The prognosis of distal cholangiocarcinoma (dCCA) remains poor; thus, the identification of new therapeutic targets is warranted. Phosphorylated S6 ribosomal protein indicates a mammalian target of rapamycin complex 1 (mTORC1) activity, and mTORC1 plays a central role in controlling cell growth and regulating glucose metabolism. We aimed to clarify the effect of S6 phosphorylation on tumor progression and the glucose metabolic pathway in dCCA.Thirty-nine patients with dCCA who underwent curative resection were enrolled in this study. S6 phosphorylation and the expression of GLUT1 were evaluated by immunohistochemistry, and their relationship with clinical factors was investigated. The effect of S6 phosphorylation on glucose metabolism with PF-04691502 treatment, an inhibitor of S6 phosphorylation, was examined in cancer cell lines by Western blotting and metabolomics analysis. Cell proliferation assays were performed with PF-04691502.S6 phosphorylation and the expression of GLUT1 were significantly higher in patients with an advanced pathological stage. Significant correlations between GLUT1 expression, S6 phosphorylation, and SUV-max of FDG-PET were shown. In addition, cell lines with high S6 phosphorylation levels showed high GLUT1 levels, and the inhibition of S6 phosphorylation reduced the expression of GLUT1 on Western blotting. Metabolic analysis revealed that inhibition of S6 phosphorylation suppressed pathways of glycolysis and the TCA cycle in cell lines, and then, cell proliferation was effectively reduced by PF-04691502.Upregulation of glucose metabolism via phosphorylation of S6 ribosomal protein appeared to play a role in tumor progression in dCCA. mTORC1 may be a therapeutic target for dCCA.The online version contains supplementary material available at 10.1186/s12876-023-02815-2. Currently, cholangiocarcinoma (CCA) is classified as intrahepatic, perihilar and distal, and based on the different anatomical locations, each is characterized by specific epidemiological and clinical features , 2. DistThe phosphatidyl inositol 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) signaling cascade belongs to the critical survival programs that are typically overactivated in dCCA and promote cell survival by inhibiting apoptosis . mTOR isRecent studies have shown that mTORC1 is a key regulator of glucose metabolism in cancer , 11. Glu18F-fluorodeoxyglucose positron emission tomography (FDG-PET) /computed tomography and pathological data were obtained from the radiological and pathological reports of our institution. Pathological data included tumor size, tumor type, and T and N status according to the 8th AJCC/UICC TNM classification  > 0.7 were considered to be significant metabolites. For pathway analysis, we used MetaboAnalyst version 5.0  and the lyst.ca) .P values of < 0.05 were considered to indicate statistical significance. All statistical analyses were performed with JMP software version 14.2 for Windows .All variables are expressed as the mean ± standard deviation for continuous data. Differences between the variables were compared using Fisher’s exact test or the Mann–Whitney U test. Correlation between the continuous variables was investigated using Spearman’s rank correlation coefficient. Survival curves were estimated using the Kaplan–Meier method, and the log-rank test was used to detect differences between curves. n = 8; male, n = 31; mean age, 73.8 ± 6.5 years)  and 63.1% in the GLUT1-low group and 40.5% in the GLUT1-high group (P = 0.163).According to the immunohistochemical expression of pS6, 17 patients showed high expression levels, and 22 showed low expression levels, and the CA19-9 level, SUV-max of FDG-PET, T stage, and UICC Stage were significantly higher in the pS6-high group , GLUT1 and SUV-max , and pS6 and SUV-max  , respectively. Metabolomics related to pathways of glycolysis and the TCA cycle are shown in Fig. We next investigated the change of metabolites after PF-04691502 treatment in TFK-1. Fifty-eight of the 469 metabolites were significantly extracted by GC–MS/MS. The metabolic differences between the two groups with and without PF-04691502 treatment were investigated using OPLS-DA, and differential metabolic patterns were seen by the two plots clearly separated on the score scatter plot Fig. . To idendCCA is a highly aggressive type of malignancy. As patients in the early stages of dCCA are frequently asymptomatic, most patients receive a diagnosis at an advanced or locally unresectable stage of the disease, ending in a poor prognosis with limited systemic treatment options . CombinaThe most common and one of the first-identified biochemical features of cancer cells is glucose metabolism. Glucose is known as a primary energy and carbon source for the cells, providing not only energy in the form of ATP but also metabolites for several anabolic pathways . Cancer With the improvement of cancer genome profiling technology, a variety of molecular alterations involving both oncogenes and tumor suppressor genes have been described in CCA , and mosAs previously described, mTORC1 is associated with a variety of factors related to cancer progression, including its role as including its role as a key regulator of glucose metabolism , 11. TheAccording to the ABC-02 trial and FUGA-BT study, the combination therapy of gemcitabine plus cisplatin or TS-1 can be considered a standard treatment in patients with advanced CCA , 31. RegThis study has some limitations. First, this is a retrospective study with a small sample size. Thus, a larger prospective study will be necessary. Second, the effects of an mTORC1 inhibitor have only been investigated in in vitro experiments using cell lines. Further studies are needed to clarify the relation between S6 phosphorylation and glucose metabolism and cancer progression in vivo using experimental animals. Third, HuCCT1 and TKKK cell lines were derived from intrahepatic CCA –43. Our In conclusion, S6 phosphorylation may play an important role in tumor progression connected with the upregulation of glucose metabolism in dCCA. mTORC1 may be one of the therapeutic targets for dCCA, and novel combination therapy with mTORC1 inhibitors may potentially be warranted.Additional file 1: Supplementary Fig. 1.The inhibitory effect of PF-04691502 treatment on cell proliferation in four CCA cell lines.The inhibitory effect of PF-04691502treatment on migration ability in TFK-1 and MEC cells.Western blotting to investigate the level of cleaved caspase3 under PF-04691502 treatment in TFK-1 and MEC cells. * vs control, P < 0.05, ** vs control, P < 0.001.Additional file 2: Supplementary Fig. 2. The inhibitory effect of cisplatin/gemcitabinecombined with PF-04691502in TFK-1 and MEC cells. * vs control, P < 0.05, ** vs control, P < 0.001.Additional file 3.


Antarctic ice sheet (AIS) mass loss is predominantly driven by increased solid ice discharge, but its variability is governed by surface processes. Snowfall fluctuations control the surface mass balance (SMB) of the grounded AIS, while meltwater ponding can trigger ice shelf collapse potentially accelerating discharge. Surface processes are essential to quantify AIS mass change, but remain poorly represented in climate models typically running at 25-100 km resolution. Here we present SMB and surface melt products statistically downscaled to 2 km resolution for the contemporary climate (1979-2021) and low, moderate and high-end warming scenarios until 2100. We show that statistical downscaling modestly enhances contemporary SMB (3%), which is sufficient to reconcile modelled and satellite mass change. Furthermore, melt strongly increases (46%), notably near the grounding line, in better agreement with in-situ and satellite records. The melt increase persists by 2100 in all warming scenarios, revealing higher surface melt rates than previously estimated. High-resolution 2-km Antarctic maps reveal higher snowfall and surface melt than low-resolution products, reconciling satellite-observed ice sheet mass change. Projected higher surface melt near grounding lines threatens future ice shelf stability. The surface mass balance (SMB), i.e., the difference between snow accumulation and surface ablation from sublimation, drifting snow erosion and meltwater runoff5, primarily affects the synoptic, seasonal, interannual and decadal variability of AIS mass change6. Over floating ice shelves, surface melt triggers surface lowering, firn pore space depletion through retention and refreezing, and subsequent ponding of excess meltwater, that is eventually discharged into the ocean via crevasse and lake drainage, or runoff rivers12. As for Greenland fjords, (future) increase in surface and subsurface runoff have the potential to enhance sub-shelf basal melting and subsequent destabilisation by thinning ice shelves from below4. These combined processes, i.e., surface meltwater ponding and basal melt, can trigger ice shelf disintegration by hydrofracturing, a mechanism that reduces the buttressing effect on the grounded AIS to eventually accelerate solid ice discharge and sea-level rise13. This has previously occurred in the Antarctic Peninsula over Larsen B ice shelf (March 2002)14. As surface melt is projected to increase exponentially with future atmospheric warming15, it is expected that Antarctic ice shelves become increasingly prone to collapse17.The Antarctic ice sheet (AIS) is currently losing mass21. However, their relatively coarse grids cannot accurately resolve the complex topography of e.g., the Antarctic Peninsula, the Transantarctic Mountains or Queen Maud Land, where both snowfall accumulation and melt gradients peak in response to steep slopes22. Consequently, climate models generally underestimate orographic precipitation and propagate snowfall too far inland onto the AIS interior plateau21. A recent multi-model comparison revealed large inter-model annual SMB differences of 266 Gt year−1 5, that are primarily controlled by the grid resolution used in regional climate models23. Model evaluation using in situ measurements from automatic weather stations (AWS) (1992–2018)24 and remote sensing from the satellite radar scatterometer (QuikSCAT) (2000–2009)25 likewise suggests a general melt underestimation in e.g., the regional climate model RACMO2.3p218.Regional climate models and earth system models, that typically run at spatial resolutions of 25–100 km, are key tools to reconstruct the contemporary SMB and surface melt in Antarctica and project their future evolution26 (1979–2021) and three global climate projections from the Community Earth System Model (CESM2)27 under a low (SSP1-2.6), moderate (SSP2-4.5), and high-end (SSP5-8.5) warming scenario (1950–2099) are used as lateral forcing for the Regional Atmospheric Climate Model (RACMO2.3p2)18, which simulates the contemporary and future SMB (components) of Antarctica on a 27 km grid (see Methods). As a second step, statistical downscaling is applied to correct these SMB components, including surface melt, runoff, total precipitation, snowfall, sublimation and snow drift erosion, for elevation biases between the relatively coarse RACMO2.3p2 grid at 27 km and a high-resolution surface topography from the Reference Elevation Model of Antarctica at 2 km (REMA)28. Melt and runoff are further adjusted for local albedo biases, e.g., regions exposing blue ice or darker bare ice mixed with rocks, not included in RACMO2.3p2, based on a 2 km albedo map from the Moderate Resolution Imaging Spectroradiometer (MODIS) averaged for 2000–2021 (see “Methods”). The ability of statistical downscaling to refine the spatial distribution of SMB components was first demonstrated for the Greenland ice sheet, where the downscaled product realistically captured high mass loss rates over narrow ablation zones and outlet glaciers that are typically unresolved in RACMO2.3p229. Likewise, statistical downscaling to (sub-)kilometre spatial resolution proved essential to accurately quantify contemporary (and projected) mass change of the Greenland ice sheet31, its peripheral ice caps32, glaciers of the Canadian Arctic33, Svalbard34, and Iceland35, and their contribution to global sea-level rise. Using in situ and remote sensing data for model evaluation, we show that our downscaled product for Antarctica at 2 km improves upon the original RACMO2.3p2 data at 27 km, by resolving SMB and surface melt patterns in unprecedented spatial detail, notably in topographically rough regions including mountain ranges and the vicinity of the grounding line.Here we present daily SMB and surface melt products covering the grounded AIS and floating ice shelves at 2 km spatial resolution for the contemporary climate and three scenario projections until 2100. As a first step, present-day climate from the global climate reanalysis ERA5−1) , with both lower bias (−6.6 mm w.e.) and RMSE (−9.4 mm w.e.) . We integrate SMB over the whole of Antarctica (ANT), including the grounded AIS, adjacent Antarctic islands, and floating ice shelves. Accumulation in the 2 km product  of the total SMB increase, whereas the remaining 23 Gt year−1 (1%) are attributed to differences in ice mask extent  and solid ice discharge (D)1 for the period 1979–2021  (see “Methods”). In the past four decades (1979–2021), we show that modelled SMB at 2 km integrated over the grounded AIS, including Antarctic islands    and over its three sectors (0.96 < R2 < 0.99).Mass change (MB) of the grounded AIS can be quantified using the input-output method−1 for 1979–2005) compensating for D mass loss (2187 ± 142 Gt year−1) on average  persistently exceeds SMB (2168 ± 107 Gt year−1)  SMB estimates are supported by good agreement with both in situ  Fig. . We esti−1) Fig. a. The AP−1) Fig. b, c, con−1) Fig. d. The cl4, floating ice shelves are vulnerable to  high surface melt rates17 that can result in meltwater ponding, trigger ice shelf destabilisation and rapidly accelerate solid ice discharge. It is therefore critical to accurately represent surface melt rates, notably near the grounding line that separates the grounded AIS from the floating ice shelves. Statistical downscaling to 2 km has a pronounced effect on surface melt rate and distribution across Antarctica, especially over the ice shelves where melt peaks . Four sites are situated on the Larsen C ice shelf and six in Dronning Maud Land. We find that the downscaled product shows better agreement with observations than the native 27 km product  to the total surface melt increase  to the total melt increase  stem from albedo correction over blue ice areas. The downscaled product aligns with QuikSCAT estimates within uncertainties for the period 2000–2009  increase in surface melt over floating ice shelves that mainly occurs along the grounding line , 2 Gt year−1 in the APIS (9%), and 6 Gt year−1 in the EAIS sector (45%)  and moderate scenarios (5.4 ± 0.6 Gt year−2), with a stronger acceleration under a high-end warming trajectory (17.4 ± 1.3 Gt year−2). Figure To explore whether the surface melt underestimate found in the contemporary RACMO2.3p2 simulation at 27 km persists in the future, we use one CESM2 historical reconstruction HIST, 1950–2014) extended by three climate projections under a low SSP1-2.6), moderate (SSP2-4.5) and high-end (SSP5-8.5) warming scenario (1950–2099). These simulations are first dynamically downscaled to 27 km using RACMO2.3p2, and further statistically downscaled onto the 2 km grid (see “Methods”). Figure 0–2014 ex, moderat−1 for 1979–2021 in Fig. 1, the modest increase in the 2 km SMB product is sufficient to reconcile modelled and remotely sensed (GRACE/GRACE-FO) mass change both AIS-wide and at the regional scale  integrated surface melt estimates from current state-of-the-art regional climate models largely differ: 197 ± 43 Gt year−1 in MAR3v12 at 35 km (1980–2021)20, 116 ± 29 Gt year−1 in RACMO2.3p2 at 27 km (1980–2021)18, and 695 ± 132 Gt year−1 in HIRHAM5 at 12.5 km resolution (1980–2017)39. Applying statistical downscaling to RACMO2.3p2 at 27 km, we show that melt at 2 km increases by 45% to reach 167 ± 32 Gt year−1   to over 10-fold (525 Gt year−1) larger in 2090–2099 under SSP1-2.6 (cyan band) and SSP5-8.5 (red band). Most of the melt increase relative to present-day occurs along the grounding line fringing floating ice shelves, especially over Larsen C and Dronning Maud Land 41. The model is specifically adapted to represent surface processes of polar ice sheets and ice caps including the Greenland ice sheet30, Canadian Arctic33, Svalbard34, Iceland35, and Antarctica18. The model incorporates a 40-layer snow module (up to 100 m depth) simulating melt, percolation and retention into firn and subsequent surface runoff42. The model represents dry-snow densification43, drifting snow erosion44, and snow albedo based on grain size, cloud optical thickness, solar zenith angle, and impurity content45. Here we use the benchmark RACMO2.3p218 model at 27 km spatial resolution to dynamically downscale the latest ERA5 climate reanalysis (1979–2021)26 from the European Centre for Medium-Range Weather Forecasts (ECMWF). This reference run is further complemented by one historical simulation (1950–2014) and three climate projections from the Community Earth System Model (CESM2) under a low-end (SSP1-2.6), moderate (SSP2-4.5) and high-end (SSP5-8.5) Shared Socioeconomic Pathways (SSP) emission scenarios (2015–2099), dynamically downscaled to 27 km. RACMO2.3p2 is forced by ERA5 reanalysis and CESM2 climate outputs within a 24-grid-cell-wide relaxation zone at the lateral model boundaries. Forcing consists of temperature, pressure, specific humidity, wind speed and direction being prescribed at the 40 model atmospheric levels every 3 and 6 h, for the ERA5 and CESM2-forced setting respectively. Upper atmospheric relaxation is active46. Sea ice extent and sea surface temperature are also prescribed from the ERA5 reanalysis or CESM2 outputs on a 3 or 6-h basis. Firn is initialised in January 1979 (ERA5) and 1950 (CESM2) using snow temperature and density profiles from the offline Institute for Marine and Atmospheric research Utrecht-Firn Densification Model (IMAU-FDM)43. Ice albedo is prescribed as a constant field in space and time at 0.55. Surface topography is prescribed from the 1 km digital elevation model of Bamber et al.47, down-sampled to 27 km. In the absence of interactive ice dynamics in RACMO2.3p2, ice mask and topography are kept fixed. The RACMO2.3p2 model settings are discussed and evaluated in van Wessem et al.18.The polar (p) Regional Atmospheric Climate Model version 2.3p2 (RACMO2.3p2) incorporates the dynamical core of the High Resolution Limited Area Model (HIRLAM)27 is an earth system model from the Climate Model Comparison Project phase 6 (CMIP6) that simulates interactions between atmosphere-land-ocean systems on the global scale. The model includes the Community Atmosphere Model version 6 (CAM6)48, the Parallel Ocean Program model version 2.1 (POP2.1)49, the Los Alamos National Laboratory Sea Ice Model version 5.1 (CICE5.1)50, the Community Land Model version 5 (CLM5)51, and the Community Ice Sheet Model version 2.1 (CISM2.1)52 to simulate interactions between atmosphere-ocean-land and sea ice dynamics as well as snow/ice surface processes in a fully-coupled fashion. Here all components are active except for land-ice dynamics, i.e., excluding basal melting, calving, collapse of ice shelves and subsequent ice sheet thickening/thinning and advance/retreat. We use outputs from the CMIP6 CESM2 model for one historical reconstruction , and three climate projections 53 at a spatial resolution of 0.9 × 1.25°. In CESM2, CAM6 and CLM5 exclusively prescribe land use changes; atmospheric greenhouse gas and aerosol emissions are derived from the selected SSP warming scenarios54. CLM5 has been adapted to simulate runoff, melt, firn retention and refreezing in a 10 m w.e. snowpack55. Model settings are discussed and evaluated in Dunmire et al.21.The Community Earth System Model version 2.1 (CESM2.1)29, the RACMO2.3p2 contemporary climate  and projections  are statistically downscaled from the native model resolution of 27 km to an ice mask and topography defined on a 2 km grid. A 2 km grid was selected as a trade-off between computational efficiency and high spatial resolution, while maintaining manageable file size. The ice mask combines the grounded AIS mask from the Ice Sheet Mass Balance Inter-comparison Exercise-2 (IMBIE-2)2, the refined floating ice shelf mask from the Antarctic Bedrock Mapping version 2 (Bedmap2)56, and sub-Antarctic glaciers from the Randolph Glacier Inventory version 6 (RGIv6)57 down-sampled to a 2 km grid. Surface topography at 2 km is derived from the Reference Elevation Model of Antarctica (REMA)28 digital elevation model at 200 m resolution. The downscaling procedure corrects individual SMB components for elevation on the 2 km topography, using daily-specific vertical gradients estimated on the RACMO2.3p2 grid at 27 km. SMB components (X in Eq. (a) is applied to the current grid-cell to compute an intercept (b), i.e., value at sea level. These two regression coefficients are bi-linearly interpolated from the 27 km grid onto the 2 km one, and applied to the high-resolution topography at 2 km (h) as:Following Noël et al.29. Since runoff is spatially limited in Antarctica, i.e., surface melt is mostly retained or refrozen in firn, we bi-linearly interpolate runoff in space onto the 2 km grid for days with insufficient number of grid-cells experiencing runoff (<6 adjacent grid-cells). This resolution issue becomes less pronounced as the runoff zone expands following atmospheric warming, notably in the three SSP scenarios. Statistical downscaling of total precipitation is motivated by the fact that the native RACMO2.3p2 underestimates orographic precipitation, notably on the steep and rugged terrain of the Antarctic Peninsula. In addition, daily snowfall fraction (SFfrac), i.e., the fraction of snowfall on total precipitation, is statistically downscaled to 2 km following Huai et al.58. Snowfall is thus estimated as:Melt and runoff are further corrected for surface albedo in regions exposing blue ice or darker bare ice mixed with rocks  in summer, that are unresolved in RACMO2.3p2 at 27 km. To that end, we use a 2 km MODIS 16-day product averaged for the period 2000–2021. The albedo correction accounts for solar zenith angle, surface slope and aspect as discussed in Noël et al.Rainfall is estimated as a residual as:SMB is reconstructed using individual components statistically downscaled to 2 km as:29.The above statistical downscaling procedure is not mass conservative, enabling mass flux corrections that significantly improve the representation of individual SMB components relative to the native RACMO2.3p2 outputs. For a detailed description of the statistical downscaling technique, we refer to Noël et al.32, the Canadian Arctic33, Svalbard34, and Iceland35. For all these land ice masses, the downscaled product accurately represents the spatial and temporal SMB variations, as demonstrated by high and improved correlations with in situ and remotely sensed observations. The statistical downscaling technique uses elevation and albedo as primary downscaling predictors and applies the downscaling at very high (daily) temporal resolution. Three factors explain the robustness of the downscaling procedure. First, the spatial variability of individual SMB components shows strong average correlation with elevation, also in Antarctica  to the total surface melt increase obtained after downscaling (+46%). Finally, statistical downscaling estimates elevation gradients locally (using the current and at least five adjacent grid-cells) and at high temporal resolution (daily). This preserves the modelled spatial patterns and synoptic timescales enabling to capture melt and accumulation spatiotemporal variability due to local surface slope, distance to the coast, and atmospheric circulation direction and strength affecting e.g., foehn events. Sources of uncertainty that persist in the current statistical downscaling routine stem from local biases in: (1) the modelled elevation gradients (RACMO2.3p218 or CESM221) notably in regions characterised by steep slopes and sharp gradients, (2) the high-resolution surface topography (REMA)28 used for the elevation correction, (3) the ice sheet (IMBIE-2)2, glaciers (RGIv6)57 and ice shelf masks (Bedmap2)56 used for spatial integration, and (4) the satellite albedo product (MODIS) used for ice albedo correction.The statistical downscaling technique used in this study builds on previous RACMO2-based downscaling efforts over glaciated surfaces in Greenland18 and none of the CESM2 scenarios21 currently available implement the effect of ice dynamics in Antarctica, i.e., fixed present-day conditions were prescribed in our future projections. Under climate warming, the AIS and floating ice shelves are expected to retreat, calve and/or thicken/thin, which would affect the circulation and associated precipitation distribution as well as melt patterns. For instance, marginal ice thinning could trigger melt-elevation feedback, further enhancing the projected surface melt rates, while snowfall-driven ice thickening could reduce melt. These competing mechanisms will be investigated by statistically downscaling future melt projections from forthcoming fully-coupled earth system models that include Antarctic ice dynamics when these become available, as was previously done for the Greenland ice sheet35. In addition, we prescribe the present-day MODIS blue ice albedo with a base value of 0.55 when firn retreats to expose blue ice both in RACMO2.3p2 at 27 km and at 2 km. This approach remains valid in the absence of future surface darkening due to biological growth 59 or impurity deposition 60 as e.g., observed in Greenland. To our knowledge, ice darkening is not yet ongoing in Antarctica. In view of the above, our projected, statistically downscaled surface melt rates should be interpreted as conservative estimates.RACMO2.3p237 that compiles multi-year records from stakes, snow pits, ice cores, ultrasonic sounders and ground penetrating radar covering the past 1000 years . As the solid ice discharge data set does not extend beyond 2017, we apply a linear regression on the 1979–2017 period to extrapolate the time series until 2021. Although potentially missing discharge events after 2017, using a linear regression is most appropriate provided its high statistical significance , and the fact that AIS mass change variability is primarily driven by SMB processes6. Sectors include the APIS, WAIS, EAIS and surrounding Antarctic islands, i.e., detached from the grounded AIS, as well as the whole grounded AIS. For a meaningful comparison with remote sensing records, i.e., that do not discriminate surrounding islands from the AIS sectors, we partition the islands’ solid ice discharge and associated uncertainty (D = 77 ± 5 Gt year−1 in 1979–2017) into the three AIS sectors. Best agreement with remote sensing is found by attributing 20% of the flux to the APIS, 10% to the EAIS and the remainder to the WAIS sector. Note that these adjustments are small relative to the total flux in each sector , which only marginally affects our mass change estimates. Uncertainty in regional solid ice discharge is derived from Rignot et al.1. Uncertainty in modelled SMB at 2 km and 27 km is estimated as one standard deviation around the 1979–2021 mean. To estimate modelled mass change uncertainty, we sum the corresponding uncertainty from SMB and D.For large-scale SMB evaluation, we compare monthly mass change from the Gravity Recovery and Climate Experiment  and Follow-On mission  (red lines in Fig. 61, JPL RL06 from the Jet Propulsion Laboratory62, GFZ RL06 from the German Research Centre for Geosciences63 and ITSG-Grace2018 from TU Graz64. We added degree-1 spherical harmonics as in Swenson et al.65, and replaced the poorly resolved C20 and C30 coefficients by values estimated from satellite laser ranging, following the recommendations of the processing centres. Mass variations are estimated in 27 Antarctic basins following the method described in van Wessem et al.18, for each of the four GRACE/GRACE-FO data sets. The resulting time series are then combined using error-weighted averaging as in Wouters et al.66. The correction for glacial isostatic adjustment is based on the model by Ivins and James67.Mass anomalies of the AIS and its three sectors are derived from monthly GRACE and GRACE-FO spherical harmonic gravity field solutions from four processing centres, i.e., CSR RL06 from the Center for Space Research24. Six stations are installed in Dronning Maud Land and four on the Larsen C ice shelf. We use the closest model grid-cell at 2 km and 27 km resolution for comparison with observations (Supplementary Fig. 25. Uncertainty in QuikSCAT melt is estimated as one standard deviation around the 2000–2009 mean (orange band in Fig. For local melt evaluation, we use 81 annual melt records from ten AWS covering the period 1992–2018Supplementary InformationPeer Review File


Trichechus manatus manatus) commonly inhabit small depressions in the substrate or deep-water coves known as “resting holes”. Determining if manatees exhibit diel temporal trends in their call production rate and call types between microhabitats can provide insights into their diurnal and nocturnal activity patterns. Here, we investigate the diel vocalization patterns of wild Antillean manatees in two adjacent resting holes off of St. George’s Caye, Belize. Recordings of manatees were made using a bottom-mounted hydrophone located near a reef barrier reef for nine days in July of 2017 and ten days in January of 2018. To explore if and how manatee acoustic activity differs between sites, we compared the number of calls per hour, the number of manatee positive hours, the number of tonal and atonal sounds, and the number of boats detected across sites. A total of 370 hours of acoustic recordings were analyzed resulting in the detection of 3,262 calls. There were no significant differences in the number of manatee calls produced per hour between sites. The average number of calls produced by manatees decreased over the course of several days. The proportion of tonal calls decreased with hours after sunset and increased in boat presence. These results suggest manatees in this region may exhibit different diel activity patterns which appear to be influenced by the characteristics of the environment. These findings can support ongoing conservation and management efforts to safeguard species in Belize.Many marine mammals exhibit diel trends in vocal production, which can provide information on habitat use and behavioral activity. In Belize, Antillean manatees ( Balaenoptera musculus) [Peponocephala electra) [Eubalaena glacialis) [Phoca vitulina) [Megaptera novaeangliae) [Sousa chinensis) [Balaenoptera acutorostrata) [Passive acoustic monitoring (PAM) techniques offer a powerful means of studying marine mammals by providing cost-effective and minimally invasive, long duration recordings in remote locations. Moreover, they are particularly useful for examining activity when animals are not easily observed during non-daylight hours. Many marine mammals exhibit diel patterns in vocal activity in relation to feeding  ; melon helectra) ), matingacialis) ; harbor itulina) ; humpbacangliae) ), and hainensis) ; North Aostrata) ). By exaostrata) : blue whostrata) ).Trichechus manatus) faces significant challenges in its freshwater and marine habitats throughout its distribution. Declining populations suffer from high mortality rates due to watercraft collisions and habitat loss resulting from development [The West Indian manatee  inhabit diverse habitats throughout the Western Caribbean Sea, where their temporal activity patterns are not well understood [Antillean manatees  influence the patterns observed.Data for this study were gathered on the leeward side of St. George’s Caye, which is a small crescent-shaped island located 9.5 km east of mainland Belize near the Belize Barrier Reef . The cay2) a section of the eastern edge of St. George’s Caye. Site B, approximately 1 km northeast from Site A, was near a much larger oval-shaped depression used as a resting hole . The depression consisted of a silt and sandy bottom and depths of 2–5 m, surrounded by seagrass flats. Site B overlapped with a common route for boats traveling through this area of the coast of Belize, whereas boats at Site A were restricted to several small vessels owned by local fishers. Both habitats were surrounded by contiguous seagrass flats composed primarily of turtle grass , manatee grass (Syringodium filiforme), and shoal grass , interspersed with various species of algae and patches of sand.Manatee vocalizations were recorded near two resting holes in the area . Site A Two calibrated SoundTrap 300 HF  systems  were used to continuously record ambient noise and manatee vocalizations at each site. The date and time were embedded in the file name of each wav file. Recordings from Site A  were obtained from July 7–10 and July 13–16, 2017 . RecordiAcoustic files were visualized in Raven Pro 1.5 and 1.6 . RecordiManatees are known to decrease vocalization rates during feeding and social behaviors in the presence of elevated noise levels from boats . We recoWe tallied the number of manatee calls detected per clock hour for each site. Since recordings were not simultaneous and recorded during different times of year, we could not assess use of both habitats between seasons. In addition, due to the close proximity between the resting holes (~ 1 km), we statistically tested for differences between sites. If there were no differences in detection, the data from both holes were pooled together. Data were tested for normality (Shapiro-Wilk) and homogeneity of variance.day was added to create an unbiased comparison. An analysis of variance (ANOVA) was run to determine if there was a significant difference in MPH due to the day or the number of boats.Following the methodology of Cascao et al. (2020) , we calchour after sunset was calculated for each site to account for variation in daylight hours. Hour after sunset was obtained from the National Oceanic and Atmospheric Administration’s Global Monitoring Laboratory’s Solar Calculator [A binomial generalized additive mixed model  was used to assess whether the presence or absence of calls was significantly different due to time (hour: smoothed), day, and the number of boats. Hour after sunset was added as an explanatory variable to account for the differences in sunlight due to the different seasons (July of 2017 and January of 2018). Because sunset varies between the two timeframes, lculator .mgcv, effectsize, ggpubr, ggplot2, and visreg [A generalized linear model (GLM) was run to identify if the number of calls were significantly different due to time of day (hour) and the number of boats. One of the most common vocalizations produced by manatees are tonal sounds ,31,37. Hd visreg –47.Overall, we detected 3,262 wild manatee vocalizations from 370 total hours of recordings. At Site A (133 hours of recordings), we detected 2,217 calls of which 1,884 calls were classified as tonal and 333 calls were atonal. At Site B (237 hours of recordings), we detected 1,045 calls of which 856 calls were classified as tonal and 88 calls were atonal. At Site A, we detected an average of 0.55 boats/hr (range: 0–4 boats/hour) with all detections occurring between 06:00 h and 21:00 h . At Sitep = 0.395) or homogeneity of variance. Although there was a lower average MPH in the winter (0.297 ± 0.242) than summer (0.368 ± 0.160), the results of the Welch’s two sample t-test determined it was not significant (t(11.349) = 0.720, p = 0.486). Since the previous findings suggest that there was no difference between sites, we removed the variable site from the model. The best fitting ANOVA (AIC = -7.595) showed that there was a significant difference in MPH due to day . The effect size  was large for day (0.27) and small for the number of boats (0.02). MPH decreased over the course of the study, but the number of boats did not have a significant effect on detection of calls by hour.MPH from each site did not violate the assumption of normality , the hours after sunset , the day of sampling , and the interaction of day with the number of boats   determined that there was a difference in the detection of calls due to time of day (χ= 0.008) . Call dep < 0.001). A Kruskal-Wallis test used to compare the number of calls per site determined there was no difference in the number of calls due to location . Due to these findings and the sampling scheme, data were pooled and then compared by hour of sampling. The best fitting GLM  determined that there was not a significant difference in the number of calls due to hour  or the number of boats . Although, there does appear to be more calls between 23:00 h and 05:00 h  and the number of hours after sunset . The proportion of tonal calls decreased after sunset and increased in the presence of boats  determined that there was a significant difference in the proportion of tonal calls in relation to the number of boats , we confirm that manatees regularly occupy these habitats. Drone-based photo-identification studies have corroborated these findings, revealing high site fidelity among manatees in the area .T. inunguis) in Lake Ossa, Cameroon [Manatees produced vocalizations throughout day and night, but changed their production rates at different times across sites. While manatees are often considered diurnal, our study reveals vocalizations during non-daylight hours as well. This nocturnal activity has also been observed in other sirenian populations, such as dugongs around Talibong Island, Thailand , and AfrCameroon . ManateeCameroon . OverallTursiops truncatus) [We also observed an increase in manatee vocalizations in conjunction with boat presence. Similar adjustments in vocalization rates have been reported for dolphins (uncatus)  and humpuncatus)  in the puncatus) . ManateeAlthough detections were pooled, Site A exhibited more vocalizations at night, while Site B had more vocalizations during the day. Without simultaneous recordings at each site, it remains unclear if these results stem from daily patterns of movement or seasonal differences. Vocalizations were recorded in two different seasons (site A in the wet season and site B in the dry season), and Antillean manatees are known to exhibit seasonal movement . A priorHalodule wrightii [Foraging may also play a role in how sites are used. As suggested by Self-Sullivan et al. (2003)  seagrasswrightii . Althougwrightii  AlthoughAlternative explanations for the number of detections could be related to the number of individuals, demographic characteristics of the group, and concurrent behavior. The number of manatees visiting each site during the recording period is unknown. Smaller groups of manatees tend to vocalize less  than larOur examination of manatee vocal activity in different microhabitats supports the use of passive acoustic monitoring as an important tool for identifying temporal trends in manatee activity . A deepeS1 Table(XLSX)Click here for additional data file.


The findings from multi-centre trials are central to the practice of evidence-based medicine, enabling the development and implementation of new treatments. The time it takes to commence clinical trials at sites can be long, and ethics and governance approvals are key steps on the pathway to site activation. The goal of this study was to explore factors influencing the times to ethics approval, governance approval and site activation for multi-centre clinical trials.This paper assessed the associations of trial characteristics , site characteristics  and characteristics of the ethics and governance processes  with times to approvals and activation. Median times were compared between site initiations that were and were not exposed to each characteristic using non-parametric tests in univariable and multivariable regressions.p univariable = 0.012, p multivariable = 0.044), use of scope guidelines  and use of a triage process  with shorter median times for governance approval. These characteristics  plus early trial phase (p = 0.028) were also predictive of shorter median times for ethics approval in univariable analyses, but none remained predictive in multivariable models . The only factors associated with reduced overall time to site activation in both univariable and multivariable analyses were the early trial phase  and mutual acceptance of ethics approvals .There were data from 150 site activations done across 91 sites, 16 trials and 5 countries from November 2013 to November 2021. The overall median time to activation was 234 days (range 74 to 657), with ethics approval taking a median of 48 days (0 to 369) and governance approval a median of 34 days (0 to 489). Both the univariable and multivariable analyses identified associations of disease area, particularly oncology (Times to ethics and governance approvals were only one third of total trial start-up time. Factors influencing times to approval and activation were somewhat inconsistent across analyses, but it seems likely that the introduction of selected governance and ethics processes can reduce approval times.The online version contains supplementary material available at 10.1186/s13063-023-07802-2. Multi-centre randomised clinical trials are gold standard research investigations used to generate high-quality data about ways to prevent, detect or treat medical conditions . The eviIn conjunction with pressures for the rapid commencement of clinical trials is the need for oversight and regulation that can ensure the ethics and quality of the projects. Some serious breaches of medical ethics in research done during the last century have highlighted the need for careful ethical review . In paraThe ethics and governance infrastructure supporting clinical research has struggled to keep up with the numbers and complexity of clinical trials . For exaAs a response to these challenges, many governments, hospitals, and clinical sites have developed processes that are designed to improve the speed and efficiency of clinical trial applications. A recent systematic review identified almost 100 reports of interventions targeting different aspects of clinical trial administration including 45 targeting ethics approval processes or governance arrangements . AmongstClinical Research Organisations do trials in multiple sites across different jurisdictions and often use a clinical trial management system to record standard data about the passage of a trial through the various parts of the regulatory and review processes. In conjunction with data that describe the regulatory environment at each site, this provides an opportunity to explore objectively the association of different regulatory set-ups on the passage of clinical trials through the approval process.This was a retrospective cross-sectional survey of the association between characteristics of the regulatory environment and the times to site activation, ethics approval and governance approval for multi-centre clinical trials. The project received ethics approval from the UNSW Sydney Human Research Ethics Committee on the 29th of March 2021. The STROBE checklist was used to standardize this report . The guiThis study used a convenience sample of trial initiations obtained from the database (GrantPlan) of a collaborating Clinical Research Organisation, George Clinical. A primary search of the company records identified a large number of potentially eligible site initiations, though it was recognised from the outset that incompleteness of information in the GrantPlan database, and limited resource available to ascertain missing data from other sources, would limit the final number of site initiations included in the analysis. Data required for eligibility were disease area, trial phase, and country as well as the dates of initial site contact, ethics submission and approval, governance submission and approval, as well as the date of site activation or first patient recruited.George Clinical team members extracted standard data from the clinical trial management database (GrantPlan), the contracts database and other data repositories held by the company between July 2021 and September 2022. The data were provided to a researcher external to George Clinical who de-identified the information by replacing the project name, principal investigator name and site name with unique identification numbers. The standard set of variables were extracted into an Excel database for each trial . Two resThe factors that were considered as potential determinants of site activation time fell into three categories—trial characteristics, site characteristics and characteristics of the ethics and governance processes. The latter variously operated at national, sub-national or site levels. The selection of exposures for evaluation was based on two systematic reviews that assessed factors previously reported to influence time to trial start-up , 12. SitThe key trial characteristics considered were the disease area  and the trial phase . The site characteristics recorded were the ownership status (government or private) and the country . Researchers were unable to find the ownership status of many trial sites for the Asian countries. The exposures relating to the ethics review process were the use of scope guidelines by the ethics committee; a requirement for mutual acceptance of other ethics committee findings; and an ethics process that triaged applications as low, medium, or high risk. The exposures relating to the governance review were the use of scope guidelines by the governance body; and a governance approval process that triaged applications as low, medium, or high risk.An outcome was the time taken to achieve site activation defined as the date that ‘site activation’ was recorded in the clinical trial management system. The date of initial site contact made by the clinical research organisation was used as the date at which the trial start-up process commenced. For 19 trials without a documented ‘site activation’ date, the date of site activation was imputed as the date the first patient was recruited. Additional outcomes were the time from submitting to obtaining ethics approval and the time from submitting to attaining governance approval. The unit of measurement for time was days.P-values < 0.05 were considered statistically significant. All analyses were done using R version 4.1.0 and RStudio 2022.07.2 Build 576 [The primary analysis was based on data from 150 site activations including 19 for which missing ‘site activation’ dates were imputed as the date of first patient recruitment. Since the distributions of the times across the included trials were noted to be substantively right-skewed, summary data for site activation, ethics approval and governance approval were reported as medians and ranges. Overall median times and ranges were first summarised for each outcome with all data available and then summarised separately for each subgroup for factors of interest. Differences in the median times across each subset for factors of interest were tested first using univariable regressions and non-parametric tests  on log-transformed outcome data. We then repeated the analyses using multiple regression methods including all the variables from the univariable analysis, to assess the joint effects of the exposures. Records with missing or unknown values were excluded from relevant analyses with, for example, analysis of the effects of government versus private ownership restricted to Australia because this information could not be obtained for overseas sites. For the analyses of factors influencing time to site activation, a subsidiary analysis was done including only the 131 trials for which a date of site activation was recorded, without the 19 trials with imputed data  were excluded because required information was not immediately available in the GrantPlan database and there was no resource available to extract and compile information from other data repositories held by the company. Ultimately there were 150 instances of site activation done at 91 different sites in 5 different countries available for analysis (Table p = 0.001), the country in which the trial was done (p = 0.039), private ownership of the centre conducting the trial (p = 0.039), provisions to allow for the mutual acceptance of other ethics committee approval (p = 0.031) and initiation during or after the COVID-19 pandemic (p = 0.007). In the multivariable analysis, these associations persisted for only earlier trial phase (p = 0.013) and the presence of mutual acceptance of ethics provisions (p = 0.030). Disease area was significantly associated with time to site activation in the multivariable analyses alone (p = 0.026) with a longer median duration for neurology trials.The overall median time to site activation was 234 days with a range that extended from 74 to 657 days , disease area (particularly oncology) (p < 0.001), the use of scope guidelines (p < 0.001 univariable), mutual acceptance provisions (p < 0.001 univariable) and triaging according to risk (p < 0.001 univariable). None of these findings persisted in the multivariable analyses .The median time to ethics approval from ethics submission was 48 days (range 0 to 369 days) Fig. , Table 3p = 0.012), use of scope guidelines for governance review (p < 0.001) and a process for triaging review based on risk (p < 0.001). All these findings persisted in the multivariable analysis . In addition, in the multivariable analysis alone, studies done during or after the COVID-19 pandemic had a longer time to governance approval that did trials approved pre-COVID (p = 0.013).The median time to achieve governance approval was 34 days (range 0 to 489) Fig. , Table 4There were multiple associations of the characteristics of trials, sites, and review processes with times to regulatory approval and site activation. Both the univariable and multivariable analyses identified associations of disease area, use of scope guidelines and use of a triage process with shorter median times for governance approval. These characteristics plus early trial phase were also predictive of shorter median times for ethics approval in univariable analyses, but none remained predictive in multivariable models. The only factors associated with reduced overall time to site activation in both univariable and multivariable analyses were early trial phase and mutual acceptance of ethics approvals.In terms of the process characteristics potentially modifiable by institutions there was evidence that streamlined governance processes could reduce governance approval times. Corresponding evidence for benefits from streamlining ethics processes was more limited though mutual acceptance of ethics review outcomes was the only process intervention associated with reduced overall time to site activation. In general, there was a disconnect with benefits of process interventions for ethics or governance timelines not translating into reduced overall times for site activation. This is likely a consequence of the fairly short median times for achieving governance (median 34 days) and ethics (median 48 days) approvals which constituted only about one third of the much longer median time to site activation (234 days).Ethics and governance approval times are widely considered to be barriers to rapid trial start-up, but these analyses show that other processes in the pathway to site start-up take much more time to be achieved. So, while enhancing ethics and governance interventions can play a role in speeding site activation, the average impact may be limited. Further work to identify whether it is related factors such as the preparation of applications for ethics and governance reviews, or separate issues such as budget negotiations, contract finalisation and other site processes that accrue most of the additional required to achieve site activation.The positive association of governance interventions with shorter time to governance approval observed in these analyses supports the implementation of governance processes that define the scope of governance review (resulting in a median difference of 51 days) and triage projects according to risk (resulting in a median difference of 57 days). The alignment of the favourable findings for these interventions in the current analyses with positive findings for these types of interventions in prior reports provides further support for their likely value .The results for ethics interventions on ethics approval times were less compelling with considerable inconsistency across the findings for the univariable and multivariable analyses. The observation that schemes that support mutual acceptance of ethics review were associated with shorter overall time to site activation provides additional support for a likely benefit from this strategy. Prior research has also identified mutual acceptance of ethics review as a priority ethics intervention and the totality of the evidence across this study and prior investigations suggests it is likely to be effective , 17. BasThere were several non-modifiable characteristics of studies, like trial phase and disease area, for which associations with time to approval were also observed. Deeper investigation of the reasons why particular types of projects were associated with shorter approval times may provide insight into ways that approval times and site start-up may be reduced. For example, it may be that some aspect of trial start-up has been optimised by an initiative undertaken in a specific disease area, and this could be generalised to other specialities. The findings regarding the effects of the COVID-19 pandemic on approval times in this study were inconclusive. Anecdotal reports suggest that ethics and governance interventions to achieve rapid approval and start-up of COVID-19 studies dramatically reduced timelines for selected projects, but it is unclear whether these changes provided broader system gains or were at the expense of non-COVID-19 projects . SystemaA key strength of this study was the ability to more directly and objectively quantify the association of potential determinants of time to trial start-up identified in prior qualitative and semi-quantitative studies . The joiIn conclusion, although ethics and governance reviews do not represent the majority of approval time, these analyses support the introduction of streamlined ethics and governance processes by governments and health departments seeking to reduce the time to clinical trial start-up. The introduction of process enhancements should be accompanied by the collection, analysis, and reporting of meta-data to objectively quantify impact.Additional file 1: Supplementary Table 1. Factors influencing time to trial start-up (days) restricted to 131 site initiations with ‘site activation’ date.Additional file 2. STROBE Statement—checklist of items that should be included in reports of observational studies.


This study aims to investigate the feasibility of the anterior transpedicular root screw (ATPRS) intervertebral fusion system for the cervical spine and provide a basis for the design of the ATPRS intervertebral fusion system.1) was determined when the upper and lower screw paths did not overlap. When the screw was tangent to the medial edge of the Luschka joint, the insertion point was determined as the entry point (P2). Measurements were taken and recorded for the following parameters: distance from the screw entry point to the midline of the intervertebral space (DPM), the simulated screw length, inclination angle, cranial/caudal tilted angle, the anterior–posterior (AP) and mediolateral (ML) diameters of the cervical intervertebral space, the heights of the anterior, middle, and posterior edges of the cervical intervertebral space, and the curvature diameter of the lower end plate of the cervical vertebral body. Statistical analysis was performed on the measurement results.A total of 60 healthy adult cervical spine CT images examined from our hospital were selected, including 30 males and 30 females, with an average age of 39.6 ± 4.8 years. The image data was imported into Mimics 21.0 software in DICOM format for 3D model reconstruction. Simulated screw insertion was performed on both sides of the midline of the intervertebral space. The entry point (P1P2) showed an increasing trend from C3-C7 in both male (2.92–6.08 mm) and female (2.32–5.12 mm) groups. There were statistical differences between men and women at the same level (P < 0.05). The average screw length of men and women was greater than 20 mm, and the upper and lower screw lengths showed an increasing trend from C3 to C7. In the area where screws could be inserted, the range of screw inclination was as follows: male group upper screw (47.73–66.76°), lower screw (48.05–65.35°); female group upper screw (49.15–65.66°) and lower screw (49.42–63.29°); The range of cranial/caudal tilted angle of the screw was as follows: male group upper screw (32.06–39.56°), lower screw (29.12–36.95°); female group upper screw (30.97–38.92°) and lower screw (27.29–37.20°). The anterior–posterior diameter and mediolateral diameter of the cervical intervertebral space showed an increasing trend from C3 to C7 in both male and female groups. The middle height (MH) of the cervical intervertebral space was greater than the anterior edge height (AH) and posterior edge height (PD), with statistical differences (P < 0.05). The screw entry area (PThrough the study of CT images of the cervical spine, it was determined that the ATPRS intervertebral fusion system has a feasible area for screw insertion in the cervical intervertebral space. The anterior transpedicular screw (ATPS) technology was proposed in 2008 by Koller et al.  they subP > 0.05) in the CT values of the bone surrounding the ATPRS path compared to those of the ATPS. However, the CT values were found to be statistically different (P < 0.05) when compared to the VBS [However, based on previous research, our team found some limitations of ATPS technology in clinical applications: 1. the upper screw entry point of ATPS is too close to the upper edge of the vertebral body, and the distance between the plate and the upper intervertebral disc is too close. This proximity may accelerate degeneration of the upper segment intervertebral disc. 2. The ATPS necessitates complete penetration of the pedicle during screw insertion, requiring high levels of accuracy. This increases the risk of injury to the vertebral artery, nerve root, and cervical spinal cord , 9, 10.  the VBS . These r the VBS . Additio the VBS –16. The  the VBS , 18. Als the VBS . TherefoIn our research, a total of 60 healthy patients, who underwent cervical CT scans at our institution from May 2021 to August 2021 were retrospectively selected, including 30 males and 30 females, aged 25–50 years, with a mean age of 39.6 ± 4.8 years. In addition, all patients were excluded from any infectious, traumatic, neoplastic, degenerative disease, congenital, or developmental involving the spine. All patients were scanned by a helical CT scanner . The study protocol was approved by the institutional ethics committee of Ningbo No.6 Hospital of Ningbo University (CODE: k2020019) and written informed consent from all study participants.All the CT images were imported into Mimics Medical 21.0  in DICOM format for three-dimensional reconstruction of the cervical spine model Fig. . The spe1) of the ATPRS intervertebral fusion system to the midline of the intervertebral space  . And the simulated screw head was positioned at the intersection of the posterolateral edge of the vertebral body and the axis of the pedicle in the horizontal plane, as well as close to the lower edge of the pedicle in the sagittal plane . In the ace Fig. . Previou 2) Fig. . ConsideTo minimize errors, through sagittal, horizontal, and coronal fluoroscopy, screws were precisely inserted into anatomical positions. Meanwhile, all parameters were measured three times by a senior spine surgeon, and the average was used as the final value , 22.The relevant parameters of the intervertebral spaces were measured. (1) Mediolateral (ML) diameter of the intervertebral space: that was to measure the distance of the line connecting the medial edge of the Luschka joint as a reference for the design of the left and right width of the ATPRS intervertebral fusion system Fig. A. (2) An1, measured and recorded the relevant parameters ; (2) Simulated screw length (SL1); (3) α1 angle: the angle between the simulated screw axis and the midsagittal plane of the vertebral body on the horizontal plane; (4) β1 angle: the angle between the simulated screw axis and the middle section of the intervertebral space in the sagittal plane. The simulated screw was inserted into the vertebral body at point P2, measured and recorded the relevant parameters ; (2) Simulated screw length (SL2); (3)α2 angle: the angle between the simulated screw axis and the midsagittal plane of the vertebral body on the horizontal plane; (4)β2 Angle: the angle between the simulated screw axis and the middle section of the intervertebral space in the sagittal plane. Then DMP2—DMP1 was the screw entry area (P1P2). The above parameters can be used as a reference for the design of the screw entry position, screw length, and screw entry direction of the ATPRS intervertebral fusion system.The simulated screw was inserted into the vertebral body at point Pers Fig. . (1) Disl plane;  β1 angleP < 0.05 was considered statistically significant. All analyses were performed using SPSS 21.0 software . The results of statistical analysis were plotted using GraphPad Prism 9.5 software .Data were described as mean and standard deviation (Mean ± SD). The independent samples t-tests were performed to compare the data between left and right on the same cervical level. If the variances of the data were homogeneous, ANOVA was used to compare the data of C3-C7; if they were not, a non-parametric test was used. A total of 60 cases of cervical spine CT imaging data were observed and measured in this study, including 30 males and 30 females. A total of 5040 data were summarized as follows statistical analysis.p < 0.05)  Fig. .Table 1Mp < 0.05)  Fig. .Table 2AP < 0.05)  Fig. .Table 3T1 of the C3-C7 range was (3.56–3.98) mm in the male group, (3.81–4.20) mm in the female group; the average DMP2 of the C3-C7 range was (6.90–9.64) mm in the male group, (6.51–8.93) mm in the female group. The average DMP1 in both male and female groups showed a decreasing trend from C3 to C7. Besides, the average DMP1 in the same segment in the male group was smaller than that in the female group, but there were no significant differences (P > 0.05)  , that is DMP2—DMP1, ranged from (2.92–6.08) mm in the male group and (2.32–5.12) mm in the female group. And the average value of P1P2 in both male and female groups showed an increasing trend from C3 to C7. In the same segment, the average value of P1P2 in the male group was greater than that in the female group, and there were statistical differences (P < 0.05). Additionally, there were statistically significant differences in the P1P2 of cervical intervertebral space at different segments (P < 0.05)  mm in the male group, and (21.07–22.94) mm in the female group; the average SL1 of the lower screw of the C3-C7 range was (21.10–23.49) mm in the male group, and (20.20–22.62) mm in the female group. And in Table 2 of the upper screw of the C3-C7 range was (24.56–29.61) mm in the male group, and (23.50–28.32) mm in the female group; the average SL2 of the lower screw of the C3-C7 range was (22.74–27.5) mm in the male group, and (22.18–26.59) mm in the female group. No matter at P1 or P2 point, the length of the upper and lower screws in the male or female group showed an increasing trend from C3 to C7, and the average length of the upper or lower screws in the male group was greater than that in the female group at the same segment of the intervertebral space. The comparison between males and females in the same segment of SL1 and SL2, as well as the comparison between different segments within the same gender, are illustrated in Fig. In Table 22.35–23.8 mm in te was 21.–23.49 mm1 of upper screw form C3 to C7 was (47.73–51.44) ° in the male group and (49.15–52.41) ° in the female group; the average α1 of lower screw form C3 to C7 was (48.05–51.36) ° in male group and (49.42–51.27) ° in the female group. In Table 2 of upper screw form C3 to C7 was (59.46–66.76) ° in male group and (58.67–65.66) ° in female group; the average α2 of lower screw form C3 to C7 was (58.49–65.35) ° in male group and (57.04–63.29) ° in female group. Furthermore, in both male and female groups, statistical differences existed between the upper and lower screws α1 angle and upper and lower screws α2 angle at the same segment (P < 0.05). The comparison between men and women in the same segment of the screw α1 angle or α2 angle and the comparison between different segments of the same sex are shown in Fig. From Table  C7 was 4.05–51.361 of upper screw form C3 to C7 was (32.06–34.67) ° in the male group and (30.97–33.25) ° in the female group; the average β1 of lower screw form C3 to C7 was (29.12–32.04) ° in male group and (27.29–31.24) ° in the female group. In Table 2 of upper screw form C3 to C7 was (35.47–39.56) ° in the male group and (35.50–38.92) ° in the female group; the average β2 of lower screw form C3 to C7 was (34.18–36.95) ° in male group and (34.23–37.20) ° in the female group. Furthermore, in both male and female groups, statistical differences existed between the upper and lower screws β1 angle and upper and lower screws β2 angle at the same segment (P < 0.05). Figure 1 and β2 angles of the screw, as well as the comparison between different segments within the same gender.From Table 7 was 29.–32.04 ° Anterior cervical decompression and fusion (ACDF), as a standard surgical procedure for the treatment of cervical degenerative and traumatic diseases, is widely used in clinics . This apMimics software, as a professional interactive medical image control system, can convert two-dimensional images into three-dimensional models, which can more intuitively measure and observe the corresponding tissues and organs. It has been widely used in orthopedics , 29. In By measuring the CT images of the cervical spine, it was found that the ML diameter of C3-C7 intervertebral space was (16.48–21.55 mm), and the AP diameter of C3-C7 intervertebral space was (15.47–17.29 mm) in the male group. The ML diameter of the C3-C7 intervertebral space was (15.75–20.20 mm), and the AP diameter of the C3-C7 intervertebral space was (14.16–15.95 mm) in the female group. This is compared with the C3-C7 intervertebral space ML diameter range (16.13 ± 1.99 mm) and intervertebral space AP diameter range (16.08 ± 1.84 mm) measured by Wang et al. . The intMorphologically, the upper endplate of the cervical vertebrae is generally flatter, while the lower endplate is typically more concave. Feng et al.  conducte1P2) of the ATPRS intervertebral fusion system ranged from 2.92 to 6.08 mm in the male group and from 2.32 to 5.12 mm in the female group. The P1P2 showed an increasing trend from C3 to C7 in both male and female groups, which may be related to the changes in intervertebral space height and pedicle position. The average value of P1P2 in the male group was greater than that in the female group, aligning with the morphological and anatomical differences between male and female cervical spines. And there were statistical differences between them (p < 0.05). These results indicated that there is a screw placement area in the cervical intervertebral space, ensuring non-overlapping screw paths for the upper and lower screws. Furthermore, the screw placement area gradually increases from C3-C7 intervertebral space. The ATPRS intervertebral fusion system is feasible in morphology and anatomy.According to the measurement results, the screw entry area (PPrevious studies have demonstrated that the length, diameter, and thread type of the screw can impact its fixation strength –37. ThroTables The screw cranial/caudal tilted angle was also different in different cervical segments. Through measurement, it was found that the screw cranial and caudal tilted angle ranged from 29.12° to 36.95° and from 32.06° to 39.56°, in the male group within the screw entry area of C3-C7; In the female group, the lower screw cranial angle ranged from 27.29 to 37.20° and the upper screw caudal tilted angle ranged from 30.97° to 38.92°. Overall, the cranial/caudal tilted angle of the ATPRS intervertebral fusion system exceeds that of the ATPS technology, but it remains within the angle range of the conventional Zero-P, indicating its feasibility , 39.However, this study also has some limitations. First, the sample size is small, the elderly population was not included in the study, and the representativeness is limited, so further large sample measurement is needed. Second, this study is the preliminary study of the ATPRS intervertebral fusion system, and its biomechanical properties need to be verified by later experiments. Third, the operability of the ATPRS intervertebral fusion system needs to be further improved.In conclusion, this study verified the feasibility of the ATPRS intervertebral fusion system in cervical morphology and anatomy through cervical CT imaging research and preliminarily obtained the relevant parameters of the ATPRS intervertebral fusion system, which provided some basis for the design of ATPRS intervertebral fusion system.


The SARS-CoV-2 spike protein contains a functionally important fatty acid (FA) binding site, which is also found in some other coronaviruses, e.g. SARS-CoV and MERS-CoV. The occupancy of the FA site by linoleic acid (LA) reduces infectivity by ‘locking’ the spike in a less infectious conformation. Here, we use dynamical-nonequilibrium molecular dynamics (D-NEMD) simulations to compare the allosteric responses of spike variants to LA removal. D-NEMD simulations show that the FA site is coupled to other functional regions of the protein, e.g. the receptor-binding motif (RBM), N-terminal domain (NTD), furin cleavage site, and regions surrounding the fusion peptide. D-NEMD simulations also identify the allosteric networks connecting the FA site to these functional regions. The comparison between the wild-type spike and four variants  shows that the variants differ significantly in their responses to LA removal. The allosteric connections to the FA site on Alpha are generally similar to those on the wild-type protein, with the exception of the RBM and the S71–R78 region, which show a weaker link to the FA site. In contrast, Omicron is the most different variant, exhibiting significant differences in the RBM, NTD, V622–L629, and furin cleavage site. These differences in the allosteric modulation may be of functional relevance, potentially affecting transmissibility and virulence. Experimental comparison of the effects of LA on SARS-CoV-2 variants, including emerging variants, is warranted. The spike glycoprotein, which is located on the surface of the virion, mediates SARS-CoV-2 entry into host cells by binding primarily to the receptor angiotensin-converting enzyme 2 (ACE2)  as well Biomolecular simulations have provided molecular-level insights into SARS-CoV-2 spike structure and dynamics, uncovering the effects of mutations, predicting interactions, and revealing allosteric connections in the protein Amaro and. Equilibhttps://cov-lineages.org/global_report_B.1.617.2.html). It harbours six mutations and three deletions in the spike  (https://stacks.cdc.gov/view/cdc/108671). By the middle of 2021, a variant of Delta with the K417N mutation (nicknamed as ‘Delta plus’) was identified in Nepal and quickly spread to the rest of the world (https://cov-lineages.org/lineage.html?lineage=AY.100). Note that although Delta plus spread worldwide, it did not displace Delta in the same way as the Omicron did . The Omicron BA.1 variant (hereafter referred to as Omicron) was initially detected in South Africa in November 2021 (https://ourworldindata.org/grapher/covid-variants-bar?time=2022-01-31). This variant includes up to 40 mutations, deletions, and insertions on the spike, e.g. A67V, H69Δ–V70Δ, T95I, G142D, V143Δ, Y144Δ, Y145Δ, N211I, L212Δ, D215E, PED insertion in position 215, G339D, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, Y505H, T547K, D614G, H655Y, N679K, P681H, N764K, D796Y, N856K, Q954H, N969K, and L981F  C and shober 2021 . It sprend L981F . Omicronnd L981F .Hundreds of D-NEMD simulations were performed to analyse the responses of the wild-type spike and the Alpha, Delta, Delta plus, and Omicron variants to LA removal. The models used here were taken from We have also compared our Omicron model with the cryo-EM structure of Omicron sub-lineage BA.2 , the D-NEMD simulations performed here do not attempt to sample state transitions, such as the opening or closing of the RBD. Instead, these simulations allow for the identification of the first steps involved in the propagation of the structural changes within the protein and the order of the events associated with this process. Conformational rearrangements taking >10 ns are not be sampled, meaning that additional regions of the spikes may also respond to LA removal.The perturbation used here, as well as in our previous work , is desiD-NEMD simulations reveal the complex cascade of conformational changes induced by LA removal and identify the pathways through which these changes propagate within the protein. The structural response quickly propagates from the FA site to the specific and well-defined regions of the spike in all variants . SeveralThe networks connecting the FA site to functional regions of the spike are similar in all variants, thus apparently conserved . SimilarCross-correlation matrices were determined and mapped for the wild-type, Alpha, Delta, Delta plus, and Omicron systems in D-NEMD simulations  and equiThe cross-correlation maps computed from the LA-bound equilibrium trajectories  demonstrSignificant variations in the responses of the RBM (mainly the A475–C488 segment) were observed among the five virus spike proteins . In the The responses of the NTD differ significantly among variants, particularly in the S71–R78, H146–E156, and L249–G257 segments . For exaAll variants show weaker structural responses of the S71–R78 segment than the wild-type spike  and S29,Alpha, Delta, and Omicron show the enhanced structural rearrangements of the L249–G257 region in the NTD relative to the wild-type spike  compared to the wild-type spike . D614G sThe regions surrounding the FP, notably D808–S813 and the FPPR, are also affected by LA removal  strengthen the links to the FA pocket, others  abate them.The coupling of the FA site to the NTD, in particular to the S71–R78, H146–E156, and L249–G257 segments, is greatly affected by mutations in and around these regions. While deletions around position 156 (E156Δ–F157Δ in Delta) enhance the allosteric connection to the FA site, deletions around position 144 (V143Δ–Y145Δ in Omicron) diminish that connection. Deletions near position 71 (H69Δ–V70Δ in Alpha) weaken the response of S71–R78 and the allosteric link to the FA site. Mutations in the regions next to L249–G257  can amplify the structural rearrangements induced by LA removal, reinforcing the connection to the FA pocket.The D-NEMD simulations also reveal that substitutions leading to an increased positive charge in the region preceding the furin cleavage site (i.e. P681R in Delta and Delta plus and N679K in Omicron) apparently reinforce the allosteric link to the FA pocket. Conversely, the D614G mutation in Delta, Delta plus, and Omicron significantly reduces the coupling of V622–L629 to the FA site.Our results demonstrate that D-NEMD simulations are a valuable tool to study allostery, identify and explore the allosteric networks operating within the spike, and predict the impact of future mutations in these pathways. D-NEMD simulations provide an effective approach to characterize allosteric effects , effectsmjad021_Supplemental_FilesClick here for additional data file.


Currently, new synthetic procedures based on active‐site imprinting followed by an ion exchange reaction, e.g. Zn‐to‐Fe, are producing single‐site M−N−Cs with outstanding activity. Based on the same replacement principle, we employed a conservative iron extraction to partially remove the Fe ions from the N4 cavities in Fe−N−Cs. Having catalysts with the same morphological properties and Fe ligation that differ solely in Fe content allows for the facile determination of the decrease in density of active sites and their turn‐over frequency. In this way, insight into the specific activity of M−N−Cs is obtained and for single‐site catalysts the intrinsic activity of the site is accessible. This new approach surpasses limitations of methods that rely on probe molecules and, together with those techniques, offers a novel tool to unfold the complexity of Fe−N−C catalyst and M−N−Cs in general.M−N−C electrocatalysts are considered pivotal to replace expensive precious group metal‐based materials in electrocatalytic conversions. However, their development is hampered by the limited availability of methods for the evaluation of the intrinsic activity of different active sites, like pyrrolic FeN We herein used the equivalence of an active site extraction to the poisoning of active sites to develop a new method for the determination of site density, utilization factor and TOF. The method is reminiscent of stripping techniques but since there are no probe molecules involved it can be applied to different classes of M−N−C directly at the relevant pH. This salt templating strategy allows to achieve high yields and the final morphology of the catalyst can be finely tuned by simply adjusting the mixture composition.2+ ions facilitates the formation of N4 moieties.4 sites of the pristine Fe−N−C catalyst using 2.4 M HCl, a non‐oxidizing acid, and moderate temperatures of 100 °C for different times. Based on their elemental composition, samples are named with their approximate stoichiometry with emphasis on the active‐ and Fe‐removed FeN4 site, i.e. [FeN4]N32C520 indicates the pristine sample and [FeN4]x[N4]x1−N32C520 the partially Fe‐extracted ones . The composition obtained from elemental combustion analysis is confirmed by scanning electron microscopy energy‐dispersive X‐ray spectroscopy (SEM/EDX) spectra  and small impurities of Al and Si, most likely due to the crucible and lid employed in the synthesis, are also found. The presence of Cl is attributed to the washing of the sample. Importantly, [FeN4]x[N4]x1−N32C520 samples do not present more Cl compared to the pristine sample, excluding functionalization of the carbon scaffold from the HCl treatment employed to remove the Fe. Moreover, the Fe content in the Fe‐extracted samples is too little to be detected in the SEM/EDX analysis. SEM images show the aerogel‐like structure of the catalysts before and after Fe extraction  in a ZnClmixture Tm=250 °C mixture Tm=250 °C mixture Tm=250 °C mixture Tm=250 °C mixture Tm=250 °C mixture Tm=250 °C 4]N32C520 at 4.2 K show the presence of two quadrupole doublets with a 3 : 1 intensity ratio. Such doublets are characteristic for atomically dispersed FeN4 sites 2+ with covalent character or Fe3+ and therefore points to O2 coordinated Fe+II−N4 sites. The second doublet (herein for the cryo‐measurements referred to as D2) with an IS of ≈0.74 mm s−1 and a QS of ≈3.7–3.8 mm s−1 suggests high‐spin Fe2+, as in a bare tetrapyrrolic Fe+II−N4 structure. A magnetically split sextet component is an indication of only 8 % nanoscopic FeIII oxidic clusters. Due to the low relative area of this sextet, these clusters are herein neglected for clarity. Worth nothing is the sharpness of the two doublets, namely a line width of 0.90 mm s−1 and 0.55 mm s−1 for D1 and D2 respectively. These values are unusual in Fe−N−C catalysts and more common in molecules, likely pointing to a high homogeneity of the FeN4 environment.4]0.17[N4]0.83N32C520 .Cryo‐Mössbauer spectroscopy measurements of N32C520 has a Tafel slope of ≈60 mV dec−1, quantifying the fast kinetics of the catalyst. The comparison of activity after the removal of active metal centres is comparable to the nitrite stripping method, where comparison of activity is carried out before and after active site poisoning. This allows for the TOF calculation of FeN4 sites, according to Equation −1), which act as pristine and deactivated states (corresponding to the poisoned state in stripping techniques). This is possible because the extraction naturally targets accessible Fe sites. The gravimetric Fe content should not be used as SD metric due to the potential presence of different Fe phases or buried FeN4 sites, although the herein used synthetic method based on active‐site imprinting followed by Zn‐to‐Fe ion exchange promised potential for the exclusive presence of accessible FeN4 sites.A rotating disc electrode (RDE) setup was employed to measure the activity and derive the TOF value of the catalysts in O4 sites under more realistic PEMFC conditions compared to the nitrite stripping method, i.e. pH 1. For several extracted samples the kinetic current densities can be plotted over the product of molar iron concentration and the Faraday constant. The linear fit reveals the TOF as the slope. At 0.8 VRHE, Δikin and ΔSD have a value of 2.4 A g−1 and 9.85×10−5 mol g−1 when using the longest leached [FeN4]0.17[N4]0.83N32C520. This gives a TOF value of 0.25 s−1. The more accurate graphical analysis results in a slope of 0.24 s−1 . The TOF value is in line with reported values for Fe−N−C catalyst at this potential, obtained via CO cryo‐sorption and nitrite stripping methods,−1 at 0.8 VRHE specifically to tetrapyrrolic FeN4 sites. Since this intrinsic activity is below reported specific activity of Fe−N−Cs, the results suggest that more active FeNx sites exist.[−1 obtained via extracting method, a theoretical value of 2.9 A g−1 at 0.8 VRHE is calculated. This calculated value is close to the measured value of 2.7±0.3 A g−1 obtained at the same potential, showing that the utilization factor corresponds to 93±10 % in RDE measurements, confirming that active sites obtained via transmetalation reaction are highly accessible. Calculation based on the graphical analysis (with a TOF of 0.24 s−1) results in a theoretical kinetic current density of 2.8 A g−1 and a utilization factor of 96±11 %.Using Equation (1) it is possible to calculate the TOF of the extracted FeN4 sites are also accessible to the electrolyte and were hence ORR active.In conclusion, we introduce here a new methodology to derive the specific catalytic activity by means of TOF and utilization of active sites in atomically‐dispersed M−N−C electrocatalysts. In contrast to the established methods like CO cryo‐sorption and nitrite stripping, this method does not rely on probe molecules but solely on the possibility to replace the active‐metal centre with protons. Since no selective binding is involved, the method can be used for any atomically‐dispersed M−N−C catalyst if metal contents are known. The principle of the method is further eliminating questions regarding how many CO molecules bind the active site or how many electrons are transferred in the electrochemical stripping process of NO  or in the concentration of the probe molecule. This allows for the application of this method at operating conditions, i.e. both in acidic and alkaline electrolytes and even at higher temperatures. As long as an extraction of the active metal sites is possible, this method can be extended to all kinds of M−N−Cs and other reactions, holding the potential to push the understanding of this type of materials further.RHE is assigned specifically to the ORR activity of tetrapyrrolic FeN4 sites (intrinsic activity). Since higher TOF values than 0.24 s−1 for Fe−N−Cs were previously reported it may be concluded that other active sites need to be targeted to approach Fe−N−C catalysts for the application in fuel cell electric vehicles.In the present work the catalyst can be approximated a single‐site catalysts. Hence, the TOF value at 0.8 VThe authors declare no conflict of interest.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.Supporting InformationClick here for additional data file.