Zirconia has been used for rehabilitation of edentulous spaces approximately for a decade, and there have been several reports regarding the clinical performance and retention of zirconia crowns. Outstanding mechanical properties, biocompatibility, and excellent aesthetics make zirconia-based crowns as a popular crown among the current all-ceramic crowns in restorative dentistry. However, restoration with a zirconia crown is a challenging treatment. The goal of this study was to assess the current literature to summarize the studies reporting the effective risk factors on retention of zirconia crowns to provide clinicians with a useful point of view in the decision-making process for use of these restorations. Literature based-search was performed to find related articles until August 2020 using EMBASE, Google Scholar, and MEDLINE. Search terms used were “zirconia restorations properties,” “zirconia crowns clinical performance,” “zirconia crown survival,” “biological complications,” and “zirconia crown retention.” Results were limited to papers available in English. The references of all related literature were also searched for further citations. Overall, although clinical long-term and follow-up studies are a vital requirement to conclude that zirconia has great reliability, it seems that zirconia crown restorations are both well tolerated and sufficiently resistant. The treatment of edentulous spaces with an osseointegrated dental implant is a known treatment modality and scientifically accepted . Every iDuring the last few decades, because of esthetic quality and high success rate, metal-ceramic crowns have been the restoration of choice . RecentlDespite the probable problems, recently, the demand for zirconia, due to the zirconia mechanical properties, is increasing considerably. Since zirconia-based restorations are a topic of current interest in the light of recent studies that have demonstrated the excellent biological and mechanical properties of these restorations, a comprehensive review introducing effective factors on its retention is warranted. The goal of this study was to assess the current literature to summarize the studies reporting the effective risk factors on retention of zirconia restorations in crowns to provide clinicians with a useful point of view in the decision-making process for use of these restorations. Literature based-search was performed to find related articles until August 2020 using EMBASE, Google Scholar, and MEDLINE. Search terms used were “zirconia restorations properties,” “zirconia crowns clinical performance,” “zirconia crown survival,” and “zirconia crown retention.” Results were limited to papers available in English. The references of all related literature were also searched for further citations. We assessed subjects, abstracts, and the full-text paper of the records retrieved from the databases for probable inclusion. Data obtained are categorized as follows.2) has some features  making it the material of choice where high functional and esthetic issues are concerned [2O3) as a stabilizer. Compared with other all-ceramic core materials, the most important advantage of Y2O3 is their high fracture resistance which represents by their superior flexural strength and fracture toughness [Zirconia  and facilitate the aging process. A raise in stress or moisture on zirconia may cause the transformation of its crystals to a monoclinic phase with the formation of microcracks that raise water penetration, surface deterioration, and crack propagation, resulting in decreased resistance to overload . It has Fracture resistance of zirconia is strongly affected by the amount of occlusal load and characteristics of the implant-abutment . When a A main advantage of zirconia compared with titanium is attributed to its outstanding aesthetics. The optical behavior of zirconia differs with its composition, crystal size, and machining methods applied . The impConsidering the type of material used in restorations, it has shown that zirconium oxide induces a lesser phlogistic reaction than titanium restorative materials . In addiGiven the increasing popularity of zirconia, several complications have reported in the literature. Various researchers have reported the causes of zirconia restorations failure. According to the studies of layered zirconia, chipping of the veneering porcelain is the most commonly reported complication –37. BesiSome authors suggested that an ideal luting agent provides sufficient retention for ceramic crowns. In general, luting cements contain at least two mixed pastes. It has been shown that voids and air bubbles generated in mixed pastes may introduce into the cementation agent and lead to degradation of mechanical features . Clinicaμm did not have any considerable effect on restoration retention [Cement thickness is another main parameter influencing the retention of the crown. Nevertheless, when cement space is insufficient, it will cause crown seating discrepancies. The cement space can improve the outflow of excess cement and seating of a crown, lower the seating forces, and decrease the elevation of restorations, consequently resulting in retention of the restoration , 53. Theetention . The finetention , 55. Howetention  evaluateIn terms of survival, clinical, and esthetical outcomes, a small number of clinical trial studies have assessed the overall success rate of zirconia crowns. In a systematic review, Jung et al. showed 4.5% chipping after an observation period up to 5 years . In a re1⁄2 which is weaker than Zirconia-TZP (9.42 MPa·m1⁄2) but is comparable with In-Ceram Alumina (5.00 MPa·m1⁄2) [4 ceramic crowns, under moist conditions with 49 N in 1.2 million chewing cycles (5 years simulated) and temperature changed from 5 to 55°C, was 1789.6 N (±658.9). In a similar study performed by Okutan [4 ceramic crowns in 1.2 million chewing cycles were consistent with rates obtained by Ortorp et al.'s study. However, they declared that cementation type may provide the different rates, for instance, mean fracture loads for ZrSiO4 ceramic crowns cemented with Ketac Cem was 1662 N (±433) and for crowns cemented with Panavia 21 EX was 1957 N (±806). The zirconia crowns have high chemical resistance and considerable biocompatibility. In Encke et al.'s study, the chemical solubility tested by the exposure method at 80°C in a 4% acetic acid solution is 7.2 μg·cm−2.In the study of Ortorp et al., the total incidence of complications was somewhat high; however, if the usual complications were excluded, for instance, excess of cement detected at next check-up, temporary pain after cementation, and loosened crowns that easily could be recemented, the complication rate was 9 percent. Before the zirconia era, the mean rate of complications incidence in a review of all-ceramic studies was 8 percent . In the Pa·m1⁄2) , 61. They Okutan , the meaIn this study, there are limitations that should be noted. The current study is a narrative review, and it has been criticised for lacking synthesis and rigour, although narrative reviews may be broader in scope than systematic reviews. In addition, narrative reviews have been criticised for rarely employing peer-reviewed methodologies, or duplicate curation of evidence, and for often failing to disclose study inclusion criteria. Despite these limitations, narrative reviews remain frequent within the literature, as they offer breadth of literature coverage and flexibility to deal with evolving knowledge and concepts.In conclusion, the authors concluded that zirconia crowns are a promising prosthodontic valid alternative to metal ones and show good clinical performance based on observation and in vivo investigations. Although clinical long-term and follow-up studies are a vital requirement to conclude that zirconia has great reliability, it seems that zirconia crown restorations are both well tolerated and sufficiently resistant. However, several aspects remain to be studied and assessed. On top of all, the in vivo prospective studies on zirconia crowns to assessing the long-term clinical success; therefore, more research with long-term randomized clinical trials on the subject is currently suggested. In addition, an updated systematic review/meta-analysis, using PRISMA guidelines can be an appropriate way of reviewing the topic to provide clinicians with useful point of view in the decision-making process for use of these restorations.


Retraction note:Malaysian Journal ofMedical Sciences has been requested by the administrator of the youthin mind in the UK who is in charge of the SDQ questionnaire becausea translation of the Malay Parent-version Questionnaire into the Malay Children-versionwas done and published without the necessary authorisation via the author of themanuscript, Dr Idayu Badilla Idris and co-authors.The retraction of the manuscript titled above from the Editor-in-ChiefMalaysian Journal of Medical Sciences


The resilience of small and medium-sized enterprises (SMEs) to disruptive events is significant as this highly prevalent category of business forms the economic backbone in developed countries. This article provides an overview of the application of a computational modelling and simulation approach to evaluate SMEs' operational resilience to flooding based on combinations of structural and procedural mitigation measures that may be implemented to improve their premises' resistance to flooding and safeguard their business continuity. The approach integrates flood modelling and simulation with agent-based modelling and simulation (ABMS) within a modelled geographical environment. SMEs are modelled as agents based on findings of semi-structured interviews with SMEs that have experienced flooding or are at risk of flooding. In this paper, the ABMS has been applied to a new case study of the major flood event of 2007 in Tewkesbury. Furthermore, to enable an evaluation of the operational resilience of manufacturing SMEs in terms of the relative effectiveness of flood mitigation measures, a new coefficient based on production loss is introduced. Results indicate structural mitigation measures are more effective than procedural measures. While this result is intuitive, the approach provides a means of evaluating the relative effectiveness of combinations of mitigation measures that SMEs may implement to enhance their operational resilience to flooding.This article is part of the theme issue ‘Urban flood resilience’. For example, resilience has been defined as the adaptation ability of an organization to return to a stronger state post-disturbance [Business and organizational resilience to disruptions, disturbances and discontinuities is an evolving area of research –7. Howevturbance , and as turbance . In partturbance –13 with turbance ,15 and fturbance –19. In sturbance . Similarturbance  and its turbance .In relation to natural disasters, including extreme weather events, it has been recognized that small businesses need to proactively prepare for such situations  and becoIn addition to SMEs being recognized as lacking organizational resilience to disruptive events , a reasoIn many domains, computational modelling and simulation offers an inexpensive and time-efficient means of carrying out what-if scenarios and investigations into alternative strategies for a given situation. In particular, agent-based modelling and simulation (ABMS) is one of the most prominent computational approaches used, which enables investigations into how the dynamics of a real-world system are likely to be affected by changes to internal or external factors . FurtherIn this paper, to follow, the methods employed in the computational modelling and simulation approach used to evaluate SMEs' operational resilience to flooding are summarized and the case study to which the approach has been applied is presented. In the approach, a modelled geographical environment provides the common physical environment for the simultaneous modelling and simulation of a flood event and SME operations before, during and after this event. The case study of the flooding experienced in Tewkesbury, Gloucestershire, was selected due to the extreme nature of the event and its impact in this urban area on manufacturing SMEs. Prior to presenting and discussing the results obtained by applying the approach, simulation experiments in terms of flood mitigation measures that SMEs can implement are defined and a measure, based on production capacity loss, is proposed to enable an evaluation of manufacturing SME operational resilience. Finally, conclusions of the research are summarized and an indication of the direction of future work is given.2.In this research, computational modelling and simulation forms the approach to enable an evaluation of SMEs' operational resilience to flooding. (a)©, namely the Topography layer, Integrated Transport Network™ layer and Address layer. Each of these layers includes geographical information systems (GIS) data, which can be represented visually as shown in A model of the geographical environment of the urban area under consideration is required as it provides a common physical environment in which to simultaneously perform flood event simulation and agent-based simulations of SMEs' operations. The modelled geographical environment has been constructed using data from three layers of the ordnance survey (OS) MasterMapIn ©. Furthermore, 16 of these 92 manufacturing SMEs were directly affected by the flood event modelled and simulated. Thus, these 16 manufacturing SMEs, assumed to be micro-sized given their dominance, were the focus of the agent-based simulation experiments defined in §4 and discussed in §5.In the geographical area of Tewkesbury considered in §3, 692 SMEs were identified, 92 of which were manufacturing SMEs according to the Address layer from OS MasterMap(b)©'s Topography Layer, river survey data and Digital Terrain Model (DTM) data. Hydrographs provide a time series of flow (discharge) over the duration of a flood. In this study, measured hydrographs of the River Severn and River Avon were used for input to the LISFLOOD-FP 1D model upstream of the geographical urban area of Tewkesbury under consideration. OS MasterMap©'s Topography Layer  provides building polygon and land use data allowing the assignment of no-flow areas around buildings and the application of different surface roughness (based on their resistance to flow) to the land use classes in the LISFLOOD-FP 2D model. Buildings were considered to be a constant 5 m above local ground-level elevation. River survey data provide information regarding the elevation of the river channel in the LISFLOOD-FP 1D model; this was obtained from the existing ISIS 1D model provided by the Environment Agency and was used to represent the river channel in the 1D model. In the LISFLOOD-FP 2D model, the DTM datasets from the Environment Agency were used to represent the topography of the floodplain. The DTM was produced from the light detection and ranging (LiDAR) datasets obtained from an airborne mapping technique that uses a laser to measure the distance between the aircraft and the ground. The DTM represents elevation of the floodplain at regular grid intervals of 2 m. Finer resolution datasets are available; however, these provide only a small increase in accuracy and their use is computationally intensive in simulations of longer duration rainfall events in the LISFLOOD-FP model.Flood modelling and simulation involved using linked one-dimensional (1D) and two-dimensional (2D) models within the LISFLOOD-FP hydrodynamic model, which was developed at Bristol University . In LISF(c)Agent-based modelling has been used to represent SMEs and associated organizations, such as suppliers and customers, and the relationships between them in the context of a flood event. Furthermore, agent-based simulations, allied with flood simulation, have been performed to evaluate the effect of implementing flood mitigation measures on the operational resilience of SMEs to an extreme inundation event. Behaviours of agents representing SMEs have been obtained primarily from transcripts of semi-structured interviews with over one hundred SMEs from across the UK that have experienced flooding or are at risk of flooding. That is, a detailed analysis of these transcripts was undertaken manually, which revealed a variety of behaviours that SMEs may exhibit before and after a flood event. Furthermore, the conditions that would need to be in place to cause an SME to exhibit particular behaviours were gleaned from the interview transcripts along with indications of the interdependencies between behaviours. In addition, the typical duration range of each behaviour was established based on statements made by SME employees in the interview transcripts. For example, pre-flood, an SME receiving Environment Agency warnings may take action to reduce the possible damage and disruption caused by flood water entering its premises by moving equipment and raw materials to ‘safer' locations, which would prevent them from being affected. Post-flood, an SME may interact with their insurance company, suppliers, customers and other organizations that will assist in the company's recovery. Details of SME attributes and behaviours modelled, and the relationships between them, can be found in . In addiIn an agent-based simulation, for each manufacturing SME at each tick (representing a 30 min period), production capacity is determined based on the proportion of available employees and machines, the current level of raw materials, and whether or not the premises has power; note that all machines are assumed to be located at ground floor level. That is, at any simulation tick, if all employees and machines are available, sufficient raw materials are in stock to manufacture products, and power is being supplied to a manufacturing SME's premises, then production capacity is 100%. This level of production capacity is expected pre-flood, until employees evacuate the premises or unless they are relieved from production operations and used to carry out preventative actions to reduce potential damage. By contrast, during the flood event, production operations are suspended or not possible meaning production capacity is zero. Post-flood, at some point during recovery, production will be resumed and capacity increases from zero until it eventually reaches the pre-flood level of 100%, typically following a nonlinear profile as a function of the availability of employees and machines, raw material levels, and whether or not the premises has power. For each manufacturing SME, its ‘recovery' profile will be influenced to some degree by the actions undertaken pre-flood, but most significantly by the flood mitigation measures put in place aimed at preventing or minimizing the level of flood water entering its premises and the disruption to business continuity. In the agent-based simulations performed, flood mitigation measures have been categorized as structural or procedural. A list of these measures is given in §4, in which a number of simulation experiments are defined and the procedure for determining an operational resilience coefficient as a function of loss in production capacity is outlined.3.a and during the inundation event based on output from flood modelling and simulation in figure 3b–d. Furthermore, figure 3b–d provides an indication of the extent of the flooding at various times.In South West England, on 20 July 2007, two months' worth of rain fell in 14 h resulting in widespread flooding of Tewkesbury in Gloucestershire. Tewkesbury is vulnerable to flooding due to its location relative to two rivers, the Severn and the Avon, which meet in the town. Flooding lasted for approximately two weeks severely affecting the town through a combination of pluvial and fluvial flooding. Due to the large proportion of highly developed areas in Tewkesbury, a significant proportion of the rainfall resulted in fast run-off. Also, the heavy rainfall overwhelmed the drainage and sewerage systems, which led to localized pluvial flooding in the town. The prolonged intense rainfall event led to unprecedented levels of flooding as the rivers Avon and Severn burst their banks in many places on 21 and 22 July. Representations of the geographical area of Tewkesbury pre-flood are shown in figure 3©, a one-to-one mapping was enabled between the water depth at each location as it varied throughout the time frame of the flood event modelled and the precise locations of all SMEs, including the manufacturing SMEs focused on in the case study area of Tewkesbury.In the flood modelling and simulation of the extreme flood event of July 2007 in Tewkesbury, the LISFLOOD-FP hydrodynamic model was used to simulate flow propagation using the measured hydrographs of the River Avon and River Severn. Furthermore, within the hydrodynamic model, the land use and river topography datasets enabled the establishment of flow pathways in the rivers and the town of Tewkesbury. The flood was simulated from 17.30 on 19 July to 23.30 on 1 August, with the flood inundation steadily increasing and peaking on 22 July. In terms of output, the model predicted flood depth, flow velocity and inundation period. On 22 July, flood depths of up to 8.5 m in the river channel and over 3 m in the town were predicted by the simulation. As the flood gradually receded in the latter part of July, Tewkesbury essentially became an island, particularly in the High Street area. Throughout the two-week period flood simulation, water depths were recorded at half-hour intervals at all easting and northing locations within the modelled geographical environment study area. Given the modelling of this environment involved the use of the Address layer of OS MasterMapIn terms of flood model validation and calibration, the approach taken involved comparing the simulated water level obtained from the model with the measured/observed water level at Mythe Bridge in Tewkesbury over a 30-day period from 22.00 on 11 June 2007. That is, using the model, in line with standard practice, the adjustment of the channel roughness and floodplain roughness parameters was varied until the output agreed with over 90% of the observed water level measurements at Mythe Bridge. It is highlighted that data scarcity is a challenge for flood model validation. Thus, the next steps for validation of the flood model require more data from actual flood events, for example, via remote sensing.4.(a)To evaluate manufacturing SMEs' operational resilience to an extreme flood event, seven agent-based simulation experiments have been defined and performed. These simulation experiments have been defined to evaluate the effect of different sets of structural and/or procedural flood mitigation measures that an SME can put in place to improve their operational resilience to flooding. Structural measures are physical changes made to an SME's premises to prevent water inundation or lessen the damage should this happen. By contrast, procedural measures are those actions and activities an SME can undertake to safeguard business continuity as far as is possible. In (b)t5, is shown in t1, production capacity is 100% assuming all employees and machines are available, sufficient raw materials are in stock to manufacture products and power is being supplied to the manufacturing SME's premises. The period t1–t2 corresponds to the time during which an SME's employees may take action to prepare for the flood event that may start at or after t2 and end before t3. In t1 to t2, the SME's production capacity is shown to decrease nonlinearly from 100% to zero. Note that if an SME were to take no preparatory action due to employees evacuating the premises immediately, then production capacity would drop from 100% to zero in a single simulation tick. From t2 to t3, which encompasses the flood event, the SME's production capacity is zero. Post-flood, the SME will undertake actions that bring about a resumption in production capacity at t3. From this time until t4, the SME's production capacity recovers until it reaches 100%. Again, the SME's production capacity is shown to vary (increase) nonlinearly, depending on actions taken pre- and post-flood, and the flood mitigation measures put in place.In this research, the concept of operational resilience is inspired by the resilience triangle  and exteIn t1 to t2 and t3 to t4. The first integral is associated with the pre-flood preparatory actions of a manufacturing SME whereas the second integral corresponds to the post-flood recovery actions undertaken. Also, flood mitigation measures taken by an SME will influence the impact of a flood event in terms of damage to its premises and disruption to its operations. That is, flood mitigation measures will influence the characteristics of the lines from t3 to t4.In equation (4.1), the two integrals signify the nonlinearity of the functions from n sub-intervals of equal length a and b can be expressed asIn consideration of equation (4.1) and In relation to equation (4.1), which is used to determine production capacity loss, an operational resilience coefficient, 5.Each agent-based simulation experiment defined previously in In The variations in the ‘recovery' profile of manufacturing SMEs for each experiment as seen in t5 is taken as that recorded in the experiment with the greatest time taken for manufacturing SMEs to resume 100% production capacity. That is, in experiment 1, which is as expected, since in this case SMEs implemented none of the flood mitigation measures. Specifically, t5 corresponds to simulation tick 2124, which equates to a simulation duration of 1062 h or 44 working days and 6 h. Thus, for experiment 1, the time t4 and t5 are the same. Taking the same simulation duration for all experiments enables a direct comparison to be made between them in terms of the average production capacity loss of all 16 flood-affected manufacturing SMEs and the associated average operational resilience coefficient.In all experiments, the simulation time t4 corresponds to the time at which manufacturing SMEs resumed 100% production capacity; in loss (bar charts) and ORc (red dots) for each simulation experiment. In relation to t4–t1 corresponds to the time at which manufacturing SMEs' production capacity is first reduced, due to employees being occupied with taking preparatory actions or the flood water reaching their premises and/or employees evacuating the premises, through to the point post-flood when those businesses restore 100% production capacity. The period t3–t2, which includes the duration of the flood event, corresponds to the time during which SMEs have zero production capacity. The post-flood period t4–t3 corresponds to the time at which production capacity is resumed through to it reaching 100%.In consideration of c of 0.711. The difference between the operational resilience coefficients for these two experiments is 0.192, which is viewed as relatively small and is clearly related to both the severity and duration of the flood event considered. As expected, a comparison of values of In t-test was carried out at two points in time during the agent-based simulation for each experiment, namely in the recovery period at t = 1000 ticks and t = 1200 ticks. At the earlier point considered in the recovery period of SMEs (t = 1000 ticks), mean production capacity is not significantly different between experiments 2 and 3 , 2 and 7  and 3 and 7 . Similarly, at this point in the recovery period, this is the case when comparing experiments 1 and 5 . At time t = 1200 ticks in the recovery period, for experiments 2, 3 and 7 the mean production capacity remains not significantly different. In addition, at this point in the recovery period, for experiments 2 and 3 no significant difference is observed with experiments 4 and 6, which themselves are not significantly different.In order to determine if the means of one experiment output data are significantly different from another, a paired 6.A computational modelling and simulation approach has been developed and used to facilitate an evaluation of manufacturing SMEs' operational resilience to extreme flood events. The approach, which couples flood modelling and simulation with agent-based modelling and simulation, provides a means of assessing the relative impact of different types and combinations of flood mitigation measures which SMEs' may implement to limit the damage to their premises, and contents thereof, and disruption to business operations that an extreme inundation event may cause. As a case study, the 2007 extreme flood event in Tewkesbury has been modelled and simulated, and a number of agent-based simulation experiments performed with each corresponding to manufacturing SMEs having implemented different combinations of structural and/or procedural flood mitigation measures. Results suggest that structural flood mitigation measures are more effective than procedural measures in terms of enhancing the operational resilience of manufacturing SMEs. Further, the experiments performed enable an assessment of the relative effectiveness of the different combinations of measures. However, while not included in the approach developed in this research, the financial cost associated with different flood mitigation measures is acknowledged as an important factor for SMEs to consider when deciding which measures could be put in place.While recognizing the need for careful interpretation of any ABMS results, this research provides the basis of a contribution in terms of informing SMEs of the relative effectiveness of mitigation measures, and combinations thereof, and supporting small business decision-making regarding the implementation of these measures to make their premises more resilient and resistant to flooding. Furthermore, the findings of this research could provide an initial basis for SMEs to consider engaging with (a) UK Government grant schemes to fund particular mitigation measures that improve their property's resilience or resistance to flooding, and (b) the British Insurance Brokers' Association's commercial insurance scheme aimed at improving the ability of this important type of business to find suitable and affordable flood insurance. That is, in terms of resilience and resistance to flooding, this research may encourage better uptake of mitigation measures by SMEs with premises at risk of flooding, which would be recognized in terms of the cost and terms of insurance.Scope for future work exists in terms of introducing more flood mitigation measures and defining more simulation experiments, with varying combinations of flood mitigation measures. Also, SMEs from different industrial sectors could be considered as well as different geographical locations. In addition, different flood events in terms of severity and duration could be considered, as it is anticipated that these factors will influence the relative difference between operational resilience coefficients for varying combinations of flood mitigation measures. While the case study presented in this paper has focused on the evaluation of SMEs' resilience to a single flood event, it is possible that multiple flood events could occur in relatively quick succession, meaning SMEs would be faced with greater and more complex challenges. Thus, the occurrence of multiple flood events is a potential area of further work. In terms of further development of the model, potential areas for investigation include modelling and capturing the number of insurance claims, loss of staff time and the number of companies going out of business. Given SMEs have such small numbers of employees, a further aspect for inclusion in the model is the rate of return to work post-flood, which will have an impact on these firms' recovery.


Background: We set out to quantify shared genetic ancestry between unrelated kidney donor-recipient pairs and test it as a predictor of time to graft failure.  Methods: In a homogenous, unrelated, European cohort of deceased-donor kidney transplant pairs , we calculated, using common genetic variation, shared ancestry at the genic  and genomic level. We conducted a sub-analysis focused on transmembrane protein coding genes  and attempted replication of a previously published nonsynonymous transmembrane mismatch score. Measures of shared genetic ancestry were tested in a survival model against time to death-censored graft failure.Results: Shared ancestry calculated across the human leukocyte antigen (HLA) significantly associated with graft survival in individuals who had a high serological mismatch (n pairs = 186) with those who did not have any HLA mismatches indicating that shared ancestry calculated specific loci can capture known associations with genes impacting graft outcome. None of the other measures of shared ancestry at a genic level, genome-wide scale, transmembrane subset or nonsynonymous transmembrane mismatch score analysis were significant predictors of time to graft failure.Conclusions: In a large unrelated, deceased-donor European ancestry renal transplant cohort, shared donor-recipient genetic ancestry, calculated using common genetic variation, has limited value in predicting transplant outcome both on a genomic scale and at a genic level (other than at the HLA loci). A perfect HLA “match” does not guarantee a successful outcome and in individuals with zero HLA mismatches, acute rejection and early graft failure are still present3. This indicates that other, potentially genetic, factors influence graft outcome and the success of the transplant.Organ allocation is a major issue in the field of transplantation. It is vital that organs are matched in a way that facilitates the best possible outcome for the recipient and for the transplanted organ, so that the organ goes to the person for whom it will last the longest. For many decades, renal transplants have been allocated largely on the basis of preferential HLA scoring, with reports dating back as far as 1965 showing the impact of HLA matching on graft outcome4. However, it is unclear to what extent these differences are attributable to genetic, socioeconomic, and/or behavioural factors6. A recent study of donor and recipient kidney transplant pairs found that ethnically matched transplants had significantly better graft survival, when compared to non-ethnically matched pairings. However this significance disappeared when adjustment was made for clinical variables including HLA mismatch, sensitization, sex, age and cold ischaemic time7. Thus, the impact of shared ancestry between the kidney donor and recipient on graft outcome remains unclear.There are large differences in graft survival between ethnicities, with African Americans having the poorest graft survival rates8 using non-synonymous variants from transmembrane protein genes. In a cohort of 53 donor-recipient kidney transplant pairs of admixed ethnicity , this score was significantly associated with estimated glomerular filtration rate (eGFR), after correcting for HLA mismatches , donor age and time of eGFR measurement post-transplant. A similar mismatch study based on non-synonymous variation in non-HLA transmembrane and secreted protein-encoding genes also found that a greater level of mismatch between the donor and recipient associated with reduced graft survival9.Recent studies have developed distance scores based on exome sequencing data which are reported to predict graft outcome. For example, one study created an allogenomic mismatch score10, identity-by-state (IBS) and identify-by-descent (IBD) measures.The explosion of dense genotype single nucleotide polymorphism (SNP) data has allowed for the accurate measure of shared ancestry at the individual and also population level. There are a number of methods for quantifying shared ancestry including haplotype “painting”In this study, we set out to investigate the impact of shared genetic ancestry between donor-recipient transplant pairs, on graft outcome. We quantified shared genetic ancestry at the genomic level, genic level and across a specific subset of transmembrane protein encoding genes and tested these shared ancestry measures as a predictor of time to graft failure in a population of unrelated, European, deceased-donor kidney transplant pairs.11. All transplants were deceased donor grafts and paired on the basis of preferential HLA matching and recipient waiting time. Transplants in the UKIRTC cohort took place between 1981–2007. Only data on the first transplant was considered. All individuals were GWAS genotyped as part of the UKIRTC and the Wellcome Trust Case Control Consortium 3  were recruited via the United Kingdom and Ireland Renal Transplant Consortium (UKIRTC)Extended data, Supplementary methods for details)12, 2) have donated/received a renal transplant and 3) be unrelated to level of 3rd degree relative .The following inclusion/exclusion criteria were applied: participants must have 1) been of European ancestry  – seeExtended data, Supplementary methods12 for details on imputation. Details on HLA typing were published elsewhere11.Clinical predictors of graft survival were tested using STATA v13 in a Cox proportional hazards model and significant variables were included in the analysis as covariates. Acute rejection status was available for 1,099 individuals in our cohort. SeeEthics approval was granted by the Hammersmith and Queen Charlotte's & Chelsea Research Ethics Committee REC No 08/H0707/1.We quantified shared genetic ancestry between donors and recipients at a genome-wide scale using three methods.Method 1: Identity by descent (IBD). IBD here refers to the amount of shared genetic material between two individuals that is inherited from a recent common ancestor. We quantified the proportion of the genome that is IBD between the donor-recipient pairs using the PIHAT function in PLINK14. The data was pruned for linkage disequilibrium using a 1000-kb window size, 100-kb step size and r2 threshold of 0.2.Method 2: Identity by state (IBS). IBS quantifies the number of shared alleles between two individuals. Alleles that are IBS can be inherited from a recent common ancestor or shared by chance. We quantified the proportion of shared alleles across the genome between each donor and recipient pair using the DST measure in PLINK14. Data was pruned for linkage disequilibrium following the same criteria as outlined above for the IBD method.Method 3: Chromopainter. We created a mosaic of an individual’s genome from the haplotypes of all the other individuals in the dataset using Chromopainter10. We calculated the matrix of donated haplotype lengths and associated haplotype-donors, for each individual in our dataset (i.e. the “chromolength” output from Chromopainter). The correlation between the chromolength chunks  of the donor and recipient in a given donor/recipient pair was calculated using the “corr” function in Microsoft Excel (with a perfectly matched mosaic genome having a score of 1). The correlation was then used as the measure of shared genetic ancestry.R survival package (version 2.41–3) and the cox.ph function16. We analysed two different survival analysis models; in the ‘full’ model we included significant clinical predictors as covariates, in the ‘baseline’ model we excluded clinical covariates.These three measures of shared ancestry were tested against time to graft failure using a Cox Proportional Hazards Model using theUCSC Genome Browser Table Browser via the “Genes and Predictions” group on the USCS gene track17. The coordinates with a 50-kb buffer region added were used to extract the imputed genotype information for each individual in each donor recipient pair using PLINK, creating a file per genic locus. The files were pruned for LD in PLINK (“–indep-pairwise” command) using 1000-kb window size, 100-kb step-size and r2 threshold of 0.2. The PIHAT and DST scores were calculated for each of the thinned genic region files using PLINK’s --genome command. The PIHAT and DST scores for each gene were then extracted for each donor recipient pair.We examined whether shared ancestry between donor and recipient pairs at any specific gene, calculated using the IBD PIHAT and IBS DST methods, was associated with graft survival. Hg19 (human genome assembly 19) coordinates of protein-coding loci were obtained using the15. We corrected for multiple testing via the Bonferroni method. The total number of loci tested was 40,053 but greater than 50% of these were transcripts coded from overlapping regions and so we only considered independent loci  when correcting for multiple testing.PIHAT and DST scores for each gene was tested against time to graft failure, adjusting for significant clinical covariates, using R’s survival packageAs sanity check for the genic approach, we assessed whether genic shared ancestry measures could detect the known effect of the HLA on transplant outcome. As the UKIRTC dataset is composed of donor recipient pairs who were paired by preferential HLA matching and thus skewed towards pairs with fewer mismatches, we focused on the subset of transplant pairs with 0, 5 or 6 serological HLA mismatches. Time to death censored graft failure was tested against the total serological HLA mismatch measure, and against the IBD and IBS measures, in a Cox proportional hazards model using R. As this is a replication of the HLA mismatch measures, we did not apply Bonferroni correction and used a standard significance threshold of p=0.05.9. PIHAT and DST scores were extracted for these loci from the per-genic region results (see methods section 5.3). The PIHAT score was summed across all of the transmembrane genes to create an overall score. This transmembrane PIHAT score was then normalized, so the mean was 0 and standard deviation was 1. The same process was repeated for DST. The normalized transmembrane DST and PIHAT scores were then tested against time to graft failure in a Cox proportional hazards model using the survival package in R. Models were adjusted for significant clinical predictors of time to graft failure .As a subgroup analysis, we focused on the scores for transmembrane protein coding genes specifically, calculated in donor-recipient pairs using the IBD PIHAT and IBS DST measures (see methods section 5.2). The list of transmembrane protein coding was obtained using the same methods described previouslyWe also analysed the same set of transmembrane genes applying a univariate approach, where the PIHAT/DST calculated for each gene was considered separately and tested against time to graft failure as per the previous paragraph. To correct for multiple testing within this sub-group analysis, each gene was corrected for as opposed to each transcript (as some genes had multiple overlapping transcripts). In total, we corrected for 4,873 tests.9. Following the protocol as described by Reindl-Schwaighoferet al.9, we imputed the HLA eplet mismatches using HLA matchmaker. Next, using VEP we annotated the imputed genotypes. We used the DR-mismatch program9 to calculate the nonsynonymous transmembrane mismatch score. We also calculated the overall genotype mismatch score and the overall nonsynonymous mismatch score (i.e. not limited to transmembrane protein encoding genes). Matching the parameters of the analysis presented inExtended data, Supplementary Table 512 for cohort description). We carried out a Cox proportional hazards model against time to death censored graft failure of the interquartile range of the nonsynonymous transmembrane mismatch score including genome-wide mismatch score, genome-wide nonsynonymous mismatch score, HLA serological mismatch, HLA eplet mismatch, donor age, donor sex, transplant centre and IBD (using PIHAT score as measure). We also tested the nonsynonymous transmembrane mismatch score in a univariate model which was not adjusted for additional covariates.Finally, we carried out an exact replication analysis of the nonsynonymous transmembrane mismatch score which was recently reported to predict time to graft failureExtended data, Supplementary Table 112). Donor age and acute rejection at 1 year emerged from the Cox model as significant predictors of graft failure and therefore were included as covariates in our shared ancestry survival analysis.Graft failure data was available for 1,808 donor-recipient pairs in our cohort with a total of 399 failure events (death censored). The average time to death censored graft failure was 6.04 years  and average follow-up in those without a failure event was 8.87 years . In order to determine the influence of clinical covariates on time to graft failure in the UKIRTC dataset, we applied a Cox proportional hazards model  on time to death censored graft failure using a Cox proportional hazard model.Extended data, Supplementary Figure 112 for distributions of Chromopainter, IBD and IBS measures). Of these pairs, 927 had no detectable IBD relationship (i.e. PIHAT = 0) with 888 pairs having a PIHAT greater than 0. Due to the large number of pairs with PIHAT = 0, we carried out subsequent analyses on two groups; 1) those pairs who shared an IBD of less than or equal to 3rd degree relative, excluding those with no detected IBD and 2) pairs with an IBD of less than or equal to 3rd degree relative, including those with no detected IBD .These shared ancestry measures were successfully calculated on 1,815 donor-recipient pairs  or baseline models . Both IBD and IBS were highly significantly correlated with total serological mismatch scores .Having reproduced the known predictive ability of HLA serological scores, we next compared, in the same group of individuals, the IBD and IBS HLA scores, to time to graft failure in a Cox proportional Hazards model. IBD and IBS scores were both significantly associated with time to graft failure with more shared IBD, or a greater amount of IBS associated with a longer time to graft failure see. When weThe concordance statistic measures the proportion of pairs of individuals in which the individual with the higher-risk predictor had a failure event before the individual with the lower-risk predictor. We tested this statistic for the serological HLA score and the IBD/IBS scores  = 0.03; IBS across HLA concordance = 0.56, SE =0.05; IBD across HLA concordance = 0.57, SE = 0.05). This indicates that IBS/IBD per gene measures can capture known associations with genes impacting graft outcome.Extended data, Supplementary tables 9–1212).We then went on to test shared ancestry in individual genes across the entire genome. We compared the IBS and IBD measures calculated from each coding region in the genome  to the afore-mentioned outcome measures. No gene reached genome-wide significance, for either the IBD or IBS measures (seeThe HLA-A (IBD p = 0.017 and IBS p = 0.045) and DR (IBD p = 0.009 and IBS p = 0.01) loci came out in the top 5% of the distribution for the time to graft failure analysis, but did not survive correction for multiple testing (see Supplementary table 3).Extended data, Supplementary tables 11–1212).We also examined the per gene IBD and IBS scores in a baseline model which excluded clinical covariates. No single gene survived correction for multiple testing  or full models .Given previously published analysisExtended data, Supplementary tables 13 –1712).Transmembrane genes were also analysed in a univariate model, where the IBD/IBS measure for each transmembrane gene was tested against time to graft failure. None of the transmembrane genes reached significance after correcting for multiple testing  models .Finally, we went on to attempt to replicate the findings of Reindl-Schwaighoferrd degree relative, has limited value in predicting transplant outcome both on a genomic scale and at a genic level in deceased donor European ancestry renal transplant pairs. Our findings also suggest that IBD and IBS-based distance methods can be used to capture serological mismatch scores, and show comparative predictive ability.Our findings show that shared donor-recipient genetic ancestry, beyond 3rd degree relative) deceased-donor and recipient pairs is not a clinically relevant predictor of graft survival. This is an important finding as it suggests that when choosing between deceased donors and recipients and where all of North-West European ancestral background, the level of shared ancestry (beyond 3rd degree) between donor and recipient is irrelevant.Our analysis of shared ancestry at the genome-wide level indicates that, in a European-descent homogenous population, the level of shared ancestry between unrelated .19. It is probable the HLA genes would have reached genome-wide significance in our genic analysis, if we had larger numbers of donor: recipient pairs and/or a cohort of transplant donors and recipients which had not been paired on the basis of preferential HLA matching.We did not find any single gene that significantly associated with time to graft failure. This result indicates that, beyond the HLA, single gene shared-ancestry effects do not have a clinically relevant impact on graft survival. Notably, the IBD and IBS measures calculated at HLA-A and DR were found in the top 5% of genes most significantly associated with time to graft failure, but did not reach genome-wide significance. However, we found an effect of shared ancestry calculated across the HLA when we compared highly mismatched individuals for HLA serological typing, to those who were perfectly matched. We also showed a highly significant correlation between the total number of HLA serological mismatches and the amount of shared genetic ancestry calculated across the same HLA loci . This demonstrates that these shared ancestry measures can pick up clinically relevant genetic differences between donors and recipients, and indeed have potential as a proxy for serological testing. This is in line with previous studies that showed known associations with the HLA region can be picked up using IBD measures8 and genome-wide association study (GWAS) based analysis9 found that a score created via the quantification of specifically non-synonymous allelic mismatches at transmembrane and secreted proteins significantly predicted graft outcome whereas our shared ancestry measures considered all variation (i.e. including synonymous variation). We attempted to replicate the findings of the GWAS-based transmembrane nonsynonymous mismatch score9; we did not see a significant correlation between the score and time to death censored graft survival with or without adjustment for additional covariates. However, we did see the same direction of effect as the original study. Potentially, differences between the cohort in this study and the original study may explain the lack of significance in our analysis. Our cohort was an older era and so was exposed to different immunosuppressants compared to that in the original study which was a more contemporary cohort. Further analysis with additional patient cohorts is required to determine whether this mismatch score will replicate in cohorts beyond that in the original report. The previous exome study8 captured both common and rare variation, whereas our study considered common variation only. It is also possible and indeed likely that advancements in immunosuppressants are suppressing the effect of shared ancestry.Neither IBD nor IBS measures calculated across transmembrane protein coding loci were predictive of graft survival in our analysis. A previous exome mismatch studyIn a large deceased-donor European ancestry renal transplant cohort, the amount of shared genetic ancestry between a donor and recipient had limited value in predicting transplant outcome both on the genome scale and at a genic level. However, the distance measures described in this study could describe a similar amount of the variability that is captured through serological HLA typing, and so have potential as an alternative to serological testing. Although we did not detect an effect of shared ancestry on graft outcome, studies capturing rare variation as well as studies examining admixed populations may uncover an important role of shared genetic ancestry on graft outcomes.peterconlon@beaumont.ie) or Gianpiero L. Cavalleri .The data used and/or analysed in the presented study was GWAS genotype chip array data and clinical data collected as part of the UKIRTC. Due to the sensitivity of the clinical patient data and genotype data used in this study, we are unable to share the data publicly. Access can be requested by researchers at accredited institutions. Access to data can be requested by emailing Peter J. Conlon  contains the following extended data:Supplementary Tables 9–16 are available as individual DOCX files as part of the repository project.CPS, GLC and PJC designed the analyses. CPS carried out the data analyses and wrote the manuscript. GLC and PJC supervised the data analysis and manuscript writing. GML coordinated the data collection and genotyping of the UKIRTC dataset. The UKIRTC members carried out the patient recruitment, clinical data collection and provided DNA samples/genotype information for patients. All authors reviewed and provided feedback for the manuscript. Stapleton and colleagues use data on Deceased donor transplants from the UK/IR transplant registry to show that genome wide IBS/IBD do not independently associate with graft failure. They also do not find prior association with Austrian cohort data regarding total non Synonymous mismatches in genes predicted in a transmembrane or secreted location.et al, and Zhang et al, 2020 (not referenced - should be appropriately referenced)1.et al. report which was a clearly admixed cohort.The homogeneity of the patient cohort used here could be depicted using a PCA plot based on the 1000 genome data. This would show difference between this and ZhangAn IBD distribution plot will also help visualize this.Details of the genotyping method used i.e. SNP chip etc. are missing. Were SNP chip versions different across data from this large /multicenter cohort?Was imputation performed? Details of pipeline used should be provided?Why were higher levels of relatedness excluded? Including them could still bring out a role for IBD that is greater than HLA mismatches?Is HLA serological mismatch used here? Both prior reports used PCR based mismatches. While PCR based data is also referenced later - it is unclear. Could have led to differences in findings.In the correlation with HLA mismatch levels and within group comparisons the 0 vs 5/6 is shown. The role of IBS/IBD in other levels of mismatches should be tested. In these intermediate levels a greater role may be identified. Overall valuable data to report. These are important data to report from this homogenous north west European cohort. These findings are different from Reindl-Schwaighofer Is the work clearly and accurately presented and does it cite the current literature?NoIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Kidney transplantation, long term graft damage, Donor recipient genetics.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. This is an interesting study that tests the role of genetic similarity between kidney donors and recipients in predicting long-term allograft outcomes. The study has notable strengths, including a large number of genotyped donor-recipient pairs used in the analysis and a comprehensive set of genetic similarity metrics tested as potential predictors of allograft survival. The methods are well described and the statistical models appear appropriate. The results were largely negative, leading to the conclusion that the degree of DR ancestry sharing (with the exception of the HLA region) was not significantly associated with time to allograft failure. The authors appropriately discuss the fact that these findings were based on a homogenous European cohort, and might not be generalizable to more diverse or admixed populations. Overall, the paper is informative and the negative results do provide a meaningful contribution.Given that this study produced largely negative results, it would be important to provide a power analysis (estimate the probability of type II error) and discuss the range of detectable effect sizes given the cohort size, the available follow up time, and the observed event rates. The main hypothesis of the study is that genetic donor-recipient dissimilarity would increase the risk of allograft failure by increasing the risk of rejection. It would therefore be informative to also include the analysis of rejection (any type), since rejection represents a more proximal outcome, and the study may have a better power to test for this association.I am not entirely clear why the full model presented in Table 1 is adjusted for rejection events, since presumably rejection would mediate the effects on allograft survival. This model should probably be adjusted for HLA mismatch instead of rejection .It would also be informative to see the following in the supplement: (1) histograms for the distributions of the key DR ancestry similarity metrics tested as predictors in the study, (2) PCA plot for the DR cohort in relationship to major continental ancestries, (3) QQ-plots for gene-based similarity tests. Please add HGNC-approved gene symbols to the Supplemental Tables. I would also consider replacing the term “genic regions” with “gene regions”.  I do have few minor suggestions that could improve the manuscript:Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Human genetics.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Dr. Stapleton and colleagues have produced a well-structured, well-written and refreshingly honest overview of genetic analyses undertaken to assess the relationship of shared genetic ancestry and time to graft failure in kidney donor recipients.  Sufficient background information relevant to the study has been provided. The methods are thoroughly described and potential limitations of the analyses are made very clear. The results are depicted clearly and discussed in a very balanced manner.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?I cannot comment. A qualified statistician is required.Are all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Clinical geneticsI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.


Muscle sympathetic nerve activity (MSNA) is known as an effective measure to evaluate peripheral sympathetic activity; however, it requires invasive measurement with the microneurography method. In contrast, peripheral arterial stiffness affected by MSNA is a measure that allows non-invasive evaluation of mechanical changes of arterial elasticity. This paper aims to clarify the features of peripheral arterial stiffness to determine whether it inherits MSNA features towards non-invasive evaluation of its activity. To this end, we propose a method to estimate peripheral arterial stiffness  The autonomic nervous system consists of the sympathetic and parasympathetic nervous system, and the balance between these systems regulates the physical and mental state.1, respiration2, electroencephalography3, pupil4, and skin temperature5. Heart rate variability (HRV) analysis is an easy and representative method to evaluate autonomic nervous activity1. This method focuses on the periodic fluctuations present in heartbeats. The low frequency (LF) and high frequency (HF) components in HRV are known to synchronise with cardiac sympathetic/parasympathetic nervous activity and cardiac parasympathetic nervous activity, respectively1. This method, however, evaluates only cardiac autonomic nervous activity and cannot evaluate peripheral autonomic nervous activity.Numerous methods for evaluating autonomic nervous activity from various physiological responses have been proposed using information derived from heart rate6. In this method, muscle sympathetic nerve activity (MSNA) can be measured directly by inserting a needle electrode into the unanesthetised leg or arm percutaneously. Microneurography, however, has a limitation for measuring MSNA as this method requires an invasive procedure, which places additional strain on subjects. Meanwhile, our research group proposed the peripheral arterial stiffness as an index to noninvasively evaluate peripheral autonomic nervous activity8. We also showed that quantitative evaluation of human pain sensation was possible with the peripheral arterial stiffness8.Microneurography has been proposed as a representative method for evaluating peripheral autonomic nervous activity9, and the peripheral arterial stiffness reflects this contraction. Therefore, peripheral arterial stiffness may exhibit features of MSNA. Previous studies reported that the frequency components of MSNA contain information about vital signals: the approximately 1 Hz10 of MSNA synchronise with heartbeat, the 0.15–0.4 Hz component synchronise with respiration rhythm11, and the 0.04–0.15 Hz component correlates with systolic blood pressure11. The MSNA thus may have a potential to be noninvasively evaluated using the peripheral arterial stiffness if it preserves the above-mentioned components. However, this method can only estimate the peripheral arterial stiffness based on heartbeat8, and this sampling frequency is insufficient to determine whether peripheral arterial stiffness preserves the periodic components in MNSA.The MSNA has a close relationship with peripheral arterial stiffness in regulating blood pressure by contracting vascular smooth muscles7 at a high frequency was developed. The proposed method is applied to data measured during endoscopic thoracic sympathectomy surgery because it includes clear-cut fluctuations in the state of sympathetic nerve activity. Power spectral analysis of peripheral arterial stiffness was then carried out to reveal the relationship between each frequency component and the vital signals.Against the above background, this paper aims to extract the frequency information embedded in peripheral arterial stiffness. To this end, a novel method to estimate peripheral arterial stiffness12. The ETS improves sweating by clipping off the sympathetic trunk near the thoracic spine. Peripheral sympathetic nerve activity decreases after clipping the sympathetic nerve, which may reduce the response of both MSNA and peripheral arterial stiffness. Therefore, the author selected adult patients undergoing ETS as subjects. In this paper, biological signals of subjects who underwent the T3 level of ETS in the order of right and left parts were analysed. During surgery, the subjects underwent general anaesthesia and the respiratory rate was set at approximately 12 times/min (0.2 Hz) using a ventilator. Electrocardiogram, invasive radial arterial blood pressure from a catheter inserted into the right radial artery, and a photoplethysmogram from the thumb on the right hand were measured using a bedside monitor . The measured data was stored digitally at a sampling frequency of 125 Hz.Endoscopic thoracic sympathectomy (ETS) is a surgical procedure for the treatment of hyperhidrosisData from fifteen patients 16. The result of calculating AIC from pre SNB and post SNB was 14. The order of the autoregressive model was therefore set to 23. The calculated PSD was normalised by dividing with the total power in each analysis interval of each subject.Power spectral density (PSD) of peripheral arterial stiffness 17, which is a cross power spectral analysis method. The model order was determined based on Akaike’s information corrected criterion (AICC)18. The order was set to 12 because the minimised AICC calculated from pre SNB and post SNB was 19 with the significance level set at Cross power spectral density (CPSD) between the peripheral arterial stiffness The peripheral arterial stiffness (i) Heart rateThe relationship between heart rate and (ii) Respiratory rate20. The peak frequencies at HF of the peripheral arterial stiffness The relationship between respiratory rate and (iii) Systolic blood pressure21 because the LF component of MSNA is thought to induce vasomotion by sympathetic nerve activity22. Hence, the maximum MSC at LF between the peripheral arterial stiffness The relationship between SBP and Figure mentclass2pt{minimFigure Figure Figure Figure Figure Figure Figure It was confirmed that the peripheral arterial stiffness mentclass2pt{minimSpectral peaks of the peripheral arterial stiffness First, it was confirmed that the regression line between the heartbeat frequencies and the peak frequencies of the peripheral arterial stiffness Second, it was confirmed that there were spectral peaks of the peripheral arterial stiffness 23. Conversely, the MSC at LF showed significant values for most subjects in pre SNB, and it was confirmed that the peripheral arterial stiffness 11. Furlan et al. reported that the MSC at LF between MSNA and SBP during the tilt test was significantly greater than at rest11. This result indicated that common periodic oscillations in both MSNA and SBP were induced at LF because of the sympathetic hyperactivity associated with the tilt test24. Meanwhile, the power ratio at LF of peripheral arterial stiffness Finally, the peaks in the average MSC between peripheral arterial stiffness see Fig. . The MSCsee Fig. . Hence, 25. The skin sympathetic nervous activity is known to reflect in the photoplethysmogram26. Therefore, the effect of skin sympathetic nerve activity on peripheral arterial stiffness This paper clarified that peripheral arterial stiffness Supplementary Information 1.


The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. Despite having some limitations related to the need to modify the production process or to have a laboratory to prepare the samples for analysis through desktop instruments, near-infrared spectroscopy is one of the most used technologies for inexpensive analysis of foodstuffs. Thus, the miniaturization of infrared devices allows a wider industrial applicability of this technique. Information on the use of miniaturized infrared tools in the pet food sector is currently very limited, and the present research is the first attempt to predict the total and gelatinized starch, insoluble fibrous fractions, and mineral content of ground and intact dry pet food using the handheld NIR scanner SCiO™. Results from the current study revealed no significant differences in the predictive ability of the instrument using both ground and intact samples. The instrument offers a potential for screening purposes of both total and gelatinized starch, revealing the potential to monitor their content and ratio in commercial dog food on a large scale. Improvements such as widening the wavelength range is expected to increase prediction models’ accuracy.The aim of the present study was to investigate the ability of a handheld near-infrared spectrometer to predict total and gelatinized starch, insoluble fibrous fractions, and mineral content in extruded dry dog food. Intact and ground samples were compared to determine if the homogenization could improve the prediction performance of the instrument. Reference analyses were performed on 81 samples for starch and 99 for neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), and minerals, and reflectance infrared spectra (740 to 1070 nm) were recorded with a SCiO™ near-infrared (NIR) spectrometer. Prediction models were developed using modified partial least squares regression and both internal  and external validation. The best prediction models in cross-validation using ground samples were obtained for gelatinized starch  and total starch (RPD = 2.33), and S (RPD = 1.92), while the best using intact samples were obtained for gelatinized starch (RPD = 2.45), total starch (RPD = 2.08), and K (RPD = 1.98). Through external validation, the best statistics were obtained for gelatinized starch, with an RPD of 2.55 and 2.03 in ground and intact samples, respectively. Overall, there was no difference in prediction models accuracy using ground or intact samples. In conclusion, the miniaturized NIR instrument offers the potential for screening purposes only for total and gelatinized starch, S, and K, whereas the results do not support its applicability for the other traits. Product quality is one of the most important elements underpinning consumer confidence. The dog food industry pays great attention to the quality of both raw materials used in the production process and final food products in order to offer high-quality foods. Dog food products available on the market should be able to supply the digestible nutrient amounts needed to guarantee the complete provision of the animals’ nutritional requirements in each phase of their life as well as maintain their health status.Starch constitutes up to 50% of dogs’ dry diet and represents an important source of digestible energy due to the release of glucose after its digestion. Moreover, from a technological point of view, its presence is necessary to obtain the specific honeycomb structure of kibbles . Since dAccording to Van Soest et al. , fibrousFurthermore, for the manufacturing companies, it is important to monitor the mineral content of foods, for its impact on the animals’ health and growth . Both maNear-infrared spectroscopy (NIRS) is currently one of the most widespread technologies for the rapid and inexpensive analysis of foodstuffs, and it is also widely applied in pet food factories to predict the products’ gross composition in terms of moisture, protein, and fat. Its main advantages are as follows: (i) the possibility to perform the analyses of multiple compounds simultaneously in a rapid and easy way, without compromising the sample since it is a non-destructive method; (ii) the absence of chemical products usage and thus of chemical waste; and (iii) the lower analytical costs compared to other techniques . MoreoveThe objective of the present research was to investigate the feasibility of the handheld spectrometer to predict total and gelatinized starch, fibrous fractions, and mineral content in extruded dry dog food. The comparison of the predictions made on intact and ground samples aimed at determining whether homogenization could improve the predictive ability of the instrument.A total of 99 extruded dog food sealed commercial packages of 2, 2.5, and 3 kg were collected in a pet food factory in Northern Italy  and stored in the dark and at room temperature in the laboratory of the Department of Agronomy, Food, Natural resources, Animals and Environment of the University of Padova  for analysis. The dry dog food varieties used in this study were representative of the Italian pet food market in terms of composition, and they were intended for both puppy and adult dogs of small, medium, and large breed sizes. This sampling methodology was intended to maximize the ample nutrient variability necessary to develop accurate prediction models . From eaAll 99 ground samples were analyzed for macrominerals , trace minerals , NDF, ADF, and ADL. Total and gelatinized starch were determined on 81 ground samples due to the limited number of assays that could be performed from the kit used.Mineral analyses were performed by mineralization of 350 mg of each sample in closed vessels with nitric acid in a microwave digestion system . After dilution in ultrapure water to obtain a volume of 25 mL, the concentration of minerals was quantified by inductively coupled plasma optical emission spectrometry Ciros Vision EOP ; Ca was determined at 317.933 nm, while the other minerals were determined as follows: P at 178.287 nm, Mg at 285.213 nm, Na at 589.592 nm, K at 766.941 nm, S at 182.034 nm, Al at 167.078 nm, B at 249.677 nm, Ba at 455.404 nm, Cr at 267.716 nm, Cu at 324.754 nm, Fe at 259.941 nm, Li at 670.780 nm, Mn at 257.611 nm, Mo at 202.095 nm, Ni at 231.604 nm, Sr at 407.771 nm, V at 292.464 nm, and Zn at 213.856 nm [Aspergillus niger  and making up to volume with deionized water . Thereafter, the sample solution with KOH and glacial acetic acid was added with 2 mL of amyloglucosidase solution and incubated overnight at 40 °C. After cooling at room temperature, the solution was diluted with deionized water to 100 mL; then, an aliquot of 10 mL was transferred to a 10-mL glass tube, centrifuged at 2700× g for 10 min, and the supernatant filtered through a 0.45 µm filter. For the quantification of glucose, 10 µL of the filtered supernatant were injected in a high-performance liquid chromatography spectra system equipped with Aminex HPX 87H column  using an aqueous solution of sulfuric acid 0.0025 N as mobile phase and working conditions of a 0.6 mL/min flow rate and 38 °C internal temperature; a glucose standard solution as well as a calibration line were prepared. For the glucose standard solution, 200 mg of D-(+)-glucose anhydrous  were weighed in a 50-mL glass flask and made up to volume with deionized water. Subsequently, a known aliquot of the glucose standard solution for each calibration level was transferred to a 25-mL flask and made up to volume with sulfuric acid 0.1 N. Starch quantification was performed in duplicate.Total starch was quantified by an internal method of the laboratory following the directions of the Association of Official Analytical Chemists (AOAC) . In brieGelatinized starch was quantified as described by İnal et al. , using a−1), at intervals of 1 nm (13 cm −1). To reduce the incidence of anomalous reflectance values due to the heterogeneity of the surface caused by the casual arrangement of the product, spectra, which contained 331 data points, were determined in each sample 10 (intact sample) or 5 times (ground samples). Recordings were performed on 50 g of kibble placed in a plastic bag by applying the scanning head at 1 cm over the surface at different points. Then, spectra were collected through Mosaic software , converted to absorbance as log(1/reflectance), and each sample replicate was averaged for the subsequent development of NIRS prediction models.Spectra were recorded using SCiO™ , the handheld web-based wireless instrument that operates in reflectance mode scanning the NIR region, in the wavenumber range between 740 and 1070 nm . Prediction models for total and gelatinized starch, and for the fibrous fractions were developed through modified partial least squares regression analysis performing both a leave-one-out cross-validation and an external validation, whereas prediction models for macrominerals and trace minerals were developed only performing cross-validation due to the limited number of samples. The leave-one-out cross-validation uses the entire dataset and excludes a single sample in each iteration; the external validation used a subset of 75% of samples of the entire dataset as a calibration set to produce a prediction equation to be tested on the remaining 25% of samples. To create the two subsets, the full dataset was randomly divided, ensuring a similar mean and standard deviation for each trait.T-statistic value for T outliers detection to 2.5 standard error. Thus, samples with a predicted value larger than 2.5 standard error of cross-validation from the respective reference value were removed. The data underwent some combinations of scattering corrections  and several derivative mathematical treatments , cross-validation (SECrV), and external validation (SEP); the coefficient of determination of calibration (R2C), cross-validation (R2CrV), and external validation (R2ExV); and the residual predictive deviation of cross-validation (RPD) and external validation (RPDExV). The RPD interpretation was based on Williams [In order to increase the accuracy of the calibration, three passes of outliers’ elimination were done setting the critical moothing ). The deWilliams , who indTotal starch content averaged 32.26 ± 7.15% (as fed), while the mean gelatinized starch content was 21.69 ± 5.86%, leading to a ratio between gelatinized and total starch of 0.67 ± 0.11 . The insThe average raw absorbance spectra (log(1/reflectance)) of ground and intact samples are depicted in 2CrV ≥ 0.40 developed using leave-one-out cross-validation for starch, fibrous fractions, and minerals of ground and intact samples are reported in 2CrV = 0.84) and total starch , whereas insoluble fibrous fractions and minerals exhibited lower accuracies , with the only exception of S . In intact samples, the best calibration models were generated for the same traits  but with slightly lower accuracies for gelatinized starch  and total starch , and rather higher accuracies for insoluble fibrous fractions . The mineral with the most accurate prediction model in intact samples was K . The results of external validation (2ExV = 0.89) and intact samples . In ground kibbles, the lowest prediction accuracy was obtained for NDF, followed by ADL and ADF, whereas in intact kibbles, the lowest prediction accuracy was observed for ADF, followed by NDF and ADL. Overall, the best results were achieved with no scatter correction (NONE) or D, and first or second derivative as mathematical pre-treatment. Due to the unsatisfactory results, statistics of external validation for minerals were not reported.The performance of NIRS prediction models with Rlidation  confirmeDog foods are produced mainly by international companies whose formulations are based on worldwide recognized guidelines  ), so theSeveral studies on commercial dry dog foods reported similar values for starch content ,29. The The overall amount of fibrous fractions was greater than results from other studies. In particular, the average NDF was greater than the value reported by De-Oliveira et al.  for six The macro and trace mineral content chemically analyzed corresponded or slightly exceed (without overcame the safe upper limit) the recommended doses reported by the NRC . An extrThe average raw spectrum  is consiCrV > 2.0), and the sample preparation  provided similar calibration statistics for those compounds  and good for an approximate screening in intact samples , which was most likely because of the small quantities of these components and the narrow range of wavelengths in which the instrument works. However, studies performed using laboratory instruments with a greater light source and operating in a wider range of wavelengths revealed the good prediction ability of NIRS for fibrous fractions [2CrV > 0.66) for S in ground samples and for K in intact samples. No satisfactory models were obtained for any other mineral tested  using both cross- and external validation. This can be explained because, unlike organic molecules, minerals can be detected if chelated in organic complexes or indirectly if they have an effect on hydrogen bonds [In general, the quantitative prediction of total and gelatinized starch obtained by cross-validation can be considered good for a rough screening (; RPDCrV ompounds . When thractions ,45,46. Sractions , predicten bonds  and ofteen bonds , and to en bonds  and Goi en bonds  have assThe present study suggests that total and gelatinized starch can be successfully predicted using the handheld SCiO™ instrument; this opens the opportunity to monitor their content and ratio in commercial dog food on a large-scale. However, the instrument is not adequate to predict insoluble fibrous fractions as well as mineral content, except for S and K, and in general to perform quality and process controls. The miniaturization of the NIR instruments is an advantage for the pet food industry to perform fast inspections along the production chain, but to date, the performance allows only a rough evaluation of some components; improvement, such as widening the wavelength range would likely increase its accuracy. Unlike other tools, the handheld miniaturized infrared spectrometer could be used in those factories where the economic investment required to install NIR instruments for at-line predictions is not affordable.


Solanum lycopersicum L.), the structural changes that occur during the graft establishment are little understood. Using histological techniques, the present work examines the time course of changes on the anatomical structure of the graft junction in functional tomato homografts and compares it to that of heterografts and non-functional grafts. No apparent differences were detected between homo- and heterografts, showing similar tissue development. At 10 days after grafting, the cell walls of the scion and rootstock in the area of the graft junction were thicker than usual. Undifferentiated cells and new vascular tissue emerged from the pre-existing vasculature. Adventitious roots appeared mainly on the scion, arising from the pre-existing vasculature. At 20 days, more pronounced vascular tissue was visible, along with large areas showing vascular connection. At 210 days, vestiges of the changes undergone in graft development were still visible. Generally, non-functional grafts presented layers of necrotic remains and deposition of cell wall material in the cut edges, impeding the suitable scion-rootstock connection. Our results show that accurate changes in pre-existing vasculature and the cell walls of the adhesion line are crucial to the development of functional grafts.Despite the importance of grafting in horticultural crops such as tomato ( The regenerative properties of plants have been harnessed by growers since ancient times to graft together specimens of different varieties or even species . A graftMany complex biochemical and structural processes take place during the establishment of a graft, from the response to the initial wound, changes at the edges of the cut, the formation of callus tissue, the differentiation of new vascular tissue, and the connection of the vasculature ,9,10. AlSolanum lycopersicum L.) [Grafting is widely used with tomato (icum L.) , one of icum L.) ,5. The aAt 5 weeks post-emergence, the non-grafted control plants normally had a green shoot with a very large number of trichomes (data not shown). The tissues identified in the stem included a monolayer of epidermal cells, laminar collenchyma, photosynthetic parenchyma, storage parenchyma , primary phloem, vascular meristematic tissue, primary xylem and storage parenchyma (medullary) a,b. The al in ph in The success of grafting was high in homografts, approximately 85%, and moderate in the two types of heterografts, approximately 60%. The functional homografts and heterografts showed similar tissular changes and no apparent differences between them were detected. In addition, no differences were detected between the development of the two types of heterografts. At 10 days after grafting (DAG), a necrotic line appeared where the stem was cut . Later, 210 DAG in The thickness of the callus at the junction zone steadily increased from 10 to 20 DAG . AlthougAt 210 DAG f,g, the At 10 and 20 DAG, adventitious roots appeared sometimes on the scion , but theNon-functional grafts presented a similar visual and histological response, independently of the type of combination (homografts or heterografts). Non-functional grafts did not present graft union or scion-rootstock adherence, but often adventitious roots on the scion appeared . The cutThe distribution of the tissues in the scion and rootstock is essential in the correct establishment of the graft, in particular, the vascular meristematic tissue ,11. The Solanum lycopersicum and the most close species such as S. cheesmaniae), then to species from other groups of the Solanum section Lycopersicon, as Arcanum, Neolycopersicon, or Eriopersicon groups, after that to other sections of the genus Solanum and finally to other Solanaceae species [Although a difference in the success rate comparing Minibel homografts and Minibel-Marmande VR heterografts was found in our study, homografts and heterografts did not show ostensible histological differences, regardless of whether functional or non-functional grafts were considered. This lack of differences would be related to the fact that both varieties share a high genetic similarity . Therefo species ,17. ThenThe cell walls at the line of contact between the scion and rootstock commonly appeared thickened. These structures are thought to play a key role in graft establishment, taking part in the recognition and adhesion of the two sides of the graft ,22,23,24The tissues close to the cut also undergo profound changes ,10. In tWIND1 by the vascular meristematic tissue [WIND1 is involved in de-differentiation and callus formation via the activation of a signaling pathway in which cytokinins participate [The callus is generated by the de-differentiation of cells close to the wound ,28,29, bticipate ,31. Auxiticipate ,35,36,37ticipate . These tticipate ,40. Theiticipate ,25,41, vThe formation of adventitious roots by the scion is a response to the stress caused by the wound ,43. The Non-functional grafts (regardless of whether homografts or heterografts) lacked the ability to develop a complete graft union, mainly due to the presence of necrotic remnant which prevent the progress of the correct sequence of events that characterize the functional graft. In some cases, adherence between rootstock and scion appeared but it is likely that the deposition of a large amount of cell wall materials sealed the cut edges and prevent the exchange of substances. Lignin and/or suberin have been frequently suggested to be associated to wound responses ,47 that In summary, our study shows that the graft junction (whether in homografts or heterografts) undergoes modifications essential for adequate functioning of the grafted plant. The early stage of graft establishment in tomato is marked by thickened cell walls at the graft junction. The pre-existing vasculature plays an important role producing callus tissue and new vascular cells. By 10 days post grafting, some areas of xylem and phloem of the scion and rootstock are connected and functional. The scion vasculature is also the source of adventitious roots. Long after the graft is established, vestiges of the process of joining remain apparent. However, in non-functional grafts, although most of the events associated to the graft unio /n, such as the formation of callus constituted by undifferentiated cells and the differentiation of vascular cells, are present, the sealing of cut edges with the deposition of cell wall materials prevents the correct progression of the graft formation. Cherry tomato (Minibel) seeds (Mascarell Semillas SL) and RAF tomato (Marmande VR) (Semillas Batlle SA) were sown individually in 200 mL plastic pots containing 170 ± 10 mL of peat, placed on plastic trays. Watering with complete Hoagland nutritive solution, directly into the trays, was performed twice per week. The plants were grown in a growth chamber maintained at 23 ± 1 °C and with a 16 h light period.® and protected using Toogoo® silicon clips. The grafted plants were kept for 7 days in a growth chamber at 23 ± 1 °C, with a 16 h light period (≈35 µmol m−2 s−1) and with humid atmosphere (≈ 90% RH), which was afterwards gradually ventilated. Success of grafting  was calculated by morphological observation of union between rootstock and scion (see Grafting was undertaken when the plants stems were 4–5 mm thick (after 5 weeks of growth). Minibel homografts (scions and rootstocks from the same variety), Minibel (scion)–Marmande VR (rootstock) heterografts, and Marmande VR (scion)–Minibel (rootstock) heterografts were performed. Non-grafted (0 DAG) plants were used as controls. Thirty plants were prepared for every experimental condition. Scions and rootstocks were obtained by making a transverse cut below the cotyledon leaves. Cut faces were then joined, and the junctions wrapped in Parafilmcion see .After graft healing, the long-time grafts (210 DAG) were grown in a growth chamber maintained at 23 ± 1 °C and with a 16 h light period and watering with Hoagland nutritive solution, directly into the trays, was performed twice per week.Pith cells wall thickness in the adhesion line was measured at different DAG. One measure was reported per cell. Measurements of cell wall thickness were taken with ImageJ 1.52a software.At 10 and 20 DAG, grafts were observed with a stereoscopic microscope (Nikon 105 SMZ 1500) and photographed using a Nikon D4 full-frame camera and NIS-Elements F.3.2 106 software. The measures of callus thickness were taken with ImageJ 1.52a software.n = 5 per graft type and time point). Samples were fixed in formalin–acetic acid–alcohol (FAA) (24–48 h), before placing in increased ethanol series, isoamyl acetate, and finally embedded in paraffin wax. A rotary microtome was then used to make 12 µm sections which were stained with either safranin and fast green, hematoxylin and eosin, lugol, phloroglucinol, sirofluor (a fluorescent marker) or ruthenium red. After mounting (see w/v) p-formaldehyde in 0.1 M phosphate buffer pH 7.5 at 4 °C overnight. The fixed tissues were dehydrated in decreasing ethanol series and embedded in resin . The embedded samples were placed in gelatin capsules with resin and then incubated at 37 °C for 5 days to polymerize. Ultracut Microtome LKB 2088  was used to obtain semithin (1 µm) longitudinal sections. The sections were placed in slides coated with Vectabond® reagent  and cellulose staining was performed using 0.005% (w/v) calcofluor white   were taken from successfully grafted plants at 10, 20, and 210 DAG, and from unsuccessfully grafted plants at 10 and 20 DAG (USA) see . Nikon Et test and ANOVA variance analyses. They were performed by statistical software SPSS v.25 ; p-values < 0.05 were considered to be statistically significant.Cell wall and callus thickness differences were analyzed by Student