A better understanding of disease progression and response to therapies therefore remains of utmost importance. Here we characterize the genomic differences between early-stage untreated primary tumours and late-stage treated metastatic tumours using a harmonized pan-cancer analysis  of two unpaired primary4 and metastatic5 cohorts of 7,108 whole-genome-sequenced tumours. Metastatic tumours in general have a lower intratumour heterogeneity and a conserved karyotype, displaying only a modest increase in mutations, although frequencies of structural variants are elevated overall. Furthermore, highly variable tumour-specific contributions of mutational footprints of endogenous  and exogenous mutational processes  are present. The majority of cancer types had either moderate genomic differences  or highly consistent genomic portraits  when comparing early-stage and late-stage disease. Breast, prostate, thyroid and kidney renal clear cell carcinomas and pancreatic neuroendocrine tumours are clear exceptions to the rule, displaying an extensive transformation of their genomic landscape in advanced stages. Exposure to treatment further scars the tumour genome and introduces an evolutionary bottleneck that selects for known therapy-resistant drivers in approximately half of treated patients. Our data showcase the potential of pan-cancer whole-genome analysis to identify distinctive features of late-stage tumours and provide a valuable resource to further investigate the biological basis of cancer and resistance to therapies.Metastatic cancer remains an almost inevitably lethal disease The genomic differences between primary and metastatic tumours are assessed across 23 cancer types using pan-cancer whole-genome analysis. Advanced metastatic tumours are frequently able to resist aggressive treatment regimes6. Despite the many efforts to understand these phenomena9, we still have limited knowledge of the contribution of genomic changes that equip tumours with these extraordinary capacities. Thus, it is essential to characterize genomic differences between primary and metastatic cancers and quantify their effect on therapy resistance to understand and harness therapeutic interventions that establish more effective and more personalized therapies10.Metastatic spread involves tumour cell detachment from a primary tumour, colonization of a secondary tissue and growth in a hostile environment5, large-scale comparative studies between the two tumour stages remain limited due to the logistical challenges associated with obtaining pan-cancer cohorts of primary and metastatic cancers. To circumvent this issue, most comparison studies have relied on unpaired whole-exome data or have adopted more targeted approaches with a specific focus on driver gene landscapes13. However, these efforts have frequently involved separated processing pipelines for primary and metastatic cohorts, complicating the analysis of genomic features that are highly sensitive to the selected data-processing strategy15. A recent study that uniformly analysed more than 25,000 tumours16 has provided a comprehensive overview of the genomic differences, driver alteration patterns and organotropism using clinical gene-panel sequencing as a base. However, this genomic analysis approach prevented the exploration of the full spectrum of genomic alterations that have a role in tumorigenesis, such as structural variation and mutational scarring.Although extensive whole-genome analyses of primary or metastatic tumour types have been conducted5, which included 4,784 samples from 4,375 patients with metastatic cancers. Then, we reprocessed 2,835 primary tumour samples from the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium4 using the open-source Hartwig analytical pipeline17 to harmonize somatic calling and annotations of events, and to eliminate processing biases  inventory of 7,108 matched tumour and normal genomes from two unpaired primary and metastatic cohorts. We first collated the Hartwig Medical Foundation (Hartwig) datasetWe next focused on 23 cancer types from 14 tissues with sufficient sample representation, comprising 5,365 tumour samples  to explore genomic differences between primary and metastatic tumours Fig. . Within 9. Our results support the model that metastatic lesions generally have lower intratumour heterogeneity16, which may be explained by a single major subclone seeding event from the primary cancer and/or by severe evolutionary constraints imposed by anticancer therapies.We first explored global genomic differences between primary and metastatic tumours across the aforementioned 23 cancer types. Metastatic tumours showed an overall increase in clonality compared with their primary tumour counterparts Fig. . Particu18. Only metastatic kidney renal clear cell, prostate and thyroid carcinomas showed substantial changes compared with primary tumours, encompassing 91% (43 of 47) of all significant discrepancies. Besides the poor prognostic marker 8q gain in metastatic prostate carcinoma19, all discrepancies were associated with an increased prevalence of chromosomal arm losses at the metastatic setting. Remarkably, 30% (14 of 46) of the metastatic-enriched chromosome arm losses were retained when comparing non-WGD tumours  genome fraction, WGD22 and TP53 alterations23) in the metastatic cohort , collectively encompassing SBSs, DBSs and IDs, was only moderately increased in metastatic tumours compared with primary tumours across the 23 cancer types tested ). In fact, 15 of the 23 cancer types had no significant increase in mutation burden for any mutation type. Only five cancer types  had a consistent increase for the three mutation types at the metastatic stage, although the mutation profiles lacked systematic differences between primary and metastatic tumours Fig. . Finally24 (ID8) was enriched in six cancer types commonly exposed to radiation-based treatment  and polycyclic aromatic hydrocarbon metabolites from chemotreatments26 (DBS2) also displayed greater metastatic mutation burden contribution in a tumour-type-specific manner  mutations per sample in six metastatic tumours  that reached statistical significance, with breast and stomach cancers the types with the strongest increase (more than 500 APOBEC mutations per sample). Other cancer types, such as cervical and bladder urothelial carcinomas, also showed enhanced APOBEC activity , but they did not reach significance due to already high intrinsic APOBEC activity in the primary tumours. The metastatic breast cancer samples also had a higher percentage in clustered APOBEC hypermutation variants than primary tumours  that exhibited an increased SBS1 contribution and three cancer types  that had an increased SBS5/SBS40 mutation burden. The increase in clock-like mutations in thyroid and prostate cancers, as well as diffuse B cell lymphomas to a lesser extent, may be explained by a larger proportion of older patients with metastatic disease. However, SBS1 metastatic enrichment was also present in cancer types with highly similar age population distributions Fig. .Additional focused analyses will be needed to obtain a better understanding of the mutational signature differences that we observed in smaller subsets of cancer types (and subtypes) and metastatic locations  did not show such enrichment  and the estimated fold change of the SBS1 mutation rate in the metastatic cohort . This increase was observed in 13 of 23 (56%) cancer types Fig. . FinallySmall (less than 10 kb) deletions were the most enriched SV types in metastatic tumours  alterations in prostate carcinoma and MDM2 (ref. 35) amplifications in breast ER+/HER2− carcinomas, among others. Genomic instability features, such as genome ploidy and TP53 alterations, showed a strong pan-cancer association with deletions and duplications , including 8 (34%) tumour types with a significant increase Fig. . ProstatPTPRD in kidney renal clear cell carcinoma, CREBBP in pancreatic neuroendocrine tumour, and RET and TP53 alterations in thyroid carcinoma). Most metastatic-enriched cancer drivers had a cancer-type-specific enrichment, including well-established resistance gene drivers associated with anticancer therapies, such as AR and ESR1 alterations in patients with prostate and ER+ breast carcinomas treated with hormone deprivation therapies38  showed a metastatic enrichment across multiple cancer types  and lung adenocarcinoma  showed a substantial proportional increase in the metastatic cohort  that were either significantly enriched  or exclusively found  in a cancer-type-specific and treatment-specific manner  showed an intense transformation of the genomic landscape in advanced tumorigenic stages  or whether there are stochastic triggers of metastatic disease in relatively indolent primaries are still to be determined. To fully address these, larger pan-cancer sets of matched biopsies from the same patient, as already implemented in various cancer-type-specific studies47 and from the tumour microenvironment48 will be needed to further dissect and better understand metastasis and resistance to cancer therapies.This study faced various limitations, such as the use of different laboratory workups and sequencing parameters used for primary and metastatic tumour samples, although we demonstrated that this does not severely have an effect on the overall detectability of clonal somatic variants  using the Benjamini–Hochberg procedure. An adjusted P < 0.05 was deemed as significant.Each mutation in the .vcf files was given a subclonal likelihood by PURPLE. Following PURPLE guidelines, we considered mutations with subclonal scores equal or higher than 0.8 to be subclonal and mutations below the 0.8 threshold to be clonal. For each sample, we then computed the average proportion of clonal mutations by dividing the number of clonal mutations by the total mutation burden . Finally, for each cancer type, we used Mann–Whitney test to assess the significance of the clonality difference between the primary and metastatic tumours. In addition, we leveraged biopsy site data in patient reports to further investigate differences in metastatic tumour clonality according to the metastatic biopsy site  segments (as determined by PURPLE) were rounded to the nearest integer. Second, arm coverage of each integer CN was calculated as the fraction of chromosome arm bases with the specific CN divided by the chromosome arm length . We defined the arm-level ploidy level as the CN with the highest coverage across the whole arm (in the example above it would be 2). Third, we computed the most recurrent chromosome arm ploidy levels across all chromosome arms per sample .n. If a sample did undergo WGD and its observed genome ploidy was less than six, the estimated genome ploidy was deemed to be 4n, and 8n if the observed genome ploidy was six or more. An observed genome CN of more than eight was not found in our dataset.Next, we estimated the true genome ploidy by taking WGD status (given by PURPLE) into account. If a sample did not undergo WGD, its total expected genome ploidy was deemed to be 2P value was FDR adjusted across all arms per cancer type. Finally, q < 0.01 and a normalized arm ploidy difference higher than 0.25 was deemed to be significant.Then, for each chromosome arm in each sample, we defined the normalized arm ploidy as the difference between the arm-level ploidy level and the expected genome ploidy. The resulting value was classified as 1 for differences higher than or equal to 1 (representing arm gains), as −1 for differences lower than or equal to −1 (representing arm losses) or as 0 (no difference). Normalized arm ploidy values were averaged across all samples from a cancer type in a cohort-specific manner . A Mann–Whitney test was performed per cancer type and chromosome arm to assess the mean difference in arm gains or losses at the cancer-type level. The resulting 20. The LOH score of a given sample represents the sum of all LOH regions divided by the GRCh37 total genome length. A genomic region is defined as LOH when the minor allele CN < 0.25 and major allele CN ≥ 0.8.To compare the differences in aneuploidy scores and the LOH proportions in each group, a Mann–Whitney test was performed per cancer type. The aneuploidy score represents the number of arms per tumour sample that deviate from the estimated genome ploidy as previously describedTP53 as well as the fraction of WGD samples per cohort, a Fisher’s exact test was performed per cancer type. Any TP53 driver alteration  was considered in the analysis. Multiple driver mutations per sample in a single gene were considered as one driver event. WGD was defined as present if the sample had more than 10 autosomes with an estimated chromosome CN of more than 1.5. P values were FDR corrected across all cancer types. A q < 0.01 was deemed to be significant for all statistical tests.To compare the fraction of samples with a driver mutation in 51; https://cancer.sanger.ac.uk/signatures/) was determined using the R package mutSigExtractor .The number of somatic mutations falling into the 96 SBS, 78 DBS and 83 ID contexts  was then used (with default settings) to extract a maximum of 21 SBS, 8 DBS and 10 ID de novo mutational signatures. This was performed separately for each of the 20 tissue types that had at least 30 patients in the entire dataset .The extracted de novo mutational signatures with high cosine similarity (≥0.85) to any reference COSMIC mutational signatures with known cancer-type associationsWe calculated the pairwise cosine distance between each of the de novo signature profiles.We performed hierarchical clustering and used the base R function cutree to group signature profiles over the range of all possible cluster sizes .We calculated the silhouette score at each cluster size to determine the optimum number of clusters.We grouped the signature profiles according to the optimum number of clusters. This yielded 27 SBS, 7 DBS and 8 ID de novo signature clusters 52. Some clusters were an aggregate of two known signatures, such as SBS_denovo_clust_2, which was a combination of SBS2 and SBS13, both linked to APOBEC mutagenesis. Other clusters had characteristic peaks of known signatures, such as DBS_denovo_clust_4, which resembled DBS5 based on having distinctive CT>AA and CT>AC peaks. Finally, DBS_denovo_clust_1 was annotated as a suspected POLE mutation and MMRd, as samples with high contribution (more than 150 mutations) of this cluster are frequently microsatellite instable (MSI) or have POLE mutations. Likewise, DBS_denovo_clust_2 was annotated as a suspected MMRd as the aetiology, as samples with high contribution (more than 250 mutations) of this cluster were all MSI. See Supplementary Table For certain de novo signature clusters, we could manually assign the potential aetiology based on their resemblance to signatures with known aetiology described in COSMIC53.After applying the aetiology assignment, the de novo extraction resulted in 69 SBS, 13 DBS and 18 ID representative mutational signatures /(median contribution in primary tumours + 1)). We considered the aetiology contribution between primary and metastatic tumours to be significantly different when q < 0.05, and log2 fold change ≥ 0.4 or log2 fold change ≤ −0.4 (= ± ×1.4).We then compared the activity  of each mutational process between primary and metastatic tumours. For each sample, we first summed the contributions of signatures of the same mutation type  with the same aetiology, hereafter referred to as ‘aetiology contribution’. Per cancer type and per aetiology, we performed two-sided Mann–Whitney tests to determine whether there was a significant difference in aetiology contribution of primary and metastatic tumours. Per cancer type and per mutation type, we used the p.adjust base R function to perform multiple testing correction using Holm’s method. Next, we added a pseudocount of 1 to the contributions (to avoid dividing by 0) and calculated the median contribution logq < 0.05 and median difference was 0.01 or more.Relative aetiology contribution was calculated by dividing aetiology contribution by the total contribution of the respective mutation type . To determine the significant difference in relative aetiology contribution, we performed two-sided Mann–Whitney tests as described above. We also calculated the median difference in contribution . We considered the relative aetiology contribution between primary and metastatic tumours to be significantly different when P values using two-sided Fisher’s exact tests, and effect sizes by multiplying Cramer’s V by the sign of the log2(odds ratio) to calculate a signed Cramer’s V value that ranges from −1 to +1 . We then used the p.adjust base R function to perform multiple testing correction using Bonferroni’s method.We also determined whether there was an increase in the number of samples with high aetiology contribution  in metastatic versus primary cohorts. For each signature, a sample was considered a hypermutator if the aetiology contribution was 10,000 or more for SBS signatures, 500 or more for DBS signatures or 1,000 or more for ID signatures. For each cancer type, for each aetiology, we performed pairwise testing only for cases in which there were five or more hypermutator samples for either metastatic or primary tumours. Each pairwise test involved calculating 54 that is based on the characteristic peaks of the COSMIC SBS1 signature profile: single-base CpG > TpG mutations in NpCpG context. To ensure that these counts and the downstream analyses are not affected by differential APOBEC exposure in primary and metastatic cohorts, we excluded CpG > TpG in TpCpG, which is also a characteristic peak in the COSMIC SBS2 signature profile. In addition, for skin melanoma, CpG > TpG in [C/T]pCpG, which overlaps with SBS7a, was excluded. To obtain the SBS5 and SBS40 counts, we relied on their exposures derived from the mutational signature analyses performed in this study (described above).To count the SBS1 mutations, we relied on the definition from ref. To assess the correlation between SBS1 burden and the age of the patient, at biopsy we performed a cancer-type and cohort-specific linear regression . To avoid spurious effects caused by hypermutated tumours, samples with a TMB greater than 30,000 as well as those with SBS1 burden greater than 5,000 were excluded.For each cancer type and cohort, we then computed 100 independent linear regressions by randomly selecting 75% of the available samples. We selected the median linear regression (based on the regression slope) as representative regression for further analyses. Similarly, confidence intervals were derived from the 1st and 99th percentile of the computed regressions.P < 0.01 were deemed as significant. Finally, to ensure that the differences were uniform across different age ranges , we only considered significant cancer types in which the metastatic linear regression intercept was higher than the primary intercept.To evaluate the significance of the differences between primary and metastatic representative linear regressions (hereafter referred to as linear regression for simplicity), we first filtered out cancer types that failed to show a positive correlation trend between SBS1 burden and age at biopsy in both primary and metastatic tumours . Next, for each selected cancer type, we computed the regression residuals of primary and metastatic SBS1 mutation counts using, in both cases, the primary linear regression as baseline. The primary and metastatic residual distributions were then compared using a Mann–Whitney test to evaluate significance. Cancer types with a Mann–Whitney SBS5/SBS40 correlations were computed following the same procedure and using the sum of SBS5 and SBS40 exposures for each tumour sample. If none of the mutations were attributed to SBS5/SBS40 mutational signatures, the aggregated value was set to zero. In the ploidy-corrected analyses, we divided the SBS1 mutation counts  by the PURPLE-estimated tumour genome ploidy.i and PPredi are the estimated number of SBS1 mutations for a given age ith according to the metastatic and primary linear regressions, respectively. Similarly, the mean estimated SBS1 burden difference (SBS1diff) was defined as: For each cancer type, the mean fold change (fc) was defined as SBS1 individual mutations were identified as described in the previous section. For SBS5 and SBS40 mutations, we used a maximum likelihood approach to assign individual mutations to the SBS5 and SBS40 mutational signatures in a cancer-type-specific manner.For every SBS1 (and SBS5/SBS40 mutation), we then assign the clonality according to the PURPLE subclonal likelihood estimation, in which only mutations with subclonal (SUBCL) likelihood ≥ 0.8 were considered as such (see above).For each tumour sample, the SBS1 clonality ratio  was defined as the ratio between the proportion of clonal SBS1 mutations (30 (Supplementary Table We computed for each primary cancer type the average number of SBS1 per year as the number of SBS1 mutations divided by the age of the patient at biopsy (only considering primary samples and excluding hypermutated samples as described above). We then used a Spearman’s correlation to assess its association with the estimated mean SBS1 mutation rate fold change in metastatic tumours (see above). In addition, to exclude potential biases in our primary cohort, we repeated the same analysis relying on an independent measurement of primary cancer SBS1 yearly accumulation. Specifically, we used the best-estimated accumulation of SBS1 per year from ref. 55 chains one or more SVs and classifies these SV clusters into various event types (‘ResolvedType’). We defined deletions and duplications as clusters with a ResolvedType of ‘DEL’ or ‘DUP’ whose start and end breakpoints are on the same chromosome . Deletions and duplications were split into those less than 10 kb and 10 kb or more in length , based on observing bimodal distributions in these lengths across cancer types . Next, we calculated relative enrichment as follows: log10(median SV-type burden in metastatic tumours + 1) − log10(median SV-type burden in primary tumours + 1); and calculated fold change as follows: (median SV-type burden in metastatic tumours + 1) / (median SV-type burden in primary tumours + 1). When calculating relative enrichment and fold change, the pseudocount of 1 was added to avoid the log(0) and divide by zero errors, respectively. Fold changes are displayed with a ‘>’ in Fig. q < 0.05, and fold change ≥ 1.2 or fold change ≤ 0.8We then compared the SV-type burden between primary versus metastatic tumours as shown in Fig. 33) and MSI (determined by PURPLE) status; (3) the presence of mutations in 345 cancer-associated genes , hereafter referred to as ‘gene status’; and (4) treatment history, including the presence of radiotherapy, the presence of one of the 79 different cancer therapies as well as the total number of treatments received. All primary samples and all metastatic samples without treatment information were considered to have no treatment. Genome ploidy and total number of treatments received were numeric features, whereas all of the remaining were boolean  features. In total, there were 429 features.To identify the features that could explain increased SV burden, we correlated SV burden with various tumour genomic features. This included: (1) genome ploidy (determined by PURPLE); (2) homologous recombination deficiency (determined by CHORD10(SV-type burden + 1) and was correlated with the 429 features using multivariate linear regression models (LMs). This was performed separately for each of the seven SV types, and for each cancer type (or subtype). In the SV main analysis  involved training of three independent LMs with (1) both metastatic and primary samples (primary + metastatic), (2) only Hartwig samples (metastatic only), and (3) only PCAWG samples (primary only). This was done to filter out correlations between features and increased SV-type burden solely due to differences in feature values between primary and metastatic tumours. We then required features that positively correlated with SV-type burden in the primary + metastatic LM to independently show the same association in the metastatic-only or primary-only LMs. Only genomic features that independently showed positive correlation with the SV burden were further considered as significant .Remove boolean features with too few ‘true’ samples.(i)For the primary + metastatic LM, remove gene status features with less than 15 ‘true’ samples.(ii)For the metastatic-only and primary-only LMs, remove gene status features with less than 10 ‘true’ samples.(iii)For the remaining boolean features, remove features with less than 5% ‘true’ samples.(2)10(SV-type burden + 1) versus all features.Fit a LM using the lm base R function to correlate logEach of the three LMs was trained as follows:P < 0.01 as described in the previous section ‘Comparing SV burden between primary versus metastatic cancer’).Only keep LM analyses for which there was significant increase in SV-type burden for the respective cancer type (For primary + metastatic LM:(i)P < 0.01Regression (ii)P < 0.01Coefficient (iii)Coefficient more than 0(3)For metastatic-only LM or primary-only LM:(i)P < 0.01Coefficient (ii)Coefficient more than 0For each LM analysis, we used the following filtering criteria to identify the features that were correlated with increased SV-type burden:V for boolean features. Cliff’s delta ranges from −1 to +1, with −1 representing complete enrichment in primary tumours, whereas +1 represents complete enrichment in metastatic tumours. Cramer’s V only ranges from 0 to 1 (with 1 representing enrichment in either primary or metastatic tumours), the sign of the log(odds ratio) was assigned as the sign of the Cramer’s V value so that it ranged from −1 to +1. Features with an effect size of more than 0 were considered as those that could explain the SV burden increase in metastatic cancer when compared with primary cancer.Finally, to determine which features (of those correlated with increased SV-type burden) were enriched in metastatic tumours compared with primary tumours (and vice versa), we calculated Cliff’s delta for numeric features and Cramer’s 5 and LINX55. Only drivers with a driver likelihood of more than 0.5 were retained. Fusion drivers were filtered for those that were previously reported in the literature. Similarly, we manually curated the list of drivers and removed SMAD3 hotspot mutations because of the high-burden mutations in low-mappability regions. The final driver catalogue contained a total of 453 driver genes and the final fusion catalogue contained 554 reported fusions.We relied on patient-specific cancer driver and fusion catalogues constructed by PURPLETP53 mutation and TP53 deletion in the same sample were considered as one driver event). Cancer-type-specific Mann–Whitney test was performed to assess differences between primary and metastatic tumours. An adjusted q < 0.01 was deemed to be significant.To compare the number of drivers in primary and metastatic tumours, we then combined fusions with the LINX driver variants to calculate a patient-specific number of driver events. Drivers that concern the same driver gene but a different driver type were deemed to be single drivers  and cancer type in each cohort (metastatic and primary). A second contingency matrix was constructed for the fusions. Partial amplifications were considered as amplifications, whereas homologous disruptions were considered as deletions. These contingency matrices were filtered for genes that show a minimum frequency of five mutated samples in either the primary or the metastatic cohorts. Then, a two-sided Fisher’s exact test for each gene, cancer type and mutation type was performed and the 56 to those derived from three different databases  that were classified based on a common clinical evidence level (https://civic.readthedocs.io/en/latest/model/evidence/level.html) as previously described5. In our study we only considered A and B levels of evidence, which represent variants that have been FDA approved for treatment and are currently being evaluated in a late-stage clinical trial, respectively. A variant was determined to be ‘on-label’ when the cancer type matches the cancer type for which the treatment was approved for or is being investigated for, and ‘off-label’ otherwise. Only actionable variants of the sensitive category were considered . Sample-level actionable variants such as TMB high/low or MSI status were not evaluated, because of their tendency to overshadow the other variants, especially in the off-label category. Furthermore, wild-type actionable variants were not considered in this analysis for the same reason. Variants related to gene expression or methylation were not considered due to lack of available data. In addition, we found actionable variants derived from leukaemias to be very different from the solid tumours in our dataset, which is why we excluded them for this analysis. For the analysis of proportion of samples bearing therapeutically actionable variants, we considered that the highest evidence level was retained for each sample following the order A on/off-label to B on/off-label. To assess enrichment of actionable variants globally and at the A on-label level in metastatic tumours, a Fisher’s exact test was performed pan-cancer-wide and per cancer type. An adjusted P < 0.05 was deemed to be significant. Fold changes in frequency are only shown for cancer types with a global significant difference.To determine the amount of actionable variants observed in each sample, we compared our variants annotated by SnpEff (v5.1)P values were FDR adjusted per cancer type and q < 0.05 was deemed to be significant. In Extended Data Fig. To determine which variants contribute the most to the observed significant frequency differences, individual actionable variants were tested for enrichment in metastatic tumours using a Fisher’s exact test per cancer type and tier level. We aimed to pinpoint drivers that are potentially responsible for lack of response to certain cancer treatments in the metastatic cohort. Hence, we devised a test that identifies driver alterations that are enriched in groups of patients treated with a particular treatment type compared with the untreated group of patients from the same cancer type . We created 323 treatment and cancer-type groups by grouping patients with treatment annotation according to their treatment record before the biopsy. One patient might be involved in multiple groups if they have received multiple lines of therapy or a simultaneous combination of multiple drugs. Only 92 treatment and cancer-type groups with at least ten patients were further considered in the analysis.We first performed a driver discovery analysis in treatment and cancer-type (or subtype)-specific manner. We explored three types of somatic alterations: coding mutations, non-coding mutations and CN variants (see below for detailed description of each driver category). Driver elements from each alteration category were selected for further analysis.P values were adjusted with a multiple-testing correction using the Benjamini–Hochberg procedure (α = 0.05). An adjusted P value of 0.05 was used for coding mutations and CN variants. An adjusted P value of 0.1 was used for non-coding variants due to the overall low mutation frequency of the elements included in this category, which hampered the identification of significant differences.For each driver alteration from (1), we compared the alteration frequency in the treated group to the untreated group of the same cancer type. Each driver category (coding and non-coding mutations and CN variants) were evaluated independently. We performed a Fisher’s exact test to assess the significance of the frequency differences. Similarly, we computed the odds ratio of the mutation frequencies for each driver alteration. The We then annotated each driver element with information about the exclusivity in the treatment group. We labelled drivers as treatment exclusive if the mutation frequency in the untreated group was lower than 5% or we annotated as treatment enriched otherwise. In addition, we manually curated the identified drivers with literature references of their association with each treatment category.Finally, the overlap of patients in multiple treatment groups (see above) in the same cancer type prompted us to prioritize the most significant treatment association for each driver gene in a particular cancer type. In other words, for each driver gene that was deemed as significantly associated with multiple treatment groups in the same cancer type, we selected the most significant treatment association, unless a driver-treatment annotation was clearly reported in the literature.Hence, for each cancer type  and treatment group, we performed the following steps:The full catalogue of TEDs and their mutation frequencies can be found in Supplementary Table 60 with default parameters to identify cancer driver genes from coding mutations. A global q < 0.1 was used as a threshold for significance. Mutation frequencies for each driver gene were extracted from the dNdScv output. We defined the mutation frequency as the number of samples bearing non-synonymous mutations.We used dNdScv (v0.0.1)61  to identify non-coding driver elements in five regulatory regions of the genome including 3′ untranslated regions (UTRs), 5′ UTRs, long non-coding RNAs, proximal promoters and splice sites. For each element category, we extracted the genomic coordinates from Ensembl v101. Each regulatory region was independently tested. To select for significant hits, we filtered on adjusted P values (FDR < 0.1) and a minimum of three mutated samples. We defined the mutation frequency as the number of mutated samples for each significantly mutated element in the treatment group.We used ActiveDriverWGS62) (v2.0.23) on each of the 92 treatment and cancer-type groups using the following settings:We ran GISTIC2  were then annotated with functional elements using the coordinates from Ensembl v101. The frequency differences between treated and untreated cohorts on every gene was assessed with Fisher’s exact test as described above. For this, we first calculated the focal amplification and deep depletion status of every gene within each sample. A gene was amplified when the ploidy level of the gene was 2.5 ploidy levels higher than its genome-wide mean ploidy level (as measured by PURPLE), and deleted when the gene ploidy level was lower than 0.3 . We observed that the majority of the peaks contained multiple significant gene candidates (after multiple correction q < 0.05) and therefore we retained the gene most closely positioned to the peak summit, which is the most significantly enriched region across the treated samples. Next, we also found recurrent peaks across multiple treatment groups per cancer type that are not, or less, present in the untreated control group because most of the Hartwig samples have received multiple treatment types. We therefore merged peaks with overlapping ranges to produce a single peak per genomic region per cancer type. For each collapsed peak, we selected the treatment type showing the lowest q value for the gene near the peak summit. Deletion and amplification peaks were processed separately.The focal GISTIC peaks  in a cancer-type-specific, gene-specific and driver-type-specific manner.Further information on research design is available in the Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41586-023-06054-z.Supplementary InformationThis file contains Supplementary Notes 1-4Reporting SummaryPeer Review FileSupplementary Data 1Mutation profiles of de novo signatures that were extracted with non-negative matrix factorization.Supplementary Table 1Primary and metastatic cohorts metadata.Supplementary Table 2Karyotype and genomic instability measurements.Supplementary Table 3Mutational signatures absolute and relative contribution.Supplementary Table 4SBS1 mutation rate.Supplementary Table 5Structural variants.Supplementary Table 6Driver alterations.Supplementary Table 7Therapeutic actionability of variants.Supplementary Table 8Treatment associated drivers (TEDs).


Tandem repetitiveness of ribosomal DNA (rDNA) makes it unstable, posing the challenge in maintenance particularly in the “immortal” germline, which forms continuous lineage of cells and organisms. Two competing models [unequal sister chromatid exchange (USCE) model and extrachromosomal rDNA circle reintegration model] have been proposed as a mechanism underlying rDNA magnification, a process identified over 50 y ago to recover rDNA copy number (CN). The present study provides empirical evidence and computer simulation that support the USCE model and provide explanations to observations that were previously deemed inconsistent with the USCE model. A revised model proposes that asymmetric stem cell division of germline stem cells is the critical cell biological aspect that enables USCE to effectively increase rDNA CN. Ribosomal DNA (rDNA) encodes ribosomal RNA and exists as tandem repeats of hundreds of copies in the eukaryotic genome to meet the high demand of ribosome biogenesis. Tandemly repeated DNA elements are inherently unstable; thus, mechanisms must exist to maintain rDNA copy number (CN), in particular in the germline that continues through generations. A phenomenon called rDNA magnification was discovered over 50 y ago in Drosophila as a process that recovers the rDNA CN on chromosomes that harbor minimal CN. Our recent studies indicated that rDNA magnification is the mechanism to maintain rDNA CN under physiological conditions to counteract spontaneous CN loss that occurs during aging. Our previous studies that explored the mechanism of rDNA magnification implied that asymmetric division of germline stem cells (GSCs) may be particularly suited to achieve rDNA magnification. However, it remains elusive whether GSCs are the unique cell type that undergoes rDNA magnification or differentiating germ cells are also capable of magnification. In this study, we provide empirical evidence that suggests that rDNA magnification operates uniquely in GSCs, but not in differentiating germ cells. We further provide computer simulation that suggests that rDNA magnification is only achievable through asymmetric GSC divisions. We propose that despite known plasticity and transcriptomic similarity between GSCs and differentiating germ cells, GSCs’ unique ability to divide asymmetrically serves a critical role of maintaining rDNA CN through generations, supporting germline immortality. Ribosomal DNA (rDNA) loci harbor hundreds of tandemly repeated ribosomal RNA (rRNA) genes to meet the high demand of ribosome biogenesis, with rRNA synthesis constituting ~80% of total cellular transcription in the cell . TandemlDrosophila melanogaster has long served as an excellent system to monitor rDNA CN changes, particularly because it has only two rDNA loci , while most other model multicellular organisms have several rDNA loci  at rDNA loci allows one chromatid to “steal” copies from its sister, producing sister chromatids that have reciprocally gained and lost rDNA copies . The othRecently, we reported mechanisms that contribute to rDNA magnification. We observed that under the magnifying condition, dividing GSCs (germline stem cells) exhibited asymmetry in rDNA CN, with higher rDNA CN being preferentially inherited by GSCs than its differentiating daughter, leading us to propose that GSCs gained rDNA CN via USCE D 3). GS. GS3). GWe also reported that the retrotransposon R2, which specifically inserts into the 28S rDNA sequence , is requ22In this study, by using Drosophila genetics, cytology, and computer simulation, we investigated how the process of rDNA magnification is integrated in the biology of asymmetric GSC divisions and symmetrically dividing differentiating cells (GBs/SGs). We provide evidence that rDNA magnification is a unique feature of GSC biology. In contrast, ectopic activation of R2 in differentiating germ cells is harmful, leading to marked reduction in the number of differentiating germ cells. Collectively, we propose that GSCs’ unique characteristic to divide asymmetrically is critical for rDNA CN maintenance and thus germline immortality.Z9bb used in this study, see Methods (Z9bb X chromosome (whether it recovered rDNA CN or not) can be assayed in the offspring (Z9bb is combined with a Y chromosome completely lacking rDNA (0Ybb), the total low rDNA CN induces magnification, leading to CN recovery on Z9bb locus  is referred to as the “magnifying condition,” and the Z9/Ybb genotype that does not induce rDNA magnification is referred to as the “nonmagnifying condition” hereafter.Although rDNA magnification likely occurs in wild-type animals to support transgenerational maintenance of rDNA CN , rDNA ma Methods ] are useffspring A. When bZ9 locus A. In conNA locus A. The coz9bb/Y0bb)  . Howeverz9/Ybb0) , R2 knocz9/Ybb0) E. These Because the increased DSB formation in GSCs under magnifying conditions is dependent on R2, we reasoned that DSBs primarily being induced in GSCs but not SGs may be due to biased expression of R2 in GSCs compared to SGs under magnifying conditions E.We examined the expression of R2 by RNA in situ hybridization under nonmagnifying and magnifying conditions. RNA in situ hybridization allowed single-cell resolution, enabling us to determine in which cell type R2 is expressed A and B. The fact that DSB formation and R2 expressions are more prominently induced in GSCs compared to SGs suggests that rDNA magnification may be a unique feature of GSCs. Moreover, we previously showed that R2’s requirement in rDNA magnification was limited to early germ cells (GSC to 2-cell stage SGs) because knockdown of R2 in >4-cell stage SGs did not have any impact on rDNA magnification , suggestTo further assess this idea, we used computer simulation to evaluate the impact of USCE in GSCs vs. SGs on rDNA CN change. We considered two questions: 1) how does biased or unbiased inheritance of USCE products during asymmetric GSC divisions impact rDNA CN? and 2) how does USCE during symmetric SG divisions impact rDNA CN?Top), GSCs would continue to lose rDNA CN, which results in all future GBs inheriting rDNA loci from GSCs that had lost the rDNA CN. Overall, in this scenario, it is expected that GBs’ rDNA CN (thus sperm’s rDNA CN) gradually decrease over time. In contrast, in the second scenario, where GSCs inherit sister chromatid that gained rDNA CN (Bottom), GSCs gradually increase rDNA CN, and so do GBs: Although GBs inherit lower rDNA CN than GSC for each division, their rDNA CN will increase over successive GSC divisions because GBs’ DNA is synthesized using GSCs’ DNA, which continuously increase rDNA CN.The first question is prompted by empirical evidence suggesting that GSCs appear to inherit more rDNA CN than GB during magnification . However rDNA CN A, BottomMethods). The initial rDNA CN was set either at 200 (for nonmagnifying condition) or 100 (for magnifying condition), although the pattern of rDNA CN increase or decrease over time is not expected to be impacted by initial CN. The frequency of GSC inheriting increased rDNA CN was set at 80%, 50% (random), or 20%. The frequency (80% or 20%) were chosen because we observed that the frequency of nonrandom sister chromatid segregation was around 80%  may affect rDNA CN. We modeled potential scenarios of USCE in mitotic germ cells, incorporating parameters drawn from empirical data , with the mean CN being 136.3 and 135.9, respectively. These results imply that USCE in GBs/SGs has little, if any, contribution to overall rDNA CN in sperm.While USCE in GBs/SGs alone does not appear to explain rDNA magnification, it is possible that USCE in these cells serves as a mechanism to enhance rDNA CN expansion in combination with USCE in GSCs. Therefore, we modeled the scenario where both GSCs and GBs/SGs undergo USCE E. SimilaTaken together, our empirical evidence and computer simulation support a model of rDNA magnification, in which USCE in GSCs generates rDNA CN asymmetry, followed by biased inheritance of improved rDNA CN by GSCs. Moreover, GSCs are the major contributing source of rDNA CN expansion, whereas USCE in differentiating germ cells (GBs/SGs) has no major contribution to rDNA CN increase.The simulation suggested that USCE in GBs/SGs has minimal potential to facilitate rDNA magnification D and E. bam-gal4 driver (bam > R2) (bam > R2 indeed induces DSBs (monitored by γH2Av staining) in ≥4 cell SGs, where bam-gal4 is expected to be active .To test whether SG are sensitive to rDNA magnification-inducing DSBs, we expressed R2 in ≥4 cell SGs using am > R2) . We confbam-expressing SGs). Therefore, we propose that R2 is primarily up-regulated in GSCs under magnifying conditions to protect SGs from cell death, which have higher DNA damage sensitivity.Upon expression of R2, the gross anatomy of the testis appeared to be normal in newly eclosed males, compared to wild type. However, after 2 wk, we observed a marked decrease in the numbers of SG and postmitotic SC cysts D–G. The Because rDNA repeats are essential but unstable genetic loci, it is critical to maintain their CN for the germline lineage to continue. This is akin to the need of telomere maintenance for germline immortality , 31. rDNbobbed (bb)” chromosomes, which have lower-than-threshold rDNA CN , supports the USCE model and explains the observations that were originally deemed inconsistent with USCE as the source of rDNA magnification. First, the emergence of offspring that recovered rDNA CN more than twofold was considered to be inconsistent with the USCE model unless multiple USCE events occurred in successive germline mitoses . The preOur study reveals an interesting “division of labor” between GSCs and SGs, where GSCs are specialized for rDNA magnification through USCE and SGs are specialized in the maintenance of genome integrity with their higher sensitivity to DNA damage. This division of labor may provide an answer as to why GSCs undergo consistent asymmetric divisions. The asymmetric fate of GSC division (producing one GSC and one GB) was initially interpreted as simply a mechanism to maintain tissue homeostasis by generating one stem cell and one differentiating cell . However384250In summary, the present work establishes GSCs as a unique cell population capable of achieving USCE-mediated rDNA magnification, thereby maintaining germline immortality. Our study provides an insight into how characteristic properties of these specific cell types contribute to the mechanisms that maintain vulnerable rDNA loci (and perhaps other tandemly repeated DNA), a common challenge most eukaryotes face.Z9y w bb (1 eq1y–/Df(YS)bb (DGRC #101260), y w; nos-gal4   . All aniTestis Immunofluorescence staining was performed as previously described . In shorRNA in situ hybridization samples were prepared as previously described . In short test. For multisample comparison of germ cell cyst number  test.For analyses that quantified percent γH2Av or R2 positive cells  and 3, wt number G, signifP > 0.95 for both directions, supporting that the two groups might be different within 2 copies of rDNA, but they fall into this equivalence range. The distribution and the median of the rDNA CN in sperm are plotted. The custom code used to simulate the rDNA CN is available on GitHub (https://github.com/TomoKumon/).For each stem cell lineage, the stem cell divides every 12 h for 2 wk , and each stem cell division generates 16 sperm due to four mitotic divisions in SG/GB. For each round of stem cell division, USCE may occur in GSC or SG/GB at frequencies specified in each panel of Dataset S01 (DOCX)Click here for additional data file.


Therefore, the additional annual irrigation water needs for the newly established fields between 2003 and 2022 cultivated to cash crops rose by 696 million l. To detect LUC effects on soil quality, soil samples of onion and garlic fields of different ages were collected employing a false-time-series approach. Results reveal increasing soil pH and salt concentrations and falling ground water tables, which reflects a negative water balance and ground water extraction above recharge levels. Our study provides evidence that the newly established telecoupled production systems on Mont Bagzam threaten the sustainability of existing local agricultural production and related livelihoods of agro-pastoralists.Little is known about the long-distance telecoupling effects of urban food demands on land use changes (LUCs) in remote oases of the Southern Sahara. Using the example of two typical oasis settlements on Mont Bagzam in the southern Aϊr Mountains of Niger which are linked to regional and global markets by an unpaved road since 2015, this study aimed at analyzing time trajectories of LUCs and related changing agricultural production patterns. LUCs were quantified for 1955 to 2022 using GIS-based mapping of agriculture and natural vegetation based on historical aerial photographs, CORONA and multi-spectral satellite images, and high resolution drone-based surveys. The results show a major increment in actively used agricultural land in the 850 ha watershed of the two oases from 11 ha in 1955 to 13 ha in 2003 and 68 ha in 2022 as well as the addition of 92 irrigation wells to 16 existing ones between 2003 and 2022. LUCs and evapotranspiration calculated from climatic data of a local weather station allowed to estimate changes of irrigation water needs in the selected watershed. While annual precipitation averages only 214 mm, local reference evapotranspiration may reach 1,476 mm year Oasis agriculture dates back to prehistoric times and is one of the most durable modes of farming and managing scarce natural resources –3, such While the role of North African and Arabian oasis settlements as remote production locations for local food production and often ancient trading hubs is well documented, there is very little data on the evolution of oases in the Saharan Desert of Niger. This is all the more surprising as they have for long played a significant role for transnational trading of goods ,13,14 anLocated at the southern fringe of the Saharan Desert, the Aïr Mountains with their highest peak Idoukal-n-Taghès (2022 m above sea level (asl)) on the massif of Mont Bagzam, are sparsely populated by sedentary Kel Ewey Touareg settling in different oases and practicing agro-pastoralism since many centuries . The spaTriticum aestivum L.), barley (Hordeum vulgare L.), millet (Pennisetum glaucum L.), and alfalfa (Medicago sativa L.). Traditionally also grown on the ancient, deep volcanic soils are vegetables such as potato (Solanum tuberosum L.), onion (Allium cepa L.), and cabbage (Brassica oleracea L.) sometimes intercropped with fruit trees such as citrus (Citrus L.), fig (Ficus carica L.), lime (Citrus × latifolia), pomegranate (Punica granatum L.), and date palm (Phoenix dactylifera L.). The latter are part of the classical three-story agroforestry arrangement fostering agricultural productivity through decreasing air temperature and maintaining higher air humidity inside the oasis [For many decades on Mont Bagzam traditional oasis gardens were either irrigated by spring water channeled through canals to the fields or by human- or animal-powered draw wells limited to fetching groundwater close to the surface and irrigating small basins. Cultivated subsistence cereals comprised wheat  a time trajectory of available remote sensing datsets allows to detect land use changes (LUCs) at sufficient resolution to match them with survey records and (ii) the observed changes in land use patterns affect the sustainability of the agro-ecosystems as indicated by increased pressure on water resources and soil quality.Mont Bagzam in the south of the Aϊr Mountains of Niger consists of a dissected and heavily eroded plateau of peralkaline granites intersected by metamorphic rocks and ancient Cenozoic volcano chimneys surrounded by vast areas of lawa debris. The plateau comprises twelve small-scale oasis systems, which are partly connected by unpaved roads . Despitesāqiyah) of fetching ground water.Our study focused on the approx. 100-year-old oasis of Emalawlé  and the 70-year-old oasis of Aoukadédé  with their watersheds comprising a total area of 820 ha. The old oasis centers contain irrigated gardens divided over generations according to traditional maternal inheritance rights. This takes account of traditional Tuareg livelihood strategies in which husbands are absent during a sizeable part of the year practicing caravan trade, while their wives are responsible for the household and childcare. In Emalawlé agricultural plots are irrigated in 5–7 day intervals from one collectively managed spring, while fields in Aoukadédé and most newly established fields are daily irrigated from individually managed wells nowadays almost all equipped with motor pumps rather than the traditional animal driven, low-capacity systems  installed in July 2021 in the village of Emalawlé. These data complemented rainfall records determined with a traditional pluviometer from 2005–2022 .Average monthly temperatures varied between 13°C and 30°C whereby summer temperatures may reach 40°C in the shade and 57°C in full sunshine while winter temperatures can fall down to -2°C. The average daily solar radiation amounts to 51,700 LUX between 6:30 am and 6:30 pm, whereby maximum radiation values may reach 130,000 LUX. Relative air humidity is highest during the short rainy season in July/August with a daily maximum of 76% in August and in January with 40%, while during the other months of the year it remains < 25% .Allium sativum, November–May) and onion (July–October) followed by a short fallow period in June. Parts of some fields are also cultivated with potato from February until November. To simplify the assessment of the crop evapotranspiration demand of these fields, we assumed that they comprised a crop rotation of irrigated garlic and onion without fallow periods.For the assessment of changes in crop water requirements due to the establishment of new large-scale fields in the studied watershed, the monthly crop evapotranspiration demand under optimal agronomic and soil water conditions was estimated. Most of these new fields are cultivated with a simple cash crop rotation of garlic (c) for onion and garlic was computed in monthly time intervals as:0 is the reference evapotranspiration (mm day-1) and kc is the crop coefficient that depends on crop type and development stage. ET0 refers to the evapotranspiration from a well-watered hypothetical grass surface with a fixed crop height, albedo and surface resistance [Therefore, the potential crop evapotranspiration  were defined using the single crop coefficient approach [c ini whereby during crop development crop coefficients increased by constant daily rates to the level given by kc mid. For the mid-season period, crop coefficients were constant at kc mid and for the late season stage, crop coefficients were assumed to decline steadily to the value given by kc end  monthly averages of the previously described climatic measurements of shade air temperature , solar radiation, shade humidity, and wind speed were used , G for the soil heat flux density (MJ m-2 day-1), T is the mean daily air temperature (°C), u the wind speed at 2 m height (m s-1), es the saturation vapor pressure (kPa), ea the actual vapor pressure (kPa), ∆ the slope of the vapor pressure curve (kPa°C-1), and γ stands for a psychrometric constant (kPa°C-1). Average wind speed (u) was set to 2 m s-1 and soil heat flux (G) to 0 as its magnitude is usually small [ETns) and the outgoing net long wave radiation (Rnl):s stands for the incoming short wave radiation (MJ m-2 day-1). Net outgoing long wave radiation (Rnl) was determined as:−9 MJ K-4 m-2 day-1, Tmax,K for the daily maximum temperature (K), and Tmin,K for the daily minimum temperature (K). The short wave radiation Rs0 on a clear-sky day (MJ m-2 day-1) was set equal to Rs since on Mount Bagzam clouds usually only occur during the short rainy season.Net radiation was computed as the difference between incoming net short wave radiation (Rs) is closely related to air temperature, it was calculated as:max)) and minimum (e°(Tmin)) air temperatures. The values of e° were also taken from a reference table [As the mean saturation vapor pressure (ece table .a) can be calculated from the relative humidity:max stands for the maximum relative humidity (%) and RHmin for the minimum relative humidity (%).The actual vapor pressure (epan) was measured using a water bucket  since a standard Class-A evaporation pan was not available [pan is related to ET0 by an empirically derived pan coefficient (Kp) and was therefore computed as:p) was defined as 0.45 for a low humidity area, with medium wind speed and a dry fallow area [For verification of calculated ET a real “pan” evaporation processing was performed using the open-source Quantum GIS software (QGIS vers. 3.10). Thereby Landsat scenes were atmospherically corrected with the Semi-Automatic Classification Plugin  which acAs an indicator for live green vegetation monitoring, the Normalized Difference Vegetation Index (NDVI) is commonly used since the respective red (R) and near infrared (NIR) satellite bands contain over 90% of the vegetation information :NDVI=  Fig 5) sTogether with the collection of 40 GTPs distributed across the area and the recording of all field boundaries in April/May 2021 using a handheld GPS [To investigate farm-based causes for land use changes on Mont Bagzam as a result of market demand-driven production of onion, garlic, and potato, all gardens of the study region were visited, and a total of 35 household surveys were conducted . The farming households were asked about property rights, ages of their gardens, agricultural practices including inputs and yields as well as about temporal changes in cropping patterns . The ansTo assess the effects of land use changes on irrigation water needs (IN) for cash crop production, the amount of additional evapotranspiration demands of onion and garlic was calculated for the newly cultivated area from 2003 onwards, since before that date crop production was subsistence-oriented.-1) was estimated for crop water supply by a combination of irrigation and rainfall [c (mm year-1) is the potential crop evapotranspiration and Pe (mm year-1) the yearly sum of effective precipitation.To this end, the IN  was calculated after [2) refers to the difference in cropping land between 2003 and 2022 and IN (l m-2 year-1) the annual irrigation needs for onion and garlic fields.The yearly irrigation water needs of the additional irrigated area  plus an unquantified amount of sheep and goat manure, cultivated, and harvested manually. Soil collection was performed by extracting five samples (0–10 cm) diagonally in each field before pooling. All samples were analyzed for soil pH, soil organic carbon (SOC), carbon/nitrogen (C/N) ratio, electrical conductivity (EC), exchangeable and extractable phosphorus (P) and potassium (K), and extractable calcium (Ca), magnesium (Mg), sodium (Na), iron (Fe), and aluminum (Al) as described elsewhere .3 and MgCO3), measured by a calcimeter, from the total carbon content. Extractable nutrient contents in the soil including P, K, Ca, Mg, Na, Fe, and Al were measured with an Inductively Coupled Plasma–Optical Emission Spectrometry (ICP–OES), after an Aqua Regia digestion. Plant available (exchangeable) P and K were determined with the ICP–OES after a calcium-acetate-lactate (CAL) extraction [Prior to analyses all soil samples were air-dried, sieved to < 2 mm particle size, and visible plant roots were removed. Soil pH was determined at a soil/water ratio of 1/2.5 by a glass electrode . EC was recorded using a digital conductivity meter  at a soil/water ratio of 1/2.5. Soil total C and N were measured by a thermal conductivity detector . SOC was determined by deducting the soil inorganic carbon content  to determine the relationship between different durations of cultivation and key soil parameters, defined by the Pearson correlation coefficient at p < 0.05. Soil salinity was expected to increase with duration of field cultivation given a negative water balance between evapotranspiration and precipitation at regular irrigation. SOC was expected to be low given the only recent onset of soil cultivation, sparse natural vegetation, and high turnover rates of organic carbon due to the prevailing climatic conditions .The study was authorized by the Ministre de l’Enseignement Superieur et de la Recherche, Niamey, Niger under Permit N°00206 of 28/02/2022 while the data collection procedure and subsequent use of the data was approved by the Central Ethics Committee of the University of Kassel, Germany.Since the construction of an unpaved road in 2015 connecting the villages of Mont Bagzam to the major regional marketplace of Agadez, agricultural production expanded and several new gardens cultivated with cash crops evolved, not only in the watershed between Aoukadédé and Emalawlé, but on the entire Mont Bagzam. A multitude of new wells were established, operated with diesel water pumps, for the irrigation of new, comparatively large-scale fields with cash crops between the old oasis centers.The NDVI analyses of Landsat images of the selected watershed of Emalawlé and Aoukadédé showed an increase in the area of dense vegetation (cropland and trees) from 0.3 ha in 1987 and 13.2 ha in 1994 to 15.3 ha in 2014 and 12.2 ha in 2016, to 33.5 ha in 2018, and 42.8 ha in 2021 . The areFor the time span of 1955 until 2003  the results of manual land use classifications indicated an increase in cultivated land area of only 20%, while during the past eight years land under cultivation has tripled. Prior to 2000 the inhabitants lived in small tent type structures and clay houses, whereas from 2003 onwards increasingly cemented structures using stones and loam were identified. Since 2014 the watershed of Emalawlé and Aoukadédé underwent massive changes in agricultural land and groundwater use with sprawling new fields in formerly lawa rubble-covered areas .Field sizes in the old oasis of Emalawlé averaged 0.25 ha, whereas newly established fields since 2016, surrounded by protective fences, have average sizes of 1.7 ha. Most of the newly established fields belong to the population of Emalawlé who managed to clear the newly acquired land from stones and bushes with the help of cheap hired labor from Houssa lands in southern Niger or Nigeria .Traditional palm groves and fruit trees are only cultivated in the old oasis centers, whereby the fruits of 470 palm trees counted in 2022 serve no longer as an income source since their manual fertilization and harvest is too costly compared to the procurement of higher quality imported dates. Typically, every new field has an individual well, up to 20 m deep and operated by a motor pump. From 2003 to 2022 the total number of operational wells in the watershed has increased from 16 to 108.The records of agricultural produce in the storage facility at Tokadi showed that garlic, onion, and potato are the only exported products from Mont Bagzam . In the 0) calculated by climatic data from August 2021 –August 2022 amounted to 1,476 mm year-1. Monthly ET0 was highest in May with 153 mm and lowest in January with 85 mm. Actual pan evapotranspiration (ETpan) was measured from December 2021 –December 2022 and amounted to 2,699 mm year-1. The derived actual ET0 pan was 1,215 mm year-1, thus 18% lower than the potential ET0 derived from climatic data . However, there was a tendency of increasing pH and Na over time . Especia-1 soil on average) and Fe (28.05 mg g-1 soil in average) reflecting long periods of basalt weathering.C/N ratios slightly declined with cultivation time of newly established fields whereby SOM and SOC contents were generally low . Exchangeable P slightly increased over time, whereas exchangeable K declined . All soiThe results of our remote sensing analyses combined with ground truthing provide evidence of massive changes in the 820 ha watershed of Emalawlé and Aoukadédé within the past seven years. Prior to road construction in 2015 agricultural activities were determined by subsistence needs of the local population. Therefore, crop production was dominated by cereals and vegetables cultivated on small terraces. Dates, millet, and surplus animals were traded against salt and other necessities by camel and donkey ,15. AfteThese human-induced changes were reflected in our time series analyses of NDVI values and LUC data obtained from manual classification of agricultural fields. However, NDVI analyses also showed that the distribution and quality of sparse vegetation, apart from human and grazing activities, heavily depend on the amount and distribution of rainfall in the year of analysis and the precedent one. These dependencies are in line with other studies applying NDVI for identifying LUC ,37. The Data on exported agricultural produce from Mont Bagzam reflects the reported changes in land use whereby a doubling of agricultural land in Emalawlé between 2020 and 2022 led to an increase in marketable onion by 60% in the respective time interval. The focus on onion production coincides with the rising national net export numbers for onion to meet market demands of neighboring countries, especially Ghana, Ivory Coast, and Benin ,39. EvenRather than climate change, stated as a major threat for agricultural systems in other arid and semi-arid regions ,43, the e/ET0 = 1/10 and the reliance on rainwater for irrigation, sustainable intensive agriculture under surface irrigation will require reliance on a large impluvium area and improved retention of runoff water from the temporary water streams (“Wadi” or “Kori”) that drain Mont Bagzam’s floodwaters to the foothills. The agricultural exploitation of large areas cleared from bushes and stones results in increasing risks of runoff leading to enhanced soil erosion and flooding events as demonstrated by other studies on mismanagement in dryland farming systems [The focus on growing cash crops on an area that grew by 55 ha in the last two decades requires annual application of additional 696 million l irrigation watercompared with small-scale and low-input subsistence farming before 2014 on 13 ha. The ongoing expansion of land and the related construction of wells have already led to a reported falling of groundwater levels across the plateau of Mont Bagzam and drying up of village wells. Given a yearly ratio of P systems ,50.Soil sample analyses of Aoukadédé and newly established fields of Emalawlé revealed slightly increasing pH levels and trends for rising Na concentrations in the topsoil with cultivation time. The observed imbalance between rainfall, evapotranspiration, and water inputs as well as the unsuitability of monocropping cash crops under these conditions may be reflected in rising pH levels, EC, and Na concentrations in the future . Our surTo ensure future livelihoods on Mont Bagzam, maintenance of agricultural production on increasing fields will require introduction and widespread use of water harvesting approaches such as deviation of runoff water and interception in cisterns or “false wells” and the application of drip irrigation and mulching. The effectivity of such water and land care approaches has been successfully demonstrated in the Middle East ,53, but Onions produced on Mont Bagzam are a prime example of how telecoupling of production and consumption driven by booming urban markets of the sprawling West African coastal cities across distances > 2500 km under very difficult infrastructural conditions offers new livelihood opportunities . In a wiEven though the identified changes in agricultural production and implications for water use and soil fertility within this study applying a mixed-methods approach seem consistent, further studies are needed. Detailed climatic data have only been recorded for one year and soil parameters and changes using a false-time-series approach were determined on a limited number of locations with IN being calculated by using a simplified approach. To further assess implications of land use transformation for these marginal agroecosystems over time, investigations should also be done on available groundwater resources. Water use efficiency needs to be calculated field- and crop-based and field tests are needed to monitor effects of alternative cropping systems using drip irrigations and agroforestry gardening for cash crop production.Transformation of oasis systems on Mont Bagzam in Niger is triggered by rapid growth of the local population and new marketing opportunities in remote urban centers for high quality, easily storable, and bulk-transportable cash crops thriving under desert conditions. While in the short-term, rural populations on Mont Bagzam take great advantage of this new income opportunities, our data indicate that in the longer-term over-exploitation of rain-dependent water resources and declining soil fertility threatens sustainable agricultural land use and social coherence. The far-reaching telecoupling effects of global food supply networks on rural marginal areas are often neglected although they may severely endanger the preservation of biodiversity, traditional knowledge, and ultimately cultural identity. Therefore, more integrated trans-boundary approaches of land use and related policies are required that foster the economically profitable and sustainable use of marginal areas with highly fragile ecologies that undergo rapid regime shifts as a consequence of global, urbanization-driven rural-urban transformation.S1 TableQuantities of onion, garlic and potato registered at the storage facility of Tokadi from May 2020 to May 2022.(XLSX)Click here for additional data file.S2 TableSoil chemical properties (0–10 cm) of selected onion and garlic fields (n = 27) in the oases of Emalawlé and Aoukadédé taken in 2021 and 2022.(XLSX)Click here for additional data file.S1 File(PDF)Click here for additional data file.


Pelvic organ prolapse (POP) refers to symptomatic descent of the vaginal wall. To reduce surgical failure rates, surgical correction can be augmented with the insertion of polypropylene mesh. This benefit is offset by the risk of mesh complication, predominantly mesh exposure through the vaginal wall. If mesh placement is under consideration as part of prolapse repair, patient selection and counseling would benefit from the prediction of mesh exposure; yet, no such reliable preoperative method currently exists. Past studies indicate that inflammation and associated cytokine release is correlated with mesh complication. While some degree of mesh-induced cytokine response accompanies implantation, excessive or persistent cytokine responses may elicit inflammation and implant rejection.Here, we explore the levels of biomaterial-induced blood cytokines from patients who have undergone POP repair surgery to (1) identify correlations among cytokine expression and (2) predict postsurgical mesh exposure through the vaginal wall.Blood samples from 20 female patients who previously underwent surgical intervention with transvaginal placement of polypropylene mesh to correct POP were collected for the study. These included 10 who experienced postsurgical mesh exposure through the vaginal wall and 10 who did not. Blood samples incubated with inflammatory agent lipopolysaccharide, with sterile polypropylene mesh, or alone were analyzed for plasma levels of 13 proinflammatory and anti-inflammatory cytokines using multiplex assay. Data were analyzed by principal component analysis (PCA) to uncover associations among cytokines and identify cytokine patterns that correlate with postsurgical mesh exposure through the vaginal wall. Supervised machine learning models were created to predict the presence or absence of mesh exposure and probe the number of cytokine measurements required for effective predictions.PCA revealed that proinflammatory cytokines interferon gamma, interleukin 12p70, and interleukin 2 are the largest contributors to the variance explained in PC 1, while anti-inflammatory cytokines interleukins 10, 4, and 6 are the largest contributors to the variance explained in PC 2. Additionally, PCA distinguished cytokine correlations that implicate prospective therapies to improve postsurgical outcomes. Among machine learning models trained with all 13 cytokines, the artificial neural network, the highest performing model, predicted POP surgical outcomes with 83% (15/18) accuracy; the same model predicted POP surgical outcomes with 78% (14/18) accuracy when trained with just 7 cytokines, demonstrating retention of predictive capability using a smaller cytokine group.This preliminary study, incorporating a sample size of just 20 participants, identified correlations among cytokines and demonstrated the potential of this novel approach to predict mesh exposure through the vaginal wall following transvaginal POP repair surgery. Further study with a larger sample size will be pursued to confirm these results. If corroborated, this method could provide a personalized medicine approach to assist surgeons in their recommendation of POP repair surgeries with minimal potential for adverse outcomes. Pelvic organ prolapse (POP), defined as symptomatic descent of the vagina and surrounding pelvic organs, affects approximately 50% of parous women and 6% of nonparous women between ages 20 and 59 years , with alInflammatory responses are associated with mesh exposure due to asymptomatic mesh infection that inhibits the mesh from integrating with the surrounding environment . While sLeveraging a patient-specific, multifaceted immune response for the prediction of postsurgical complications is an ideal problem for the application of principal component analysis (PCA) and supervised machine learning models. In fact, this approach has been used to predict complications following other surgical procedures as well as progressive disease outcomes. In a liver transplant study, Raji and Vinod Chandra  applied PCA and supervised machine learning have also been applied to biological measurements for predicting medical outcomes. Tseng et al  built a The application of PCA and machine learning to predict postsurgical complications in women after POP surgery has also shown promising results. In the study of Jelovsek et al , statistIn this preliminary study, we explored the levels of baseline and stimulus-induced cytokines in blood isolated from patients who had undergone POP repair surgery with a polypropylene mesh. Proinflammatory and anti-inflammatory cytokine levels from these data were analyzed using PCA to establish the principal components (PCs) and to identify associative or opposing trends among cytokines. In addition, supervised machine learning models were applied to demonstrate predictive capabilities when models were trained with either all 13 cytokines or a smaller group of 7 cytokines determined most effective by a random forest method. The results demonstrate that leveraging PCA and supervised machine learning models to predict outcomes of vaginal mesh implantation has the potential to benefit future patients when they are faced with this surgical decision, which carries a relatively high risk of unsuccessful surgical outcome.t test based on an a priori power analysis, which indicates the number of patients for a given theoretical minimum study power as a function of the expected difference between patients with and those without mesh exposure, or the Cohen d. We assumed a conservative study power of 0.80 and a 100%, or 2-fold, difference in the level of a given cytokine between individuals with and without mesh exposure, equivalent to a Cohen d of 1. Here, 20 patients with equal distribution among the 2 groups are needed to observe the difference with a probability of .1. Participants with POP recurrence or taking medications that would alter inflammatory response were excluded from this study.In total, 20 healthy, nonpregnant female participants aged 56-89 years at Prisma Health Greenville Memorial Hospital with a history of surgical intervention to correct POP via a procedure that used polypropylene mesh were selected for the study. The participants, who were not matched, included 10 who experienced postsurgical mesh complication in which the implanted mesh protruded through the vaginal wall  and 10 participants who did not experience this complication post surgery. This sample size was estimated as an effective cohort for the pilot study using a 1-tailed The study protocol was approved by the institutional review board (IRB) of Prisma Health (Pro00067964). Informed consent from all study participants was obtained using an IRB-approved informed consent form. All samples collected and data analyzed were deidentified and followed IRB protocol.Blood samples were obtained from the 20 selected participants. Approximately 12 mL of blood was drawn from the upper extremity of each participant into 3 BD Vacutainer EDTA-coated tubes. Deidentified blood samples were then transferred on ice to a laboratory facility at the University of South Carolina School of Medicine Greenville for immediate processing. Each participant’s blood sample was divided into equal aliquots for 24-hour incubation at 37 °C under 3 distinct conditions: (1) incubation with inflammatory agent lipopolysaccharide (LPS) at 20 ng/mL (positive control), (2) incubation with sterile polypropylene mesh area of 2 cm × 2 cm , and (3) incubation alone (negative control). After incubation, the plasma layer was collected following centrifugation  and immediately stored at –80 °C.Cytokine levels in each blood sample were quantified using the bead-based MILLIPLEX Human Cytokine/Chemokine/Growth Factor Panel A—Immunology Multiplex Assay (EMD Millipore Corp), which is composed of analytes for target cytokines interleukin 1α (IL-1α), IL-1β, IL‑2, IL-4, IL-6, IL-8, IL-10, IL-12p40, IL-12p70, IL-17A, interferon-gamma , and granulocyte-macrophage colony-stimulating factor (GM-CSF). Frozen plasma samples were thawed at room temperature and analyzed following Milliplex protocol guidelines. Cytokine concentrations were measured using a Bio-Plex 200 (Bio-Rad) and Bio-Plex Manager software (Bio-Rad). Sample volume was doubled to ensure measurable levels of cytokines, and assay output data were adjusted to reflect concentrations in plasma samples. Each multiplex assay was performed in duplicate, and cytokine levels were evaluated in 3 independent measurements.Cytokine data gathered from the multiplex immunoassay were analyzed using data mining and predictive analytical methods. PCA was used to identify important cytokines by studying their contributions to each PC as well as to discern associations between cytokines. Supervised machine learning models were created to determine whether cytokine levels can accurately predict which patients are more likely to experience mesh exposure post surgery.The statistical programming language R  was used to analyze raw cytokine data values generated from the multiplex immunoassay. The imported data structure contained 60 observations (20 participants × 3 independent measurements) and 40 total variable fields (13 cytokines × 3 blood treatments + 1 target variable). The target variable was the participant’s outcome, which indicated a postsurgical complication that participants might have experienced following POP surgery. Observations marked “presence” represent participants who experienced mesh exposure through the vaginal wall. Observations marked “absence” represent participants who did not experience any mesh exposure through the vaginal wall. Univariate and multivariate methods were used to explore the data set, including identifying missing values, analyzing outliers, and visualizing frequency distributions.is the sample mean and ix and n are the individual observations and number of observations, respectively, within the sample [z-score standardization was also applied to scale each cytokine variable, thus ensuring that the mean was equal to 0 and SD equal to 1. Biplots were created to visualize PCs with the highest degree of variance explained. The eigenvectors were overlayed on the biplots to visualize correlations and identify hidden patterns between cytokines.PCA was performed using the FactoMineR package   to idente sample . Each cySupervised machine learning models were created using the caret package   in the RAdditionally, this process was replicated to study the effects of reducing the number of cytokines needed to predict a postsurgical mesh exposure. A random forest algorithm was used to select important cytokines for this study. These models were trained and tested for accuracy, sensitivity, and specificity as detailed above. The results are compared to models trained with all 13 cytokines.To identify significant associations among the cytokines, PCA was used to examine a total of 60 blood samples (20 participants × 3 blood treatments). Among the 20 participants, 10 experienced postsurgical mesh exposure through the vaginal wall and 10 did not. When PCA was used to examine only blood samples incubated with polypropylene mesh, PC 1 and PC 2 explained 60.1% and 13.1% of the total data variance, respectively B. FigureIn order to visualize associations between the participants presenting the absence or presence of postsurgical mesh exposure through the vaginal wall, a biplot illustrating individual participants was created . This biFour supervised machine learning models incorporating all 13 cytokines were trained using 70% (42/60) of the available 60 observations (20 participants × 3 independent measurements); the remaining 30% (18/60) was used to test the models’ accuracy when predicting the presence of mesh exposure through the vaginal wall. All 4 machine learning machines achieved at least 62% (26/42) training accuracy . ArtificAdditional models and predictive analyses explored whether a smaller set of cytokines could achieve similar predictive results. Feature selection using a random forest method identified a group of 7 cytokines capable of yielding effective predictive analysis: IL-1β, IL-8, IL-12p40, IL-12p70, TNF-α, IL-17A, and IL-6. Among patients with POP who undergo mesh implantation surgery, 17% of them experience mesh exposure through the vaginal wall . This raThe PCA analysis illustrated in The cytokines that contribute most to each PC segregate into proinflammatory and anti-inflammatory cytokines . When cyWhen juxtaposing the biplot of polypropylene-stimulated cytokine observations B with thWhen creating models trained with a subgroup of 7 cytokines , selecteThis study implemented rigorous research methods to identify physiological relationships among cytokine markers and developed robust machine learning models to predict mesh exposure; yet, some limitations should be noted. First, because this is a pilot study, the sample size is limited to 20 participants within a single hospital system. Nevertheless, this limited sample size predicted 83% (15/18) accuracy, a level that compares favorably with another predictive model study by Chu et al  that achWhile this preliminary study is limited to a sample size of just 20 participants, this novel approach to using cytokine response to predict POP surgical outcomes has successfully distinguished important cytokines and their correlations. Moreover, these relationships point toward prospective therapies that could promote better surgical outcomes. Supervised learning models also demonstrate a high level of accuracy, specificity, and sensitivity, even when a smaller group of cytokine data is used. This result suggests that blood cytokine analysis might be feasibly used in a clinical setting to predict POP surgical outcomes. Further study with a larger patient population will be needed to confirm the utility of this method. If successful at a larger scale, this approach has the potential to change perspectives in which surgeons would recommend and proceed with POP repair surgeries and to prevent undesired outcomes of mesh-related surgeries in patients.


All but one patient underwent a one-stage reconstruction including neurolysis and extra-anatomical nerve transfer alone (n = 2) or combined with anatomical reconstruction by sural nerve grafts (n = 2). One patient underwent a two-stage reconstruction, which involved a first stage anatomical brachial plexus reconstruction followed by a second stage nerve transfer. Neurotizations were performed as double (n = 3), triple (n = 1) or quadruple (n = 1) nerve or fascicular transfers. Overall, at least one year postoperatively, successful results, characterized by a muscle strength of M3 or more, were restored in all cases, two patients even achieving M4 grading in the elbow flexion. This patient series challenges the widely held dogma that brachial plexus reconstruction in older patients will produce poor outcomes. Distal nerve transfers are advantageous as they shorten the reinnervation distance. Healthy, more elderly patients should be judiciously offered the whole spectrum of reconstructive methods and postoperative rehabilitation concepts to regain useful arm and hand function and thus preserve independence after a traumatic or nontraumatic brachial plexus injury.Negative expectations regarding nerve reconstruction in the elderly prevail in the literature, but little is known about the effectiveness of nerve transfers in patients with brachial plexus injuries aged over 60 years. We present a series of five patients  aged between 60 and 81 years (median 62.0 years) who underwent nerve reconstruction using multiple nerve transfers in brachial plexopathies. The etiology of brachial plexus injury was trauma ( Traumatic brachial plexus injuries mostly affect active male individuals in their second or third decade of life and cause enormous morbidity. Nerve transfers have been established as standard treatment, in addition to microsurgical neurolysis, direct repair and interposition grafting . Highly Responsible factors for nerve regeneration have been studied intensively in animal models, with clear evidence of age-related impairment in nerve regeneration . FunctioAlthough there are limiting factors for nerve regeneration in senescence, there may be a role for nerve reconstruction procedures in improving functional outcome. As a general rule, nerve transfers are a reliable method in brachial plexus surgery with specific advantages over nerve grafting . A shortThe purpose of this study was to investigate whether elderly patients with brachial plexus injury, defined as aged over 60 years, are suitable candidates for surgical restoration of upper extremity function using nerve transfers.In this retrospective, single-center analysis, all patients who met the following criteria were included: (1) received nerve reconstruction by the senior author using nerve transfers for a brachial plexus injury within the last decade; (2) aged 60 years or above; and (3) were available to long-term (>1 year) follow-up. This study has been approved by the institutional review board and all patients gave their informed consent.All patients underwent postoperative physiotherapy and occupational therapy following a structured rehabilitation program . An emphFunctional outcome of the reinnervated muscle group was assessed with the Medical Research Council grading system and measurement of active joint mobility. According to the distribution, normality data is displayed as either mean ± standard deviation (SD) or median ± interquartile range (IQR) for descriptive analysis. For each strength level (M0–M5), the range of motion of the respective joint is indicated.n = 2) and iatrogenic lesions through spinal surgical laminectomy, tumor excision and radiation for breast cancer (n = 3).A group of five patients  aged between 60 and 81 years  was identified. Specific patient characteristics are displayed in n = 2) or combined with anatomical reconstruction using sural nerve grafts (n = 2). One patient had anatomical brachial plexus reconstruction first and second stage nerve transfer. Nerve transfers were performed as single (n = 2), double (n = 1), triple (n = 1) or quadruple (n = 1) nerve or fascicular transfers. Mean delay of surgery after injury was 13 months (range 0–31). It is noted that one patient had a progressive brachial plexus palsy after irradiation therapy (P3) and another patient had immediate reconstruction post tumor resection in a one-stage procedure (P5). Detailed description of surgical procedures and outcome is shown in All but one patient underwent a one-stage reconstruction including neurolysis and extra-anatomical nerve transfer alone (n = 1), moderate weakness of index finger flexion improving over time (n = 1) and persistent co-contraction of the brachialis muscle and wrist/finger flexors (n = 1).Complications included transient painful paresthesia in the hand , but no detailed data on elderly patients was presented . Jain etAlthough our group size is limited, the patient characteristics suggest that etiology of injury in elderly patients differs from younger brachial plexus patients. While they can also suffer from traumatic accidents, reflecting their high activity level in sports and leisure time, a considerable proportion, three out of five in our cohort, were paralyzed due to age-typical non-traumatic reasons, i.e., malignancy and associated medical treatments  or other sequelae of age-related pathologies. However, supporting hand function through minor neurosurgical procedures, such as nerve transfers, can help patients maintain an active and healthy lifestyle even in their “aged” years.A number of experimental studies ,16 and cSimilar results were also documented for individuals of advanced age after nerve transfer operations. Weaker biceps strength after using a single ulnar fascicle transfer in patients with brachial plexus injuries led to the development of a double fascicle transfer by adding a median nerve fascicle to brachialis transfer ,18. ConsOn the other hand, more recently, three cases of successful nerve transfers of complex nerve lesions in elderly patients were published, of whom two were septuagenarians. Willis and Ahmadi in 2019 reported on a patient aged late 60s with radial-to-axillary nerve transfer, resolving axillary nerve palsy due to proximal humerus fracture-dislocation treated with hemiarthroplasty .These results are comparable with the favorable outcomes in our small series of five patients, which showed a high rate of successful restoration of at least antigravity muscle power for shoulder abduction and elbow flexion after nerve transfers. We attribute our positive results to a relatively short delay between nerve injury and muscle reinnervation, which is acknowledged as a crucial factor for functional recovery after nerve repair. Although increased patient age has been determined as an important negative factor in scientific studies with regard to impaired axonal regeneration, cortical reorganization and cognitive adaption, nerve transfers offer the advantages of shortened reinnervation distance and optimal donor nerve health ,23. The Furthermore, innovative rehabilitation concepts, such as early structured motor training using surface electromyography biofeedback , have deThe coordination of movements, which tends to be worse in the older population, was not specifically analyzed in this article . MarchinIt is remarkable that active learning of new motor skills and training brain plasticity through activities like dancing have been shown to improve physical and cognitive function and slow the decline in quality of life in geriatric individuals with dementia and Alzheimer’s disease . Thus, eElderly patients may soon become the most relevant population to benefit from cognitive nerve transfers to treat spasticity or paresis in upper motor neuron syndrome, i.e., due to stroke ,33. As l