Surgical site infections can lead to serious complications and present a huge economic burden. Established wound infections can be difficult to eradicate so preventative measures, including antimicrobial dressings, are advantageous.6 colony forming units (CFU) per 10 microliter of the challenge organisms. Dressings were incubated at 35°C ± 3°C for up to seven days; total viable counts (TVCs) were performed to determine bacterial bioburden.The antimicrobial activity of an ionic silver, ethylenediaminetetraacetic acid (EDTA) and benzethonium chloride-containing (ISEB) surgical cover dressing (SCD) was compared with two other silver-containing SCDs (silver sulfate and ionic silver carboxymethylcellulose [CMC]) and a non-silver–containing CMC SCD control using an in vitro model. The dressings were tested against a range of gram-positive and gram-negative bacteria found in wound environments, including antibiotic resistant strains, using a direct inoculation simulated wound fluid (SWF) model. Dressings were fully hydrated with SWF and inoculated with a final concentration of 1 × 10All challenge organism levels remained high for the CMC SCD control and silver sulfate SCD throughout the test period. A greater than 95% reduction in TVCs was observed by four hours for all challenge organisms for the ISEB SCD, with non-detectable levels (<70 CFU per dressing) reached within 24 hours and sustained throughout the test period. Antimicrobial activity was less rapid with ionic silver CMC SCD, with 9 of 11 challenge organisms reaching undetectable levels within 6 to 72 hours.A more rapid antimicrobial activity was observed for the ISEB SCD compared with other dressings tested within this in vitro model. Centers for Disease Control and Prevention as infections that occur after surgery in the part of the body where the surgery took place.6 Silver is a broad-spectrum antimicrobial and clinical evidence has suggested that silver SCDs may reduce the incidence of SSI.7–9 However, the National Institutes of Health has estimated that 80% of SSIs10 involve complexes of micro-organisms embedded in a self-produced matrix of extracellular substance called biofilm.11 This biofilm complex provides a defense against both the immune response and antimicrobials,2 including silver,12 making it difficult to eradicate once established. Preventing SSIs and the formation of biofilm is therefore a logical route to improve patient outcomes.Many healthcare institutions have adopted preventative measures to reduce the incidence of SSIs because of their aforementioned impact. Possible preventative measures include pre-operative bathing, surgical hand preparation, antibiotic prophylaxis, and the use of silver-containing antimicrobial surgical cover dressings (SCDs).13–15 Inclusion of a carboxymethylcellulose (CMC) fiber layer, which forms a cohesive gel in contact with wound exudate to sequester and immobilize bacteria, in a silver-containing SCD may potentially reduce the risk of SSIs and protect against biofilm.16 A next-generation, silver-containing carboxymethylcellulose dressing (NGAD), which combines antimicrobial silver ions with antibiofilm agents benzethonium chloride (BEC) and ethylenediaminetetraacetic acid (EDTA), was developed to reduce bioburden further. Ethylenediaminetetraacetic acid is a metal chelating agent that has previously been shown to disrupt biofilms,17 and BEC is a synthetic quaternary cationic surfactant intended to reduce the surface tension within biofilm.19 This NGAD has been adapted into an ionic silver, EDTA, and BEC (ISEB)-containing SCD, bringing the additional antibiofilm advantages into use post-surgery to help protect against potential SSIs. Previous in vitro experiments have demonstrated that NGAD agents act synergistically, rapidly decreasing bacterial populations present in biofilm complexes.20 However, although there is evidence to support these individual features, the antimicrobial properties of the ISEB SCD against planktonic phenotype of bacteria have not yet been compared with other silver-containing SCDs available.Several foam- or fiber-based SCDs containing silver compounds are commercially available, with differing structures leading to varying levels of antimicrobial activity.The purpose of this study was to compare the antimicrobial activity of the ISEB SCD with two other commonly used silver-containing SCDs (ionic silver CMC and silver sulfate) and a non-silver CMC SCD control, using an in vitro simulated wound fluid (SWF) model inoculated with known planktonic phenotype cultures of SSI-causing bacteria.The dressings used in this study and their silver concentrations are presented in Media used during the protocol included SWF , MRD (Neogen), pre-dried Tryptone Soy Agar (TSA) plates (Neogen), and Dey-Engley Neutralizing Broth .Challenge organisms implicated in SSIs were selected, including both gram-positive and gram-negative species. Strain reference numbers, species names, their antimicrobial resistance properties and other relevant information are shown in 8 colony forming units (CFU) per milliliter. A quantitative count was performed to ensure the correct inoculum level. The dressings were then hydrated fully with 5 mL of filtered SWF and inoculated with 10 microliter of challenge organism, making the final bacterial content 1 × 106 CFU per dressing  was performed immediately after inoculation of the dressing, for further confirmation of the initial challenge level.The SCD test and control dressings were aseptically cut into 5 cm lengths, width remaining as stated for the dressing, therefore not altering wound contact area plus adhesive. Dressings were transferred to sterile 300 mL containers. Challenge organisms were prepared by dispersal into MRD to achieve a density of 1 × 10dressing . As an aInoculated dressing containers were wrapped in parafilm and incubated at 35°C ± 3°C for 2, 4, 6, 24, 48, 72, 96, or 168 hours (7 days). To ensure that dressing samples incubated for longer time periods remained fully hydrated, 1 mL of simulated wound fluid was added to the dressing containers at 48 hours before being returned to 35°C ± 3°C for the remaining relevant test period. There were three replicates for each dressing incubation period.After the relevant incubation times, the dressings were removed from the incubator and aseptically transferred to a stomacher bag containing 70 mL of Dey-Engley Neutralizing Broth  before b8 CFU per milliliter for all organisms tested except for Corynebacterium amycolatum, which struggled to increase in numbers over the test period but maintained numbers throughout  by the end of the test period  within six to 72 hours. Coagulase-negative d day 7;  whereas by day 7 .Pseudomonas aeruginosa at 2 hours; The silver sulfate SCD was unable to reduce the numbers of any of the challenge organisms inoculated onto the SCD by the end of the seven-day testing period , althoug20Overall, the ISEB SCD demonstrated rapid antimicrobial activity, within the dressing, in this in vitro SWF model, reducing a range of bacterial species to undetectable levels within 24 hours, including antibiotic-resistant strains. The rate of kill was more rapid with the ISEB SCD than with ionic silver CMC SCD, despite the only difference being the introduction of the antibiofilm agents (BEC and EDTA) in the ISEB SCD, indicating that the addition of such agents enhances antimicrobial activity. This is consistent with previous studies, although against biofilms, demonstrating that the combination of silver and the additional agents BEC and EDTA produce a synergistic effect on antimicrobial activity.2 This biofilm phenotype is difficult to remove once formed because of its recalcitrance to antimicrobial agents and the patient's own immune system.2 The ISEB SCD demonstrated antimicrobial activity against the organisms that are known to form biofilm in vivo, consistent with the performance of NGADs in in vitro biofilm models.22 Moreover, the causative organism in 70% to 95% of SSIs are human skin commensals that exist in polymicrobial microbiomes on the skin.23 Therefore, the rapid antimicrobial activity and if required, the antibiofilm properties, of the ISEB SCD may be particularly helpful in preventing the development of difficult-to-treat, biofilm-associated SSIs.The rapid kill rate of bacteria observed with the ISEB SCD may be particularly beneficial in the prevention of SSIs. Biofilms initially form from planktonic bacteria that colonize on wound surfaces and biofilm forms rapidly.®-Molnlycke, Gothenburg, Sweden) while the ionic silver SCDs use gelling CMC . As previously discussed, CMC is able to immobilize bacteria24 and may facilitate bacterial contact with the active agents within the dressing. Silicone on the other hand, is impermeable to bacteria14 and may prevent such contact. Previous studies have shown that the addition of a silicone layer can hamper antimicrobial activity, preventing the silver content in the dressing to contact and kill bacteria.15A notable finding was the improved antimicrobial activity observed with the ionic silver SCDs compared with the silver sulphate SCD, despite the latter containing a nearly 10-fold higher silver content . The dif14 Another in vitro study evaluating four silver-containing dressings found that bacterial growth with silicone adhesive wound contact layers was considerable compared with dressings with CMC gelling fiber contact layers, which had negligible or absent levels of bacteria despite having five to 11 times lower silver content.15 Together with our findings, these studies show the importance of dressing technology and design, and suggest that dressing structure rather than silver content, drives differences in antimicrobial performance. This variation in dressing design could explain the lack of consistent findings in the effectiveness of silver-containing dressings in SSI prevention.25One study reported that foam dressings with adhesive silicone wound contact layers did not prevent bacterial proliferation, while gelling fiber dressings killed bacteria in a flat bacteria-seeded-agar model.27 and fungi28 in SSIs. Additionally, as a general limitation of in vitro work, findings may not be generalizable to the clinical situation; however, the method used is an adapted variation of the American Association of Textile Chemists and Colorists (AATCC) test method 100 ,26 which is often adapted and used to test antimicrobial efficacy of dressings. Although there is evidence to suggest that the NGAD improves healing outcomes in chronic wounds,30 clinical studies on its use in the prevention of SSI have yet to be conducted. Previously, a randomized controlled trial on the ionic silver CMC SCD found a 10-fold reduction in the incidence of orthopedic SSIs7. Therefore, an important future direction is to determine whether the enhanced antimicrobial properties of the ISEB SCD over the ionic silver CMC SCD observed in the current in vitro study, translate into a greater reduction of SSI incidence in clinical studies.A limitation for this study was that the challenge organisms selected only represent aerobic organisms commonly implicated in SSIs, despite the implication of anaerobic speciesAlthough the current in vitro model demonstrates overall antimicrobial efficacy, there are other dressing features that are important in surgical wound management, including duration of wear, exudate management, pain on removal, wear comfort, and flexibility. Such features contribute to the overall performance of the dressing and can only be fully assessed in the clinical setting.In conclusion, the findings from the current study indicate that the ISEB SCD has improved antimicrobial performance in an in vitro direct inoculation simulated wound fluid model against planktonic phenotype SSI-causing bacteria compared with other silver-containing SCDs.


The compact size of iiSNP amplicons compared to short tandem repeat (STR) markers increases the likelihood of successful amplification with degraded DNA samples. Allele frequencies and relevant forensic statistics were calculated for each population group as well as the aggregate population sample. Examination of sequence data in the regions flanking the targeted SNPs identified additional variants, which can be combined with the target SNPs to form microhaplotypes (multiple phased SNPs within a short-read sequence). Comparison of iiSNP performance with and without flanking SNP variation identified four amplicons containing microhaplotypes with observed heterozygosity increases of greater than 15% over the targeted SNP alone. For this set of 1036 samples, comparison of average match probabilities from iiSNPs with the 20 CODIS core STR markers yielded an estimate of 1.7 × 10 When highly compromised biological samples are encountered, DNA template molecules may be too short for efficient amplification of any region beyond 100 to 200 bases in length using standard polymerase chain reaction (PCR) amplification. The largest PCR amplicons are most adversely affected by fragmented or inhibited samples, leading to a characteristic downward trend in detection intensity with increasing amplicon size. For the most highly compromised DNA samples, few or no STR markers will amplify in a typical human identification (HID) multiplex. In such cases, markers with smaller PCR amplicons are better suited to HID applications ,4. SinglPrior to the introduction of next-generation sequencing methods at the turn of the millennium, obtaining DNA sequences was laborious. For forensic applications, DNA sequences could be analyzed individually using Sanger sequencing , or smalWe present the sequencing results and allele frequencies for these 94 iiSNPs, and additional variation contained in amplified regions flanking the targeted SNPs, in four sets of samples representative of the US population . This work facilitates statistical calculations in investigative DNA identification efforts where the populations characterized here are relevant.Anonymous liquid blood samples with self-reported ancestries were purchased from Interstate Blood Bank  and Millennium Biotech, Inc.  or provided by DNA Diagnostics Center  as buccal swabs from paternity testing samples anonymous to NIST. A total of 1036 samples were included in this study, the same samples previously reported by our group ,29,30, dSamples were analyzed as previously described  with thePrimary data analysis was performed using Universal Analysis Software (UAS) version 1.3 (Verogen) . SNP genhttps://github.com/Ahhgust/STRaitRazor, accessed on 26 August 2022). Allele calling thresholds used with UAS data (above) were also applied to the results of this in-house analysis.As an alternate approach to the UAS, an in-house method incorporating STRait Razor v3.0 (SR3)  was usedThe finalized SNP call set was used as input for STRAF 2.0  for calc6 Markov chain steps and 1 × 105 dememorization steps on a locus-by-locus basis.Arlequin 3.5  was usede = 1/(p2 + q2), where p and q are the frequencies of the two allelic states for a biallelic SNP. For each locus, Ae was calculated for each population tested using population-specific allele frequencies from the dataset.The number of effective alleles for each locus was calculated using the equation: ARandom-Match Probabilities for individual SNP profiles were calculated using frequency data from the 1000 Genomes Project  for the A total of 97,384 genotype calls can be made for a population of 1036 samples at 94 loci. In the current study, 96,889 genotypes are reported after manual curation of the UAS genotype calls and comparison with an orthogonal analysis method  for an oACR was generally consistent across loci , with a Locus rs338882 exhibited lower average coverage for the reference allele [C] (73.45× ± 41.82×) versus the alternate allele [T] (146.82× ± 81.47×), with an average ACR of 0.51 ± 0.13 , Polymorphism Information Content (PIC), Probability of Matching (PM), Power of Discrimination (PD), Observed Heterozygosity (Hobs), Power of Exclusion (PE), and Typical Paternity Index (TPI)) calculated in STRAF  are presp < 0.05). When performing numerous pairwise comparisons, it is expected that some level of type-1 errors  will be observed due to random chance when using a significance threshold suitable for discovering linkage disequilibrium indicators. This is exemplified by the observation that, of the 913 SNP pairs with t-test p-values < 0.05, only 36 pairs are physically located on the same chromosome (p < 0.0001 only in the Caucasian category); these loci are physically separated by 190 Mb of DNA sequence on Chromosome 3.Testing for Linkage Disequilibrium in Arlequin returned 913 SNP pairs with exact T-test values below Arlequin’s default significance level  with s < 0.05 . Again, e values for all populations. The original literature from the SNPforID Consortium recommending these three loci for identity-informative purposes [e values reflect slight allele frequency variation among populations from different regions of the globe. This highlights the importance of using appropriate population frequency data for weight-of-evidence calculations.The number of effective alleles per locus is shown in purposes  characteComparison of UAS genotype calls with those generated by an in-house analysis method incorporating SR3 yielded 97,222 concordant genotype calls from 97,384 possible genotypes (99.8% concordant). Genotypes that did not satisfy minimum thresholds by both analysis pipelines were considered concordant with the UAS calls . The remaining 162 discordant genotypes were mostly no-calls by the SR3, where the presence of errors at various positions within sequencing reads excluded those reads from the count of reads corresponding to the ‘correct’ genotype call. This mechanism caused the read count to drop below allele calling thresholds in 154 cases. In eight instances, the SR3 analysis recovered genotypes that did not satisfy minimum thresholds in the UAS call set.Close inspection of the genotypes from the two analyses revealed an incorrect UAS genotype call for one sample at SNP locus rs10092491. This sample was typed by the UAS as homozygous T, whereas the sequence analyzed by the in-house analysis resulted in a heterozygous T/C genotype. The UAS interpreted 109 of 196 reads (>50%) as deletions , which dThe region containing SNP rs10092491 with an adjacent deletion represents a microhaplotype  obtained with the in-house analysis method. Further examination of the output of genotype calls from the in-house analysis indicated MHs of one or more flanking SNPs (plus the UAS target SNP) in 74 of the 94 iiSNP amplicons in the ForenSeq DNA Signature Prep Kit . Of thesobs (15% to 26%) as compared to the target SNPs alone, consistent with the published literature [obs from between 5% and 15%, while the remaining 62 loci with microhaplotypes exhibited low (<5%) or no increase in Hobs. Some microhaplotypes were observed at low frequency; 36 loci had singleton observations  representing private variation which had negligible impact on Hobs in this study.Of the 74 loci with microhaplotypes identified, four microhaplotypes associated with target SNP loci rs876724, rs1109037, rs10776839, and rs2830795  exhibiteterature ,21. Anot−38) were approximately four orders of magnitude lower (more discriminating) than the RMP values calculated from the 20 CODIS core sequence-based STRs (mean = 2.36 × 10−34). Further, the 94 iiSNPs and sequence-based STRs outperformed length-based STR RMP calculations (mean = 1.02 × 10−28) by ten and six orders of magnitude, respectively . The assay exhibited mostly uniform coverage for heterozygous genotype calls (ACR). Two loci had frequently imbalanced allele coverage: rs6955448 and rs338882.e) in all populations in the study. Analysis of Ae values  in the short homopolymer adjacent to the target SNP locus rs10092491. This ostensibly caused misalignment by the UAS analysis algorithm, resulting in an incorrect homozygous genotype call. While this low-frequency deletion was observed in only one sample in this population study of 1036 individuals, the presence of a high number of reads interpreted as deletions could serve as an indicator of this or similar artifacts, which may not be automatically flagged by the UAS.Flanking region variation comprising microhaplotypes within the iiSNP amplicons in the ForenSeq DNA Signature Prep Kit suggests the possibility of extracting more information from the kit’s SNP content by analysis of the full sequence string. Microhaplotypes associated with target SNP loci rs876724, rs1109037, rs10776839, and rs2830795, are likely to routinely provide additional information. Some flanking variation seen at low frequency may be of benefit to kinship analysis. The full complement of 94 biallelic iiSNPs produces extremely low random-match probabilities, making complex additional analyses beyond the UAS optional. The iiSNP random-match probabilities are comparable to values calculated for sequence-based alleles of STRs, both of which outperformed length-based STRs by several orders of magnitude in this study.The NIST 1036 sample set was used here to characterize performance of the iiSNP content of the ForenSeq DNA Signature Prep Kit in terms of technical performance, population genetic parameters, and direct comparison with RMP values from STR markers by length and sequence. In the absence of corroborating genotype data for the 94 iiSNP loci, we used a parallel analysis method to improve the accuracy of genotype curation and to provide frequency information for sequence variation in flanking regions of the amplicons. The use of the NIST 1036 sample set in this study adds to the extensive forensic marker information available for these samples and maintains their relevance in facilitating technology transition.


PIEZO1 coding variants with protective effects were identified in the NEIGHBOR dataset: R1527H,  and a variant that alters a canonical splice donor site, g.16-88737727-C-G Hg38 . Both variants showed similar effects in the UK Biobank and the R1527H also in the FinnGen database. Several common variants also reached study-specific thresholds for association in the NEIGHBORHOOD dataset. These results identify novel variants in several mechanosensitive channel genes that show associations with POAG, suggesting that these channels may be potential therapeutic targets.Although glaucoma is a disease modulated by eye pressure, the mechanisms of pressure sensing in the eye are not well understood. Here, we investigated associations between mechanosensitive ion channel gene variants and primary open-angle glaucoma (POAG). Common  single nucleotide polymorphisms located within the genomic regions of 20 mechanosensitive ion channel genes in the K2P, TMEM63, PIEZO and TRP channel families were assessed using genotype data from the NEIGHBORHOOD consortium of 3853 cases and 33,480 controls. Rare  coding variants were assessed using exome array genotyping data for 2606 cases and 2606 controls. Association with POAG was analyzed using logistic regression adjusting for age and sex. Two rare  Intraocular pressure (IOP) is the only modifiable risk factor, and is the target of current medical and surgical approaches for glaucoma treatment1. Despite the known importance of IOP in disease progression, we only have limited understanding of the proteins and molecules that regulate IOP, and the mechanisms by which elevated IOP leads to RGC loss. As the primary sensors that mediate many responses to mechanical signals2, mechanosensitive ion channels may play a role in both IOP regulation and the pathologic responses of RGCs to IOP.Primary open-angle glaucoma (POAG) is a progressive, neurodegenerative disease leading to loss of retinal ganglion cells (RGCs) and irreversible blindness4, and the validation of the TRAAK/TREK two-pore domain K + (K2P) channels and TMEM63  channel families as mechanosensitive6. In addition, many members of the TRP  channel family have been implicated in sensing pressure and stretch in mammals7, including TRPV19, TRPV210, TRPV411, TRPC113, TRPC314, TRPC515, TRPC617, TRPA119, TRPP120, TRPM321, TRPM422 and TRPM723. Mechanosensitive channel families play diverse physiological roles in human health and disease, ranging from touch, blood-pressure sensing and hearing28. However, their roles in the eye are not entirely clear. Several in vitro and mouse studies have suggested that mechanosensitive ion channels may play a role in glaucoma, either by regulating aqueous humor outflow and IOP37, or by modulating RGC survival41. However, clinical evidence in humans implicating the role of mechanosensitive channels in glaucoma is lacking.In recent years, significant advances have been made in our understanding of mechanosensitive ion channels, including the discovery of the PIEZO family of mechanically activated channelsIn this study, we surveyed mechanosensitive ion channel genes in the K2P, TMEM63, PIEZO and TRP channel families and asked whether common and rare genetic risk variants in these genes are associated with POAG using data from independent human genetic datasets.KCNK2 (TREK1); rs8016340, TMEM63C; rs3124515, TRPM3; and rs34419652, TRPV2). The TRPV2 SNP is an expression quantitative trait loci (eQTL) in at least one tissue type in the Gene-Tissue Expression (GTEx) database, suggesting that this SNP can impact gene expression. Two SNPs reached the significance threshold for HTG  and 4 SNPs for NTG . We next investigated association for these SNPs and glaucoma phenotypes in FinnGen. While none of these SNPs reached nominal (P < 0.05) significance for disease association, two SNPs showed consistent direction of effects including rs34419652 (TRPV2 and POAG) and rs2026109 (TRPM3 and NTG)  with minor allele frequencies (MAF) greater than 5% in individuals with European Ancestry located within the genomic regions harboring the genes of interest including 50 Kb upstream and downstream of the gene to capture regulatory elements. Table CNK2 TREK; rs80163DNA variants impacting protein structure (coding variants), while often rare in populations, can have large effects on human traits and disease. To evaluate potential roles for protein coding variants in the mechanosensitive genes in POAG, we evaluated rare (MAF < 1%) variants effecting protein structure  using exome array data available for two of the NEIGHBORHOOD cohorts, NEIGHBOR and MEE .TRPC1, has interesting evidence of association (P = 6.34E−3) with POAG in the UK Biobank  using SKAT-O and only missense alleles . This allele is enriched in the Finnish population and the direction of effect was consistent in FinnGen  and also in the UK Biobank  . The distribution of this variant also suggests protective effects in POAG  and the direction of effect was also consistent in the UK Biobank    that showed nominal association with POAG in the NEIGHBOR and MEE samples . This variant also showed consistent evidence of association with POAG in the UK Biobank and also in FinnGen (Table TRPA1 (A122V) was also nominally associated with POAG in the NEIGHBOR and MEE samples . However, this variant had the opposite direction of effect in the UK Biobank   and a variant that alters a canonical splice donor site (genomic location 16-88737727-C-G Hg38). These variants also showed similar effects in the UK Biobank and the R1527H also in the FinnGen database. A PIEZO1 gain-of-function polymorphism (e756del) common in African Americans was previously not found to be associated with glaucoma phenotypes44. It is unclear if the two alleles we identified confer gain or loss of function. Future studies are needed to elucidate the effects of these alleles on channel function.Two rare PIEZO1 and PIEZO2 genomic regions showed interesting associations with NTG and POAG respectively, although neither of these SNPs had evidence of association in the FinnGen dataset.Common noncoding SNPs located in the 43 shows that PIEZO1 and PIEZO2 are expressed in both the ocular anterior segment and the retina, with strongest expression in the lymphatic endothelium, recently recognized as contributing to Schlemm’s canal function45. Previous in vitro studies have implicated PIEZO1 and PIEZO2 in aqueous outflow regulation. PIEZO1 activity in trabecular meshwork cells has been proposed to increase conventional aqueous ouflow35. In contrast, modulating PIEZO2 expression in iridocorneal tissues does not affect the conventional outflow pathway or IOP, but may affect unconventional outflow pathways or aqueous humor production36. PIEZO1 and PIEZO2 are also expressed in astrocytes of the optic nerve head46. PIEZO1 has been suggested to contribute to astrocyte reactivity47, and PIEZO2 expression in the optic nerve head was upregulated after transient IOP elevation46. Future studies are needed to fully elucidate the roles of PIEZO1 and PIEZO2 in different ocular tissues.Published single-cell and single-nucleus RNA sequencing dataP < 0.05) in the NEIGHBOR and MEE samples were also found in TRPA1 (A122V) and in TMEM63B (V307M). However, neither of these were associated with disease risk in the UK Biobank or in the FinnGen dataset. The TMEM63B variant did show consistent direction of effect in both the UK Biobank and in FinnGen. TMEM63B is expressed in retinal ganglion cells . A TRPV2 SNP (rs34419652), an eQTL, was significantly associated with POAG risk in NEIGHBORHOOD and showed a consistent direction of effect in FinnGen. A TRPM3 SNP (rs3124515) was significantly associated with POAG in NEIGHBORHOOD. A KCNK2 (TREK1) SNP (rs2841593) was associated with POAG risk in the NEIGHBORHOOD dataset, although this result did not replicate in FinnGen. KCNK2 has been suggested to sense mechanical stretch in the trabecular meshwork and regulate IOP30. The TRP channel genes are expressed in both the anterior segment and the retina  reached threshold significance for NTG in NEIGHBORHOOD.Multiple in vitro and animal studies have also suggested roles for TRPV1 and TRPV4 in glaucoma pathogenesis, including roles in IOP regulation56. Nonetheless, loss-of-function mutations in humans suggests their involvement in mechanosensory processes57.We selected to investigate a subset of TRP channels that have been implicated in mechanosensation in this study. It remains controversial whether these channels are directly or indirectly activated by mechanical forces43  with exome array data to assess rare coding variation. A strength of our study is that the cases and controls have had clinical examinations. While the sample size is relatively large, it is also potentially limiting for very rare variants and for common variants with small effects. For replication, we used two additional independent datasets: FinnGen, a large population dataset with both common and rare variant association results for a range of glaucoma phenotypes, and the UK Biobank, also a population dataset with glaucoma association results for rare coding variants derived from whole exome sequence data. A limitation of both the FinnGen and the UK Biobank datasets is that glaucoma classification is based on diagnosis codes, and for the UK Biobank also self-report. This may create some variability in glaucoma diagnosis. Another limitation of our analysis is that we used exome array data for assessing rare coding variants. Because the exon array is comprised of selected rare coding variants, it is not equivalent to the full set of variants that can be identified by exome sequencing. Further evaluation of the genes of interest identified in this study using whole exome or whole genome sequencing would be of interest. It would also be valuable to include ethnically diverse populations in future studies.24. We find novel variants in several mechanosensitive ion channel genes that show interesting associations with POAG. Future functional studies are warranted to determine the effects of these variants on channel function, as well as on glaucoma phenotypes.We surveyed 4 large mechanosensitive ion channel families—K2P, TMEM63, PIEZO and TRP—to discover associations between genetic variants in these genes and POAG60. Briefly, the NEIGHBORHOOD dataset includes eight independent datasets with a total of 3,853 cases and 33,480 controls. A harmonized POAG definition was adopted across these data sets based on the following criteria: (1) open anterior segment angles, (2) reproducible glaucomatous visual field loss on reliable tests or (3) an eye with cup-disc ratio of at least 0.7 with one visual field showing glaucomatous loss, and (4) no identifiable secondary cause for optic nerve disease. Elevated intraocular pressure (IOP) was not a criterion for POAG definition, but if present, there had to be no secondary causes on anterior segment examination.NEIGHBORHOOD case and control recruitment and definitions have been reported previouslySixty-seven percent of cases had a history of elevated IOP (≥ 22 mm Hg) measured in a clinical setting and were classified as HTG (high-tension glaucoma). Cases with IOP < 22 mm Hg (without treatment) measured in the clinic at the time of study enrollment were classified as NTG . Cases undergoing IOP-lowering therapy at the time of enrollment were included in the HTG group if they had a documented history of IOP > 22 mm Hg prior to treatment, and cases undergoing IOP-lowering therapy at the time of enrollment were included in the NTG group if they did not have recorded pressures > 22 mm Hg before treatment. Pretreatment IOP measurements were not available for all cases.58. For the GWAS case and control samples were genotyped on Illumina 660W , Affymetrix 500 K, Affymetrix Mapping 5.0, or Affymetrix 6.0 arrays . The genotype imputation was based on 1000 Genomes panel (March 2012). For each dataset, age, sex, and study-specific principal components were adjusted in logistic regression models using ProbABEL61. In the meta-analysis, inverse variance weighted method was performed in METAL (2011-03-25 release) with genomic control correction62. Association analyses were done for POAG overall as well as the HTG and NTG subgroups58.Association data for SNPs located within genomic regions that contain the selected mechanosensitive channel genes was extracted from the NEIGHBORHOOD GWAS dataP value for association was selected as representative of the overall result for each genomic region. We used a p value correction for the number of genomic regions examined to determine statistical significance (P = 0.05/20 = 0.0025).To examine the NEIGHBORHOOD association results for genomic regions that include the mechanosensitive genes of interest, we extracted data for all SNPs located within the genomic region that included the gene as well as 50 Kb on both the 5’ and 3’ ends of the gene of interest. We did not include TRPC5 because it is located on the X chromosome and the X chromosome was not included in the NEIGHBORHOOD GWAS analysis. The SNP with the smallest https://www.gtexportal.org/home/) was used to identify SNPs that are expression quantitative trait loci (eQTLs) and hence may influence expression levels of the genes of interest.The Gene-Tissue Expression (GTEx) database  and high (≥ 95%) concordance with previous Illumina 660 K Beadchip genotypes59 where available (about 80% of samples). Recorded sex in the clinical records was verified with genotyped sex by two criteria: mean fluorescence intensity on the X and Y chromosomes, plus genotype heterozygosity on the X chromosome and call rate on the Y, allowing male and female samples to have heterozygous X-linked and successful Y-linked genotypes, respectively. Samples were tested for pairwise relationships and unexpected duplication using KING64, testing overall genomic sharing by robust kinship estimation, and proportion shared 0, 1 and 2 alleles identical by descent under the assumption of population homogeneity.2606 cases and 2606 controls from the NEIGHBORHOOD NEIGHBOR and MEE cohorts were submitted to the Center for Inherited Disease Research (CIDR) for genotyping using the Illumina HumanExome BeadChip . Illumina Genome Studio  and PLINK65, including representative HapMap CEU, YRI, CHB and JPT samples as reference populations. A principal components analysis was conducted using over 52,040 independent (pairwise r2 < 0.1), common (MAF ≥ 0.005) SNPs and the smartpca program in EIGENSOFT to detect finer population structure. Of the first 20 principal components, the first, sixth and eighth were significantly associated (P < 0.05 by logistic regression) with POAG status.European ancestry was verified from the first two principal components derived from genotypes at 9000 ancestry-informative markers by means of the SNPweights programP > 10−6 by Fisher exact test). Genotype clustering was confirmed for rare (MAF < 0.02) variants using genotype calls from zCall66 run with a stringent Z-score threshold of Z = 21 for calling heterozygous genotypes, from a GenomeStudio report containing genotype calls and X and Y intensity values as input. Every rare SNP with two or more additional heterozygous calls by zCall than by GenCall was reviewed in Genome Studio, and, if necessary, cluster locations were adjusted manually.Initial QC screens for markers included call rate (≥ 98%) and consistency with Hardy–Weinberg proportions  less than 1% and CADD (Combined Annotation Disruption Depletion) scores of > 15. A CADD score of 15 indicates that the variant is in the top 5% of deleterious alleles within the human genome69 (https://app.genebass.org/) and association analyses using genome-wide genotypes from FinnGen (https://r8.finngen.fi/).GWAS and exome array association results were compared to association analyses completed using exome data from the UK Biobankhttps://spliceailookup.broadinstitute.org/) was used to predict splicing alteration as a consequence of PIEZO1 canonical donor splice variant (16-88737727-C-G).Splice AI (Supplementary Tables.


How cells make decisions is one of the great mysteries of life. Understanding the molecular mechanisms regulating cell fate decisions is key to manipulating cell behavior to produce safe cell therapy products used for gene editing and transplants. Cell fate decisions, including proliferation, apoptosis, differentiation, self-renewal, and migration are regulated by signals from the microenvironment and the cellular state at the time when signals are received. Both environmental signals and cellular states are dynamic and change constantly creating heterogenous cellular responses of otherwise homogenous cell populations . ChangesTreichel and Filippi review the role of the cell cycle in hematopoietic stem cell (HSC) fate decisions and discuss evidence that HSC fate and cell cycle progression are coupled. HSCs are mostly quiescent and only divide occasionally to generate progeny when needed. After division HSC daughter cells can either retain stem cell properties and return to dormancy and/or continue to divide to differentiate into mature blood cells. However, not all HSCs are the same and their function can be stratified based on cell cycle kinetics and their divisional history. As HSC function declines progressively with an increasing number of past divisions, HSC fate decisions seem to be inherently linked to the cell cycle (Treichel and Filippi discuss and summarize recent insights that shed light on this relationship and highlight evidence that provides important clues for future research:ll cycle . HoweverHigh HSCs enter the cell cycle faster than CDK6Low HSCs (1) HSC exit from quiescence is regulated by the CDK6/cyclin D complex as CDK6Low HSCs , 2) HSC Low HSCs , and 3) Low HSCs .Oses et al. focused on the cell cycle-dependent localization and redistribution of OCT4, SOX2, and NANOG during PSC differentiation. They hypothesized that the S-phase functions as a window of opportunity to execute changes in chromatin in cells that received differentiation cues in G1. Using live cell imaging of fluorescent reporter for OCT4, SOX2, and HP1α the authors quantified how OCT4 and SOX2 condensates redistribute during cell cycle progression. They specifically focused on transcription factor redistribution in S-phase using the cell cycle reporter PCNA that can distinguish early-, mid-, and late S-phase. Oses et al. discovered that in response to differentiation signals in G1 pluripotency transcription factors redistribute during the early-S to mid-S transition. Although further work is required, this work suggests that the early S-phase is a critical time window when chromatin remodels to execute fate decisions.The original research provided in this Research Topic further explores the relationship between cell cycle and cell fate determination. Work in pluripotent stem cells (PSCs) identified the G1 phase of the cell cycle as the critical “window of opportunity” when cells are sensitive to signals that induce changes in gene expression required for differentiation. PSCs in G1 respond to differentiation cues whereas cells in S or G2 phases do not respond until the following cell cycle . During Jiang et al. investigated how the Fibroblast Growth Factor Receptor 1 Oncogene Partner (FOP) regulates cell cycle progression. FOP is a centrosomal protein involved in microtubule anchoring, ciliogenesis, and cancer development. Primary cilia are antenna-like organelles formed by microtubules, which are present in quiescent cells (G0 phase) and are resorbed when cells re-enter the cell cycle  during division. During division, proper mitotic spindle assembly and function are critical for faithful chromosome segregation into the two daughter cells and therefore cell cycle progression. The mitotic spindle is responsible for the accurate segregation of chromosomes and consists of microtubules, motor proteins, and microtubule-associated proteins, including HURP, a spindle-assembly factor that bundles and stabilizes kinetochore fibers (Didaskalou et al. identify several novel HURP interaction partners, show HURP interacts with distinct complexes in metaphase, and demonstrate that its spatiotemporal dynamics depend on phosphorylation at Ser627.e fibers . HURP isUnderstanding the mechanisms underlying fate decisions will improve our understanding of stem cell function and differentiation. This knowledge will allow us to manipulate cell fate decisions to produce high-quality cell therapy products at scale. Recent research presented in this Research Topic and elsewhere suggests that cell fate decisions are intrinsically linked to the cell cycle and events during cell division . Despite


Geochronology indicates a rapid transition (tens of Myrs) from primary to secondary crust building on the Moon. The processes responsible for initiating secondary magmatism, however, remain in debate. Here we test the hypothesis that the earliest secondary crust (Mg-suite) formed as a direct consequence of density-driven mantle overturn, and advance 3D mantle convection models to quantify the resulting extent of lower mantle melting. Our modeling demonstrates that overturn of thin ilmenite-bearing cumulates ≤ 100 km triggers a rapid and short-lived episode of lower mantle melting which explains the key volume, geochronological, and spatial characteristics of early secondary crust building without contributions from other energy sources, namely KREEP . Observations of globally distributed Mg-suite eliminate degree-1 overturn scenarios. We propose that gravitational instabilities in magma ocean cumulate piles are major driving forces for the onset of mantle convection and secondary crust building on differentiated bodies. Overturn of late stage lunar magma ocean cumulates triggers a rapid & short-lived episode of lower mantle melting that explains the key volume, geochronological, & spatial characteristics of the earliest secondary crust on the Moon (Mg-suite). These concepts were largely developed through exploration of the Moon, and its rock record still provides the most direct evidence for magma ocean and CMO epochs. Here the lunar magnesian-suite of samples stand out . Their forsteritic olivine composition anchors the Mg-suite mantle source to initially deep-seated lunar magma ocean (LMO) cumulates, and their presence within the primary lunar crust demands mobilization of said deep-seated cumulates toward the surface via CMO7. Geochronology further indicates that Mg-suite petrogenesis, and by extension possibly CMO, occurred near-contemporaneously with primary lunar crust solidification9. Thus, the Mg-suite plays a pivotal role in unraveling the magmatic transition from primary to secondary crust building on the Moon. Despite these critical links to early lunar evolution, a lack of consensus remains regarding the operative mechanisms responsible for generation of early secondary magmas and their global extent13.Akin to the theory of plate tectonics on Earth, the magma ocean and cumulate mantle overturn (CMO) hypotheses work in concert as the guiding paradigms for the formation and redistribution of mantle and crustal material on terrestrial bodies10. The KREEP signature observed in Mg-suite samples is surprising because the formation of KREEP is tied to the final stages of LMO crystallization, contrasting with the primitive origins demanded by their major element chemistry. Determining the role of KREEP during Mg-suite petrogenesis is important because its high concentrations of U, Th, and K make KREEP a major source for radiogenic heat in the magmatic evolution of the Moon15. KREEP-induced melting was recently proposed to be the primary mechanism for explaining the observed lunar crustal dichotomy12, potentially determining the production and distribution of Mg-suite magmatism6.The Mg-suite samples returned by the Apollo missions are confounding because they contain elevated concentrations of incompatible elements thought to be associated with a KREEP component 20, geochemical models demonstrate no need for KREEP to produce Mg-suite parental melts derived from primary LMO cumulates11, and remote sensing observations identify candidate Mg-suite locations across the lunar surface23, far beyond the Procellarum KREEP Terrane (PKT) where KREEP appears most concentrated. If KREEP is not a primary driver of Mg-suite petrogenesis, CMO would rise as a central geologic process for initiating secondary crust building on the Moon.Mounting lines of evidence now call into question the importance of KREEP during Mg-suite petrogenesis. KREEP-poor lunar meteorites with a chemical affinity to Mg-suite are documented16, and modern dynamical models of early mantle convection24 identify overturn timing as a critical component to cementing a CMO origin for Mg-suite. However, the abundance, timing, and spatial extent of lower mantle melting during CMO has yet to be fully quantified. Moreover, the last decade has delivered advances in both geochronology and global mineralogical analysis of the lunar crust that present new challenges to the CMO hypothesis and place new constraints on Mg-suite petrogenesis.KREEP-free geochemical links between Mg-suite and CMO have been recently forwarded30. Primary crust samples 60025, 62237, and lunar anorthositic meteorite Yamato 86032 provide a weighted average age of 4361 ± 21 Ma from the Sm-Nd isotopic system. Concordance with multiple chronometers  has been established for 60025, which yields a tightly constrained age of 4360 ± 3 Ma. The most reliable ages determined for secondary Mg-suite samples 15445 (4332 ± 79 Ma), 67667 (4349 ± 31 Ma), and 78238 (4334 ± 34 Ma) obtained via the Sm-Nd isotopic system yield a median of 4340 ± 9 Ma30. Samples 67667 and 78238 also yield concordant Rb-Sr ages 25 and 78238 further yields a concordant 207Pb/206Pb age (4332 ± 18 Ma)9, indicating a record of magmatic emplacement and crystallization. These ages are concordant with the whole rock isochron age for the Mg-suite of 4348 ± 25 Ma, which includes samples from Apollo 14-1730. The dataset for both ferroan anorthosites (FAN) and Mg-suite samples is small and emphasizes the need for future geochronological investigations and additional sample return missions. Nevertheless, petrologic context requires that the primary lunar crust formed prior to secondary Mg-suite intrusions, and the most robust data above imply these two events were separated by only tens of millions of years or less. Using the weighted average age of FAN and the whole rock Mg-suite isochron above, the maximum disparity between FAN (4361 + 21 = 4382 Ma) and Mg-suite (4348 − 25 = 4323 Ma) dictates that CMO-driven origin models must produce secondary crust building within ~59 Myrs after primary crust formation. Further, the small variance associated with the whole rock isochron Mg-suite age itself (± 25 Myrs) requires that initial secondary crust building was short-lived, or ≤ 50 Myrs in duration.First, geochronological work identifies concordant dates for putative primary lunar crust and secondary Mg-suite samples3 data  to Mg-suite samples35. Outcrops of pink spinel anorthosites along with olivine- and orthopyroxene-rich exposures (major mafic constituents of Mg-suite rocks) are observed in fresh and undisturbed crater central peaks across the lunar surface23, indicating excavation of pre-existing crustal material. From these studies, the Mg-suite appears to be broadly distributed across the Moon and not isolated within a single regional terrane . The limited abundance of Mg-suite lithologies in the lunar crust therefore constrains the extent of melting in associated petrogenetic models.Second, combined petrological and reflectance spectroscopy studies have linked orbital detections of pink spinel anorthosites from Mane Fig. . The pre37 to examine the spatial and temporal aspects of mantle melting produced by the upwelling return flow of primary magma ocean cumulates in response to CMO. We advance the existing geodynamic model by quantifying the timing and extent of lower mantle melting and integrating available data from geochronology, petrologic studies, and orbital spacecraft, to determine if (i) CMO-induced decompression melting of the lower mantle is capable of producing sufficient volumes of Mg-suite material, (ii) the magmatic duration of CMO-induced melting is consistent with the small variance observed in the most reliable Mg-suite crystallization ages, and (iii) the onset of CMO-induced melting can reconcile the apparent rapid transition from primary to secondary crust formation on the Moon. The spatial distribution of melting is then evaluated to test whether (iv) a CMO origin can simultaneously satisfy the observed extent of global Mg-suite exposures. In so doing, we identify physical properties of lunar CMO that ultimately satisfy modern observations of early secondary crust building.Taken together, the emerging picture is that the Mg-suite formed near contemporaneously with primary FAN production during a short magmatic interval, is broadly distributed across the Moon, and constitutes a modest fraction of the lunar crust. Here we employ a modern three-dimensional mantle convection model37 and test the effects of ilmenite-bearing cumulate (IBC) thickness and viscosity contrast between the IBC layer and underlying mantle. Each simulation begins with a model Moon consisting of five layers from bottom to top: core, lower mantle (Mg-suite source), upper mantle, IBC layer, and crust. Our lower mantle is ~3% denser than the upper mantle  assumes an initial temperature profile equivalent to the peridotite solidus. The peridotite solidus also approximates the calculated effective solidus (~1647 °C at 4 GPa)11 of the experimentally determined6 bulk lunar lower mantle (Mg-suite source), which is further consistent with calculated mantle potential temperatures (>1600 °C) at the time of Mg-suite formation45. For these reasons the peridotite solidus serves as both our initial temperature profile of the mantle and its effective solidus in Runs 1–11. The local production of lower mantle melting in response to IBC-driven cumulate overturn is then solved using parameterized equations benchmarked by previous work46. Additional runs were performed testing the effects of both cooler and hotter initial temperature profiles on magmatic timing and melt volume, and these are also summarized below. Further details of our model inputs and justifications for explored parameter space are included in our supplementary information.We investigate the thermochemical evolution of density-driven cumulate mantle overturn and convective return flow of the lower mantle using a numerical three-dimensional model of spherical geometry36. The total volume of decompression melt derived from the lower mantle during IBC-driven cumulate overturn is then converted to volume percent of the lunar crust to compare with the natural observations  is defined by the estimated amount of Mg-suite material within the lunar crust, or ~6–30 vol.% of the total lunar crustons Fig. . The ref30), or ≤50 Myrs duration  is defined by the estimated duration of Mg-suite magmatism based on concordant dating of Mg-suite samples. Here we define the magmatic duration of Mg-suite using the variance of the whole rock isochron  considers the interval of time between primary and secondary crust building. This constraint is defined by the maximum disparity between primary FAN and secondary Mg-suite ages (including their variance), or ~59 Myrs30 Fig. . In this30 Fig. . The tim3 data23, 85 contained evidence for Mg-suite material. Criteria for Mg-suite material was defined as multiple observations of pink spinel or olivine (or both) using multi-temporal images, and/or the observation of orthopyroxene in the absence of clinopyroxene . Given that 85 out of 164 total central peaks contained spectral signatures consistent with Mg-suite material, we determined an exposure proportion of 0.52 for the lunar surface. Our selection of this dataset23 is based on their extensive search of craters across the lunar surface that have excavated pre-existing crustal material  ranging from near-surface depths to the crust-mantle boundary, and their use of a common approach for mineral identification. Our model does not capture magmatic emplacement depths, but previous work34 demonstrated that Mg-suite primary melts can reach levels of neutral buoyancy throughout the crust, consistent with the remote identifications used here. To make the comparison between natural observation and model, we randomly sample the surface of our models 164 times to replicate the number of craters investigated. Each sampling location is a synthetic crater, and the area sampled by the synthetic crater is determined by the scaling relationship between central peak and crater diameter48 using the diameters of the craters reported23. If melt from the lower mantle is present in a sampled area, we tally an identification of Mg-suite  in 1% increments  and run the same 1000 random cratering iterations for each percentage step. The resulting data can be taken to evaluate the spatial effects on global melt distribution within a system of low degree (MDT = 2–3%), moderate (MDT = 4-5%), and higher degrees of partial melting (MDT = 6–7%). Since the total melt fraction retained in the matrix during partial melting is not expected to be > 3% at any given time, our model assumes that the total melt volumes are not significantly changed with increasing MDT .Constraint 4 (exposure proportion) accounts for the detectability of Mg-suite rocks in craters across the lunar surface. Of 164 fresh and undisturbed crater central peaks examined with M23 to be 5103 ± 243 km, which is nearly half the circumference of the Moon (~5460 km), or the maximum farthest neighbor distance achievable. Further, we report the average nearest neighbor distance to be 266 ± 246 km. The high variance associated with the average nearest neighbor distance indicates a widespread distribution  and is inconsistent with a regional cluster of exposures  considers the total spatial distribution of Mg-suite rocks across the lunar surface. Although the complete distribution of subsurface Mg-suite is unknown, the observed spatial distribution of Mg-suite exposures can be quantified by measuring the current distance between each detection and its farthest neighboring detection. If Mg-suite detections are confined to a small region of the Moon for example, the farthest neighbor distance for each detection will be relatively short compared to the farthest neighbor distance of globally distributed Mg-suite locations. We calculate the average farthest neighbor of observed Mg-suite exposuresResults are assessed using the following constraints to determine which models are most consistent with the natural observations.33.All Runs 1–11 successfully meet Constraint 1. Downwelling of thicker IBC layers generally leads to greater total melt volume derived from the responsive upwelling of the lower mantle Fig. . The IBC38, the duration of decompression melting is finite in the absence of sustained mantle convection. At a given IBC thickness and viscosity contrast, cases with a lower mantle reference viscosity resulted in shorter magmatic durations and quicker magmatic timing relative to cases using higher mantle reference viscosity  co-satisfy Constraints 2 and 3 by producing magmatic durations < 50 Myrs and magmatic timing within 59 Myrs of time zero  is estimated for regions of upwelling mantle49.Ascent rates determined for lunar primary melts and time scales estimated for melt extraction in regions of upwelling mantle do not significantly change our results for magmatic duration or timing that are on the order of ~1–10 s of millions of years  and secondary Mg-suite Figs. , 6. Chroism Fig. . In this30. Other chronological approaches suggest LMO solidification occurred earlier, and perhaps as early as 4510 Ma55. If the earlier LMO solidification dates are accurate, this would require CMO-induced Mg-suite magmatic timing on the order of ~100–150 Myrs. Runs 1 and 2 with 30 km thick IBC and low viscosity contrast (10-1–10-2) produce magmatism on this timescale  models are therefore better aligned with rheological expectations and uniformly produce magmatic timing in < 59 Myrs and magmatic durations < 50 Myrs. Reconciling an older FAN formation age (~4.5 Ga) with Mg-suite petrogenesis by IBC-driven CMO may require future revisions to lunar chronology and the rheology of LMO cumulates. Whereas we show that near-contemporaneous primary and secondary crust building is entirely consistent with current geochronological and rheological constraints 55 or rapid compaction of the cumulate pile led to a metastable mantle stratigraphy57. Silicate-driven mantle convection is thus possible in a long-lived, partially solidified magma ocean56, and could result in syn-FAN decompression melting. If so, silicate overturn generally works in favor of reconciling a contemporaneous relationship between primary FAN and secondary Mg-suite. Nevertheless, petrologic and geochronologic context requires that FAN production preceded secondary magmatic intrusions.The first ~80% of LMO solidification is likely rapid60 predict formation of the high-density IBC layer after FAN production and, perhaps more importantly, prior to both urKREEP and complete LMO solidification. This is important because the formation of IBC reduces overturn initiation timescales to thousands of years38. Our results of IBC-driven overturn therefore remain valid considering long-lived residual magma oceans since the time zero of our model is predicated on the isotopic closure ages of FAN and not the complete solidification age of the LMO 34 are thus capable of ascending through the cool (~1000-1150 °C) and relatively dense (~2893–3161 kg m-3) syn-FAN residual magma ocean59. Such a scenario could account for both Mg-suite primary melts acquiring evolved trace element characteristics from the residual magma ocean in addition to buoyancy forces predominantly controlling Mg-suite melt transport34. Regardless, our results imply that an IBC layer formed within millions to tens of millions of years of FAN closure to satisfy the geochronologic constraints of Mg-suite magmatism.Here we note that LMO models65, ultimately resulting in the observed geochemical asymmetry of the lunar surface66 and potentially leading to Mg-suite production. In this scenario, widespread mantle convection like our modeling shows can be rapidly (within hours) induced by thermal anomalies from the SPA impact61. If secondary crust building was initiated during this SPA-induced stage of early mantle convection, geochronology then requires that the SPA impact be coincident with primary crust formation at ~4361 Ma. A minimum age of ~4.3 Ga has been inferred for SPA based on a reexamination of the areal density of impact craters using Gravity Recovery and Interior Laboratory data67, and is thus consistent with the hypothesis above. However, this scenario ultimately remains untestable by radiometric dating methods in the absence of samples returned from SPA.An alternative hypothesis to IBC-driven overturn is that the South Pole-Aitken (SPA) impact triggered overturn of a metastable mantle stratigraphyWe now discuss results from a set of models that test cooler and hotter initial temperature profiles for the LMO cumulates compared to that considered above. It is clear from our spatial analysis and range of melt detection threshold that CMO, with the exception of Run 11 and its degree 1 upwelling, is capable of explaining the global distribution of Mg-suite observed by orbital spacecraft regardless of timing and melt volume constraints  to promote quicker magmatic timing and to fully quantify the overturn process in this scenario (Run 3C_i). Despite satisfying the geochronological constraints with this low reference viscosity . Run 6H produced magmatic duration and timing of 10 and 29 Myrs, respectively, compared to 20 and 56 Myrs for Run 6. Run 6H yielded a total melt volume equivalent to 23 vol.% of the lunar crust compared to 13 vol.% produced by Run 6. Run 1H resulted in a magmatic duration and timing of 16 and 58 Myrs, respectively (compared to 69 and 156 Myrs in Run 1). Run 1H also yielded a total melt volume equivalent to 57 vol.% of the lunar crust (compared to 8.2 vol.% in Run 1).Our additional modeling provides new insight into the temperature profile of the lunar mantle at the onset of cumulate overturn. Within the evidence-based framework indicating a petrogenetic link between CMO and Mg-suite, the insufficient melt volumes produced by Runs 3C and 3C_i suggests that thermal conduction of the lower mantle could not have been extensive at the time of overturn. A cool pre-overturn cumulate pile is therefore not favored. Instead, hotter initial temperatures work to decrease magmatic timing and duration, consistent with constraints from geochronology  can reproduce the key volume, geochronological, and spatial characteristics of the earliest secondary crust on the Moon  and high viscosity contrast of 10-2 or greater. This is because lowering the reference viscosity of the mantle serves to decrease the magmatic duration and quicken magmatic timing  required a greater viscosity contrast with the IBC layer  demonstrates that the IBC layer is well resolved by our calculations  but did not find any significant changes to our results , respectively87. The Moon is highly depleted of the volatile element K90, and we apply a K/Th ratio of 250066. A major finding of this work is that the origin of Mg-suite can be explained by decompression melting of the lower mantle and thus, independently from the distribution of KREEP.Our model assumes 50% of all heat producing elements  are concentrated in the IBC layer37. Following previous work37, we therefore treat the initial thickness of the ilmenite-bearing cumulate (IBC) layer as a free parameter by modeling thicknesses of 30, 50, 100, and 150 km to explore the effects of IBC thickness on the dynamic return flow patterns and decompression melting of the lower mantle (Mg-suite source).Numerical and experimental simulations of LMO crystallization predict thin IBC layers (≤ 50 km) based on mass balance and phase equilibria, and thicker IBC layering up to 150 km is possible when considering dynamic redistribution of IBC diapirs during the LMO solidification process43. Viscosity is both temperature and compositionally dependent and we explore the range of IBC viscosities both constrained by experiment41 and defined in previous modeling37. Following previous work37, we vary the reference viscosity of the lunar mantle with the approximated rheology of peridotite, which can range from 5 × 1020–1021 Pa s , water content, and melt fraction37. It is for these reasons that we treat the viscosity contrast between the IBC and underlying mantle as a free parameter varying from 10-1–10-4. Considering the IBC thicknesses explored here, the possible ilmenite fraction of the IBC layer is estimated to be ~1.5–11.5 vol.%, corresponding to a viscosity contrast ≥ 3 orders of magnitude41. We also present results from end-member cases such as thin IBC layers paired with a low viscosity contrast  and thick IBC layers with the viscosity contrast considering pure ilmenite  to explore a range of possible physical combinations.The viscosity contrast between the lunar mantle and IBC plays a key role in determining the dynamics of CMOSupplementary Information


Background: Systemic sclerosis (SSc) is a connective tissue disease manifesting with progressive fibrosis of the skin and internal organs. Its pathogenesis is strictly associated with vascular disfunction and damage. Salusin-α and salusin-β, endogenous peptides regulating secretion of pro-inflammatory cytokines and vascular smooth muscle proliferation, may potentially play a role in SSc pathogenesis. Objectives: The aim of this study was to assess the concentration of salusins in sera of patients with SSc and healthy controls and to evaluate correlations between the salusins levels and selected clinical parameters within the study group. Materials and methods: 48 patients with SSc  and 25 adult healthy volunteers  were enrolled. All patients with SSc were treated with vasodilators and twenty-seven of them (56%) also received immunosuppressive therapy. Results: Circulating salusin-α was significantly elevated in patients with SSc in comparison to healthy controls . Patients with SSc receiving immunosuppression had higher serum salusin-α concentrations compared with those without immunosuppressive therapy . No correlation was observed between salusins concentrations and skin or internal organ involvement parameters. Conclusions: Salusin-α, a bioactive peptide mitigating the endothelial disfunction, was elevated in patients with systemic sclerosis receiving vasodilators and immunosuppressants. Increased salusin-α concertation may be associated with the initiation of atheroprotective processes in patients with SSc managed pharmacologically, which requires verification in future studies. Systemic sclerosis is an autoimmune connective tissue disease characterized by progressive fibrosis of the skin and internal organs. Microvascular changes with endothelial disfunction, epigenetics, and complex autoimmune responses are the major factors contributing to the development of the disease . In systAmong the candidates to be considered as systemic sclerosis biomarkers are salusins. These are two bioactive peptides, named salusin-α and salusin-β, which are derived from the TOR2A precursor, preprosalusin ,10. SaluA receptor) and stimulation of nitric oxide secretion (through the ETB receptor) [Due to its involvement in vascular homeostasis pathways, salusins may play a role in fibroproliferative vasculopathy in systemic sclerosis. One of the important factors in vascular tone regulation is disbalance between nitric oxide and endotelin-1 (ET-1), both secreted by the endothelium, which may be relevant for the progression of endothelial disfunction in patients with systemic sclerosis ,17. A vaeceptor) ,18,19. Seceptor) ,21. In receptor) . The dysregulation of endothelin-1/nitric oxide ratio may also contribute to cardiovascular disorders associated with endothelial disfunction, such as atherosclerosis and arterial hypertension . In the A retrospective single-center pilot cross-sectional study was conducted at the Department of Dermatology, Medical University of Warsaw, Poland. Its results were reported in line with the strengthening the reporting of observational studies in epidemiology (STROBE) statement . The priThe study protocol was approved by the institutional review board, the Ethics Committee at the Medical University of Warsaw . The study was completed in accordance with the ethical standards of the 1964 Helsinki declaration with future revisions and international conference on harmonization good clinical practice guidelines.Adult patients with systemic sclerosis  consecutively admitted between May 2019 and July 2021 to the Department of Dermatology, Medical University of Warsaw, Poland were considered eligible for inclusion in this study. Patients were undergoing their treatment in accordance with the current recommendations of the Polish Dermatological Society . Only inIn this study, a review of inpatient medical records was the main source of demographical and clinical data. All participants had their blood samples collected for further evaluation, including salusin-α and salusin-β concentration assessment. Other tests were performed as part of their routine clinical assessment. For patients in the experimental (systemic sclerosis) group, demographic information and medical details were collected, including current treatment and comorbidities. Findings in the recent imaging examinations were retrieved, such as high-resolution computed tomography (HRCT) of the thorax performed within the last year, diffusion lung capacity for carbon monoxide (DLCO) value assessed within the last year, and the esophageal X-ray with contrast from the previous three years. Complete blood count test results , serum creatinine levels , eryThe control group consisted of healthy volunteers, from whom only demographic details (age and BMI) were collected apart from the blood samples used for the determination of their salusin-α and salusin-β concentrations. Individuals from the control group were not diagnosed with metabolic diseases and did not have past or present history of glucocorticoids treatment or other immunosuppressive medications. Salusin-α and salusin-β levels were analyzed at the Laboratory of Immunodermatology, Department of Dermatology, Medical University of Warsaw, Poland. Enzyme-linked immunosorbent assay kits  were used as per the manufacturer’s protocol.p values < 0.05 were considered statistically significant. No correction for multiple comparisons was applied. All calculations were completed and plots created using the psych [For the purpose of descriptive analysis, continuous variables were evaluated using histograms, the Shapiro–Wilk test and Q-Q plot analysis. Normally distributed variables were reported using means and standard deviations, while non-normally distributed ones were summarized with medians and ranges. Qualitative variables were described using the numbers of events and frequencies. To compare differences in continuous variables between the groups, Student’s t-test for normally distributed or Mann–Whitney U test for non-normally distributed parameters were used. The assumption of equal variances was verified with the Levene’s test. For the comparison of categorical variables with all expected values of at least 5, the Chi-squared test was utilized. Otherwise, the Fisher’s exact test was applied. Simple linear regression was used to assess the relationship between serum salusin-α and salusin-β concentrations in patients with systemic sclerosis, healthy volunteers and both groups combined. To find correlations or associations between preselected variables, Spearman’s ranked correlation and Gaussian graphical model analysis were used . All instances of missing data were assumed to be missing completely at random and deleted pairwise. No data were imputed. Two-sided he psych , the qgrhe psych , the seohe psych , and thehe psych  modules he psych ,36.p = 0.292), age , and BMI  between the experimental and control groups.Forty-eight patients with systemic sclerosis  and twenty-five healthy volunteers  were enrolled in this study. Detailed characteristics of the study group are presented in p = 0.004; p = 0.662). Salusin-α and β concentrations were strongly correlated with each other .No statistically significant associations were detected between the presence of Scl-70 (anti-topoisomerase I) or ACA and salusin-α or β concentrations . Similar results were obtained for salusin-β . No statistically significant correlations or associations were detected between salusins concentrations and parameters reflecting disease involvement of skin or other organs in systemic sclerosis ; however, the subgroup was represented by two patients only. No such observation was made for salusin-α . No correlations were observed between the presence of thyroid disease (either hypo- or hyperthyroidism) and salusin-α  or β concentrations . No statistically significant association was detected when the occurrence of other autoimmune disorders  was compared with salusin-α  or salusin-β serum levels .Diabetic patients had significantly decreased salusin-β levels .Selected patients were treated with single-drug immunosuppression (n = 27) together with oral medications of rheologic properties  on a daily basis or intravenous ones  while admitted to the hospital. Immunosuppressive medications used by the patients included mycophenolate mofetil (n = 16), methotrexate (n = 10), and cyclophosphamide (n = 1). Patients not receiving immunosuppression therapy, were prescribed with rheologic medications only. Patients undergoing immunosuppressive treatment had statistically significantly higher salusin-α concentrations than those on rheologic therapy only , which is consistent with their common origin from one precursor peptide. As expected, their concentrations were lower and better linearly correlated in healthy volunteers  than in patients with systemic sclerosis , in whom it is hypothesized that these mediators may play a role in disease pathogenesis leading to their higher concentrations and noticeable balance disturbances.In our study, we compared the concentrations of salusin-α and salsin-β between the groups of patients with systemic sclerosis and healthy volunteers. We found statistically significant elevation of salusin-α in individuals with systemic sclerosis (p = 0.035) and β  was reported; however, a potential clinical association could not be identified. This finding may be related to renal function of the patients, as salusins are also produced in the kidneys. Nevertheless, none of the patients had a documented history of current acute kidney injury (AKI) or end-stage renal disease (ESRD).A moderately strong negative association between serum creatinine and salusin-α , Koca et al.  observedElevated salusin-α concentrations were reported by Ozgen et al.  in a groAs previously mentioned, salusin functions and concentrations were well-investigated in mice models and in vitro studies. Nonetheless, the reports in skin and connective tissue diseases involving humans stay inconclusive due to the complexity of occurring processes and misidentified confounders such as pharmacotherapy and comorbidities .An important factor not considered in previously discussed reports on salusins was the frequent use of long-term systemic corticosteroid therapy, which was an exclusion criterion in our study. Long-term corticosteroid intake is considered to be a strong confounding factor due to possible influence on various physiological and inflammatory processes; therefore, the association between the biomarker concentration and the treatment used may be potentially affected. In our study, patients receiving oral treatment with corticosteroids as well as other factors alleviating immune responses  were not enrolled due to potential interference with inflammatory parameters  and, consequently, biomarker concentrations.Erden et al.  showed dIn Behçet disease, Ozgen et al.  performeIn our study, we observed a statistically significant correlation between immunosuppression and antiatherogenic salusin-α–patients receiving immunosuppressive medications with higher salusin-α concentrations. The anti-inflammatory and atheroprotective properties of selected non-corticosteroid immunosuppressive agents were reported in the literature .The immunosuppressive medication with the widely proven impact on endothelial disfunction is methotrexate ,49. MethFurthermore, complex anti-atherosclerotic and anti-inflammatory properties of mycophenolate mofetil metabolite were described , i.e., vBrief reports are available regarding the atheroprotective properties of cyclophosphamide. In a low dose, cyclophosphamide was shown to inhibit atherosclerosis in murine model by a reduction of Th1 response and monocyte/macrophage migration to the plaque .It can be hypothesized that vasodilative and anti-inflammatory processes inducted by non-corticosteroid immunosuppressive agents could possibly induce salusin-α production and, in result, enhance other processes against endothelial disfunction in systemic sclerosis. Nonetheless, the association between immunosuppression and endothelial function is not confirmed due to existing research gaps and the complexity of autoimmune processes in humans in comparison to in vitro studies .The main limitation of this study is a small sample size, which confines the ability to identify all true correlations and results in the small number of some secondary endpoints . No significant correlations were detected between salusin-β levels and other preselected parameters, which may also result from small sample size or previously reported fluctuating concentrations due to the adherence of salusin-β to plastic laboratory tubes . This stSalusins are circulating peptide biomarkers of endothelial disfunction. High serum salusin-α is a prospective marker of the preserved function of endothelial cells, while high serum salusin-β indicates the occurrence of vascular remodeling. To our knowledge, this is the first study investigating concentrations of both salusin-α and salusin-β in systemic sclerosis.p = 0.004). Furthermore, systemic sclerosis patients receiving immunosuppressive treatment had significantly higher salusin-α concentrations than those treated with rheologic medications only (p = 0.026). Both salusins levels were statistically significantly correlated with serum creatinine concentrations.In this study, elevated salusin-α concentrations were observed in patients with systemic sclerosis compared with healthy individuals (Due to the limited evidence regarding salusins in the skin and connective tissue diseases, additional research is needed to fully understand the hypothesized positive impact of salusin-α in pharmacologically treated patients with systemic sclerosis.


Selection and breeding for high‐yielding in oilseed rape have always been one of the leading objectives for oilseed rape breeders. This process becomes more complicated when all quantitative traits are considered in selection in addition to grain yield. In the present study, 18 oilseed rape genotypes along with 2 check cultivars  were evaluated across 16 environments (a combination of 2 years and eight locations) in the tropical climate regions of Iran during 2018–2019 and 2019–2020 cropping seasons. The experiments were conducted in a format of randomized complete block design (RCBD) with three replications. The obtained multienvironmental trial data were utilized to conduct multivariate analysis, genotype by trait (GT) biplot, and genotype by yield*trait (GYT) biplot . The GT and GYT biplot accounted for 55.5% and 93.6% of the total variation in the first two main components. Based on multivariate analysis and GT biplot, pod numbers in plant (PNP) and plant height (PH) were chosen as two key traits in spring oilseed rape genotypes for indirect selection due to high variation, strong positive correlation with grain yield (GY), and their high representatively and discriminability in genotype selection. The mean × stability GT biplot represented G10 (SRL‐96‐17) as the superior genotype. Based on the mean × stability GYT biplot, eight above‐average genotypes were identified that took high scores in stability, high‐yielding, and all evaluated quantitative traits at the same time. Based on the superiority index of GYT data, G10 (SRL‐96‐17) and G5 (SRL‐96‐11) indicated the best yield–trait combinations profile and ranked above check cultivars and then selected as superior genotypes. Similarly, cluster analysis using the WARD method also separated eight superior genotypes. Based on the result of the present study, GT ad GYT methodologies are recommended for trait profiling and genotype selection in oilseed rape breeding projects, respectively. Pod number in plant and plant height were detected as the most essential selection criteria for grain yield enhancement in oilseed rape. GT ad GYT methodologies are recommended for trait profiling and genotype selection in oilseed rape breeding projects, respectively. The methodology of cluster analysis based on standardized GYT data led us to separate traits based on their direct and indirect effects in addition to genotype selection. The GT biplot accounted for 55.5% of the total variation of data. The first and second principal components accounted for 32.9% and 22.6% of the variation in data, respectively , obtuse (greater than 90°), and right (exact 90°) angles represent positive, negative, and zero (no) correlation between traits, respectively. Grain yield (GY) vector formed acute angle with pod numbers in plant (PNP), grain numbers in pod (GNP), one thousand grain weight (TGW), plant height (PH), and flowering period (FP) vectors which represent their positive correlations. Grain yield (GY) and pod numbers in plant (PNP) vectors were too close to each other which emphasizes their strong positive correlation. On the contrary, days to start flowering (DSF) and days to end flowering (DEF) vectors showed no correlation with the grain yield (GY) vector.3.2.2The studied traits were ranked based on both discriminating ability and representativeness. The length of the trait vectors shows how well the trait is represented in the biplot. The greater trait vector indicates more discrimination of the trait, while the relatively short vector demonstrates an insufficient variation of the trait across genotypes  genotypes included: G10 > G5 > G20 > G14 > G11 > G2 > G19 > G16 Figure . Among tThe mean of standardized yield–trait combinations values of each genotype shows its superiority index (SI). The high value of SI indicated the superiority of the genotype  using genotype by trait (GT) and genotype by yield*trait (GYT) biplot approaches.In this study, nine quantitative traits were evaluated. There is a wide variation among the studied genotypes, as represented by the high standard deviation values Table . Pod numBased on multivariate analysis, we defined pod numbers in plant (PNP) and plant height (PH) as two key traits in spring oilseed rape genotypes selection. Pod numbers in plant (PNP) were found as ideal traits due to meeting criteria including (1) strong positive correlation with grain yield (GY) based on Pearson correlation, (2) direct effect on grain yield (GY) based on path, and (3) highest variation among the evaluated traits. Plant height (PH) was also detected as the second ideal trait due to meeting criteria including (1) a strong positive correlation with pod numbers in plant (PNP) and grain numbers in pod (GNP) based on Pearson correlation and (2) indirect effect to grain yield (GY) trough yield components traits and phenological traits. Accordingly, pod numbers in plant (PNP) and plant height (PH) were detected as key traits in the genotype selection of spring oilseed rape.GT biplot methodology has been introduced for a long time as a practical strategy for trait profiling and genotype selection in plants based on the interaction between genotypes by traits  based on Path analysis emphasized that these traits should not be neglected. Additionally, although grain yield (GY) is the major target trait, an equivalent value to other traits is allocated to it. The purpose of plant breeding is to select a genotype with desirable traits as long as they have a good yield  than GT biplot (55.5), which was consistent with a previous report on barley genotypes Kendal, . This maBased on the results of the GYT biplot, all yield–traits combination vectors are close to each other that demonstrate their positive correlation. This is another advantage of the GYT biplot compared with the GT biplot that aligns all traits to make a strong association through combination with the grain yield (GY)  included series that all categorized as above average based on the GYT biplot. Additionally, the second cluster of yield*trait combination  is composed of traits with direct effects on grain yield (GY) based on path analysis. Therefore, this methodology of cluster analysis led us to separate traits based on their direct and indirect effects in addition to genotype selection.5This study aimed to determine how quantitative traits of oilseed rape genotypes are associated to increase grain yield. Another purpose of this study was to identify superior genotypes through composition grain yield with quantitative traits for the tropical regions of Iran. In this study, 20 spring oilseed rape genotypes were utilized in the multienvironmental trials. Based on multivariate analysis and GT biplot, Pod number in plant (PNP) and plant height (PH) were detected as the most essential selection criteria for grain yield enhancement in oilseed rape. The GT biplot facilitated visual comparisons of the traits, but was flawed in genotype ranking due to the negative correlation of some traits with grain yield. Genotype assessment based on grain yield composition with quantitative traits through GYT methodology eliminated this defect. Accordingly, eight above‐average genotypes were detected. Of them, G10, G5, G14, G11, and G2 were ranked above the RGS003 check cultivar, while G10 and G5 ranked above both check cultivars , as the first and second determined genotypes. Therefore, genotypes G10 and G5 were detected as the best genotypes with the highest grain yield and outstanding quantitative traits.This research received no specific grant from any funding agency in the public, commercial, or not‐for‐profit sectors.The authors declare that they have no conflict of interest.Written informed consent was obtained from all study participants.