenuation data. We consider this an important contribution to the understanding of sea ice rheology, which is an open question for the forecasting/hindcasting of waves in and near the MIZ32.As discussed in the “entclass1pt{minima30, developed specifically to describe the formation, transport and desalinization of GPI in the Odden region of the Greenland Sea, and carefully validated with in situ measurements. Indeed, an oceanographic campaign was carried out into the Odden from March 3 to March 13 1997 on the R/V Jan Mayen30. The Odden locations visited during the cruise operations were imaged by the SAR onboard the ERS2 satellite. In particular, a couple of ERS2 SAR images gathered on March 9, 1997, in coincidence with the acquisition of a Datawell directional wave buoy at 14, and on March 11, 1997, centered at In order to determine the functional form of insitu ice samplings collected in coincidence with SAR data takes, yields, in the two dates selected, values of the equivalent ice thickness h in the range 4-9 cm, with relative error The equivalent solid ice thicknesses, predicted by the salt-flux model for the areas imaged by the concurrent ERS2 SAR images, were computed according to . CompariA total of 24 windows at increasing distance from the ice edge were selected for application of the SAR inversion scheme, to sample the overall GPI thickness spatial variability predicted by the salt-flux model. Figure 33 was adopted to account for the uncertainties in the ice viscosity and thickness, in the assumption of a linear relation between ice viscosity and ice thickness on a log-log scale. Figure GPI viscosity values were estimated after minimization of the SAR cost function, by imposing the GPI equivalent thicknesses predicted by the salt-flux model. Figure mentclass2pt{minim34, red points in Fig. h and characteristic time The data in Fig. mentclass2pt{minim27, while in the case of the Keller’s model the GPI viscosity is about one order of magnitude higher than the laboratory measurements. We think that such higher viscosity, required to fit the data with the Keller’s model, reflects the contribution of pancakes to the overall ice viscosity. Once the value of Substituting Eq.  into Eqsmentclass2pt{minimtion Eq.  providesEquations  and 11)11) are i9.On 1 November 2015, an IW-mode S1A SAR image was collected in the advancing MIZ of the Beaufort Sea  recognized three ice types, namely, young grey ice, pancakes and first year ice, along with an estimation of the primary thickness and partial concentrations for each ice type. Occasional ship-side retrieval of frazil ice and pancakes samples was also carried out as a concurrent measurement, and a number of directional wave buoys were deployed.A sharp ice edge can be detected in the S1A SAR image separating the open sea (bottom part) from the ice field. The region of icefield directly exposed to open sea appears to be mainly composed of GPI. The hourly visual observations conducted aboard the R/V Sikuliaq using the ASSIST protocol , 15 T2) and 11 (T3) SAR image tiles of size  and 11 . Daily coverage of the polar regions with a resolution of about 35 km Thicknesses from SAR retrievals using CP and Keller’s models are all within the SMOS and ASSIST range of thicknesses and show a consistent behaviour running over the ice field depth. The overall trend shows increasing thicknesses going from the ice edge up to values close to 25 cm.20.In transect T1 a good agreement between CP and Keller results is observed. At the fourth location, close to the ship, a thickness of In transect T2, thicknesses retrieved with both CP and Keller’s models agree for the first 5 km inside the ice fields (windows 1–5). A good correspondence between ASSIST thickness (15 cm) and SAR retrievals  and CP thickness  constellation. We have applied the SAR-wave inversion technique to the SAR WIDEREGION images acquired on 21, 22 and 30 March 2019, where at least one CSK SAR satellite was able to image the sea ice edge.In the context of the Year of Polar Prediction (YOPP) initiative of the World Meteorological Program37 available for each date. Details of SAR images characteristics and retrieved wave fields are listed in Table An open ocean wave field of mentclass2pt{minimA common feature of the three SAR images is represented by the dark areas adjacent to the ice edge at direct contact with the open sea, which reveal the presence of bands of pure frazil/grease ice, from which pancakes originate. The SAR images taken on 21 and 22 March almost overlapped the same area of the Weddell Sea and were able to image the outermost part of the developing GPI field; on 30 March, a wider area was imaged by the SAR instrument, which includes the region imaged on 21 and 22 March, thus showing an expansion of the GPI field. Figures As a general comment, smaller values of the thickness, much closer to the SMOS estimations, resulted from the SAR inversion, compared to the Beaufort Sea case study. In the region closer to the ice edge the inferred GPI thickness is about 3 cm higher the extremal SMOS value, with a trend to decrease when running towards the inside of the icefield, in contrast to the case study in the Arctic. The phenomenon could be caused by the action of the wave field that tends to compact the GPI in the region immediately surrounding the ice edge.h, when available. Similarly, a general agreement between the inferred thicknesses is observed for the two transects of the 30th of March.Figures A new technique aimed at the estimation of GPI thickness from the inversion of SAR image wave spectra is proposed. The intrinsic undetermination of any SAR inversion technique based on a viscous layer model is resolved with an empirically determined constitutive relationship between the viscosity and the thickness of the GPI layer, 38 on dimensional grounds, based on the hypothesis that h is an effective thickness, proportional through Eq. 12 and later modified for the SAR image cross-spectral transform28. For 42, the wind-generated ocean spectrum is first estimated. The parametric representation given by Donelan et al. (1985)43 is assumed, which depends on the inverse age of the dominant wave, 44. Then, the residual wave spectrum is estimated by assuming a parametric representation of directional swells according to the JONSWAP-Glenn spectral shape coupled with a directional spreading function of the Mitsuyasu type, properly extended for swell propagation45. This choice accounts for non-linearity in SAR imaging features induced by high swells that can occur in the polar seas. Thus, the implemented SAR retrieval of swells adopted a non-linear retrieval scheme which minimizes a cost function with the truncated Newton method implemented in IDL©with respect to the following seven parameters: the dominant wind wavenumber vector; the dominant swell wavenumber vector; the swell wave height; the shape parameters and the directional spread of the swell distribution. The Hasselmann and Hasselmann (1991)12 inversion method is applied in alternative, whenever the directional wave buoy data is available.The first step consists of the estimation of the directional open ocean wave spectrum at the boundary of the icefield from the available SAR image. The corresponding wavenumber SAR image spectrum is estimated from a tile, typically A series of adjacent SAR tiles of 12 and Engen and Johnsen28 for It is assumed that the GPI cover alters the incoming ocean wave spectrum mentclass2pt{minimmentclass2pt{minimThe two wave propagation models we consider in our analysis assume that sea ice can be treated as a viscous medium. In the presence of gravity waves, viscosity in the ice layer produces a finite normal stress on the ice-free water underneath, thereby modifying the wave dispersion relation. The main difference between the Keller’s and the CP model resides in the way they treat the contribution from pancakes. The Keller’s model implicitly treats GPI as homogeneous medium; the CP model makes the hypothesis that pancakes lie on top of the grease ice layer. The pancake layer is supposed infinitely thin in such a way that its only contribution to the wave dynamics is to generate a finite tangential stress at the top of the grease ice layer. Such tangential stress is obviously absent in the case of the Keller’s model, where the top of the ice layer corresponds to the interface with the atmosphere. In both models the normal stress at the top of the ice layer is zero.2, possibly related to global climate change, a linear wave assumption still holds in our analysis. Indeed in all cases here considered, the significant wave height is two orders of magnitude smaller than the peak wavelength  and a situation in which the pancakes are so closely packed to form an inextensible layer.46 support the modelling assumption. In this regime both the Keller’s and the CP model are described by just two parameters: the thickness h of the ice layer, and an effective ice viscosity k, the ice thickness h and the viscous boundary layer depth The latter regime is the one which concerns us; field measurements by10. The wave attenuation is the imaginary part of the wavenumber vector, For small h-dependence of The  in Eqs.  and 17)h-dependeh the asymptotic relations Eqs. h the asyh, we verify that the result in Eqs.   h, we ve


Protein phosphorylation enables a rapid adjustment of cellular activities to diverse intracellular and environmental stimuli. Many phosphoproteins are targeted on more than one site, which allows the integration of multiple signals and the implementation of complex responses. However, the hierarchy and interplay between multiple phospho-sites are often unknown. Here, we study multi‐site phosphorylation using the yeast trehalase Nth1 and its activator, the 14-3-3 protein Bmh1, as a model. Nth1 is known to be phosphorylated by the metabolic kinase PKA on four serine residues and by the cell cycle kinase CDK on one residue. However, how these five phospho-sites adjust Nth1 activity remains unclear. Using a novel reporter construct, we investigated the contribution of the individual sites for the regulation of the trehalase and its 14-3-3 interactor. In contrast to the constitutively phosphorylated S20 and S83, the weaker sites S21 and S60 are only phosphorylated by increased PKA activity. For binding Bmh1, S83 functions as the high‐affinity “gatekeeper” site, but successful binding of the Bmh1 dimer and thus Nth1 activation requires S60 as a secondary site. Under nutrient-poor conditions with low PKA activity, S60 is not efficiently phosphorylated and the cell cycle dependent phosphorylation of S66 by Cdk1 contributes to Nth1 activity, likely by providing an alternative Bmh1 binding site. Additionally, the PKA sites S20 and S21 modulate the dephosphorylation of Nth1 on downstream Bmh1 sites. In summary, our results expand our molecular understanding of Nth1 regulation and provide a new aspect of the interaction of 14-3-3 proteins with their targets. Metabolism provides the energy and building blocks for all cellular functions. The regulation of metabolism needs to be responsive to many different external signals such as nutrient concentrations, and internal signals such as cell cycle state. Many of these signaling pathways have been identified, but how they quantitatively regulate metabolic activity is often poorly understood. Additionally, numerous signaling pathways, such as nutrient sensors and stress response pathways, converge on important metabolic pathways. Even if the effect of individual signals is well-studied, the integration and hierarchy of multiple signals acting on metabolism often remains unclear.S. cerevisiae is an interesting example to study complex metabolic regulation. This pathway is physiologically4 and industrially7 relevant, it is regulated by multiple pathways such as nutrient and stress responsive signaling8, and is regulated by multiple mechanisms on transcriptional and post-transcriptional level9. In brief, the disaccharide trehalose and its derivatives serve as a carbohydrate storage, as chemical stress protectant, and as signaling molecules. It is thus built up in high amounts during stresses such as heat shock and desiccation11, in cells approaching stationary phase12 or growing slowly in nutrient-poor conditions14. In fact, trehalose concentrations have been shown to anti-correlate with growth rate15. During slow growth, it builds up through the G1-phase and is degraded periodically over the rest of the cell cycle20.The trehalose pathway in 21. Nth1 has been extensively studied as a model for metabolic regulation because it has both an interesting regulatory mechanism and is experimentally well accessible: we and others have shown that the catalytic activity of Nth1 is determined by both the cell cycle kinase CDK (cyclin dependent kinase)19 and the metabolic kinase PKA (protein kinase A)23. Another feature that makes Nth1 an interesting model is its regulation by the 14-3-3 protein Bmh124. 14-3-3 proteins are conserved across eukaryotes as regulators of apoptosis, cell cycle control, and nutrient-sensing pathways26. In yeast, among many other functions, Bmh1 (and Bmh2) binding leads to a conformational change and activation of Nth128. Deletion of Bmh1/2 leads to loss of trehalase activity22. The binding of the Bmh1 dimer is regulated by phosphorylation of Nth1 on its interaction sites S60 and S8329. Therefore, Nth1 is an interesting case to study both the interdependency of multi-site phosphorylation and how multiple phosphorylation sites can be read and translated into an enzymatic activity by 14-3-3 proteins.Here, we focus on the regulation of the final step in the trehalose pathway, the trehalase Nth1, which converts trehalose back to glucoseHowever, while several features of Nth1 regulation have been identified, many aspects are missing for a mechanistic molecular understanding of this interesting model enzyme, including: how do the two kinases CDK and PKA jointly regulate Nth1 under different conditions? What is the role of individual PKA sites and how do those phosphorylation sites that are outside of the Bmh1 binding region 23. However, it is still unclear which sites are actually phosphorylated in vivo under different metabolic circumstances and how this translates to trehalase activity. To first confirm that both kinases specifically modify (only) their known sites, we performed in vitro phosphorylation assays. The autoradiograph of 6xHis-tagged recombinant protein revealed that Nth1WT but not Nth1S20,21,60,83A (hereafter termed Nth1∆PKA/S66) can be phosphorylated strongly by PKA, showing that the main PKA sites are these previously identified four sites 30. To further improve the separation of different phospho-isoforms, we constructed a reporter peptide, containing only the 95 amino acids long N-terminal regulatory tail linked to a 3xFLAG tag for detection  or the full length 3xFLAG-tagged Nth1 (at the endogenous locus) after re-addition of glucose to stationary phase cells causing a sharp increase in PKA activity. Analysis of the reporter construct by Phos-tag-SDS-PAGE results in a complex phosphorylation pattern of at least six differently phosphorylated isoforms. This recapitulates the phosphorylation of the 80 kDa full-length protein well, although the dynamic is somewhat slower and the shift to the higher phospho-isoforms is lower in the full-length protein  cells display a low PKA activity32 and a Cdk1 activity that oscillates over the cell cycle (low in G1 and increasing until mitosis)34.In vivo, Nth1 is activated through different signals to utilize intracellular accumulated trehalose; two of these signals we compare in this study Fig. a: firstlWT reporter protein for four days to stationary phase, where PKA activity is very low36. Surprisingly, Nth1 already exhibits at least three phospho-isoforms in addition to the unphosphorylated form showing that some of the sites are constitutively phosphorylated on a fraction of the protein molecules even in stationary phase  and CLN1 is under a hormone-inducible promoter allowing to control Cdk1 activity. Cells were arrested in G1 and then synchronously released into the cell cycle by addition of β-estradiol . Interaction studies were performed with the full-length Nth1, since the reporter is not able to bind Bmh1  leading to partial phosphorylation of the PKA sites on Nth1. To analyze the impact of Cdk1 we then additionally phosphorylated Nth1 with CyclinB-Cdk1. Immunoprecipitation of Bmh1 showed that more Nth1 was bound after phosphorylation by both CyclinB-Cdk1 and PKA than PKA only  while in the Nth1S83A mutant almost no interaction could be detected (< 10% norm. to WT)  of PP2A might recognize this region, we analyzed the phosphorylation of a truncated construct lacking the first 24 amino acids of the N-terminal tail. Indeed, compared to the S20,21A mutant, the truncation revealed an increase of a higher phosphorylated isoform already in the stationary phase which corresponds to the double phosphorylated S60/83 band. This indicates that the absence of this region causes a reduced dephosphorylation of one of the downstream sites. We thus mutated S83 to alanine in the truncated reporter to see if there is an increase in premature S60 phosphorylation. Indeed, in the truncated reporter, we detected a band of S60 phosphorylation already in the stationary phase, indicating that dephosphorylation of S60 is dependent on the first 24 amino acids of the peptide xE Fig. a which hide Fig. b.Figure 43. However, the Nth1E24A mutant showed no higher phosphorylation in the stationary phase compared to the WT  revealed that trehalase activity seems to be determined by the amount of the most highly phosphorylated isoform  sites may be able to provide this binding interface. How these alternative second binding sites are implemented structurally is outside the scope of this study, but warrants exploration to further understand 14-3-3 regulation beyond yeast.The regulation of Bmh1 binding to Nth1 by at least two kinases provides an interesting extension to the canonical model of 14-3-3 interactions. Following established models, the Bmh1 binding site pS83 acts as the high affinity “gatekeeper” site also found in many other proteins22. We propose that the region surrounding S20/21 mediates this dephosphorylation  leads to a reduced dephosphorylation of the downstream sites S60 and 83 in stationary phase cells. Interestingly, a phospho-mimetic S20ES21E mutant also leads to increased phosphorylation of S60. This suggests that one function of the PKA sites S20 and S21 is to shift the balance between phosphorylation and dephosphorylation of the downstream Bmh1-binding sites S60 and S83. While the enzyme needs to be dephosphorylated when cells are going into stationary phase, the phospho-sites need to be protected upon glucose replenishment. This is especially relevant since PP2A is also activated upon glucose addition49. Once Bmh1 has bound S60 and S83, this shields them from premature dephosphorylation.Phospho-regulation is not just determined by kinases, but rather by the balance between kinases and phosphatases. The phosphatase PP2A has been previously suggested to regulate Nth1ion Fig. . Mechani22. Alternatively, this region could be contributing to the stability of Nth1, but we have so far not found any evidence for this.While we have identified regulating dephosphorylation as one function of the phospho-sites S20 and 21, it is clear that this region must also have an additional role in regulating Nth1 catalytic activity. All mutations we made in the region spanning S20 and S21 led to a reduction of catalytic activity by at least 50%. We suggest two possible mechanisms: firstly, since this unstructured flexible region of the protein is not clearly resolved in the published structure, the very N-terminal amino acids including S20 and S21 could have an unappreciated structural function in supporting Bmh1 binding or be involved in the structural changes following Bmh1 binding. Secondly, there could be yet another regulator binding to the N-terminal tail of Nth1, such as the previously suggested Dcs150, our findings may guide the investigation of other targets of multi-site phosphorylation, and their interactions with 14-3-3 proteins.Taken together, our results greatly expand our understanding of the molecular mechanisms governing the regulation of the model enzyme Nth1 by PKA, CDK, and Bmh1. Since PKA and CDK have many common targets, and CDK sites are enriched on Bmh1 interactorsSaccharomyces cerevisiae W303 derived background. Plasmid containing NTH1 were constructed using standard molecular cloning. Plasmids were linearized with either SalI in the promoter (full-length constructs) and integrated into the genomic NTH1 promotor or with StuI in the URA3 region (reporter constructs) and integrated into the URA3 locus. All constructs were Sanger-sequenced. Cell cycle inducible strains from our previous study16 were used. Estradiol inducible strains were transformed and maintained on YPD plates containing 100 nM β-estradiol (Alfa Aesar). A detailed strain list is included in the All strains were constructed using homologous recombination in a prototrophic Cells were grown on minimal media ), pH adjusted to 5, with either 1% glucose  or 1% ethanol.The cultures were inoculated in 1% glucose minimal media (GMM) from an overnight preculture to an optical density of 0.2. After four days, cells were released from stationary phase by 1:5 dilution in fresh GMM.16: two sequential 24-h pre-cultures were grown on 1% ethanol minimal medium (EMM) media containing 15 and 10 nM β-estradiol (Alfa Aesar), respectively. To induce cell cycle arrest, cells were filtered, washed and the filter resuspended in estradiol-free EMM (starting OD600 was between 0.1 and 0.2). Before release, inducible LexApr-CLN1 strains were arrested for 15 h. Cells were released into the cell cycle by addition of 200 nM β-estradiol (dissolved at 1 mM in 100% ethanol). Cell cycle arrest and release were verified by bud count at 60 × magnification in a light microscope.Cell cycle experiments were performed similarly to our previous study1 arrested cells that were glucose-starved, two sequential 9 h and 15 h pre-cultures were grown on 1% GMM supplemented with 50 mM potassium phthalate containing 80 nM and 50 nM β-estradiol, respectively. Cells were arrested for 6 h in 0.5% glucose minimal medium supplemented with 50 mM potassium phthalate (starting OD600 was ~ 1.2). Cells were diluted in glucose minimal medium to a final concentration of 1% glucose with or without addition of 200 nM β-estradiol. To verify glucose depletion, glucose was measured with a commercial kit from .For Gg for 1 min and the cell pellets were washed once with 750 µl minimal medium without glucose, frozen in liquid nitrogen and stored at − 80 °C.1.5 ml of cell culture were sampled and chilled on ice for 1 min. Cells were harvested by centrifugation at 21,200g followed and supernatants were transferred into fresh tubes. An additional extraction step was performed with a 5-min incubation in the 90 °C water bath, followed by a centrifugation and combining the supernatants. Extracted trehalose was frozen at − 20 °C. The trehalose concentration was determined enzymatically with a commercial kit . The absorbance was measured spectrophotometrically with a FLUOstar OPTIMA (BMG LABTECH).Trehalose was extracted by adding 200 µl boiling water (90 °C) to the frozen cell pellets and placing the samples in a boiling water bath (90 °C) for 10 min. During incubation, the samples were vortexed vigorously every 2 min. A 5-min centrifugation at 21,2002 according to the instructions from the manufacturer. Gels were electrophoresed at 15 mA/gel for 5.5 h for the full-length protein and until the front reached the end of the gel for the reporter. For phosphatase treatment, cells were lysed with urea lysis buffer without phosphatase inhibitor. Diluted lysates were treated with Lambda phosphatase (New England Biolabs). For Western analysis, gels were blotted on a dry system , Nth1-3XFLAG was detected with anti-FLAG M2 antibody , Bmh1-V5 was detected with anti-V5 antibody , and Alexa Fluor 680 goat anti-mouse antibody . Blots were imaged on a Peqlab Fusion SL Vilber Lourmat. Bands were quantified using the image analysis software Image Studio Lite Ver 5.2.5 (Li-COR https://licor.app.box.com/s/4hrk823vov7vittqjg3onj51tb0wbo6w). All blots reported in the figures are additionally shown in full-length in the Supplementary File. Additionally, alternative exposures are presented for high-contrast blots.Cells were directly sampled into two volumes of 75% methanol, 15 mM Tris–HCl (pH 7.5) (prechilled to − 20 °C) and centrifuged at 4000 rpm at 4 °C. Pellets were frozen in liquid nitrogen and stored at – 80 °C. Lysates were prepared using a bead beater in urea lysis buffer  supplemented with 1 × EDTA-free protease and phosphatase inhibitor cocktail (GoldBio). To separate the phosphorylated species of Nth1-3xFLAG, 8% SDS–polyacrylamide (Biorad 29:1) gels were used for the full-length protein and 10% SDS–polyacrylamide gels were used for the 95 aa reporter constructs. These were supplemented with the 100 µM Phos-tagAcrylamide AAL-107  and 200 µM MnCl2, 0.1% Triton X-100, 2 × EDTA-free protease and phosphatase inhibitor cocktail (GoldBio), 70 µg/ml DNAse [(3895.8 µ/mg) PanReac AppliChem]. Crude extracts were centrifuged at 13,300 rpm for 10 min at 4 °C to remove cell debris.Cells were sampled into three volumes of ice-cold buffer  and centrifuged at 4000 rpm at 4 °C. Pellets were frozen in liquid nitrogen and stored at − 80 °C. Lysates were prepared by bead beating in 400 µl lysis buffer  and once with lysis buffer. Immunoprecipitation was carried out at 4 °C under continuous gentle agitation for 1 h. Immunoprecipitates were washed once with lysis buffer and six times with wash buffer and subsequently boiled in 30 µl 1XSDS sample buffer  for 3 min.3XFLAG-tagged Nth1 was immunoprecipitated using Anti-FLAG M2 magnetic beads . Magnetic beads were washed three times with wash buffer  and centrifuged at 4000 rpm at 4 °C. Pellets were frozen in liquid nitrogen and stored at − 80 °C. Lysates were prepared by beating in lysis buffer supplemented with 5% glycerol. Crude extracts were centrifuged at 13,300 rpm for 10 min at 4 °C to remove cell debris.Cells were arrested in G2, 0.25 mg/ml BSA, 500 µM ATP and ~ 0.5 µg commercially available human CyclinB-Cdk1 (Merck). The reaction was carried out at 30 °C and was stopped using SDS-PAGE sample buffer after 5 min.For Cdk1 phosphorylation, 10 µg protein in 5 µl lysis buffer were mixed with 20 µl kinase reaction buffer containing 20 mM MOPS pH 7.2, 10 mM glycerol 2-phosphate, 4 mM MgCl16 and 6xHis-Bmh123 were expressed from pET28a vector, Nth1-Strep was expressed in pASK-Iba3. Recombinant Nth1 and Bhm1 proteins were expressed in BL21(DE3)RP cells. 6xHis-Nth1 was induced with 0.3 mM IPTG at 23 °C, and 6xHis-Bmh1 was induced with 0.5 mM IPTG at 37 °C. For induction of Nth1-Strep, 250 ng/µl anhydrotetracycline was used. Standard cobalt affinity chromatography with 200 mM imidazole for elution was used for purification of His-tagged proteins. Purification of Nth1-Strep was performed using Strep-Tactin II Superflow (IBA Lifesciences). Clb2-Cdk1 was purified from yeast cells overexpressing Clb2-TAP as described previously52.6xHis-Nth12, 20 mM imidazole, 2% glycerol, 0.2 mg/ml BSA, 500 nM Cks1 and 500 µM ATP . PKA  in final concentration 90 U/µl and 1 mM MnCl2. The proteins were eluted with SDS-PAGE sample buffer and bound Nth1-Strep was detected by Western blotting using StrepMAB-Classic antibody (IBA Lifesciences) and HRP-conjugated anti-mouse IgG antibody .Nth1-Strep (200 ng per sample) was phosphorylated with cyclin B-Cdk1 and/or PKA , resulting in full phosphorylation by Cdk1 and partial phosphorylation by PKA. BL21RP lysate containing induced 6xHis-Bmh1 was loaded on Chelating Sepharose resin, washed, and mixed with phosphorylated Nth1-Strep. The mixture was kept on a shaker for 10 min, followed by washing of the Chelating Sepharose beads with 25 mM Tris–HCl, pH 7.4, 150 mM NaCl, 5 mM CaClSupplementary Information.


Whole-body Patlak images can be obtained from an acquisition of first 6 min of dynamic imaging over the heart to obtain the arterial input function (IF), followed by multiple whole-body sweeps up to 60 min pi. The use of a population-averaged IF (PIF) could exclude the first dynamic scan and minimize whole-body sweeps to 30–60 min pi. Here, the effects of (incorrect) PIFs on the accuracy of the proposed Patlak method were assessed. In addition, the extent of mitigating these biases through rescaling of the PIF to image-derived IF values at 30–60 min pi was evaluated.K1, k3, and both K1 and k2) multiplied by 2, 1.5, and 0.75; and addition of noise . Subsequent Patlak analysis using the original IF (representing the PIF) was used to obtain the influx constant (Ki) for the differently simulated TACs. Next, the PIF was scaled towards the (simulated) IF value using the 30–60-min pi time interval, simulating scaling of the PIF to image-derived values. Influence of variabilities in IF and rate constants, and rescaling the PIF on bias in Ki was evaluated.Using a representative IF and rate constants from the literature, various tumour time-activity curves (TACs) were simulated. Variations included multiplication of the IF with a positive and negative gradual linear bias over 60 min of 5, 10, 15, 20, and 25% (generating TACs using an IF different from the PIF); use of rate constants  to < 5%.Percentage bias in Ki estimates. Consequently, dynamic Patlak imaging protocols may be performed for 30–60 min pi making whole-body Patlak imaging clinically feasible.Simulations suggest that scaling of a (possibly incorrect) PIF to IF values seen in whole-body dynamic imaging from 30 to 60 min pi can provide accurate  The star uptake . Throughr uptake , 14. Howr uptake –17.Dynamic PET imaging allows for spatiotemporal activity concentration distribution measurement which can provide voxel-wise metabolic information when used by tracer pharmacokinetic modelling methods, for example, full kinetic analysis, i.e., Patlak analysis –21.Up to recently, dynamic PET imaging was mainly performed using single-bed/single-axial field-of-view acquisitions. Currently, with state-of-the-art PET/CT systems, whole-body dynamic (Patlak) images can be obtained from a combined acquisition of first 6 min of dynamic imaging over the heart to obtain the arterial input function (IF) followed by multiple whole-body sweeps up to 60 min pi. This procedure followed by a standard static whole-body PET, however, can take a total examination time to 75 min , includi18F-FDG imaging [k3 and (if it exists) k4) is recommended before implementation [The use of a population-averaged input function (PIFs) could obviate the need for the first dynamic scan and minimize whole-body sweeps to an interval of 30–60 min pi  making w imaging , 23–26. entation . TherefoK1 was 0.301 min−1, k2 was 0.600 min−1, and k3 was 0.047 min−1 [Cblood represents the original representative left ventricle arterial IF, and Ctissue is the obtained TAC. The PET TAC was then generated using Eq. Vb equal to the blood volume fraction.To explore the effects of (possibly incorrect) PIFs on the accuracy of Patlak analysis based on dynamic whole-body PET acquisition from 30 to 60 min pi, various tumour time-activity curves (TACs) were simulated. To this aim, a representative IF from previously acquired data (acquisition and processing described in ) was use47 min−1 , 27. TACSimulations were performed in the Python programming language using an in-house written code.y = 1 to y = 1.25 and starting at y = 1 to y = 0.75 in the case of 25% bias. These simulations were also reversed, e.g., the IF was multiplied by a positive and negative linear function starting at y = 1.25 to y = 1 and starting at y = 0.75 to y = 1 in the case of 25% bias. Variations in IF accounted for a total number of 35 simulations.Through the multiplication of the IF with a positive and negative gradual linear bias using different slopes over 60 min, variations in IF were simulated. Differences in slope steepness included a positive and negative gradual linear bias from one to 5, 10, 15, 20, and 25% multiplied by the IF, e.g., the IF was multiplied by a positive and negative linear function starting at K1, k3, and both K1 and k2) multiplied by 2, 1.5, and 0.75 . These unt rate , respectunt rate .Ki) for the differently simulated TACs. Subsequently, the incorrect PIFs were scaled towards the correct value using the 30–60-min pi time-interval simulating scaling of the PIF to image-derived values. After rescaling, Ki were obtained using these adjusted PIFs to see the extent to which previously obtained biases in Ki could be mitigated. A schematic overview regarding the modification and rescaling of the IF is shown in Fig. To show the extent to which incorrect PIFs influence the accuracy of Patlak analysis, analyses using the original IF (representing the PIF) were used to obtain the influx constant . Percentage bias in Ki before and after rescaling of the PIF. The effect of variations in rate constants combined with a gradual modification of the IF on the percentage difference in Ki before and after rescaling of the PIF is shown in Fig. Ki before and after rescaling of the PIF, see Fig. Figure Tumour quantification using SUVpeak following the PERCIST guidelines describes stable metabolic disease as an increase or decrease in SUVpeak of less than 30% . HoweverKi biases to < 5%. However, there were three incidences (out of 290) which resulted in remaining biases > 5% after rescaling: the combination of 25% gradual IF modification and k3*2 resulted in a remaining Ki bias of 8%, the combination of 25% gradual IF modification and k3*1.5 resulted in a remaining Ki bias of 7%, and the combination of 20% gradual IF modification and k3*2 resulted in a remaining bias in Ki of 6%. When using PIFs for whole-body Patlak imaging in patients with high nuclear grade and/or high proliferation activity tumours , this sKi bias of − 1.2, − 10, and − 20%, respectively (data not shown). This indicates that the Ki bias through the use of a  PIF is small compared to possible biases in case of large blood volume fractions. With regard to the acceptable accuracy level of 5% when using a PIF for estimating the tumour kinetic behaviour, the acceptable total bias would be 25%, which is just within the PERCIST recommendations [Please note that when using Patlak analysis, bias may occur even with a perfectly correct IF. Bias in the Patlak analysis may occur as a result of not incorporating the fractional blood volume in the Patlak equations. Blood volume fractions of 0, 8.9, and 20% resulted in a Patlak ndations . Yet, fondations  resultinKi would be around 4% [A similar study to develop a simplified Patlak protocol through using PIFs based on clinical data was performed by S. Yao et al. . Here, sround 4% , which iAnother study that explored the alternative of using a PIF instead of arterial blood sampling found a very high correlation between the two methods . The addKi estimates. Consequently, dynamic Patlak imaging protocols may be performed for 30–60 min pi making whole-body Patlak imaging clinically feasible.Simulations suggest that scaling of a possibly incorrect PIF to (image derived) IF values seen in whole-body dynamic imaging from 30 to 60 min pi could be a good strategy to obtain accurate


The PDZ domain of Dishevelled 3 protein belongs to a highly abundant protein recognition motif which typically binds short C-terminal peptides. The affinity of the PDZ towards the peptides could be fine-tuned by a variety of post-translation modifications including phosphorylation. However, how phosphorylations affect the PDZ structure and its interactions with ligands remains elusive. Combining molecular dynamics simulations, NMR titration, and biological experiments, we explored the role of previously reported phosphorylation sites and their mimetics in the Dishevelled PDZ domain. Our observations suggest three major roles for phosphorylations: (1) acting as an on/off PDZ binding switch, (2) allosterically affecting the binding groove, and (3) influencing the secondary binding site. Our simulations indicated that mimetics had similar but weaker effects, and the effects of distinct sites were non-additive. This study provides insight into the Dishevelled regulation by PDZ phosphorylation. Furthermore, the observed effects could be used to elucidate the regulation mechanisms in other PDZ domains. PDZ can bind a number of various partners ranging from short C-terminal peptides through intramolecular motifs6 to lipids10. PDZ is a relatively small 80–100-residues-long domain, composed of six 11. The affinity of PDZ towards various ligands can be dynamically modulated by disulfide bond formation12 and post-translation modifications such as methylation13 or phosphorylation15,which can be present on both the ligand19 and the PDZ25. However, a molecular understanding of how the affinities are modulated by phosphorylation and what the associated structural changes are remains elusive26.Protein-protein interactions play a crucial role in many biological processes. The PDZ domain28 such as a Dishevelled protein (DVL), a key component of Wnt signaling pathways29. Upon Wnt pathway activation, DVL is heavily phosphorylated by multiple different kinases, of which the most important are casein kinase 1 (CK1) and NEK2. Our unbiased proteomic screen in cells31 has recently shown that the PDZ of DVL is phosphorylated at four residues in a kinase-specific pattern. Moreover, we showed that two out of these four phosphorylation sites in DVL PDZ could modulate PDZ affinity towards the DVLs C-terminus, which is associated with an auto-inhibitory function32. PDZ phosphorylation sites are conserved in all metazoa; it is therefore anticipated that the PDZ phosphorylation code is essential for DVL’s function and the modulation of its interactions with downstream effectors. However, how PDZ phosphorylation sites and/or their combinations affect the structure and binding affinity of PDZ to cognate ligands is unknown.The versatile binding properties of PDZ are typically exploited in signaling hubs and scaffolding proteins34. Moreover, simulations allowed us to directly compare phosphorylations to their corresponding phospho-mimetic mutants, commonly used in experiments. The key findings were validated by nuclear magnetic resonance (NMR) spectroscopy and biological assays.Here, we set out to study the aforementioned phosphorylation sites of the PDZ from the third isoform of human DVL (hDVL3)see Fig. . We usedA general trend in our simulations was that the PDZ domain remained relatively stable, with only loops and extensions being significantly mobile. The highest Root Mean Square Fluctuation (RMSF) was observed for 10 residues in the long loop between strands entclass1pt{minimasee Fig. . The shosee Fig.  and it tentclass1pt{minimaFirst of all, we examined the phosphorylation of S263. S263 resides on strand The interaction of the S263E mimetic with R320 was weaker compared to the phosphoserine, and was only transient in our simulations  . The chemical shift perturbations of all residues in all PDZ mutants and wt are shown in supplementary information  affinity towards a peptide from its own C-terminus aa 698-716) was tested by NMR titration experiments  cells35. In this assay, Wnt3a signal transduction—analyzed by Dual-Luciferase TopFlash reporter gene assay  we did observe a slight activation even in the absence of Wnt3a, and similarly to the S263E mutant, observed an increased activation level after the addition of Wnt3a with respect to the wt. To test if the observed effects were specific to mimetic we prepared alanine mutants as controls. All controls were able to rescue cells and had response similar to wt DVL3 , which is a crucial component29 of an ancient and evolutionarily conserved Wnt signaling pathway. Phosphorylation plays a crucial role in Wnt signaling and in DVL regulation, where upon activation DVL gets heavily phosphorylated by a plethora of kinases. However, only recently the systematic study of DVL phosphorylation sites was performed drawing a connection between particular kinases and their respective phosphorylation sites31. Here we studied a subset of these residues located in the Dishevelled PDZ domain. We characterized the effects of single and multiple phosphorylations and corresponding mimetic mutants. An uncommon approach in the field of PDZ domains, where most of the current phosphorylation studies focus on PDZ ligands41 and effects of direct PDZ phosphorylation remains scarce34.The PDZ domain is a protein-protein recognition motif that is crucial for many biological processesIn simulations, we studied the four phosphorylations sites S263, S268, S280, and S311, together with their phospho mimetics. The PDZ phosphorylations appeared to have three major effects on the PDZ structure: an electrostatic interaction that bridged the canonical binding groove, a change in the conformation of the 36. Moreover, our DVL3-S263E mutant exhibit a distinctive phenotype, in vitro and behaved as a constitutively active form. Such activation is in line with the reported ‘open/closed’ states of DVL36 and the recently published study of DVL, where phosphorylation reduced the binding of the C-terminus to PDZ, resulting in DVL activation in vivo32. Furthermore, a similar bridge across the binding groove was previously described in the experimental study of INAD PDZ5, where a disulfide bridge was formed across the binding groove that obstructed access to the binding site12. In INAD PDZ5 crystal structure, the interaction was accompanied by a partial unfolding of the We observed an interaction across the binding groove between R320 and pS263/S263E in our simulations. This interaction could obstructs access to the PDZ binding site and suggested a reduced affinity to the ligand. Indeed, a reduction in affinity was obtained between PDZ S263E and the C-terminus ligand in the NMR titration experiment. Despite the agreement with our simulations, our NMR results do not demonstrate that the ligand binds to the binding groove of PDZ. Nevertheless, this is expected as the C-terminus of DVL was previously shown to bind to the PDZ binding groove in DVL1 and the ligand C-terminus differed from ours only by a single isoleucine to valine mutation45 and together with the 47. Furthermore, unfolding/rearrangement of 48. The 53, which is usually stabilized upon ligand binding55. In agreement with our simulations, the NMR data demonstrated slightly reduced ligand binding in the S280 mutant compared to the wt. Accordingly, S280E fully rescues cell response to the Wnt/b-catenin signalling with a slightly higher response to the activator Wnt3a compared to the wt, which could be caused by the reduced affinity towards the C-terminal ligand. Note that our simulations suggest this effect to be stronger for phosphorylated PDZ in vitro.Our simulations suggest that modifications of S280 had more subtle effects on PDZ structure and ligand binding than S263. We found that both S280E and pS280 participate in the two types of interactions with either K283 from the 56.In all other simulations, the effects on PDZ were smaller and could not be deduced from the effects of individual modifications of S263 and S280. Thus in general, our simulations suggest that phosphorylations other than S263 and S280 seem to have a modulating effect on the PDZ structure and could fine-tune its interactions. Interestingly, a similar effect of multiple phosphorylations on protein structure was observed in a recent simulation study where one phosphorylation had a strong effect while the other only modulated the effect further57. In general, by increasing the number of phospho/mimetics in the PDZ, the interactions observed in single phospho/mimetic variants were either not affected or weakened, when further modifications were far from or close to the initial ones. For example, when both In simulations, we observed that different phospho/mimetic combinations had non-additive effects on both PDZ’s structure and its flexibility which was shown to be important for PDZ recognition58, but similar or even stronger interactions are expected to occur in the presence of multivalent ions such as 59. Moreover, the ion-mediated interactions are likely to be environment- and salt-dependent and could be used as an additional regulation mechanism. For example, in the non-canonical Wnt/61.Our simulations shown an interaction mediated by positively charged sodium ions between two close negatively charged side-chains. Such ion-mediated interactions were occasionally found in mimetic and more often in phosphorylated systems due to the higher negative charge density of phosphate. The interactions of pS263/S263E with pS280/S280E and of pS268/S268E with pS311/S311E were the most significant. Note that the observed ion-mediated interaction might be too strong for sodium ions in the current force-field63 or lysine63, e.g. R320 with pS263 or K283 with pS280, were stronger than the mimetics.In all simulations, the mimetics seemed to have a relatively stabilizing effect on the PDZ domain compared to phosphorylations, which in certain cases induced local PDZ disruption. The stronger effect of phosphoserine compared to glutamic acid could originate from its stronger electrostatic interaction, in particular when the phosphate is doubly deprotonated (charge − 2e). Therefore, the newly formed interactions between a phosphate group and arginineIn general, our simulations suggest that single site phosphorylations or mimetics have similar effects with the exception of S268. In such a case, we observed a large-scale rearrangement of the long In systems with two or more modified phosphorylation sites, the differences between phosphorylated and mimetic variants increased with the increasing number of modified sites. The highest discrepancy was observed in the simulation with all four sites modified (S263–S268–S280–S311), where the mimetic behaved very similar to wt, while the phosphorylated version differed from wt in both the 53) or inducing the unfolding of the 45. Such structural modifications of PDZ are in agreement with the reduced PDZ-ligand affinity found for the S280E mimetic in NMR. The simultaneous phosphorylation of PDZ at different sites increased the complexity and non-additivity of observed effects, and amplified differences between mimetics and phosphorylation variants. The most apparent non-additive effect was found in PDZ with pS263 and pS280, where phosphates did not behave independently because of salt/pH dependent phosphate-cation-phosphate interaction. The obtained understanding of the phosphorylation-induced changes to PDZ at atomistic resolution could be useful for insights into other PDZ domains and could bring us closer to understanding DVL and Wnt regulation.To conclude, we studied phosphorylation-induced structural changes in the PDZ domain from Dishevelled protein, a key component of Wnt signaling pathways. We focused particularly on the third isoform of human DVL protein modified at four recently discovered phosphorylation sites in PDZ in vitro. The phosphorylation of S263 created a salt bridge across the binding groove, which suggests the possibility of S263 being an on/off ligand binding switch regulated by NEK2 kinase. These simulation results are supported by NMR titration experiments with the S263E mimetic, which exhibited a negligible PDZ-ligand affinity compared to the wt. Moreover, the reduced PDZ-ligand affinity correlates with the constitutively activated phenotype observed for the S263E mimetic in our biological rescue assay. The phosphorylation of S280 exhibited more complex behavior, either stabilizing the 65. As a template, we used the crystal structure of the hDVL2 PDZ (PDB code 2rey) which shares 96.28% sequence identity. Missing loops and an extra residue at the C-terminus were added via MODELLER66. The generated models were evaluated based on DOPE and GA341 scores, and the best structure was selected and used for the study. The homology model was stable for the length of our simulation, The wild-type PDZ domain (aa 245-338) from hDVL3 was constructed via homology modeling using MODELLER v9.11see Fig. .67 visualization software using the mutagenesis tool and PyMTs plugin68, respectively. Each phosphoryl group was considered to be fully deprotonated , followed by an NPT ensemble . Each equilibration was performed for 0.1 ns followed by a production simulation for at least 300 ns in the NPT ensemble. The temperature was kept at 309.15 K with a velocity-rescale thermostatFor the specific labeling of proteins, the 83. Site-directed mutagenesis was employed to prepare the phosphomimetic mutants. E. coli BL21(DE3) transformed with pETM11-PDZ (wt or mutants) was propagated in 1-l cultures of minimal media (The DNA sequence of the PDZ domain of human DVL3 (aa 243–338) was cloned into the pETM11 vector containing an N-terminal 84. For titration experiments, NMR measurements were performed in a 600 MHz Bruker Avance III spectrometer equipped with a 1H/13C/15N TCI cryogenic probehead with z-axis gradients at the CEITEC Josef Dadok National NMR Centre. Chemical shift assignments were obtained using the 4D-CHAINS technology85 was used to estimate the partial specific volume of the protein, buffer density, and buffer viscosity. The data were analyzed with the continuous c(s) distribution model in the program SEDFIT v15.01c86. For the regularization procedure, a confidence level of 0.68 was used. The plots of c(s) distributions were created in GUSSI 1.3.187.The sedimentation velocity experiments were performed in a ProteomeLab XL-I analytical ultracentrifuge  equipped with an An-60 Ti rotor. Measurements of sedimentation velocity were done at 60000 rpm and 20  see Fig.. Absorba® Reporter Assay System . Antibodies: FLAG M2 (F1804) from Sigma, Cell cultures: Dulbecco’s modified Eagle’s medium, Gibco, Life Technologies, REF41966-029, fetal bovine serum , penicilin/streptomycin , L-glutamin , inhibitor LGK974 , Wnt3a recombinant protein , recombinant human R-spondin 1 . TopFLASh assay: Dual-LuciferaseDVL1/DVL2/DVL3 KO HEK293 T-Rex (DVL TKO T-REx described in35) were cultured in Dulbecco’s modified Eagle’s medium  with the addition of 10% fetal bovine serum , 1% penicillin-streptomycin , and 1% L-glutamine .HEK293 T-REx cells [human embryonic kidney (wt T-REx cells)], 88, pCDNA3.1-Flag-hDVL3 S280E89, and Super8X TOP Flash90. The site-directed mutagenesis of pCDNA3.1-Flag-hDVL3 was performed with a QuikChange II XL Site-Directed Mutagenesis Kit (Agilent) according to the manufacturer’s instructions. Mutagenesis primers used: pCDNA3.1-Flag-hDVL3 S263E: FWThe plasmids used were described previously: pCDNA3.1-Flag-hDVL3TATAACTTCTTGGGCATCGAGATTGTGGACCAAAGCAAC, RV:GTTGCTTTGGTCCACAATCTCGATGCCCAAGAAGTTATA. All plasmids were verified by Sanger sequencing.91. The antibodies used were Actin (4970) from Cell Signaling Technologies and FLAG M2 (F1804) from Sigma.For transfection, cells were seeded at 150,000 cells/well in a 24-well plate. On the next day, the cells were transfected using polyethylenimine (PEI) at a concentration of Supplementary Figures.


Neurotransmitter transporters (NTTs) are involved in the fine-tuning of brain neurotransmitter homeostasis. As such, they are implicated in a plethora of complex behaviors, including reward, movement, and cognition. During recent decades, compounds that modulate NTT functions have been developed. Some of them are in clinical use for the management of different neuropsychiatric conditions. The majority of these compounds have been found to selectively interact with the orthosteric site of NTTs. Recently, diverse allosteric sites have been described in a number of NTTs, modulating their function. A more complex NTT pharmacology may be useful in the development of novel therapeutics. Here, we summarize current knowledge on such modulatory allosteric sites, with specific focus on their pharmacological and therapeutic potential. Synaptic transmission is a fundamental feature of the communication between neurons . After t+ and Cl– are required in the case of DAT, NET, and SERT, and Na+ and K+ in the case of the excitatory amino acid transporters (EAATs) 1–5. Ionic concentration underlies the ability of the NTTs to accumulate substrate on one side of the cellular membrane citalopram. The most potent one was the selective serotonin reuptake inhibitor citalopram, but also the related compounds paroxetine and sertraline showed significant effects, while fluoxetine, venlafaxine, and duloxetine had no effects [3H]imipramine, although with a very low potency [3H]citalopram dissociation experiments nisoxetine in NET [3H]-dopamine, but only with partial efficacy (40–60%). The partial efficacy is present even at saturating concentrations, suggesting that its binding must halt the catalytic efficiency , without being a competitive inhibitor -dopamine uptake experiments show a mixed profile as voltammetry experiments performed in acute striatal slices demonstrate that KM822 reduces cocaine inhibition of dopamine uptake without affecting dopamine release. Moreover, KM822 reduces the psychostimulant-mediated increase in locomotion, suggesting it as a possible candidate to treat addiction . KM. KM75]. max of [3H]glycine uptake without changing its Km, an indication of allosteric inhibition paroxetine binding, consistent with an allosteric mechanism of action or an atypical inhibitor mode of action, binding to the orthosteric binding site in an inward-facing SERT. Moreover, cysteine accessibility analysis revealed that ATM7 stabilizes the outward-open conformation of SERT [In SERT, mutagenesis studies in extracellular loops 1 and 3 established residues that control transporter function ,101. By  of SERT . Finally of SERT , thus in2+) is present in many parts of the brain and modulates a number of receptors and transporters and is thus involved in regulating neurotransmission [2+ modulates the reuptake and release process of DAT, but not SERT or NET [Zinc  coordinate a binding site for Zn2+ –112. The of NTTs . Bindingormation ,112. In ransport ,110, elivelocity ,113 at l by Zn2+ ,113 open by Zn2+ . Importaric site –109. Zn2 earlier . A detaiAllosteric sites have been largely exploited in pharmacology and especially in the field of GPCRs and ion channels ,115. TarIn addition, the coupling between transporter-mediated substrate uptake and efflux has still to be clarified: the fact that an abnormal basal efflux is seen in pathophysiological conditions, that different compounds can selectively target uptake, efflux or both, suggests a complex interplay between uptake and efflux that may be amenable to the development of innovative therapeutics see . The exi+ binding site discovered in DAT, EAAT1, EAAT4, and GlyT1 serves as an example of the latter. The implementation of alternative tools for understanding how drugs can affect the transport cycle, in combination with classical pharmacological assays, may help in dissecting specific compound-related features and develop new therapeutic strategies towards allosteric modulation in a rational manner (see To date, the only clinically approved NTT inhibitors with allosteric properties belong to the family of antidepressants  and the nner see . Above a


Northeast Atlantic climate shifted into the Quaternary Ice Age around 2.6 M yr ago. Until now, however, the detailed changes associated with this inception of an Ice Age have remained obscure. New high-quality three-dimensional seismic data reveal a detailed geological record of buried surfaces, landforms and sedimentary architecture over vast parts of the Norwegian North Sea. Here, we show the sequence of near-coast geological events spanning the Northeast Atlantic inception of an Ice Age. We identify the location of immediate pre-glacial fluvially derived sandy systems where rivers from the Norwegian mainland built marine deltas. The stratigraphic position of a large submarine channel, formed by enhanced meltwater from initial build-up of local glaciers, is also shown. Finally, we document the transition to full ice-sheet growth over Scandinavia from the ice sheet’s earliest position to the later pattern of debris-flow lobes reaching the present-day shelf edge. Northeast Atlantic climate shifted into the Quaternary Ice Age around 2.6 Myr ago. Here, the authors use 3D seismic data from the northern North Sea to document detailed changes in continental-margin sedimentary architecture spanning the transition from a fluvially dominated environment to an icehouse world. Until now, however, the detailed changes in continental-margin sedimentary architecture associated with this transition to an “icehouse” world have remained poorly understood. The recent availability of large blocks of high-resolution industry three-dimensional (3D) seismic data now allows imaging of the sediments and landforms that record this major environmental shift and enables inferences on changing geological processes to be made.A dramatic climate shift led the Northeast Atlantic into an Ice Age around 2.6 M yr ago at the beginning of the Quaternary Period. In deep-ocean sediments this transition is recorded as increasing volumes of iceberg-rafted debris (IRD) delivered to the surrounding seas as ice sheets built up over the adjacent mid-latitude land masses3. Huge compressive stresses uplifted Norway and the British Isles and their flanking shelves were also raised and exposed, with a subsiding basin forming between8. The East Shetland Platform was a major clastic source-area for the northern North Sea Basin. The sands making up the Utsira Formation on the western flank were produced during the Late Miocene to Pliocene16 (“Methods”). At about the same time, sandy sediments from Norway formed the Utsira Formation on the basin’s eastern side  at the base of the Norwegian Channel24.The Utsira Formation is overlain by the down-lapping prograding shelf clinoform sediments of the Quaternary Naust Formation that are often in the form of glacigenic debris-flows2) 3D seismic survey obtained from the northern North Sea between Norway and the Shetland Islands  seismic cube covering 35,410 km °N Fig. . The inlres Fig. .40. Here, we provide a summary of available age constraints on the Pliocene to Quaternary sediments of the northern North Sea, based on seismic ties and age estimates from published data. These limited age constraints were used to produce a tentative chronology for the Quaternary sediments of the northern North Sea . The base of the prograding clinoforms of the Naust Formation  has been suggested to be younger than 2.6 M yr and older than 1.4 M yr in this region, based on microfossil investigations of industry wells, including wells 34/7-4 and 34/4-715   and the top of Unit B (1.7–1.6 M yr14) Fig. .16, which has been dated to ~1.5 M yr  within Unit C Fig.  correspoSupplemmentry InformationPeer Review File


Nitric oxide (NO), produced by neuronal NO synthase (nNOS), is an important neurotransmitter and plays a role in neuronal activity including learning and memory processes. However, high levels of NO can contribute to excitotoxicity following a stroke and neurodegenerative disease. Aside from NO, nNOS also generates superoxide which is involved in both cell injury and signaling. CaMKII is known to activate and translocate from the cytoplasm to the post-synaptic density in response to neuronal activation where nNOS is predominantly located. Phosphorylation of nNOS at Ser847 by CaMKII decreases NO generation and increases superoxide generation. Conversely, NO-induced S-nitrosylation of CaMKII at Cys6 is a prominent determinant of the CaMKII inhibition in ATP competitive fashion. Thus, the “cross-talk” between CaMKII and NO/superoxide may represent important signal transduction pathways in brain. In this review, we introduce the molecular mechanism of and pathophysiological role of mutual regulation between CaMKII and nNOS in neurons.Ca The increased PSD-associated CaMKII also modulates postsynaptic proteins critical for LTP maintenance [Caroteins) . CaMKII roteins)  and the roteins) ,6,7. The the PSD a [8,9,10ntenance ,15,16.CaMKII has been known to have broad substrate specificity involved in many different cellular functions. As such, CaMKII can induce either neuroprotective or neurotoxic effects after ischemia. It was shown that CaMKII autonomous activity may be a drug target for post insult neuroprotection ,18. HoweS-nitrosylation, the addition of an NO to the thiol side chain of cysteine residues [In brain, nitric oxide (NO) participates in numerous functions, including neurotransmission, development, and neuroprotection . NO is presidues . Besidesresidues ,27. NO rresidues .According to a ternary complex containing nNOS, postsynaptic density 95 kDa (PSD-95), and the NMDAR subunit GluN2B in neuron , the proS-nitrosylation via its specific Cys6 residue [nNOS exists in γ-aminobutyric acid (GABA)ergic inhibitory interneurons where CaMKII co-localizes in rat hippocampal primary neuron b. CaMKII residue . This re2+/CaM [NO is generated by NOSs, which catalyze the conversion of L-arginine to L-citrulline and NO by transferring electrons from nicotinamide adenine dinucleotide phosphate (NADPH), via the flavin adenine dinucleotide (FAD) and flavin mononucleotide (FMN) to the heme ,40. When2+/CaM ,42. Thus2+/CaM . The eff2+/CaM .Okadaic acid-sensitive PPases are involved in dephosphorylation of nNOS at Ser847 and reversible activation of the enzyme in NG108-15 neuronal cells . RecombiThere have been several pathophysiological roles observed to be phosphorylated nNOS at Ser847 in cells and in vivo .2, which mimics the hypoxic conditions, up-regulate the expression of PP2A and down-regulate phosphorylation of CaMKII at most likely Thr286 and nNOS at Ser847 and a significantly decrease cell viability. Treatment of propofol ameliorate CoCl2/hypoxia induced cell damage via phosphorylation of nNOS at Ser847 by CaMKII [2+ requirement and facilitating electron transfer [Glutamate-induced nNOS signal is inhibited by the treatment calyculin A and okadaic acid with the similar sensitivity in mouse neostriatal slices, suggesting that nNOS at Ser847 is mainly dephosphorylated by PP2A ,50. Mousy CaMKII . Physioly CaMKII . We repoy CaMKII , which itransfer . The stu2+ via nicotinic acetylcholine receptor and activates CaMKII leading to phosphorylation of nNOS at Ser847. nNOS phosphorylated at Ser847 generates superoxide that reacts with NO to form peroxynitrite. Peroxynitrite reacts with cGMP to form 8-nitro cGMP which induces protein S-guanylation of redox sensor protein Keap1 which results in expression of cytoprotective protein such as heme oxygenase-1 [CaMKII is thought to regulate the neuroprotective pathway via phosphorylation at Ser847 of nNOS. In fact, in the cerebellar granule neurons, nicotine increases intracellular Cagenase-1 ,53. Thus2+ via many ways such as increase in extracellular glutamate, opening of ion channel and more [2+ by transient ischemia, nNOS is activated and NO production is enhanced. NO induces direct S-nitrosylation of several proteins that are involved in neurotoxicity [Under pathological conditions, such as brain ischemia, nNOS activation might be overstimulated and thus form excess NO, which triggers many downstream neurotoxic cascades form excess NO, which triggers many downstream neurotoxic cascades. Several reports have been made on the therapeutic effect of CaMKII phosphorylation of nNOS in the ischemic condition, which indicates neuroprotective effects of phosphorylation at Ser847 of nNOS by CaMKII in culture cell and animal models. Activation of nNOS plays a crucial role in neuronal injury after cerebral ischemia/hypoxia and treatment of NOS inhibitor  protected against cerebral damage . In primand more . With thtoxicity ,72. NO rtoxicity .We reported for the first time that ischemia/reperfusion causes phosphorylation of nNOS at Ser847 which is inhibited by KN-93   were recognized as key messengers in the process of thiol-based redox regulation. It is also well-known that -SH groups of some proteins can undergo reversible polysulfidation that influences their catalytic activity. S-nitrosylation and polysulfidation have similar mechanisms and occurred at acid-base motif [S-nitrosylation of CaMKII at Cys6, it was recently reported that CaMKII is sensitive to inhibition by RSS through polysulfidation at Cys6, being competitive with ATP [S-nitrosylation and polysulfidation. Thus, NO- and RSS-donors are a new generation of CaMKII therapeutics.CaMKs play pivotal roles in regulating numerous functions in response to transient elevation of intracellular Case motif . Aside fwith ATP ,99. Cys3


Dear colleague,Thank you for carefully reading our manuscript and for your valuable comment clarifying the historical evolution of the terminology associated to the described condition. We fully agree with you that the eponym Wilkie’s Syndrome was first used by Grauer in 1948, and not as we mistakenly stated in the 1920's, to honor Wilkie’s accomplishment in being the first to provide a comprehensive description of this disease in 1927.None.None.N/a.N/a.N/a.N/a.N/a.


This study aimed to investigate the strength of a novel micro‐dynamic pedicle screw by comparing it to the traditional pedicle screw.vs micro‐dynamic group): 15 vertebrae underwent instant pull‐out testing; 15 vertebrae underwent 5000‐cyclic fatigue loading testing; and 15 vertebrae underwent 10,000‐cyclic fatigue loading testing and micro‐computed tomography (micro‐CT) scanning. The peek pull‐out force and normalized peek pull‐out force after instant pull‐out testing, 5000‐cyclic and 10,000‐cyclic fatigue loading testing were recorded to estimate the resistance of two types of screws. Bone mineral density was recorded to investigate the strength of the different screws in osteoporotic patients. And the semidiameter of the screw insertion area on micro‐CT images after fatigue were compared to describe the performance between screw and bone surface.Forty‐five lumbar vertebrae received a traditional pedicle screw on one side and a micro‐dynamic pedicle screw on the other side as follows . The peek pull‐out force of traditional pedicle screw after 10,000‐cyclic fatigue loading were smaller than that of instant pull‐out test in both osteoporotic (P = 0.017) and healthy group (P = 0.029), the peek pull‐out force of micro‐dynamic pedicle screw after 10,000‐cyclic fatigue loading was smaller than that in instant pull‐out test in osteoporotic group (P = 0.033), but no significant difference in healthy group (P = 0.853). The peek pull‐out force in traditional group and micro‐dynamic group underwent instant pull‐out testing (P = 0.485), and pull‐out testing after 5000‐cyclic fatigue loading testing (P = 0.184) did not show significant difference. However, the peek pull‐out force in micro‐dynamic group underwent pull‐test after 10,000‐cyclic fatigue loading testing was significantly greater than that measured in traditional group (P = 0.005). The normalized peek pull‐out force of traditional groups underwent instant pull‐out testing, pull‐out test after 5000‐cyclic and 10,000‐cyclic fatigue loading testing significantly decreased as the number of cycles increased (P < 0.001); meanwhile, the normalized peek pull‐out force of micro‐dynamic groups remained consistent regardless of the number of cycles (P = 0.133). The semidiameter after the fatigue loading test of the traditional screw insertion area was significantly larger than that of the micro‐dynamic screw insertion area (P = 0.013).The bone mineral density showed a weak correlation with peek pull‐out force (r = 0.252, versus the traditional pedicle screw, but similar resistance in low‐cycle fatigue testing and osteoporotic group vs the traditional pedicle screw.The novel micro‐dynamic pedicle screw provides stronger fixation stability in high‐cyclic fatigue loading and non‐osteoporotic patients  Spinal fusion and rigid fixation have been the main surgical treatment options for spine surgery, such as lumbar degenerative disease, lumbar instability and scoliosisThe pedicle screw based posterior dynamic stabilization devices are frequently used as dynamic fusion devices now. Numerous pedicle‐based dynamic fixation systems are currently available in an attempt to overcome the limitation of rigid fixationThe current understanding of the dynamic spinal fusion instrument is to preserve micro motion as well as provide safe stabilization. But it is difficult for most dynamic devices to provide the same longtime effective stabilization as the non‐rigid design. Thus, a micro‐dynamic design based on pedicle screw fusion system is needed. Several studies about dynamic pedicle screw fusion system have been reported, and the dynamic pedicle screw fusion system is such a design, aiming to reduce the concentration of stress on implants and preserve the motion of instrumented and adjacent segmentsRecent studies indicated that the micro‐dynamic pedicle screw design provides an improved range of motion and load transfer behavior vs conventional pedicle screwsThe purpose of this study was to investigate the effectiveness of the novel micro‐dynamic pedicle screw for the prevention of loosening after instant insertion and fatigue loading, the resistance of the novel micro‐dynamic pedicle screw in osteoporotic patients, and the difference in the performance between the novel micro‐dynamic pedicle screw and traditional pedicle screw between the screw and bone surface in lumbar spinal fusion. For this evaluation, the pull‐out force after fatigue resistance testing at different cycles was compared between the micro‐dynamic screw and the traditional pedicle screw. In addition, the fixation strength of two types of screws was examined by comparing the surrounding bone structure of implants on micro‐computed tomography (micro‐CT) images.The experimental design of this study was approved by our Institutional Review Board prior to the initiation of the study.Ten human cadavers  were harvested for this study. All specimens were radiographed to exclude spinal deformity, fracture, or malignancy. One female cadaver was excluded due to the presence of a spinal tumor. Thus, a total of 45 formalin‐fixed lumbar vertebrae (L1–L5) from nine cadavers  were tested. The bone mineral density (BMD) was measured in all specimens. Subsequently, all skin, fascia, muscles, ligaments, and capsules were removed, leaving only the intact vertebra which was stored at room temperature until testing.Both pedicle screws were implanted following the standard protocol for posterior lumbar vertebra implantation. The depth of insertion was consistent and all screws were covered with a sleeve for pull‐out testing prior to implantation. For each vertebra, a traditional pedicle screw was implanted on one side, while a micro‐dynamic pedicle screw was implanted on the other side. All implantations were performed by one surgeon.Traditional group and micro‐dynamic group underwent instant pull‐out testing: 15 vertebrae underwent instant pullout testing after inserting traditional pedicle screw on one side and a micro‐dynamic pedicle screw on the other side.Traditional group and micro‐dynamic group underwent pull‐out testing after 5000‐cyclic fatigue: 15 vertebrae were inserted with traditional pedicle screw on one side and a micro‐dynamic pedicle screw on the other side, and they then underwent a pull‐out test after 5000‐cyclic fatigue loading testing.Traditional group and micro‐dynamic group underwent pull‐out testing after 10,000‐cyclic fatigue: 15 vertebrae were inserted with traditional pedicle screw on one side and a micro‐dynamic pedicle screw on the other side, and they then underwent a pull‐out test after 10,000‐cyclic fatigue loading testing and micro‐CT scanning. The micro‐CT scanning was performed after the cyclic fatigue loading test.The vertebrae were randomly assigned to undergo instant pull‐out testing and 5000‐cyclic and 10,000‐cyclic fatigue loading testing as follows:Traditional group and micro‐dynamic group that underwent instant pull‐out testing were subjected to axial pull‐out testing Fig. . The speTraditional group and micro‐dynamic group that underwent pull‐out testing after fatigue loading were subjected to cyclic fatigue loading testing prior to axial pull‐out testing Fig. . Each spThe samples were scanned with a high‐resolution micro‐CT system . The depth of insertion was made consistent, and the scan conditions were as follows: X‐ray voltage 55 kV, current 145 μA, 300 s, continuous non‐stepping rotation, four‐frame averaging, rotation over 360°, and integration time of 300 ms. The surrounding trabecular structure of screws in the vertebral body was damaged due to fatigue loading testing. Therefore, those images were not included in the analysis, and only pedicle zone images were analyzed Fig. . PedicleDual‐energy radiograph absorptiometry  was carried out on all specimens to determine bone mineral density (BMD). Vertebrae with a BMD <0.8 g/cm2 were classified as osteoporotic, whereas those with a BMD >0.8 g/cm2 were classified as healthyThe peak pull‐out force (PPF) was defined as the peak point of load displacement prior to the occurrence of the precipitous drop.In order to determine the performance of the same screw in different vertebrae after various cyclic fatigue loading tests, the normalized PPF (PPFn) valuesThe semidiameter was defined as the distance between the thread peak point and the center of the largest circle of the insertion cross area, semidiameter of all insertion cross slices were measured and the mean value of the semidiameter after the fatigue loading test was used to evaluate screw loosening.P < 0.05. Paired t‐tests were used to compare paired PPF, BMD, and the mean value of the semidiameter after the fatigue loading test for different screws. One‐way analysis of variance was used to examine the difference of the PPFn of the same screw among the three groups for different cycle conditions and the difference of PPF of traditional pedicle screw and micro‐dynamic pedicle screw for different cycle conditions with and without divided by BMD. Of note, Dunnett's T3 test was used to compare intragroup differences. Lastly, Pearson bivariate correlation was used to investigate the correlation between BMD and PPF.Statistical analyses were performed using the SPSS 20.0 software , and the significance level was defined as 2 , and showed a weak significant correlation with PPF   and 66.42% in healthy group (P = 0.029); in addition, the PPF of micro‐dynamic pedicle screw in fatigue loading for 10,000 cycles was 45.39% of that in instant pull‐out test in osteoporotic group (P = 0.033), but there was no significant difference in healthy group (P = 0.853)  and fatigue loading for 5000 cycles (P = 0.184)     Fig. . Meanwhi33) Fig. .P = 0.013)  Fig. .In the present study, we investigated the effectiveness of a novel micro‐dynamic pedicle screw for the prevention of loosening between the screw and bone surface using pull‐out testing under instant and cyclic fatigue conditions and micro‐CT scanning. The results indicated that the novel micro‐dynamic pedicle screw provides similar fixation stability with that provided by the traditional pedicle screw for low‐cycle fatigue and osteoporotic group. Moreover, we observed that the micro‐dynamic pedicle screw maintains great resistance even after prolonged cyclic fatigue and in the healthy group. Furthermore, several additional aspects were addressed, such as BMD testing and micro‐CT scanning and the stability of the novel micro‐dynamic pedicle screw.3). Hohn et al.et al.P < 0.0001), further suggesting that DEXA alone is an insufficient predictor of lumbar bone quality for subregions of the vertebrae, such as the pedicle. Thus, we used micro‐CT scanning to investigate screw loosening by comparing the surrounding bone structure of the insertion area. According to Nakashima et al.Various studies have demonstrated that BMD is a critical factor in determining the pull‐out forceet al.et al.Rigid implants prevent stability by controlling the movement between implants and segments. High shear stress and stiffness after rigid fixation increase the load transfer through the implant and bone‐implant interface, leading to damage of the bone and early failure of the interfaceThis study has several limitations that should be taken into consideration. Firstly, all specimens were formalin‐fixed. Thus, the bone condition was different vs that of fresh bones, which may affect the resistance to the pull‐out force and micro‐CT scanning. Secondly, micro‐CT scanning was only performed on the pedicle zone, while the vertebral body zone was not measured. This may also affect the stability of the pedicle screw.In conclusion, this study compared the performance of a novel micro‐dynamic pedicle screw vs that of a traditional pedicle screw using pull‐out testing and micro‐CT scanning. The results showed that the novel micro‐dynamic pedicle screw provides similar resistance in low‐cycle fatigue testing and favorable resistance in high‐cycle fatigue testing vs the traditional pedicle screw, and closer combination between the pedicle screw and bone. In addition, the micro‐dynamic pedicle screw provide a better fixation in the healthy group rather than the osteoporotic group, which means fixation for osteoporotic patients requires caution even using micro‐dynamic pedicle screw. The findings of this study might be beneficial in clinic. Besides, high‐quality and scale‐randomized controlled clinical trials are needed to prove findings of our study.