Salmonella Enteritidis as the target organism. To do this, we studied (1) single vs. sequential PMAxx™ addition; (2) a wash step post-PMAxx™ treatment; (3) a change of tube post-treatment before DNA extraction. The single vs. sequential PMAxx™ addition showed no difference. Results signified that PMAxx™ potentially attached to polypropylene tube walls and bound the released DNA from PMA-treated live cells when lysed in the same tube. A wash step was ineffective but transfer of the treated live cells to a new tube minimized these false-negative results. Our optimized protocol eliminated 108 CFU/mL heat-killed cell DNA in the presence of different live cell dilutions without compromising the amplification of the live cells, minimizing false positives. With further improvements, vPCR has great potential as a culture-independent diagnostic tool.Viability PCR (vPCR) uses a DNA intercalating dye to irreversibly bind double-stranded DNA from organisms with compromised cell membranes. This allows the selective amplification of DNA from intact cells. An optimized vPCR protocol should minimize false positives (DNA from compromised cells not fully removed) and false negatives (live cell DNA bound by the dye). We aimed to optimize a vPCR protocol using PMAxx™ as the intercalating agent and  Real-time quantitative PCR (qPCR) is a molecular technique that is widely used in microbiological research and the clinical diagnostic setting. Using a high-volume, multi-analyte amplification platform, qPCR can identify multiple pathogens in a single clinical sample. The assay can provide high sensitivity, rapid turnaround time, and is less labor-intensive through automation ,2. HowevCurrent vPCR assays that use PMA involve a three-step process: addition of PMA to a cell suspension (live and/or dead cells), followed by an incubation period in the dark, and then photoactivation of PMA by exposure to intense visible light. After this treatment, cells are lysed to release the DNA for qPCR amplification. Ideally, as mentioned above, qPCR signals should be generated from only live cell DNA; however, there are pitfalls associated with current vPCR assays that lead to false-positive and false-negative results ,6. FalseNumerous approaches have been suggested by different investigators to improve the performance of vPCR assays such as (1) using better-performing viability dyes that are fully impermeant to intact cell membranes ; (2) comSalmonella is the most common gastroenteric pathogen reported to the National Enteric Surveillance program  was used to prepare a 2 mM PMAxx™ stock solution containing 20% dimethylsulfoxide  in sterile DNA/RNA-free water  which was stored at −20 °C in the dark until used. To preserve PMAxx™ ability to be activated by light, experiments were performed under minimal lighting conditions. −8 as a single or a sequential PMAxx™ treatment. For the single treatment, the reagent was added to each aliquot of 100 μL cell suspension to reach a final PMAxx™ concentration of either 50 μM (2.5 μL of 2 mM PMAxx™) or 100 μM (5 μL of 2 mM PMAxx™). After adding PMAxx™, the HK cell suspensions were incubated in the dark at room temperature for 10 min, followed by exposure to intense light using the PMA Lite™ LED photolysis device  for 15 min at room temperature. For the sequential treatment, two consecutive treatments of PMAxx™ (2.5 μL of 2 mM PMAxx™ × 2) were added to reach a final concentration of 100 μM, followed by dark and light incubations after each PMAxx™ addition. After the photoactivation(s), PMAxx™-treated HK cell suspensions  were centrifuged at 17,115× g for 5 min and the PBS supernatant with PMAxx™ was removed. Rapid lysis buffer was added to the original tube (where PMAxx™ treatment and photoactivation were carried out) to extract the DNA as described in PMAxx™ solution was added to serially diluted HK cell suspensions in PBS from neat to 10−7 and 10−8 dilutions of untreated and PMAxx™-treated live cells were plated on BAP to determine the PMAxx™ effect on cell viability and growth. Based on the findings from the experiment above, a 100 μM PMAxx™ concentration was chosen as the PMA treatment. Aliquots of 100 μL of 10−8 were treated with a 100 μM final PMAxx™ concentration, and the following three experiments were performed (a) to determine the effect of photoactivation and lysis in the same PMAxx™ treatment tube after photoactivation: PMAxx™ was removed by centrifugation at 17,115× g for 5 min and the cells were resuspended in rapid lysis buffer in the same tube. DNA was extracted as described in g for 5 min. The cells were resuspended in 100 μL of rapid lysis buffer in the same tube and DNA was extracted as described in Serially diluted live cells from neat down to 105 CFU/mL of HK cells in PBS was added to each pre-coated PMAxx™ tube, followed by 10 min dark incubation and 15 min photoactivation. In the same tube, the HK cell suspension was centrifuged at 17,115× g for 5 min, the supernatant was removed, and the cell pellet was resuspended in lysis buffer and boiled at 95 °C for 15 min. Ct values from the qPCR assay were compared with 105 CFU/mL HK cells in the absence of PMAxx™ treatment. Findings from 8 to 103) of HK cells and (b) a mixture of different live cell concentrations  spiked with 108 CFU/mL HK cells at a ratio of 1:1 in a total of 200 μL reaction volume.The final optimized PMAxx™ treatment  was tested on (a) ten-fold serial dilutions  to compare more. Bonferroni post-test was used to analyze treatment differences, and the differences were considered statistically significant when p < 0.05.Statistical analysis was performed using GraphPad Prism statistical software version 5 . The Student’s 8 CFU/mL HK cell signals. In a mixture of live and HK cells, the PMAxx™ treatment eliminated 108 CFU/mL HK cells and selectively amplified live cells. We recommend using a 100 μM PMAxx™ treatment, using separate tubes for the PMAxx™ photoactivation and lysis, and removing PMAxx™ prior to transferring the cells to a new tube for lysis to avoid carryover residual PMA. Further investigations are warranted to improve the sensitivity of the vPCR assay, since even with these considerations, PMAxx™ treatments decreased the sensitivity of the qPCR assay from 103 to 104 CFU/mL. Furthermore, validation using food and clinical specimens is required to improve the vPCR assay and to develop it further as a viability assessment tool.In conclusion, our improved vPCR protocol completely removed 10


RNA-binding proteins (RBPs) are key post-transcriptional regulators of gene expression, and thus underlie many important biological processes. Here, we developed a strategy that entails extracting a “hotspot pharmacophore” from the structure of a protein-RNA complex, to create a template for designing small-molecule inhibitors and for exploring the selectivity of the resulting inhibitors. We demonstrate this approach by designing inhibitors of Musashi proteins MSI1 and MSI2, key regulators of mRNA stability and translation that are upregulated in many cancers. We report this novel series of MSI1/MSI2 inhibitors is specific and active in biochemical, biophysical, and cellular assays. This study extends the paradigm of “hotspots” from protein-protein complexes to protein-RNA complexes, supports the “druggability” of RNA-binding protein surfaces, and represents one of the first rationally-designed inhibitors of non-enzymatic RNA-binding proteins. Owing to its simplicity and generality, we anticipate that this approach may also be used to develop inhibitors of many other RNA-binding proteins; we also consider the prospects of identifying potential off-target interactions by searching for other RBPs that recognize their cognate RNAs using similar interaction geometries. Beyond inhibitors, we also expect that compounds designed using this approach can serve as warheads for new PROTACs that selectively degrade RNA-binding proteins. RNA-binding proteins (RBPs) play crucial roles in many diverse cellular processes, regulating the life cycle of mRNAs by controlling splicing, polyadenylation, stability, localization and translation, and also modulating the function of non-coding RNAs . Mammalirationally designed small-molecule inhibitors that target RBPs, however, all examples reported to date can be categorized into two general classes. The first class comprises nucleoside analogues pyrimidin-4-amine.We next sought to optimize the other side of this compound (the right-hand side), by purchasing another 50 custom analogs from Enamine. While the most potent compound from this second round was R12–8–46, we avoided this compound because catechols are well-known candidate PAINS (pan-assay interference) compounds and can also be oxidized to quinones . InsteadFigure S5). Amongst these seven compounds, we found that R12–8–44–3 yielded another 2-fold improvement in potency, ultimately providing an IC50 value of 9.7 μM ; based on this model, we anticipated that the R12–8–44–3 would also show activity against MSI2.While expression of MSI1 is tissue-restricted, its homolog MSI2 is ubiquitously expressed ,87. MoreWith this hypothesis in mind, we first built a model of R12–8–44–3 bound to MSI2 by starting from our MSI1-bound model and replacing the 17 residues that differ between MSI1 and MSI2 . The resFigure S3b) and R12–8–44 . In fact, it acted in the opposite direction: addition of R12–8–44–3 monotonically decreased MSI1’s melting temperature . While this could be a sign of apparent inhibition occurring through aggregation, there are also legitimate inhibitors that reduce their target protein’s melting temperature pyrimidine and ester linker from our top active compound R12–8–44–3 , but usea models ,95.To determine whether inhibition of MSI1/MSI2 by R12–8–44–3 would apply in a cellular context, we adapted an aptamer pull-down reporter assay that we previously used to validate candidate Musashi target genes . BrieflyTo test for inhibition of MSI2 in cells, we transfected HEK293 cells (with a high baseline MSI2 expression), with the pMS2-LUC-3’UTR from our previous studies . This veUpon treatment with R12–8–44–3, R12-neg, or Ro, we also found that the total amount of MSI2 in cells was unaffected . AffinitFigure S9). Having established 49 °C as the midpoint of the transition under these (non-equilibrium) conditions, we then treated cells with our candidate MSI2 inhibitor for 3 h, and heated to 49 °C. In both PC9 cells . As a separate negative control, GAPDH mRNA was also quantified in the context of these studies (since GAPDH is not thought to be a target of MSI2).Having shown that R12–8–44–3 engages MSI2 in these two cell lines, we next explored whether treatment with this compound also inhibits the interaction of MSI2 with known target mRNAs. Among previously described targets of MSI2 are 2 itself ,98–101. PC9 cells were then treated with 10 μM of each compound for 8 hours and then analyzed by RIP. For each MSI2 target gene, treatment with R12–8–44–3 (but not R12-neg) led to a statistically significant reduction in the amount of mRNA associated with MSI2 . CollectFigure S11a).Binding of Musashi proteins to specific target mRNAs can lead to either up- or down-regulation of the corresponding protein product . MSI2 deEffects of MSI2 on downstream targets can be readily probed using RNA knockdown to deplete MSI2; however, the cellular dependence on MSI2 activity for cell growth/survival is more challenging to evaluate. Development of R12–8–44–3 thus affords us with a tool to directly evaluate the consequence of MSI2 pharmacological inhibition in cells. Accordingly, we treated PC9 cells with R12–8–44–3 and used CellTiter-Blue assay to probe cell viability after 3 days and a clonogenic assay to probe cell proliferation after 7 days.Figure S11b), and we found results in alignment with our observations from PC9 cells. It is difficult to determine precisely why Ro and R12–8–44–3 have such dramatically different behavior in this assay: one possibility is that Ro, a repurposed compound originally reported for activity unrelated to MSI2, may exert its cytotoxic effect in these cell lines through molecular targets unrelated to MSI2. As raised by others recently [To our surprise, we found that MSI2 inhibition by R12–8–44–3 had no effect on cell growth/survival in either assay . This obrecently , our resin vitro and in vivo [Figure S12). Further, clonogenic assays performed over 7 days demonstrated that pharmacological inhibition of MSI2 provides a robust combined effect with osimertinib  specifically, overexpression of MSI2 has been identified as a mechanism underlying resistance to inhibitors of EGFR – and more importantly, depletion of MSI2 by RNA knockdown increased sensitivity to the third-generation EGFR inhibitor osimertinib both  in vivo ,74. Despmertinib .In summary, we conclude that R-12–8–44–3 directly inhibits binding of MSI2 to target mRNAs in human lung cancer and leukemic cell line models. While this inhibition alone does not prove cytotoxic, at least in these particular cell lines, MSI2 inhibition nonetheless sensitizes EGFR-mutant lung cancer cells to the EGFR inhibitor osimertinib. Taken together, these data demonstrate that R12–8–44–3 directly binds and inhibits MSI2 biologic activity in cellular models, and that it can serve as a starting point for identifying potentially useful synergistic combinations with other approved targeted therapies.de novo interactions against a relatively flat and polar protein surface.The ability to rationally design selective inhibitors of RNA-binding proteins in a robust and general way will enable development of new tool compounds to help elucidate cellular processes mediated by these interactions. Naturally-occurring examples have shown that proteins can mimic certain structural features of RNAs ,104; herThe major advantages of this mimicry approach are its generality and simplicity. In our first application of this RNA mimicry approach, we elected to restrict our initial screening to commercially available compounds. Though none of the resulting hit compounds provided complete recapitulation of the desired hotspot interactions, we found that one of these, R12, complemented the protein surface without steric clashes and provided a starting point for new inhibitors of MSI1, thus validating the computational approach. In parallel with this work, a contemporaneous study also sought to design inhibitors of RBPs via mimicry of the cognate RNA . This stTo optimize R12, we then drew from an enormous library of make-on-demand compounds to carry out a modern form of SAR-by-catalog. The availability of this resource allowed us to rapidly drive forward optimization, and ultimately led us to an inhibitor with single-digit micromolar binding affinity, R12–8–44–3. Moving forward, we expect that ongoing increases in the size of this (and competitors’) “virtual catalogs” will greatly facilitate medicinal chemistry optimization for many other projects as well.With regards to selectivity, further experimental evidence will be necessary to thoroughly and explicitly determine whether the compounds reported here engage in unanticipated interactions with any other RBPs. Nonetheless, the computational approach described herein also provides a potential strategy to identify likely off-target interaction partners: we propose that aligning candidate compounds to hotspot pharmacophores extracted from other RBPs can help identify potential off-target interactions. This can allow prioritization of select off-target RBPs for explicit biochemical testing, rather than simply collecting arbitrary off-target RBPs for evaluation. In this vein, we were especially pleased to note that R12–8–44–3 showed no inhibition for the RBP predicted as its most-likely off-target interaction, hnRNP A1.We do note, however, that predictions of potential off-target interactions in this manner are necessarily limited: both by the incompleteness of the set of RBP complexes in the PDB, and by the fact that complexes solved using x-ray crystallography are present as single points on this map, instead of clusters that reflect conformational flexibility. Even with this limitation, however, already the utility of this approach to identify potential off-target interactions is clear. While we cannot explicitly confirm that R12–8–44–3 does not inhibit any other RBPs in the human proteome, we can at least provide a rationale for why selectivity should be expected from this compound. Looking ahead, this general strategy may also enable predicting the potential selectivity of a given compound at an earlier stage, which in turn may help prioritize specific scaffolds and drive further focused optimization. Further, the most “isolated” points on our map of pharmacophore space  may reprFinally, we do acknowledge that our optimization of the R12 series did not lead to extremely potent compounds; we suspect that this may be an intrinsic limitation of the relatively flat binding site available on the protein surface. That said, PROTACs (PROteolysis TArgeting Chimeras) ,108 haveSupporting Methods section.Detailed descriptions of computational and experimental methods are provided in the


As comparison, we included TMAs of other giant cell containing bone lesions: giant cell tumour of bone (n = 75), chondroblastoma (n = 12), chondromyxoid fibroma (n = 12), aneurysmal bone cyst (n = 6) and telangiectatic osteosarcoma (n = 6). All 16 NOF samples demonstrated ERα protein expression, while all 47 CGCG and all other giant cell containing bone tumours were negative. Most NOF samples had moderate staining intensity and between 24 and 49% of the spindle cells were ERα-positive. Our findings further support the role of endocrine regulation via oestrogen in the spontaneous regression in NOF. Whether oestrogen signalling at puberty is involved in the induction of senescence in the neoplastic cells of NOF harbouring RAS/MAPK pathway mutations needs further research. Since ERα expression was not observed in other giant cell containing bone lesions with overlapping morphological features, positive ERα expression may favour the diagnosis of NOF in challenging diagnostic cases.Non-ossifying fibroma (NOF) and central giant cell granuloma (CGCG) are both benign tumours of bone with overlapping morphology and similar mutations in the RAS/MAPK pathway. However, NOF is located in the long bones with regression after puberty in contrast to CGCG which is located in the jaw bones and does not regress spontaneously. We hypothesised that endocrine regulation by oestrogen plays a role in the spontaneous regression in NOF. Therefore, we examined the expression of ERα in a series of NOF and CGCG. ERα expression (EP1) was determined using immunohistochemistry on 16 NOFs (whole slides), and 47 CGCGs (tissue microarrays (TMA’s  Non-ossifying fibroma (NOF) and central giant cell granuloma (CGCG) are both benign lesions occurring in bone, presenting with highly similar histology. NOF is however predominantly located in the metaphyseal area of long bones and is more common in the first and second decade of life. In contrast, CGCG is located in the jaw bones and is more frequent in females aged under 30 years –5. Most Recently, Baumhoer and colleagues identified KRAS, FGFR1 and NF1 mutations in 81% 48/59) of patients with NOF 8/59 of p.We hypothesised that the observed spontaneous regression in NOFs during puberty may be a result of increased endocrine regulation by oestrogen . TherefoWe were able to retrieve formalin-fixed paraffin-embedded specimens from 16 biopsies of NOF cases (diagnosed between 2007 and 2019) from the archive in the Department of Pathology, Leiden University Medical Center (LUMC). The diagnosis was made in conjoint assessment by radiologists and pathologists.In total, 47 formalin-fixed paraffin-embedded tissue samples from clinically, histologically and radiologically confirmed CGCG cases were used. In all these patients, a hyperparathyroidism was excluded by standard laboratory investigations and none was diagnosed with a CGCG-related syndrome . Tissue samples from 6 of the 47 CGCG cases were retrieved from the archive of the LUMC pathology department as biopsy material on whole slide. The tissue samples from the 41 remaining CGCG cases were retrieved as an existing tissue micro array (TMA) from the department of Oral and Maxillofacial Surgery of the Amsterdam UMC. From 7 of these 41 CGCG cases, we also used whole slide to compare result between whole slide and TMA results. The TMA was constructed with 1-mm tissue cores from decalcified formalin-fixed paraffin-embedded tissue of 41 CGCGs. These tumours were originally diagnosed and treated between 1994 and 2014. All material was handled according to the ethical guidelines described in the Code for Proper Secondary Use of Human Tissue in The Netherlands. The TMA paraffin block was subsequently sliced into 4–6-μm-thick sections in order to make slides.n = 75), chondroblastoma (n = 12), chondromyxoid fibroma (n = 12), aneurysmal bone cyst (n = 6), and telangiectatic osteosarcoma (n = 6).Furthermore, we included previously published TMAs from other giant cell containing bone tumours , includiImmunohistochemical staining was performed using ERα antibody . For immunohistochemical staining, slides were first deparaffinised and rehydrated using xylene and graded concentration of ethanol, respectively. Endogenous peroxidase was blocked in 0.3% H2O2 solution; subsequently, antigen retrieval was performed using Tris–EDTA pH 9.0 and microwaved. After a blocking step, using 30 min 5% non-fat dry milk in PBS/1%BSA, the slides were incubated overnight at 4 °C with ERα antibody, diluted 1:400 in PBS/BSA 1%. The ERα antibody was detected and visualised with BrightVision, 1 step detection anti-mouse/rabbit HRP  and DAB + substrate chromogen system . Lastly, haematoxylin was used to counterstain the slides, after which the slides were dehydrated and mounted using micromount . For the negative control, the first antibody was excluded and as a positive control, a whole slide with a breast adenocarcinoma was included.ERα expression in the samples was scored by evaluating staining intensity and the percentage of positively stained cells by two observers . The samples were assigned a score of 0, negative; 1, weak; 2, moderate or 3, strong, to indicate staining intensity, in which only nuclear staining was considered. The scores for the percentage of ERα positive cells were determined as 0 = 0%, 1 = 1–24%, 2 = 25–49%, 3 = 50–74% and 4 = 75–100% .The samples were subdivided into ERα positive or ERα negative. ERα positive was defined as an overall staining score > 0 and negative as a score of 0, in which the overall staining score is the sum of the score for staining intensity and percentage of positively stained cells.The median age of our NOF cohort was 16 years with 68% males and 32% females  and the tumours were located in the maxilla or mandible.We found that all NOF cases showed moderate expression of ERalpha in 24–49% in the bland spindle–shaped cells with oval and elongated nuclei which were intermixed with ERalpha negative osteoclast-like giant cells Fig. . We did All other giant cell containing bone tumours, including giant cell tumour of bone, chondroblastoma, chondromyxoid fibroma, aneurysmal bone cyst and telangiectatic osteosarcoma, were also completely negative for ERα expression.Our data support the hypothesis that increased endocrine regulation by oestrogen signalling through the ERalpha receptor during puberty is involved in the spontaneous regression of NOFs. Despite identical histology and molecular aberrations, spontaneous regression is not observed in CGCG and here, we show that ERalpha expression is lacking in CGCG.Thus, similar oestrogen-regulated senescence occurring in the growth plate during puberty might also be initiated in the dispersed mutant cells in NOF lesions, as previously hypothesised . This woAlmost 69% of the NOF patients are younger than 18 years in our study; however, a significant proportion of patients with CGCG is also aged below 18 (51%). Even in patients aged below 18 with CGCG, no expression of ERα was observed, indicating that rather tumour-specific micro-environmental factors play a role instead of age. The absence of ERα expression in CGCG is in concordance with a study performed by Whitaker et al. in 10 cases of CGCG [Since CGCG are exclusively located in the maxillofacial bone, it is tempting to speculate. The role of oestrogen in different stages of bone development is complex and may be different between maxillofacial bones derived from intramembranous versus long bones derived from endochondral ossification.NOF not only shows overlapping morphological features with CGCG; the histology comprised of spindle shaped cells admixed with osteoclast-like giant cells may also overlap with other giant cell containing bone tumours such as giant cell tumour of bone, chondroblastoma, chondromyxoid fibroma, aneurysmal bone cyst and giant cell rich or teleangiectatic osteosarcoma. Although correlation of morphology with the radiological differential diagnosis remains the cornerstone in diagnostic decision-making, additional immunohistochemical or molecular diagnostic markers are helpful in challenging cases with overlapping morphological features especially in scarce biopsy material. Based on our results, the finding of positive ERα expression could favour the diagnosis for NOF above other giant cell containing bone lesions after thorough radiological correlation.n = 15). We used a different antibody (EP1) to determine ER expression, which may explain these conflicting results.Nevertheless, caution should be taken using ERalpha expression as a diagnostic marker because of conflicting results when different antibody clones are used as was shown in several studies performed in breast cancer . A studyA limitation of our study is the fact that NOFs were mostly stained on whole slides, while the CGCG and other giant cell containing tumours were stained on tissue microarray. We still believe that the results are reliable since we included whole tissue slides of 7 cases of CGCG that were also included in the TMA which showed identical results; therefore, excluding false-negative IHC results due to scarce tumour material in these cases in our series of CGCG. Additionally, the TMAs including GCTB cases were positive for other antibodies .In conclusion, our findings support the role of endocrine regulation via oestrogen in the spontaneous regression in NOF, which is not observed in CGCG or other giant cell containing bone lesions. The exact role of ERα in the spontaneous regression during puberty of NOF remains uncertain and further elucidation of the mechanism by which regression is induced might reveal new therapeutic options for other RASopathies. Since ERα expression was not observed in other giant cell containing bone lesions with overlapping morphological features, positive ERα expression (clone EP1) may favour the diagnosis of NOF in challenging diagnostic cases.


Thalassiosira pseudonana, and show that fluctuations in temperature on scales of 3–4 generations rapidly selected for populations with enhanced trait plasticity and elevated thermal tolerance. Fluctuations spanning 30–40 generations selected for the formation of two stable, genetically and physiologically distinct populations, one evolving high trait plasticity and enhanced thermal tolerance, and the other, akin to samples evolved under constant warming, with lower trait plasticity and a smaller increase in thermal tolerance.Global warming is associated with an increase in sea surface temperature and its variability. The consequences of evolving in variable, fluctuating environments are explored by a large body of theory: when populations evolve in fluctuating environments the frequency of fluctuations determines the shapes of tolerance curves (indicative of habitats that organisms can inhabit) and trait reaction norms (the phenotypes that organisms display across these environments). Despite this well-established theoretical backbone, predicting how trait and tolerance curves will evolve in organisms at the foundation of marine ecosystems remains a challenge. Here, we used a globally distributed phytoplankton,  Thermal environments in nature are anything but constant, and global warming is expected to further amplify natural temperature variability. Scientific understanding about the impacts of thermal variability on the rapid evolution of thermal tolerance is exceptionally limited. What we do understand comes mostly from theory or comparative studies where species’ thermal tolerance are linked to the thermal variability of the environments they inhabit. Theory and data typically agree that species from higher latitudes that experience greater thermal variability tend to have broader thermal tolerance curves than their counterparts from thermally stable environments in low latitudes ,9, whichA key pathway toward understanding how environmental variability shapes the evolution of tolerance curves could come from understanding how the traits that underly the impacts of temperature change on fitness evolve under different scenarios of thermal fluctuations. Metabolic traits, such as rates of respiration and photosynthesis, are known to respond significantly to changes temperature and play important role in shaping the limits of thermal tolerance and the capacity for the evolution of elevated thermal tolerance . The dynThalassiosira pseudonana which has evolved for 300 generations in fluctuating environments that differed in the frequencies of fluctuations (3–4 or 30–40 generations). The fluctuations switched between 22°C and 32°C, and were run alongside stable environmental conditions at 22°C and 32°C. These temperatures represent control conditions at 22°C and warming at supra-optimal temperature at 32°C. We quantified the magnitudes of the evolutionary responses and determined whether the evolution of the thermal tolerance curve and magnitude phenotypic plasticity for each selection lines varied between stable environments and those that fluctuated on shorter versus longer frequencies. We also resequenced the genomes of the ancestor and all selections to determine whether changes in in fitness and phenotypic traits were also reflected in patterns of molecular evolution.Here we address these knowledge gaps by leveraging a long-term selection experiment  with the. 2This is a methods summary. Detailed methods that allow for reproduction or re-analysis of the experiment can be found in the electronic supplementary material. (a)Thalassiosira pseudonana (CCMP 1335) [−1 in 39.5 g l−1 artificial seawater reagents) and light intensity was at 100 µmol quanta m−2 s−1. Lineages were maintained in semi-continuous batch culture, transferred during the exponential phase. After 300 generations of selection in their respective environments, all samples were used for a full reciprocal transplant assay.A sequenced strain of MP 1335)  was obtaMP 1335) ) with ar (b)Abundance, size and fluorescence of cells were determined at each transfer using an Accuri C6 flow cytometer (BD Scientific).T. pseudonana cells from each selection environment were counted on the flow cytometer as described above and used to estimate specific growth rates (μ d−1).At the beginning and at the end of each transfer  (c)To characterize thermal tolerance curves of growth, an inoculum of 100 cells per ml from the middle of the logarithmic phase of growth was transferred into fresh media at 15°C, 20°C, 25°C, 30°C, 32°C, 35°C and 40°C, and cell count was then determined daily on an BD accuri C6 flow cytometer. (d)−2 s−1. Flash frequency and rate followed standard protocols for phytoplankton [We characterized a suite of photochemical parameters in the ancestor and each of the evolved lineages using fast repetition rate fluorometry . Measurements were taken at 22°C and 32°C. Photochemical traits were measured in response to rapid flashes at increasing light intensities from 0 to1600 µmol mplankton , with 10 (e)2 evolution at increasing light intensities up to 2000 µmol−1 m−2 s−1. The maximum rate of light-saturated photosynthesis was determined by fitting the NP data to a dynamic model of photoinhibition via nonlinear least squares regression using the methods outlined in [2 per cell and hour, were transformed to µg C per µg C following [Rates of gross photosynthesis were measured in the ancestor and all evolved lineages after 300 generations of selection when in the middle of the logarithmic phase of population growth using a Clark-type oxygen electrode. Net photosynthesis (NP) was measured as Olined in . To estiollowing . The µg  (f)T. pseudonana genome and all further data processing  was carried out following the same pipeline as described in [DNA was extracted following a standard cTAB protocol . Samplesribed in . (g)All analyses were carried out in R (v. 3.23–v. 3.51). See the electronic supplementary material for details per analysis. (i)To compare the fold-changes of evolved samples (after 300 generations ‘t300’) compared to the growth rate of the ancestor at the respective selection temperature, the ratios of growth of the ancestor at selection temperature, and the evolved sample at selection temperature were calculated, and a linear mixed model used, where that ratio was the response variable. (ii)a priori assumption of their identity was made. To do so, phenotypic and molecular (WGS) data were used to construct two Euclidean distance matrices, which served as base for PCoAs constructed within the mixOmics package (6.1–3). For the WGS data, to test for separation of samples by treatment, and within treatment variation, the Euclidean distance matrices were used to perform AMOVAs following [In order to justify our decision to treat the 22°C- and 32°C-preferring replicates from the FL selection environment as separate groups, we tested whether these replicates would repeatedly cluster with each other when no ollowing .The PCoAs show  that 22°C preferring replicates cluster with the ancestor, and samples evolved under 22°C or 32°C. Replicates preferring the 32°C environment cluster with samples from the FS environment. (iii)The time series of specific growth rates in FL-evolved lineages were analysed using a generalized additive mixed effects model  to assess whether the fitness trajectories differed between the biological replicates within the selection regime depending on the temperature of the selection regime (22°C or 32°C). (iv)Topt indicates the temperature at which growth is fastest. The breadth of the curve is the range of temperatures at which growth is a given percentage of the peak rate . We used these parameters to estimate the area underneath the curve (AUC) and compare it between treatments. The area underneath the thermal tolerance curve is a function of both curve breadth and curve height, and we, therefore, use it here to describe changes in the shape (including height) of thermal tolerance curves among our selection lines.To describe and compare characteristics of the thermal tolerance curves of growth, generalized additive mixed effects models (gamm4 as above) were fitted to the growth rate data across a temperature gradient spanning 15°C to 40°C. Several parameters describe the shapes of the thermal tolerance curves: The peak of the curve,  (v)via comparing the steepness of slopes). The steepness of slope was used as the response variable in a mixed effects model with assay temperature and selection temperature as fixed factors, and biological replicate nested within selection environment as the random factor.Phenotypic plasticity in photosynthesis and photochemical traits was calculated as described above (i.e.  (vi)ΦPSII, C and rP, parameters were each extracted from separate nonlinear mixed effects models, where ‘selection regime’ and ‘assay temperature’ were fixed effects and replicate was a random effect on the intercept. Model selection proceeded as above and suggested that the best model included selection regime and assay temperature for ΦPSII, C and rP.. 3 (a)a; electronic supplementary material, table S1), in line with previous findings [figure 1c; see electronic supplementary material, table S2 for statistics), and exacerbated in the periods of selection at 32°C. Yet, growth rates at 32°C in the FL lines were never reduced to the same level as those under constant selection at 32°C . After approximately 100 generations, growth rates during periods at 32°C recovered to and above the levels seen in the samples evolving in the 22°C stable environment, and after approximately 150 generations, two distinct populations emerged in the FL treatment , with half of the biological replicates consistently growing better at 22°C than at 32°C  and the other half growing better at 32°C than at 22°C . When we use all available phenotype or molecular data to construct principal component analyses with no a-priori assumptions about the behaviour of individual biological replicates, we see that the same replicates cluster together . The three replicates that favour the 22°C environment cluster closer to the samples evolved under the stable 22°C regime and the three replicates that favour the 32°C environment cluster closer to the samples evolved under rapid fluctuations.For the scope of this paper, we define an evolutionary response as the growth rate in the selection environment compared to the growth rate or trait value in the ancestor when exposed to the selection environment. On average, evolutionary responses of growth rates were larger in the fluctuating than in the stable environments , adapti (b)a–d; see electronic supplementary material, tables S3–S6): populations evolved in the rapidly fluctuating environments had faster growth at temperatures exceeding 32°C  than samples evolved in stable conditions. Half of the replicates from the environment that fluctuated on longer time scales (FL) behaved similarly to those evolved under rapid fluctuations. The thermal tolerance curves of the remaining FL-evolved samples more closely resembled tolerance curves of samples evolved under stable conditions.To better understand the consequences of these different evolutionary responses within and between fluctuating treatments, we now explore which environments the evolved and ancestral populations can inhabit  and the phenotypes they are capable of displaying (their phenotypic plasticity). We found that thermal tolerance curve characteristics differed between stable and fluctuating environments and between environments that fluctuated on short or longer time scales . In other words, while all evolved samples were able to maintain growth across all assay temperatures, samples from the rapidly fluctuating environment grew faster across a larger number of assay temperatures than did samples from the stable environments.Samples evolved under fluctuations also maintained larger AUCs , and growth rates at the optimum temperature  were higher than samples evolved at 22° or 32°C under stable conditions. These pronounced changes in thermal tolerance curve characteristics add to the growing body of evidence for the evolvability of tolerance curves in the absence of breadth/height trade-offs . Half of the biological replicates (growing better at 32°C than 22°C) showed curve characteristics similar to those found in samples evolved under fast fluctuations, with higher AUCs, higher Topt, and higher peak rates at Topt than samples evolved in stable environments. The other half of the biological replicates (growing better at 22°C than 32°C) evolved AUCs and rates at optimum temperatures more akin to those in the 22°C environment, however, Topt shifted to warmer temperatures markedly, such that optimum temperatures were similar to those found in 32°C-evolved samples.Samples evolved under slower fluctuations again showed two distinct patterns on the basis of their thermal tolerance characteristics a–d. Half (c)To link thermal tolerance to trait plasticity, we need to first establish a measure of plasticity that can be used across different phenotypic traits. Phenotypic plasticity is well-defined for linear reactions norms , where ta, likelihood ratio test comparing models with and without ‘selection temperature’: Δd.f. = 5, χ2 = 21.53, p < 0.001 see also electronic supplementary material, table S7 and electronic supplementary material, figure S2). The steepest slopes (i.e. the largest plastic response) evolved in samples selected in the rapidly fluctuating environment, and the warm-preferring subset of samples selected in the slowly fluctuating environment. To determine whether the evolution of high plasticity in the fast fluctuations and the presence of distinct phenotypes under slow fluctuations were reflected on a photochemical level, we used fast repetition rate fluorometry [figure 3c,d; electronic supplementary material, figures S3–S5), and assayed the evolved samples at 22°C and 32°C. We determined trait plasticity as described above for the following parameters: (i) FV/FM as the maximum quantum efficiency of photosystem II ; (ii) rP at Iopt, which describes the relative rate of photosynthesis as the amount of electron transport through photosystem II at the optimum light intensity ; and (iii) ΦPSII, as a measure of the operating photochemical efficiency of PSII . We find, again, that samples from the rapidly fluctuating FS environment and the 32°C-preferring subset of the samples evolved under the slow fluctuations displayed higher plasticity than samples from the stable environments . Although there was some variation in plasticity in the ancestor, ancestral plasticity is not indicative of the amount to which plasticity evolves across the different treatments in our case.The selection environment determined the steepness of the slopes of photosynthesis a–d for linking AUC to trait plasticity in gross photosynthesis (a), FVFM (b), rP at Iopt (c) and ΦPSII (d)). Populations evolved under rapid fluctuations generally have the highest AUC, and highest plastic responses, whereas samples evolved under stable conditions cluster with the ancestor at lower AUC values and lower levels of plasticity. The populations affiliated with 32°C, evolved under slow fluctuations cluster with those from the rapid fluctuation treatment, while the populations affiliated with 22°C cluster with populations evolved under stable conditions at 22°C and 32°C . The relationship between AUC and plasticity is less pronounced in samples evolved in the stable environments and the subset of samples from the FL selection environment that did not evolve increased plasticity.Developing a mechanistic understanding of the interactions between trait plasticity, fitness, and the environment is key to predicting which taxa and phenotypes will thrive in a warming world and how they will contribute to ecosystem functioning. The area underneath the thermal tolerance curve (AUC) describes changes in the shape of the thermal tolerance curve, and the AUC value can be used as a composite measure of the fitness–environment interaction. We found that in populations from fluctuating environments, trait plasticity increases linearly as a function of the AUC (figure 4. 4and tolerance. Rapid fluctuations in particular might be providing a stepping stone to fast growth and metabolic function at more extreme temperatures that exceed the mean of variation of the environments that they inhabit today.To make predictions about the ecological function of marine microbial primary producers in a changing world, we need to know how the frequencies of environmental fluctuations affect the current and projected scope of phenotypic plasticity and the degree to which phenotypic plasticity carries a fitness benefit under different frequencies of fluctuation. While there is some experimental evidence indicating that fast-lived phytoplankton from regions that are more variable tend to exhibit larger plastic responses ,49, no sClick here for additional data file.


Annals of Surgery 2020. The aim of this study was to examine the influence of stereo acuity on surgical performance in a laparoscopic training parkour with 3D- versus 4 K-2D-display technique.This study is a secondary analysis of the IDOSP trial published in the The surgical performance of medical students (MS), non-board-certified surgeons (NBC), and board-certified surgeons (BC) was compared using 3D- versus 4 K-2D-display technique at a training parkour in a randomized cross-over trial. Stereo acuity was tested by TNO and Titmus Stereo tests.r = 0.26, p = 0.02) and error  with the 3D screen. The TNO test did not correlate significantly with parkour performance. There was no statistically significant correlation between parkour time nor error and stereo acuity using the 4 K system (p > 0.457 respectively). Higher age showed a significant correlation with lower stereo acuity measured with TNO , but not with the Titmus test . Seven percent of the group “NBC and BC” showed reduced stereo acuity > 120 s arc with the Titmus test and 3% with the TNO test.Eighty-nine participants were included in this sub-trial. The median stereo acuity for all participants, measured with the Titmus test, was 25 s arc, with TNO test 30 s arc. Higher quality stereo vision, measured with the Titmus test, correlated significantly with a reduced parkour time . High-quality stereopsis offers an advantage when performing fine motor tasks under direct view . HoweverIn 3D laparoscopy, the images from two cameras are fused and presented as a single 3D image by a special monitor and viewed through polarized glasses . With adThere are several methods of testing stereo vision . In all Annals of Surgery 2020 [This study is a secondary analysis of the IDOSP trial published in the ery 2020 . The priThe aim of this secondary analysis was to correlate stereo acuity with surgical performance in 3D laparoscopy and 4 K-2D laparoscopy. Furthermore, two different common stereo tests  should be evaluated regarding their correlation with surgical performance in 3D laparoscopy and 4 K-2D laparoscopy. The effects of experience, fine motor skills, and age were assessed. As this is a secondary analysis and the primary endpoint of the IDOSP-Study was different from this secondary analysis, the results in this publication can therefore only be perceived as descriptive.Inclusion criteria for the IDOSP-Study , 13 wereMedical students with any experience in laparoscopic surgery, or any candidates  with any experience in the laparoscopic training parkour, non-correctable vision disorders, known impaired stereoscopic vision, or manual skill disorders were excluded from the study.Inexperienced novices , non-board-certified, and board-certified surgeons were examined by an experienced ophthalmologist  for stereoscopic vision and exclusion of manifest strabismus with five qualitative and semi-quantitative tests: Bagolini striated glasses test (near and far distance); Lang (II), Titmus, and TNO stereo tests (near distance); and cover/uncover test (near and far distance). Details concerning the most relevant stereo tests for this study are shown in Fig. A passive polarizing 3D- and a 4 K-display system (2 arms) were used to perform different tasks in a minimal invasive/laparoscopic training parkour  and 2D-4 K System “Visera 4 K Ultra High Definition” ). The position of the complete laparoscopic training parkour, the camera position in the laparoscopic training system, and the distance from study subject to the screens were standardized. The distance between the participant and the 3D screen or the 4 K screen was 130 cm.Each participant had to perform two runs of the parkour with the two different display systems. The parkour consisted of 5 tasks for medical students and 5 + 2 tasks for surgeons, which were each repeated three times. The five tasks were “rope pass,” “paper cut,” “pegboard transfer,” “needle threading,” and “needle recapping.” The two additional tasks with an increased degree of difficulty were “circle cutting” and “knot tying.” The first run of the parkour was performed with a randomized display system, the second with the other one. A detailed description of the minimal invasive training parkour can be found in the published study protocol . SurgicaThe participants’ task load for each run was evaluated by the National Aeronautics and Space Administration Task Load Index (NASA-TLX).This trial was approved by the Ethics Committee of the University of Cologne (No. 17–388). All subjects gave their written informed consent before randomization by an independent data trustee.Statistical analysis was performed using Excel  and SPSS . Each participant’s median overall parkour time and median overall parkour error per screen system were calculated and used for further evaluation.Mean and standard deviation were calculated for normally distributed data. For ordinal scaled data, median and range were given. For further statistical analysis, the stereo acuity results were grouped as either “normal” , “subnormal”  or “moderate to reduced” stereopsis  . Additiop < 0.05. The paired Student t-test was used to compare means between groups for normally distributed data. For ordinal data and data without normal distribution, the Wilcoxon rank-sum test was used.Correlations were tested by Spearman’s rho. The threshold for statistical significance was set to Between February and October 2019, a total of 89 participants of the IDOSP-Study completed stereo acuity tests as well as the training parkour and were included in this sub-trial. Forty-seven were medical students  in all eyes; 88% of right eyes and 91% of left eyes had a visual acuity of 1.0 or better.The Bagolini test was positive for far and near fixation in all subjects. The Lang II test was positive in 85 participants (200 s arc), whereas four had reduced stereovision .p = 0.024, MS vs NBC p = 0.002).The median stereo acuity for all participants, measured with the Titmus test, was 25 s arc (25 to 3550 s arc), with TNO test 30 s arc (15 to 240 s arc). The median stereo acuity for the subgroups MS, NBC, and BC can be seen in Table r = 0.34, p = 0.001). When assigned to subgroups, only 22% of participants showed full stereo acuity (25 s arc or better) with TNO compared to 71% with the Titmus test. Forty-seven percent showed subnormal stereo acuity (> 25 to 40 s arc) with TNO compared to 18% with the Titmus test. Thirty-one percent showed reduced stereo acuity (50 s arc or worse) with TNO compared to 11% with the Titmus test , but there was no significant correlation between age and results of the Titmus test .Higher age showed a significant correlation with lower stereo acuity measured with TNO  or TNO test .There was no significant correlation between NASA-TLX and stereo acuity measured by the Titmus (p < 0.01 respectively). Table Considering the 5 tasks performed by all participants, participants were significantly faster and had fewer errors when using 3D instead of 4 K-2D. This difference was statistically significant as well for the subgroup MS, but not for NBC and BC , but not to parkour error using the 3D screen .The technical level of participants showed a significant correlation to the parkour seconds  and NBC (60% and 73%), whereas it was weaker for BC (52% and 54%).p < 0.039 respectively). Table When considering 5 + 2 tasks with an increased degree of difficulty for NBC and BC, participants performed significantly faster but did not have statistically significantly fewer errors when using 3D instead of 4 K-2D (p = 0.002). Both the participants’ 3D overall parkour seconds  and the 3D overall parkour error  showed a statistically significant correlation with the Titmus test. Scatter plots with regression lines are shown in Fig. The participants’ 3D overall parkour seconds were significantly higher in Titmus subgroup 2 than in subgroup 1 (p < 0.002 respectively) as shown in Table When assigned to stereo subgroups, in all subgroups we could confirm the results from the IDOSP-Study, where the participants’ overall parkour time was significantly faster and parkour error was significantly lower with the 3D system. This effect was statistically significant for all subgroups (r was r = 0.34 (p = 0.027) and therefore higher than for the overall parkour error and seconds. There was no statistically significant correlation between 3D overall parkour error, 4 K overall parkour seconds, and 4 K overall parkour error and stereo acuity measured by the TNO or Titmus test. Details are shown in Table When considering 5 + 2 tasks with an increased degree of difficulty for NBC and BC, the participants’ 3D overall parkour seconds showed a statistically significant correlation with Titmus, but not with the TNO test. The correlation coefficient Participants of the IDOSP-Study were significantly faster and had fewer errors in the surgical parkour when using 3D instead of 4 K in all subgroups of level of experience and in all subgroups of level of stereo acuity. This study showed a significant correlation between stereo vision, measured by the Titmus test, and the participant’s median 3D parkour performance (time and error). This difference was most obvious for MS and when tasks were included that placed particularly high demand on hand–eye coordination (5 + 2 tasks with an increased degree of difficulty). High-quality stereo vision of the surgeon offered no advantages or disadvantages when using the 4 K-2D-display system.In contrast to the Titmus test, the TNO test showed the same trend but did not correlate significantly with parkour performance. One reason could be that both the Titmus test, a contour stereo test, and the 3D screen system work with polarizing glasses. In contrast, red-green glasses are used with the TNO test, a random dot stereo test. Based on the results of our study, the Titmus test is better suited to predict whether a subject will benefit from a 3D monitor system using the “state-of-the-art” passive polarizing technique.Another reason for the difference in correlation of the two different stereo tests with parkour performance is the different nature of these two tests. As previously described in existing literature, measured stereo acuity was better when using Titmus test compared to TNO test in our study (median stereo acuity measured with the Titmus test was 25 s of arc while the median stereo acuity measured with the TNO test was 30 s of arc in our study). This underestimation of stereopsis using the TNO test has been shown by other studies before  and is dp = 0.001), but 60% of all participants showed better stereo acuity levels when tested with the Titmus test compared to the TNO test.Both tests differ in the number of items and the tested stereo sensitivity values see Fig. . MeasureThe TNO test, being a random dot stereo test, measures global stereopsis (or cyclopean stereopsis), which depends on disparity-selective neurons in the primary visual cortex , 15. TheThese neural processes involve a stronger stimulus for vergence of the eyes which is necessary for motor alignment and therefore depth perception . FurtherThe finding from this study correlates to evidence from existing literature, which has found the Titmus test to be more sensitive to small changes in stereovision .Biddle et al. examined stereo acuity in 66 practicing surgeons across a range of surgical specialties . Stereo Comparable to our study, Fergo et al.  found stAnother reason for worse stereopsis with age might be an insufficient correction of refractive error, especially presbyopia. Tuna et al.  investigSuleman et al.  examinedBarry et al.  comparedOur study could confirm the hypothesis of Fergo et al., who hypothesized that surgeons with good stereo acuity can gain from 3D laparoscopy, whereas stereo blind surgeons would be unduly disadvantaged . They hiWe conclude that a high level of stereo acuity leads to a higher benefit using a 3D laparoscopic system compared to the use of a 4 K-2D system. In addition, surgical experience and fine motor skills are of great importance beyond stereoscopic vision and could partly compensate for a somewhat poorer stereo acuity.One limitation of this study is that not all participants of the IDOSP trial completed all stereo tests and orthoptic examination. Only 95% of MS (47/49), 41% of NBC (16/39), and 65% of BC (26/40) finally completed stereo acuity tests. Therefore, this subgroup is slightly different from the IDOSP-Study group. As all statistical tests were applied to this subgroup, we do not expect any bias because of this.Limitations of this study and the IDOSP trial include that the participants used their own glasses for both the parkour and the stereo tests. The glasses might have been not the best possible correction for their ametropia. Especially in participants with beginning presbyopia, they might have been undercorrected for near distance.Another possible limitation is that the monitor distance in the parkour, which was 130 cm, did not equal the test distance of the stereo tests, which are designed for a distance of 40 cm. This fact might have led to an underestimation of stereo acuity of participants with undercorrected presbyopia. As the subgroups of NBC and BC had a higher mean age than the subgroup of MS and therefore probably a higher percentage of presbyopia, this fact could bias the results. Especially the finding that untrained participants are more dependent on their stereo acuity and benefit more from a 3D monitor system than trained surgeons can partly be explained by the test modality of stereo vision with disadvantages for participants with presbyopia without best correction. However, even at a 130 cm screen distance the stereo acuity can be reduced when spectacles for distance vision are worn by participants with presbyopia. This hypothesis is confirmed by the significant correlation between stereo acuity and parkour performance we found in this study.Furthermore, the number of participants within different stereo subgroups was quite small in some subgroups and was not equal between subgroups. This could also lead to bias.Stereo acuity cannot be trained in adults. However, stereo acuity is known to be better when wearing best-corrected glasses  especialWe furthermore conclude that in future clinical studies on laparoscopic surgery using a 3D monitor system it is of critical importance to evaluate the participants’ stereo acuity and make sure that the stereo acuity is comparable between different study groups as heterogeneity in stereo acuity could otherwise lead to a significant bias of the results.


The core δ18Ootolith corresponding to the larval stage greatly varied among the individuals, indicating that the larvae experienced a wide range of thermal environments. The non-hierarchical cluster analysis performed on the core δ18Ootolith grouped fish into those with higher δ18Ootolith (lower temperature) and those with lower δ18Ootolith (higher temperature), most likely representing relative temperature difference experienced between fish born in the Sea of Japan and in the Nansei Islands area. The Nansei Islands area cluster showed more variability in the early otolith growth indicating a longer spawning season, which is consistent with the observed longer spawning duration in this area. The absolute temperature estimates based on the SIMS-measured core δ18Ootolith were significantly higher than those expected from sea surface temperature data, suggesting the effects of matrix-related bias on the temperature offsets. The relative temperature difference, however, matched well with the known spawning temperature range of the two spawning grounds. The recruitment contribution from each spawning ground  was 45% in the Sea of Japan and 55% in the Nansei Islands area. Overall, this study demonstrated the effectiveness of SIMS δ18Ootolith analysis for investigating the natal origin of fish and its potential application in fish population dynamics studies.Accurate understanding of changing population dynamics associated with climate change is critical for managing highly migratory fish species. However, long-term data on population dynamics and the resulting recruitment variability is still lacking for many species, making it difficult to predict and integrate the effects of ocean warming into management schemes. In this study, high-resolution stable oxygen isotope (δ Population mixing is a common phenomenon observed among various marine fish species where fish originating from geographically distinct spawning grounds mix as they grow and migrate to the common nursery and feeding habitats , 2. WhilThunnus orientalis) is one of the most commercially important tuna species harvested around the world whose annual total harvest value estimated to be US $207 million in 2020  in otoliths (δ18Ootolith) has been widely used as an environmental indicator for reconstructing water temperature and salinity histories of an individual fish , [The preparation of an indium mount is described in  in detai[VSMOW], ) were plin-situ on the PBT otoliths using a CAMECA IMS-1280 large radius, multi-collector ion microprobe (SIMS) at the Kochi Institute for Core Sample, JAMSTEC, in Japan. As the peak in δ18Ootolith represents the coldest temperature experienced by fish in winter, we measured δ18Ootolith values from the otolith core until the first peak in δ18Ootolith was detected to obtain a chronological profile recording the early life and immature stages (corresponding to about 7 to 9 months old) of an individual fish  focused to a spot diameter of 10 μm, resulting in a pit depth of approximately 1 μm  were accelerated at 10 kV and detected simultaneously by three Faraday cup detectors. To monitor and evaluate the relative hydrogen content contained in the otoliths, the 16OH–/16O– ratio of each δ18O measurement was background-corrected by subtracting the average 16OH–/16O– ratios of the UWC-3 bracketing analyses. The average count rates for 16O– and 18O– were 2.9 × 109 and 5.9 × 106 counts per second (cps), respectively.Each spot was sputtered with a ely 1 μm . Each an18Ootolith measurements were made on the otoliths of 46 bluefin tuna by SIMS together with 315 bracketing measurements of the UWC-3 standard. The transect length of each sample ranged from 1.02 to 1.69 mm with spot-to-spot distance ranging roughly from 50 to 200 μm. The temporal resolution of the 10 μm beam spot corresponded to 3–5 days around the otolith core based on the daily growth increment counts and several weeks to a month for the outer regions based on the relative position and ratio of the beam spot.Five spot measurements of UWC-3 calcite standard were made before and after every 10 to 15 unknown sample measurements to assess the spot-to-spot reproducibility of sample analyses and correct for instrumental mass fractionation. The spot-to-spot reproducibility throughout the analysis was mostly between ±0.3 to ±0.5‰ (± 2 SD). In total, 533 δ18O values  relative to the mean of the UWC-3 standard bracketing analyses was also used to assess the quality of spot measurements and check for any extreme outliers. The δ18O measurements that showed primary beam instability or low 16O– yield were excluded from the dataset. The final raw SIMS data are presented in After analysis, each spot was imaged and observed using electron probe micro analyzer  under scanning electron microscope (SEM) mode to check for any cracks and inclusions that might bias the δs . The se18Ootolith measurements were thus calibrated using a PBT-specific offset correction equation developed by Hane et al. ) likely reflects the natal thermal environment of fish because PBT larvae tend to stay in waters within or close to the spawning grounds. The SEM images were used to observe and count the daily growth increments around the core region. We made sure that the δ18Ootolith values taken from the otolith region deposited within 20 DPH were used as the core δ18Ootolith. The distance from the otolith core to the first opaque zone can be used as an early growth indicator as otolith length of bluefin tuna is highly correlated with fish somatic growth [18Ootolith peak (representing the lowest winter temperature experienced during the first year of life) that was determined using spline-interpolated δ18Ootolith chronological profiles. There was a strong positive correlation between the location of the first opaque zone and that of the δ18Ootolith peak , indicating that the formation of the first opaque zone in PBT otoliths occurs during their first winter. Therefore, the distance from the otolith core to the first opaque zone was shown to be an appropriate variable representing the early growth of PBT until their first winter.We used the core δc growth , 56. Then = 51.In addition to the samples analyzed in this study, 5 otolith samples analyzed in Hane et al.  were inc18Ootolith data obtained by SIMS using a species-specific oxygen isotope fractionation equation. For accurate estimation of ambient water temperature, the oxygen isotope composition of seawater (δ18Oseawater) at the time of otolith formation is needed to correct for the effect of salinity on δ18Ootolith. As there were not adequate δ18Oseawater data in Japanese waters available at the time of analysis, δ18Oseawater in each spawning ground was calculated using regional salinity–δ18Oseawater mixing curves in the Sea of Japan [18Oseawater is oxygen isotope composition of seawater and S is salinity. To account for the interannual variation in salinity experienced among fish of different year-classes, year-specific salinity data were derived from a regional high-resolution ocean model, the Japan Coastal Ocean Prediction Experiment model  and 47 vertical layers. Using year-specific salinity data during the peak spawning months , the δ18Oseawater was calculated for each spawning ground for the years 1993–2017. Salinity data at 5 m depth was used as the PBT larvae are mainly found at or near the surface [18Oseawater values were converted from the VSMOW scale to the VPDB scale by simply subtracting 0.27‰ [18Ootolith in the oxygen isotope fractionation equation is measured against the VPDB standard.Water temperature experienced during the larval stage was reconstructed from the core δof Japan  and the of Japan :δ18Ose. Th in the spawning grounds that were calculated using the JCOPE2 model. As the hatching date of each individual fish was not available, the seasonal SST  was compared with the reconstructed temperatures averaged over the fish of the same year-class. Due to the low sample size in some year-classes, the comparison was made for the 2009, 2010, and 2011 year-classes. We used the temperature estimates calculated based on the clustering results when k = 2.We evaluated the accuracy of absolute temperature reconstruction by comparing the ambient temperature exposure of PBT larvae estimated from the SIMS-measured core δ18Ootolith chronological record during the early life and immature stages of all fish samples, with δ18Ootolith values progressively enriched toward the first opaque zone , where most fish showed a gradual decrease in δ18Ootolith values during this period. The δ18Ootolith values then increased toward the first opaque zone, peaking at –0.2 to –2.1‰ (VPDB).An increasing trend was observed in the δque zone . The ave18Ootolith values corresponding to the larval stage greatly varied among the individuals, ranging between –3.8 and –1.2‰ (VPDB) with most of them falling within the range between –3.5 and –1.5‰ (VPDB) (The core δ‰ (VPDB) . The disk was 2. Clustering results when k = 3 and k = 2 both grouped individuals into those with enriched core δ18Ootolith values (lower temperature) and those with depleted core δ18Ootolith values (higher temperature). When k = 3, Cluster 1 (blue plot in n = 22) was composed by fish with relatively enriched core δ18Ootolith values ranging between –2.6 and –1.2‰ (VPDB), while Cluster 2 (orange plot in n = 12) and Cluster 3 (green plot in n = 17) were composed by fish with relatively depleted core δ18Ootolith values ranging from –3.8 to –2.6‰ (VPDB) and –3.6 and –2.4‰ (VPDB), respectively. The distance from the otolith core to the first opaque zone ranged approximately between 900–1300 μm for Cluster 1, 800–1100 μm for Cluster 2, and 1100–1500 μm for Cluster 3.The results of cluster analysis are presented in k = 2 were similar to the clustering results when k = 3, resulting in groups of fish with enriched core δ18Ootolith values (Cluster A in n = 23) and depleted core δ18Ootolith values (Cluster B in n = 28). All individuals who were previously assigned to Clusters 2 and 3 were in fact combined to form a single cluster (Cluster B), except for one individual who was assigned to a different cluster (Cluster A). Mean core δ18Ootolith for Cluster A and Cluster B were –2.0 and –3.1‰ (VPDB), respectively, with Cluster B showing significantly higher δ18Ootolith values . Although not significantly different , Cluster B showed a larger variation in the distance from the otolith core to the first opaque zone (800–1500 μm) than that of Cluster A (900–1300 μm) .The clustering results when 18Oseawater, and SST are plotted in 18Oseawater values of 0.03‰ (VSMOW) in the Sea of Japan and 0.21‰ (VSMOW) in the Nansei Islands area (The time series data (1993 to 2017) on salinity, δnds area , which y18Ootolith values (Cluster 1 and Cluster A) as those originating from the Sea of Japan and those with depleted core δ18Ootolith values  as those originating from the Nansei Islands area for the temperature reconstruction . The mean estimated ambient water temperature (± 2SD) experienced during the larval stage was 25.9 ± 3.1°C for Cluster 1 (the Sea of Japan cluster), 31.1 ± 2.7°C for Cluster 2 (the Nansei Islands area cluster), and 30.3 ± 2.9°C for Cluster 3 (the Nansei Islands area cluster). When k = 2, the mean reconstructed temperature was 26.7 ± 3.1°C for Cluster A (the Sea of Japan cluster) and 30.7 ± 2.8°C for Cluster B (the Nansei Islands area cluster).SST during the peak spawning period in the Sea of Japan from 1993 to 2017 was consistently lower than that in the Nansei Islands area , with a 18Ootolith measurements . Higher temperature estimates were evident in both clusters, with some individuals experiencing temperatures >30°C (as high as 33.4°C) in the Nansei Islands area cluster. However, the relative temperature difference between Cluster A (the Sea of Japan cluster) and Cluster B (the Nansei Islands area cluster) estimated from the core δ18Ootolith matched well with that observed in the SST data, which yielded a temperature difference of 3.7 ± 3.2°C (± 2SD) between the two clusters.The average SST (± 2SD) during the spawning season from 2009 to 2011 was 23.0 ± 2.4°C and 26.8 ± 2.0°C in the Sea of Japan and the Nansei Islands area, respectively, giving a SST difference of 3.8 ± 2.0°C between the two regions. The average reconstructed absolute temperatures for the three year-classes  were approximately 3.0 to 4.0°C higher than the corresponding SST, indicating an offset of about 0.8 to 1.1‰ (VPDB) from the SIMS δ18Ootolith and water temperature [18Ootolith chronologies likely reflects a decreasing water temperature experienced during the early life and immature stages of PBT from autumn to winter. Similarly, the initial decrease in δ18Ootolith is presumed to reflect an increase in water temperature as PBT hatched in the two primary spawning grounds would later be exposed to higher water temperatures in summer, which peaks in late August to early September.Given the negative relationship between δperature , 33 the 18Ootolith) and those experienced relatively lower temperatures (enriched core δ18Ootolith). Spawning temperatures of PBT in the two spawning grounds have been primarily inferred from the larval surveys [18Ootolith enriched- and depleted-groups detected in the clustering results therefore most likely reflect the Sea of Japan born- and the Nansei Islands area born-fish.The cluster analysis grouped fish individuals into those experienced relatively higher temperatures  in our samples corresponds roughly to 7–9°C in water temperature, which is in reasonable agreement with the known spawning temperature range in the Sea of Japan and the Nansei Islands area (see the previous paragraph). This variation was not observed in the previous study [18Ootolith of YOY bluefin. The conventional IRMS requires a larger amount of otolith powder compared to SIMS, which essentially limits the spatial and temporal resolution (10 μm for SIMS vs. >250 μm for IRMS). Such coarse resolution of the IRMS results in δ18Ootolith averaging over the entire early life stages and quite often beyond that of the fish, possibly masking the pronounced difference in the environment recorded during the egg and larval stages. SIMS technique should therefore be considered as the primary method when focusing on reconstructing and examining the early life history, particularly the larval stages of fish.The great variation in the core δus study  that use18Ootolith suggests that spawning continued for a longer period, likely reflecting a longer spawning duration in the Nansei Islands area. Spawning in the Nansei Islands area is reported to occur for 2–3 months between late April to early July [18Ootolith for Cluster B , which reflects an increasing water temperature experienced by the PBT larvae throughout the entire spawning season in the Nansei Islands area . Shiao et al. [18Ootolith peak from the otolith core was shorter for the YOY born in the Sea of Japan due to the late spawning season, resulting in a shorter growth period. Our results also showed a similar pattern for Cluster 1 (the Sea of Japan cluster) and Cluster 3 (the early-born Nansei Islands area cluster), except for Cluster 2 (the late-born Nansei Islands area cluster) which had the shortest otolith distance. This might be the result of low productivity environments that are inherent to the nursery areas in the northwestern Pacific [18Ootolith peak (or first opaque zone) alone therefore might possibly misassign individuals to the wrong natal origin, particularly for those born in the later spawning season in the Nansei Islands area. As the samples used in our study are all adult fish with unknown origin, further studies should use larvae or juvenile samples with known origin to evaluate the accuracy of the natal origin assignment by SIMS. Nonetheless, the SIMS-based core δ18Ootolith is a powerful alternative tool that can provide information about the natal thermal environment, which is critical for determining the natal origin of PBT and other fish species that undergo different temperature environments during the early life stages.The larger variation in the distance from the otolith core to the first opaque zone observed for Cluster B with depleted core δrly July , 14, wherly July , 64. Givo et al.  found th Pacific , which c Pacific  for thei Pacific , suppose18Ootolith values in the present study overestimated absolute water temperatures experienced by fish even after the offset correction of 0.41‰ has been applied. Higher absolute temperature estimates based on the SIMS δ18Ootolith measurements have also been reported in the previous studies [18Ootolith is an incomplete correction of instrumental mass fractionation caused by matrix effects [18Ootolith values are measured against the UWC-3 standard which is currently known to be the most isotopically and chemically homogeneous calcite standard. There are no reliable aragonite standard materials currently available that match exactly with the complex crystalline structure and composition of otoliths. Due to the inherent nature of the SIMS technique, contaminants from the other oxygen-bearing phases such as organic proteins [18Ootolith results have been calibrated to consider such effects, the single offset correction applied here may not be sufficient to fully address the natural variability of protein incorporation and other matrix-related bias at different life stages of otoliths. In fact, the presence of relative hydrogen content indicated by the background-corrected 16OH−/16O− ratios was higher for the δ18Ootolith measurements taken from the otolith core than that taken from the other otolith regions. This suggests more incorporation of organic matter and/or water content during the larval stage and might explain the erroneously high temperature estimates observed for both the Sea of Japan and the Nansei Islands area clusters. Nevertheless, such bias on the resulting δ18Ootolith values can be assumed to be stable and constant as the δ18Ootolith measurements were taken from the same life stage with the same analytical conditions [The SIMS-generated δ studies , 69 and  effects , 52. In proteins , 71 and proteins –74. Althnditions . Thus, t18Oseawater values. We used the seasonal δ18Oseawater instead of those corresponding to the time of otolith formation as hatching date of individuals was not available. The surface salinity in the Nansei Islands area does not fluctuate significantly throughout the spawning season, whereas that in the Sea of Japan is more subject to change due to freshwater discharge mostly from Changjiang (Yangtze) River in China [18Oseawater. The errors in salinity or δ18Oseawater estimation in the Sea of Japan could thus be a factor causing the temperature overestimation, but not to a significant degree. It is plausible to conclude that the observed temperature offsets are caused by a combination of a sample-standard mismatch, salinity uncertainty, and SIMS analytical precision.Another potential factor affecting the estimate error in temperature reconstruction is δin China . The eff18Ootolith values was shown to serve as an effective thermal indicator for assigning individual fish to its natal origin. This technique can be further used to quantify the recruitment contribution from each spawning ground and subsequently monitor and evaluate the effects of climate change on spawning and population dynamics of various fish. Based on our clustering results, natal origin of PBT for all year-classes pooled was 45% (2009–2011 year-class specific ranges: 33–50%) in the Sea of Japan and 55% (ranges: 50–67%) in the Nansei Islands area. Previous study that used otolith daily increment counts of small PBT [In this study, the use of the core δmall PBT  estimatemall PBT , suggestS1 Table(XLSX)Click here for additional data file.


The annual rainfall maxima based on δ18Osw negatively correlated with the central Pacific El Niño index. This suggested that La Niña and central Pacific El Niño events lead to heavy and light rainy seasons. The heavy rainy season had more serious impacts in recent decades, which likely increases the flood risk. In contrast, the frequency and rainfall amount of the light rainy season has not changed significantly, although a catastrophic drought has hit the MRD. Our finding concludes that the impact of the ENSO event on MRD hydrology is inconsistent in the past century.The Mekong River Delta (MRD) is an essential agricultural area for the worldwide rice supply. Floods and droughts triggered by El Niño southern oscillation (ENSO) have been threatening sustenance in the MRD. Sustainable food supplies require understanding the response of the MRD hydrology to the changing ENSO behaviour in recent decades. Here, we reconstructed the annual rainfall maxima in the MRD using the oceanic paleoclimate proxy from coral skeletons and compared them with ENSO indexes. Annual minima of coral-based seawater oxygen isotope (δ However, recent severe hydrological disasters with frequent floods and droughts threaten the MRD3. Flood events seriously impact agriculture and health hazards since the large cities and agricultural fields in the MRD are at low elevations4. Drought events, such as those in 2015 and 2019 CE, cause collapse agricultural systems by causing moisture loss from the soil and intruding saline groundwater into agricultural fields5. Over 4600 km2 of rice field was damaged, and 200,000 households suffered from safe water shortages in 2019 CE6. Understanding the dynamics of rainfall changes and the Mekong River flow rate is crucial for sustainable food supply9.Agriculture in the Mekong River Delta (MRD) is the key to sustaining the worldwide food supply. Vietnamese rice production contributed 7.5% of the total global rice exports in 2017 CE, which was supported by its production in the MRD11 approached the hydrological changes in the MRD using the observation and land-based proxy records of rainfall in the Indochina peninsula . The El Niño Southern Oscillation (ENSO) has an important role in river runoff and rice production in the MRD, as El Niño (La Niña) events would induce the short (long) wet season with a low (high) amount of rainfall17. The light rainy season during El Niño allows intrusions of saline water16. The heavy rainy season causes flood events16. Food sustainability requires how the hydrology event in MRD responds to the ENSO in the future warming earth2, as the ENSO behaviour has been changing in recent decades18. However, rainfall observations are spatiotemporally heterogeneous. Most of the proxy records and tidal data are far from the river mouth of the MRD20. These limitations of available records and the spatial heterogeneity of rainfall make it complex to reveal the past hydrological changes of the MRD. Here we investigate the frequency and intensity of hydrological changes during the last century using a coral proxy record. The chemical composition in a drilled coral core allows us to calculate an oxygen isotopic ratio in seawater  which enables a reliable reconstruction of paleolimnology24 and palaeoceanography26. Reconstruction of the interannual to decadal hydrological change using the oceanic proxy could imply mechanisms behind the flood and drought events with the anthropogenic27 and natural13 hydrological changes.Previous studiesPorites. sp, 150 cm in length, Fig. th June 2006, from the southwestern coast of Con Dao Island  and oxygen isotope ratio in coral skeletons  (see Methods). The δ18Osw was calculated from the measured δ18Ocoral by subtracting the temperature component inferred from Sr/Ca using the centring method30. We took the annual minima of δ18Osw (min-δ18Osw) as an indicator for maximum freshening. The min-δ18Osw was reported as an anomaly relative to the mean during the reference period (1981–2000 CE).We drilled a coral core  over the MRD from 1979 to 2020 CE . The annual maximum rainfall  was reconstructed following the calibration work to the min-δ18Osw and composited  with the maximum rainfallGPCP in the MRD. Based on the maximum rainfallrecon+GPCP  and Niño cold tongue (NCT) as indicators of ENSO in the central Pacific (CP) and eastern Pacific (EP) Oceans18. We investigated the teleconnection of the ENSO by comparing the maximum rainfallrecon+GPCP with the thermal gradient between the western  and central Pacific Oceans 33.The δ18Ocoral showed 82 seasonal cycles from December 1923 to June 2006  . The min-δ18Osw, which ranged from − 0.84 to 0.51‰, negatively correlated with the maximum rainfallGPCP   is much lower than δ18Osw (ca. 0‰37), river runoff and rainfall in the rainy season decrease the values of δ18Osw in the surrounding ocean. Ocean currents  along the southern coast also may affect salinity around Con-Dao Island. Our calibration work28  on the Con Dao Island showed that the influence of the ocean current is smaller than rainfall in the wet season. The correlation between min-δ18Osw and SST changes in the rainy season results from an air-sea interaction over the western Pacific Ocean38. Hence, the coral-based δ18Osw records the maximum rainfall in the MRD through the entire coral time series.Our coral-based δ39 to the maximum rainfallrecon . The field correlation analysis showed the negative correlation between the detrended SST in the CP region with one year leading and the maximum rainfallrecon+GPCP  was collected from Con Dao Island, located 90 km far from the MRD. The core was sliced into 5 mm thickness. X-ray images of slices were taken using a digital X-ray scanner to visualise the coral growth transaction and annual bands.18Ocoral) were drilled at ca. 1 mm intervals along the maximum axis of coral growth. δ18Ocoral of powdered subsample, 20–40 μg each, was analysed using a stable isotope ratio mass spectrometer (Finnigan MAT253) and an automated carbonate device (Kiel IV) at Hokkaido University. The coral skeletal powdered subsamples, 90–110 μg, were dissolved in 25% nitric acid and diluted to a Ca concentration of 7 ppm with ultrapure water for Sr/Ca determination48 on an inductively coupled plasma optical emission spectrometer, Thermo Scientific iCAP 6200 at Hokkaido University. The one-sigma precisions for δ18Ocoral and Sr/Ca data were ± 0.05‰VPDB and ± 0.07% RSD, respectively.Monthly coral skeletal powdered subsamples for geochemical analyses  based on paired measurements of Sr/Ca and δ18Ocoral using the centring method30. Centred values of Sr/Ca and δ18Ocoral  were used for the δ18Osw estimation to avoid the large uncertainty source for this estimation26. We used the slope of our Sr/Ca-SST dependency on Con Dao Island (− 0.0504 ± 0.004 mmol × mol−1/°C)28 and the slope value of the δ18Ocoral-SST relationship (− 0.18‰VPDB/ºC50). The one-sigma uncertainty of calculated δ18Osw was ± 0.06‰. The age model for the coral records was developed using the maxima and minima of the Sr/Ca values in any annual cycle as anchoring points. The anchoring points were tied to the maxima and minima of SST on Con Dao Island28. We used linear interpolation to obtain monthly resolution time series using AnalySeries software51, version 2.0.8.We calculated the δ18Osw (min-δ18Osw). Min-δ18Osw was reported as the anomaly relative to the reference period (1981–2000 CE). The reference period was defined as the 20-year period in which the min-δ18Osw and rainfallGPCP overlapped. Our coral record was compared with rainfallGPCP 18. We estimated the annual rainfall maxima  from the 3-year moving average of the min-δ18Osw based on the slope between the 3-year moving average datasets of min-δ18Osw and the maximum rainfallGPCP . The threshold value was estimated as the average value plus/minus one standard deviation in maximum rainfallrecon+GPCP during the reference period (1981–2000 CE). The bandwidth for the estimation of the occurrence rate was set to 11 years to detect decadal-scale variations. The confidence interval of the occurrence rate was determined using a bootstrap technique and a percentile-t method. Events were simulated with replacement and used for occurrence rate calculations, which were repeated 5000 times. Wavelet analyses were conducted using the “biwavelet” package in R software52. We surveyed the significance of trends in the occurrence rate and rainfall amount of the heavy/light rainy season based on the Cox-Lewis test in Caliza software32 and the Mann–Kendall trend test in R software52, respectively.We estimated the periodicity using REDFIT spectral analysisSupplementary Information.


Transcranial magnetic stimulation-evoked electroencephalography potentials (TEPs) have been used to study motor cortical excitability in healthy subjects and several neurological conditions. However, optimal recording parameters for TEPs are still debated. Stimulation rates could affect TEP amplitude due to plasticity effects, thus confounding the assessment of cortical excitability. We tested whether short interpulse intervals (IPIs) affect TEP amplitude.We investigated possible changes in TEP amplitude and global mean field amplitude (GMFA) obtained with stimulation of the primary motor cortex at IPIs of 1.1–1.4 s in a group of healthy subjects.We found no differences in TEP amplitude or GMFA between the first, second and last third of trials.Short IPIs do not affect TEP size and can be used without the risk of confounding effects due to short-term plasticity. B1, B2, B3block 1, 2, 3EEGelectroencephalographyEMGelectromyographyFDIfirst dorsal interosseousGMFAglobal mean field amplitudeICAindependent component analysisIPIinterpulse intervalM1primary motor cortexRMTresting motor thresholdTEPTMS-evoked potentialTMStranscranial magnetic stimulationToItime window of interest1The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has become an increasingly used method to assess cortical physiology in the intact human. Advantages over other brain stimulation techniques include the possibility to stimulate different superficial cortical areas ,2,3 and To test whether short IPIs may influence TEPs, we measured their amplitude trend during a block of 100 trials delivered with IPIs jittering randomly between 1.1 and 1.4 s (0.9–0.7 Hz stimulation rate). If this stimulation rate produced inhibitory short-term plasticity changes ,18, TEP 22.1We enrolled 16 right-handed healthy volunteers . Participants did not have history of neurological or psychiatric disorders, were not taking medications known to affect the central nervous system and did not have contraindications to TMS .Ethical approval: The present research complied with all the relevant national regulations and institutional policies, was in accordance with the tenets of the Declaration of Helsinki, and had been approved by the authors’ institutional review board or equivalent committee.Informed consent: Informed consent has been obtained from all individuals included in this study.2.22 biphasic magnetic stimulator, connected to a figure-of-eight 70 mm coil , over the spot on the scalp overlying the left primary motor cortex (M1) evoking the largest and most consistent MEP in the right first dorsal interosseous (FDI) muscle. We used a neuronavigation system  to monitor coil positioning throughout the experiment. We calculated the resting motor threshold (RMT) as the lowest stimulation intensity that produced a MEP of at least 50 µV in 5 out of 10 consecutive trials in the relaxed right FDI [Participants were tested in a single experimental session. They were seated in a comfortable chair and were asked to relax and fixate a cross displayed on a PC screen about 90 cm in front of them. Participants wore earphones continuously playing a masking noise designed to reduce the perception of the TMS click ,23. The ight FDI . The exp2.3EEG was recorded from 32 passive electrodes on an elastic cap  according to the international 10–20 system , using Ft is time, K is the number of channels, Vi is the voltage in channel i and Vmean is the mean of the voltage in all channels [TMS–EEG signals’ preprocessing was performed with EEGLAB 14.1.1  with thechannels .p < 0.05). Possible differences in the GMFA across the three blocks were investigated by means of a two-way repeated measures analysis of variance (ANOVA) with “block”  and “ToI”  as factors of analysis . Results are expressed as mean ± s.d. unless otherwise specified. Normality of distribution of the GMFA values was assessed by means of the Shapiro–Wilk’s test. GMFA values above or below mean ±3 s.d. were considered outliers and corrected by winsorization. p values < 0.05 were considered significant. The sphericity of GMFA value distribution was verified by Mauchly’s tests, and Greenhouse–Geisser correction was applied when necessary. Post hoc comparisons were conducted when appropriate by means of planned contrasts.Statistical analyses were performed using three time windows of interest (ToI) previously considered  ranging 3p values were found in the Shapiro–Wilk’s tests). Two significant high outliers in GMFA distributions were found and substituted through winsorization. We found no significant effect of factor “block”  and “block × ToI” interaction  in the ANOVA on the GMFA. We found a significant effect of factor “ToI” . However, planned contrast between ToIs did not return any statistically significant differences  , 32.63 (7.39) and 32.56 (7.39) epochs were averaged, respectively, for B1, B2 and B3. Cluster-based analysis showed no significant differences between TEPs recorded in different blocks in the ToIs considered in analysis 1  and analysis 2  . GMFA va > 0.05) .4We tested whether short IPIs determine changes in TEP amplitude and GMFA within a recording block of 100 TMS trials delivered over M1. The results showed that TEPs and GMFA obtained by averaging three smaller blocks of around 30 TMS pulses did not significantly differ between each other. Our results, therefore, provide evidence that frequencies of 0.7–0.9 Hz can be used to stimulate M1 in the TMS–EEG context without the risk of inducing within-block effects due to repeated TMS.Our results are in agreement with those of Julkunen and coworkers, who found that MEP amplitude remains constant during short trains of TMS , but mayWe acknowledge some limitations to the present study. As residual TMS click perception was reported by 5 out of 16 participants; therefore, TEP components around 100 and 200 ms may have been partially contaminated by auditory-evoked potentials (AEPs). While we cannot provide direct evidence to rule out this possibility, a substantial contamination of our TEPs by auditory responses is ruled against by a lack of a prominent P200, characteristic of AEPs , and by As we used subthreshold intensity, which is the most common for TMS–EEG studies on M1 where MEPs are not investigated, we cannot exclude short-term effects on TEPs’ amplitude when higher stimulation intensities are used. In addition, TEPs in each block were obtained with a relatively small number of pulses (around 30); however, previous observations have suggested that TEPs obtained with a comparable number of trials have a high similarity to those recorded with a standard number of epochs (over 100) . In conc