Short and long distance cell dispersal can have a marked effect on tumor structure, high cellular motility could lead to faster cell mixing and lower observable intratumor heterogeneity. Here we evaluated a model for cell mixing that investigates how short-range dispersal and cell turnover will account for mutational proportions. We show that cancer cells can penetrate neighboring and distinct areas in a matter of days. In next generation sequencing runs, higher proportions of a given cell line generated frequencies with higher precision, while mixtures with lower amounts of each cell line had lower precision manifesting in higher standard deviations. When multiple cell lines were co-cultured, cellular movement altered observed mutation frequency by up to 18.5%. We propose that some of the shared mutations detected at low allele frequencies represent highly motile clones that appear in multiple regions of a tumor owing to dispersion throughout the tumor. In brief, cell movement will lead to a significant technical (sampling) bias when using next generation sequencing to determine clonal composition. A possible solution to this drawback would be to radically decrease detection thresholds and increase coverage in NGS analyses. In other words, intratumor heterogeneity can be interpreted as an evolutionary process which leads to a continuously increasing number of distinct clones within the primary tumor mass2. The presence of these distinct genotypes can give fitness advantage to a particular tumor clone at a certain stage and is therefore a driving force of the malignant progression. Dispersal is a crucial factor in these evolutionary processes, however little is known about the role of cell dispersal and motility in tumorigenesis.Accumulated genetic changes in a malignant tumor comprise somatic mutations and copy number changes, gene expression alterations, and epigenetic modifications. The differential combination of these traits in individual cells leads to intratumor heterogeneity which helps a tumor to increase survival, acquire metastatic capabilities and to develop resistance against systemic chemo- and targeted therapies3, or it can be branched i.e. lineages will contain a different sets of mutations4. Recent multi-region sequencing studies are in favor of the branched evolution model in tumors5. When the mutation profiles of cancer patients are examined, we can identify mutations present in each of the samples obtained from a single tumor. Other mutations are specific to few samples only. Interestingly, some of the patients show low genetic  heterogeneity, in which case almost all of the mutations are either common in all intra-tumor samples, or exclusive in the primary tumor. The underlying process that may cause these conserved mutational profiles is unknown – a possible explanation may be a sub-clone selection process caused by clonal competition4.From the theoretical point of view, evolution of a tumor can be either linear when mutations follow each other in a serial order so that a specific lineage will contain all previous mutationshttp://cancergenome.nih.gov/) has published a large number of breast cancer samples investigated with NGS6. The results were in general agreement with the current dogma of clinical practice i.e. high mutation rates entail a lower survival rate. This established view was however questioned by findings that even marginal clones can have a prominent effect on the patients’ response to therapy and survival after drug treatment8. Moreover, a careful statistical re-analysis of TCGA data showed that a slight change to the detection strategy can lead to a six-fold increase in the number of potentially relevant mutations9 which again points to the difficulty of relating mutational frequencies to prognosis.The Cancer Genome Atlas (TCGA) of the National Cancer Institute  was purchased from Innoprot. The Mel-Juso RFP cell line (Mel-Juso-TurboFP602-GVO-CD) was purchased from BioCat. SK-MEL-28 cell line was purchased from CLS Cell Lines Service and the fourth cell line was our previously used MeWo2 atmosphere.The Mel-Juso cell line was maintained in RPMI-1640 medium, the A375 GFP, SK-MEL-28 and MeWo cell lines were cultured in DMEM medium , each supplemented with 10% fetal calf serum  and 1% penicillin–streptomycin–amphoterycin  in tissue culture flasks at 37 °C in a humidified 5% CO5 cultured cells for each PCR reaction. Genomic DNA was also extracted from the samples of the Ring cell invasion assay (see Ring cell invasion assay section). In this, the sampling was performed by cell scraper , the scratched cells were raised in growth medium, and the genomic DNA was extracted directly from the cell suspension. In each case, the concentration (ng/µl) and purity (absorbance at 280 and 260 nm) of the DNA was measured by a Nanodrop ND1000 spectrophotometer.Genomic DNA was extracted directly from each cultured cell line for mutation validation. After trypsin-EDTA treatment for disruption of cell monolayers the genomic DNA was extracted from the cell suspension with DNeasy Blood and Tissue Kit  according to the manufacturer’s recommendations. Approximately 500 ng DNA was extracted from ~5 × 10Presence of cell line specific homozygous and heterozygous mutations in the TP53, PTCH1, CDKN2A, BRAF, HRAS, NRAS, ZNF214 and NF1 were validated using Sanger sequencing. These mutations are also used to differentiate and to calculate the composition of cell line mixtures. The direct DNA sequencing was performed using genomic DNA amplified by polymerase chain reaction. Primers were designed to be located in flanking sequences previously described to contain a specific mutation in the gene according to COSMIC (cancer.sanger.ac.uk/cell_lines) to allow amplification of genomic DNA only. The used primers and primer features are listed in Supplemental Table 2O. The amplification reaction was carried out in a thermocycler  with an initial denaturation step of 3 min at 94 °C, followed by 35 cycles consisting of three steps: 94 °C for 30 sec, 53 °C for 30 sec, and 72 °C for 2 min. Annealing temperature was optimized to the primers melting temperature. The last cycle was followed by an extension step of 6 min at 72 °C. The PCR product was purified, and DNA sequencing was performed at the Department of Genomic Medicine and Rare Disorders . The DNA sequence was analyzed by BioEdit and Genedoc programs.The PCR reaction was performed in 25 µl final volume, containing 500 ng of genomic DNA, 10 mM of each dNTP , 10 µM of each of the eight primers, 5 units of Taq polymerase (Invitrogen), 2.5 µl 10x buffer, completing to the final volume with nuclease free H® conB cell exclusion silicone rings were purchased from Sarstedt AG&Co. , and were preserved in pure alcohol solution until use. The rings were placed vertically in 60 × 15 mm culture dishes . In this setting, the inner cultivation area was 3.1 cm2 per unit and the external growth surface was 17.9 cm2/well. Outline of the rings were marked on the transparent plate bottom. The first cell suspension was added carefully to the inner side of the ring with a cell number of 300,000 cells inside the ring in 3 ml volume of DMEM medium. After an overnight incubation for cell attachment, the rings were carefully removed using tweezers followed by washing the cells with 1x phosphate-buffered saline (PBS) to remove cell debris. The second cell line (MeWo in each case) was dispensed in the entire well surface in 6 ml of DMEM medium, with a concentration of 100,000 cells/ml. The marked borders of the silicone rings were monitored under light microscope . Growth medium was replenished every second day. Fluorescent photographs were taken at multiple sites along the external and inner border of the marked ring on the 7th day (after 6 day of co-cultivation)  at the HAS Research Center for Natural Sciences. Images were processed by Image J software .FlexiPERMRing cell invasion experiment was processed in two circular arcs within the cell culture dishes. The inner arc was positioned directly next to the marked border of the formal ring, its width was 10 mm (inner sample), and the second arc was positioned directly to the wall of the dish, its width was 10 mm . Sampling was performed by a sterile cell scraper. The cell combination sample set was contained 2/5/10/25 or 50% LINTERNATM-A375 cells among MeWo cells in final 1 × 106 cell/ml concentration.Sampling from the We computed Wilcoxon signed rank test to compare mutation frequencies between invading cell lines and MeWo, and to compare the degree of invasion between A375 and SK-MEL-28.Time-lapse recordings were performed on a computer-controlled Leica DM IRB inverted microscope equipped with a Marzhauser SCAN-IM powered stage and a 10x N-PLAN objective with 0.25 numerical aperture and 5.8 mm working distance. The microscope was coupled to a Zeiss Colibri illumination system and an Olympus DP70 color CCD camera for epifluorescent image acquisition.2 atmosphere in tissue culture grade Petri dishes  in a mini incubator (CellMovie) mounted on the powered stage of the microscope. A custom made time-lapse experiment manager software controlled the field of view and plane positioning, illumination and image acquisition on a PC. Phase contrast and epifluorescent images of cells were collected consecutively every 10 minutes from each of the microscopic fields for up to 72 hours. Images were edited using NIH ImageJ software.Cell cultures were kept at 37 °C in humidified 5% COvi(t), of a given cell i at time t was calculated as vi(t) = |xi(t + Δt) − xi(t)|/Δt with a suitably chosen Δt. We selected Δt = 1 h, where the typical cell displacements are larger than 10 μm, hence larger than the error of the manual tracking procedure performed with the help of a custom-made cell tracking software.Cell motility was quantified as the net displacement of tracked cells during the first 24–72 h of the recorded time period. The velocity, F(v) were calculated as shown in eq. (N(t) cell being in the cell population. The velocity distribution function F(v) gives the probability that for a randomly chosen i and t the velocity vi(t) is larger than v. Average distance of cell migration, d(τ), was calculated for a range of elapsed time lengths τ as: d(τ) = 〈|xi(t + τ) − xi(t)|〉i,t where the average 〈…〉i,t is taken over each possible choice of t and i.Average velocity given by n in eq. :1\documeAmplicons were designed using the AmpliSeq Designer software , targeting the entire coding sequence of the genes. Primers were designed to include parts of the introns to achieve a higher coverage of the coding exons. Amplicon library was prepared with the Ion AmpliSeq Library Kit 2.0. In this, primer pools were added to 10 ng of genomic DNA and PCR amplified. PCR cycles were set up to include 18 cycles of 99 °C for 2 min, at 99 °C for 15 s, and at 60 °C for 4 min, and finally a plateau at 10 °C. Primers were partially digested using a FuPa reagent, and then sequencing adapters were ligated to the amplicons. Library was purified using the Agencourt AMPure XP Reagent . The final library concentration was determined by fluorescent measurement on Qubit 2.0 instrument . Template preparation was executed using an Ion OneTouch kit on semiautomated Ion OneTouch instrument using the emPCR method. After breaking the emulsion, nontemplated beads were removed from the solution during the semiautomated enrichment process on Ion OneTouch ES instrument. Following adding the sequencing primer and polymerase, the fully prepared Ion Sphere Particle (ISP) beads were loaded into an Ion 314 sequencing chip, and the sequencing runs were performed using the Ion PGM 200 Sequencing kit . Average sequencing coverage was 600x (range 200–1200x).The sequencing was run using three regions/well with one repeat for each of the three cell lines (3 × 3 × 2 = 18 measurements). The dilution cascade was measured in duplicates (2 × 5 = 10 measurements). Four additional repeats were added as technical controls .FastQC, followed by read trimming using trimmomatic15. High quality reads where mapped to the human genome  using BWA MEM16, and converted to bam format using SAMtools. Aligned reads where processed using the GATK toolkit17 based on the GATK pre-processing best practices (https://www.broadinstitute.org/gatk/guide/bp_step.php?p=1). Mutation calling was performed using the SAMtools mpileup (http://www.htslib.org/) default parameters. Mutations were identified by first selecting regions with cell line specific mutations from the SAMtools mpileup output, followed by calculation of reference and non-reference base totals at all positions. In case of non-reference, bases had to match the alteration of the cell lines.Data from the Ion Torrent runs were analyzed using the platform-specific pipeline software Torrent Suite v3.2.1. Quality control of reads was performed with the In addition to the experimental investigations, we set up a computational model in order to correlate the experimentally observed cell behavior with a simple mathematical description of cell dispersal and heterogeneity.N x M sized matrix to simulate the surface of a plate. Each x, y coordinate pair represents a position on the plane where a cell can be placed, and movement outside of the boundaries of the matrix is prohibited. The model contains a few simplifying assumptions: cells cannot overlap, environment (e.g. medium concentration through time) is constant, apoptosis is determined as a random function, and the size of cells is identical.This model uses an Two cell types are used in each simulation, agreeing with the experiments of the invasion assay. The first cell line (inner) is placed in the middle of the plate simulating a silicone ring with a radius N × 0.1 (radius is 10% of height), while the second cell line was evenly distributed across the entire surface. The density of the inner cell line was 5%, while density of the second cell line was set to 2.5%.i” had a clonal persistence (velocity) Ci,clone_persistance of 5, 13 and 15 for the MEWO, SKMEL28 and A375 respectively, where each simulated cell “ j “ had persistence randomly selected using eq. . The program is available upon request.The modelling program was written in C programming language; data visualization was performed using the Allegro package version 5.2  compared to MEWO were significant in all four settings Fig. . MutatioTo better understand the linkage between cellular composition and mutation frequencies, we performed a calibration sequencing, where pre-determined volumes of two cell lines were mixed. The selected proportions were 2%, 5%, 10%, 25% and 50% of the A375 and MEWO cell lines as well as SK-MEL-28 and MEWO cell line pairs Fig. , each wiHigher proportion of one cell line generated frequencies with higher precision, while mixtures with even amounts of each cell line had lower precision manifesting in higher standard deviations ranging between 8–17% in case of high coverage. When including low coverage samples, standard deviation range increased to 30% Fig. .Mean frequency difference for mutation pairs in technical replicates was 5.6% (mean ranging between 2.9–10.4%) in the case of the A375-MEWO pair. Similar results were obtained by the SK-MEL-28 and MEWO calibration sequencing technical replicates, where the mean frequency difference of mutations is 3.2% ranging between 1.6% and 5.6%. Interestingly, sequencing of the NF1 and PTCH1 genes in the A375 and MEWO pairings generated higher deviations, probably due to low coverage in one of the replicates at each combination.Sequencing coverage in the calibration sequencing and ring invasion assays spanned between 100x–1200x. Coverage had a great effect on mutation frequencies in our experiments, which we further examined using a permutation test. Permutation test to calculate mutation frequency standard deviations was performed by generating/simulating reads with a predetermined mutation frequency, followed by shuffling of reads and calculation of the “measured” mutation frequency with different coverages. This process was done in five steps: 1) generating an array of 10000 elements (representing reads), 2) mutating a given F(expected) percentage of the simulated reads for frequencies between 1–99% separately, each percentage with 100 replicates, 3) shuffling of reads with Fisher-Yates shuffle, and 4) calculating the F frequency of the first N reads representing total coverages of 50x, 100x, 200x, 250x, 400x, 500x, 600x, 700x and 1000x, and finally 5) calculating the standard deviation between F(expected) and F frequencies among replicates. In this, low read coverage of a mutation generated higher average and maximum standard deviations (4.6% and 12.9% respectively), which decreased to less than 3% as sequencing coverage increased Fig. .In silico modelling was performed utilizing phenotype data obtained from the mono-culture experiments. Approximate cell doubling time was set 22 hours for the MEWO, 19 hours for the A375 and 22 hours for the SK-MEL-28 cell line. Cell movement was set using data measured at 10-hour movement: MEWO cell line movement was set to 5 microns, while the other cell lines were set to 12 microns. In line with the monoculture experiments, simulations lasted for a total of 72 hours. By tracking the movement of a few cells, we generated a random movement pattern analogous to the cell culture experiments  can have dramatic results on the final genetic composition.Determining clonal and sub-clonal heterogeneity is usually accomplished by linking mutation counts, mutation frequencies, and copy number variation statusWe have to note that the two distinct cell lines (A375 and SK-MEL-28) displayed different degree of invasion. When detection thresholds are set to an adequately sensitive level and the coverage is sufficiently robust, multi-region sequencing can enable to track such distinct clones and their contribution to intratumor heterogeneity in a clinical sample. Highly mobile subclones can be either less or more present in a given sample than less mobile subclones.Interestingly, when sequencing pre-determined mixtures of two different cell lines, 50–50% distribution resulted in the highest standard deviation in the detected cellular proportions. This was especially prominent in case heterozygous mutations were evaluated. In addition, even with a coverage at 1000x the standard deviation of the mean mutation frequencies still remained as high as 2%. We have to emphasize that here we used only two cell lines in one experiment in each setting. In a patient-derived tumor sample the different clones can all together represent a minority compared to normal DNA originating from immune cells and the tumor environment. In turn, this will result in an even smaller proportion of actual tumor cells with a given mutation in the sample. All together these results suggests that current next generation sequencing is not yet fully capable of exactly determining clonal composition and intratumoral evolution.22 often use mutation frequencies as key input information23.Motility can affect the mutation detection using next-generation sequencing and a shift in frequencies may misleadingly be interpreted as a change in clonal composition. Higher volume of a given cell line generated frequencies with higher precision, while mixtures with lower amounts of each cell line had lower precision manifesting in higher standard deviations. This is an alarming observation emphasizing a possible bias when using next generation sequencing to monitor and estimate tumor progression, since mathematical models that predict evolution pathsin silico simulation model of cellular mixing. By only setting a few basic parameters  the model delivered a results comparable to the actual experimental observations. These results strongly support our hypothesis and enables future reverse engineering tumor compositions in order to decipher the process of tumor evolution.Here we also present an in silico study has pointed out the effects of certain mutations on clonal composition using 3D models. In this, novel driver mutations decreased genetic diversity, while lack of driver mutations lead to a heterogeneous tumor24. Another limitation is the use of unobstructed space easily filled by the cells in our in vitro experiments – such conditions are only indirectly comparable to in vivo tumors. On the other hand, the growth of a tumor lasting for several years provides a similar opportunity for cancer cells to achieve a slow mixing. Finally, in our experiments we sequenced a panel of genes using targeted sequencing. In most cases, variant callers either identify germline mutations or somatic mutations in which case a normal/tumor pair is required. Because of the small size of the panel, varying coverage, and the fact that we knew where to expect the mutations, we decided on performing the analysis using a simple approach focusing on cell line specific mutations. Consequently, the applied method does not include statistical or background filtering, and cannot be employed to compute mutation calling rates in dissimilar experimental situations.A limitation of our approach is the confinement of the investigation to a 2D model. A recent In summary, we demonstrate that cell movement can significantly influence tumor composition. Current methods for studying intratumoral evolution assume that genetic lesions are homogenous between regions and represent a shared clonal origin between tumor cells. These models do not account for the fact that some cells are more mobile than others. This can lead to mis-calling clones as absent or non-contributing to heterogeneity in multi-region sequencing studies of tumor evolution. We propose an alternative hypothesis that some of the shared mutations detected at low allele frequencies represent highly motile clones that appear in multiple regions of a tumor owing to dispersion throughout the tumor. This mixing of cells can lead to a sampling bias when using next generation sequencing to determine clonal composition. A possible solution to this drawback would be to radically decrease detection thresholds and increase coverage in NGS analyses.Supplementary video 1Supplementary video 2Supplementary video 3Supplementary table 1Supplementary table 2Supplementary table 3Supplementary methods and figure


The micro waveform of His bundle potential can’t be recorded beat-to-beat on surface electrocardiogram yet. We have found that the micro-wavelets before QRS complex may be related to atrioventricular conduction system potentials. This study is to explore the possibility of His bundle potential can be noninvasively recorded on surface electrocardiogram.s , AHs  and HVs  interval recorded on surface “new electrocardiogram” and PA, AH, HV interval recorded on His bundle electrogram was investigated.We randomized 65 patients undergoing radiofrequency catheter ablation of paroxysmal superventricular tachycardia (exclude overt Wolff-Parkinson-White syndrome) to receive “conventional electrocardiogram” and “new electrocardiogram” before the procedure. His bundle electrogram was collected during the procedure. Comparative analysis of PAP > 0.05) between groups in HVs interval (49.63 ± 6.19 ms) and HV interval (49.35 ± 6.49 ms). Results of correlational analysis found that HVS interval was significantly positively associated with HV interval .There was no difference (His bundle potentials can be noninvasively recorded on surface electrocardiogram. Noninvasive His bundle potential tracing might represent a new method for locating the site of atrioventricular block and identifying the origin of a wide QRS complex. Comparative analysis of PAs, AHs and HVs interval recorded on surface “new electrocardiogram” and PA, AH, HV interval recorded on His bundle electrogram was investigated in 65 patients undergoing radiofrequency catheter ablation of paroxysmal superventricular tachycardia. Now we present our preliminary analysis.An electrocardiogram exam plays an irreplaceable role in the diagnosis of arrhythmia . To our Sixty-five patients who were proved to have a paroxysmal supraventricular tachycardia formed the subjects of this study in the First Affiliated Hospital of Liaoning Medical University. There were 31 males and 34 females, with a mean age of 52 ± 13 years (ranging from 14 to 84 years). All patients were included 4 groups according to the intracardiac electrophysiology study: 33 patients with atrioventricular nodal reentrant tachycardia; 29 patients with atrioventricular reentrant tachycardia (exclude overt Wolff-Parkinson-White syndrome); one patient with atrial tachycardia; two patients with paroxysmal atrial fibrillation. We used a “new electrocardiogram” machine (model PHS-A10) designed and developed by EmCG US company to record surface electrocardiogram. The intracardiac electrophysiology study was performed by an electrophysiological recording and the analysis system Model CardioLab 7000 .Recording conditions: The subject’s skin was firstly pretreated with sandpaper, and then special electrodes (non-cytotoxic silver/silver chloride substrate) are used to perform the test, in which the arrangement of electrodes were the same as that in a 12 lead electrocardiogram. In addition, both “new electrocardiogram” [It was coined the term of saahECG  by the developers] and “conventional electrocardiogram” have been detected synchronously by the “new electrocardiogram” machine. Moreover, the scanning speed (25 mm/s) and amplitude (10 mm/mV), and the measuring speed (25 mm/s) and amplitude (20 mm/mV) in long trace leads were selected. The micro-wavelets before P wave, before QRS complex (in P wave and PR segment) and after QRS complex (ST segment and upstroke of T wave) can be recorded by the “new electrocardiogram” machine , AHs interval  and HVs interval . The values of each intervals measured by the computer were seen in Fig. 5). The values of each intervals (ms) measured by the computer.Mapping of HVDetails concerning electrophysiologic study  were obtained as previously described . They weResting supine 12-lead electrocardiograms in sinus rhythm and His bundle electrogram in sinus rhythm were recorded before the intracardiac electrophysiology study. Two independent observers who knew the purpose of the study but were blinded to the study design and the results of all investigations evaluated the electrocardiograms and His bundle electrogram.P-value <0.05 was considered significant.The results were given as means ± s.d., Paired t tests were used to compare the index of “new electrocardiogram” and His bundle electrogram. The correlation between the same variables measured by the two methods was analyzed by using Pearson correlation analysis. All statistical analysis was performed using SPSS 16.0. A Comparative analysis of intervals recorded on “new electrocardiogram” and His bundle electrogramP > 0.05) between groups in HVs interval recorded on “new electrocardiogram” and HV interval recorded on His bundle electrogram. There were differences (P < 0.05) between groups in PAs, AHs, PR interval recorded on “new electrocardiogram” and PA, AH, PR interval recorded on His bundle electrogram, as shown in Table 2.s, AHs, HVs, PRs intervals recorded on “new electrocardiogram” and PA, AH, HV, PR interval recorded on His bundle electrogramPearson correlation analysis between PAThere were no difference ; AHs interval was significantly positively associated with AH interval ; HVs interval was significantly positively associated with HV interval ; PRs interval was significantly positively associated with PR interval , as shown in Fig. Results of correlational analysis found that PAWhy “New electrocardiogram” can record the micro waveform before QRS complex which conventional electrocardiogram couldn’t?2.s, AHs and HVs interval on “New electrocardiogram”According to the micro-wavelets before QRS complex, PR interval was divided into PAThe PHS-A10 electrocardiogram is a new device created by EmCG US company using the latest technology of the software and the hardware, and the signal processing technology. These are based on a collection of various US patents and International patents. The PhySio’s PHS-A10 is highlighted by its success in employing a novel Adaptive Mixture Technology within the electrocardiogram Signal Spectrum enabled by PhySio’s Smart Data Acquisition Module. Along with traditional electrocardiogram scanning/recording, PHS-A10 is able to accurately extract a variety of time-domain electrocardiogram electric potentials in the 0-150Hz range, and perform automated integrating signals recognition. Therefore, not only the P-QRS-T waves but also the micro-wavelets before P wave, before QRS complex (overlapped on P wave and in PR segment), after QRS complex (ST segment and upstroke of T wave) can be recorded on surface electrocardiogram , AHs interval  and HVs interval . A finding in our 100 healthy individuals was that the PAs, AHs and AHs intervals were consistent with the intra-atrial measurement PA, AH and HV intervals [s, AHs and HVs interval.3.s, AHs and HVs interval recorded on “New electrocardiogram” and PA, AH and HV interval recorded on His bundle electrogramComparative study of PA(1) In 100 healthy individuals, we have found that the new electrocardiogram can record characteristic wavelets before QRS complex: two wavelets in PR segment with higher amplitude closest to QRS complex and one to three wavelets with lower amplitude before these two wavelets) . The wavntervals . In the P > 0.05) between groups in HVs interval and HV interval. Results of correlational analysis found that HVS interval was significantly positively associated with HV interval . These suggested two wavelets closed to the QRS complex with high amplitude in HVs interval was His bundle and bundle branch potentials on surface electrocardiogram. (2) A finding of Paired t tests revealed there were differences (P < 0.05) between groups in AHs interval (79.86 ± 15.35 ms) and AH interval (77.20 ± 16.04 ms). The means difference of AHs and AH interval was in a few milliseconds and was in the range of physiological changes (autonomic nerve change) of AH interval (20–50 ms) [s interval was significantly positively associated with AH interval . Therefore, the wavelets (overlapped in P wave and after the P wave) in AHs interval may be atrioventricular nodal potential.(1) A finding of Paired t tests in our study in 65 paroxysmal supraventricular tachycardia underwent “New electrocardiogram” and His bundle electrogram (these two weren’t simultaneously recorded) was that there was no difference , but the starting point of A wave in His bundle electrogram was clear. Although these limitations didn’t have effect on clinical significance of our result, the normal scope of PAs, AHs and HVs interval can’t be applied mechanically according to the intracardiac electrophysiology study. It still required statistical analysis of large sample.(1) “New electrocardiogram” and His bundle electrogram weren’t simultaneously recorded. Therefore, autonomic nerve change may have effect on atrioventricular nodal, leading to differences between groups in AH interval and PR interval. (2) The paper speed of “New electrocardiogram” weren’t consistent with His bundle electrogram. The paper speed of “New electrocardiogram” was 25 mm/s and the paper speed of His bundle electrogram was 100 mm/s. If the paper speed of “New electrocardiogram” was 100 mm/s, the acute angle of the wavelet before QRS complex became blunt. Therefore, it was difficult to determine the starting point. To reduce the impact of paper speed, the body surface measurements were amplified (four magnification) on the computer. It can not completely exclude the impact of paper speed. (3) In AHIn conclusion, our study revealed that His bundle potential can be noninvasively recorded beat by beat in human. It has only begun with a prologue for a new research and still requires a great number of clinical and animal experiments in order to verify the clinical significance, normal scope, characteristics and mechanism of these micro waveforms. The purpose of this study is to put forth in the hope that more doctors and scientists will join hand to greet the second spring of the electrocardiogram.


We estimate quantitative precipitation variability and the high resolution and dating accuracy of this record allow us to investigate how rainfall in the region responds to D-O events. Quantitative precipitation estimates are based on observed regional amount effect variability, last glacial paleotemperature records, and estimates of the last glacial oxygen isotopic composition of precipitation based on global circulation models (GCMs). The new precipitation record suggests significant low latitude hydrological responses to internal modes of climate variability and supports a role of Caribbean hydroclimate in helping Atlantic Meridional Overturning Circulation recovery during D-O events. Significant in-phase precipitation reduction across the equator in the tropical Americas associated with Heinrich event 2 is suggested by available speleothem oxygen isotope records.During the last ice age temperature in the North Atlantic oscillated in cycles known as Dansgaard-Oeschger (D-O) events. The magnitude of Caribbean hydroclimate change associated with D-O variability and particularly with stadial intervals, remains poorly constrained by paleoclimate records. We present a 3.3 thousand-year long stalagmite δ These D-O events were first identified in Greenland ice cores but are expressed in terrestrial lakes, speleothems, and marine sediments from the North Atlantic, South America, Pacific and Indian Oceans8. The leading hypothesis to explain millennial-scale climate cycles invokes changes in the Atlantic Meridional Overturning Circulation (AMOC)9. At times, during the last glacial, the Northern Hemisphere ice sheets supplied sufficient freshwater to the North Atlantic to reduce AMOC by lowering surface ocean density10. In turn, AMOC slowdown decreased heat transport from low to high latitudes leading to cooling across the North Atlantic9. Meltwater pulses are reflected by episodes of thick ice rafted debris (IRD) deposits in the North Atlantic known as Heinrich (H) events that were generally associated with stadial episodes13.During the last ice age climate in the North Atlantic oscillated on millennial time scales from cold  to warm  episodes, often referred to as Dansgaard-Oeschger (D-O) events15 consistent with model results of AMOC slowdown17. AMOC slowdown via freshwater forcing creates a thermal asymmetry across the equator that leads to a southward displacement of the ITCZ in the Atlantic and Pacific, which then enhances precipitation in South America and the opposite in North America and northern South America, such as the Cariaco Basin19. Model results suggest, furthermore, that AMOC slowdown can induce intense precipitation reductions in the North Atlantic and India of up to 80%16. The frequency and magnitude of tropical hydroclimate variability during times of AMOC reduction remain, however, largely unconstrained by paleoclimate records. We present a last glacial stalagmite δ18O record of Caribbean climate from the Yucatan Peninsula (YP), Mexico, and attempt to reconstruct quantitative precipitation variability to establish how rainfall in the region responds to D-O events and particularly during stadial intervals. Our precipitation estimates are based on an assessment of last glacial tropical temperatures31, shifts in the δ18O composition of precipitation suggested by global circulation models (GCMs), the observed regional amount effect23, and the assumption that temperature dependence fractionation during calcite precipitation was according to the model by Tremaine et al.32 (more details in Methods). We acknowledge that this is a first attempt to estimate last glacial precipitation changes quantitatively and that uncertainties still remain, particularly, concerning the magnitude of the amount effect and the δ18O composition of precipitation, and biases due to potential calcite isotopic disequilibrium conditions, during this time interval. The new precipitation record spans the time between 26.4 and 23.2 ka BP, corresponding to stadial 2 (S2) in the North Greenland Ice Core Project (NGRIP) δ18O record20 and covers the full duration of Heinrich event 2 (H2).There is increasing evidence that D-O cycles were associated with rapid and significant hydrological responses in tropical and subtropical regions worldwide, probably linked to the position of the Intertropical Convergence Zone (ITCZ) and its belt of convective activity. Paleoclimate records, particularly, suggest hydrological variability that is out-of-phase across the equator in the Atlantic and eastern Pacific regions on millennial time scales21 , from Río Secreto Natural Reserve, a spectacular semi-inundated cave system located in Playa del Carmen City, in the Caribbean coast of the YP   has a resolution of 3 ± 1 years (1 SD) during the time interval between 26.5 and 24.6 ka BP and of 16 ± 6.7 years (1 SD) between 24.6 and 23.2 ka BP . The stalagmite δ18O record from 26.5 to ~24.5 ka BP shows no trend. At ~24.5 ka stalagmite δ18O values become progressively more positive with a statistically significant slope of −1.7‰ kyr−1 . This positive δ18O trend is associated with a decrease in stalagmite growth rates  of relatively short duration, 1–2 decades , a Hendy test 28 suggest that Itzamna’s calcite was precipitated under or near isotopic equilibrium conditions and faithfully records precipitation δ18O variability23 (see Methods for more details). Precipitation δ18O in tropical regions reflects an amount effect on interannual22 and seasonal timescales29, as confirmed by our instrumental data for the YP (2014–2016)23.The characteristics and physical conditions of the Río Secreto cave system monitored from the year 2014–2016  and thus precipitation δ18O using the local amount effect, so that the annual amount-weighted δ18O of precipitation varies in accordance with Itzamna δ18O anomalies30 , after adjusting precipitation δ18O and dripwater temperatures to reflect last glacial conditions (see Methods). The full range of stalagmite δ18O-derived precipitation values are represented by combinations of estimates of last glacial regional surface temperature (from 18 °C to 20 °C)31 and modern instrumentally-determined amount effect slopes (δP/ΔP = −0.0106‰/mm and −0.0168‰/mm)  relative to today (i.e. 1465 mm/year) similar to the regional interannual precipitation range observed today but exceeding the modern upper boundary suggested by the longest continuous instrumental record of precipitation 23 23 Fig. . Based o 21 Fig. . Notably18O-precipitation record shows significant variability on interannual and multidecadal time scales. Particularly, wavelet spectral power analysis indicates significant variability centered at periods of ~8, ~16, ~32, ~64 and ~128 years, over the first 2 kyrs of the record 36 and changes in Atlantic tropical cyclogenesis46.Itzamna precipitation record variability on multidecadal time scales, 32–64 years, may reflect a potential connection with the dominant pattern of North Atlantic sea surface temperature (SST) associated with the Atlantic Multidecadal Oscillation (AMO)49 and there is evidence that this modulation could be via the influence of ENSO on tropical Atlantic cyclogenesis50. Atlantic hurricanes are suppressed when El Niño conditions in the Pacific induce upper altitude increased wind shear in the Atlantic, thus reducing rainfall fluxes over the YP by tropical cyclones52.Higher frequency variability at an ~8 year period in the Itzamna precipitation record may reflect El Niño-Southern Oscillation (ENSO) modulation of Caribbean hydroclimate Fig. . Studies18O records spanning the Late Holocene from the YP53, Belize54 and Cuba41 and by last glacial lacustrine paleoenvironmental records from Lake Petén Itzá56. Observed and inferred hydrological change in the Caribbean and Gulf of Mexico regions during the Holocene and last glacial intervals indicate that Atlantic low latitude regions respond to internal modes of climate variability on interannual (i.e. ENSO) and multidecadal time scales (i.e. AMO) regardless of the global climate state .Interannual and multidecadal variability (~8–128 year periods) is also suggested by four other stalagmite δ55. This drying trend ended about 23.2 ky ago when mean precipitation declined by about 50% (based on the average of the three most recent data points) and the stalagmite Itzamna became ‘dormant’ for 20 thousand years. This declining precipitation trend coincides with a reduction in Itzamna speleothem growth thus reinforcing the isotopic evidence for precipitation declines 4 and at ~24.7 ka BP in an ocean sediment total reflectance L* record from the northeastern Arabian Sea 8 7 and at ~24.8 ka BP in a speleothem δ18O record from Paraíso Cave in the Amazon basin   Iberian Margin Core SU8118, one of the best-dated sediment records of H2, suggest two IRD depositional phases centered at 23.5 ± 0.2 ka BP and 25 ± 2 ka BP55, India and South East Asia, coeval with precipitation reduction in Perú7 and the Amazon Basin15, associated with H2, are consistent with model results of AMOC slowdown. Particularly, hosing experiments based on atmosphere–ocean general circulation models suggest that freshening of the North Atlantic and the ensuing AMOC slowdown and atmospheric cooling would cause significant precipitation reduction in the American tropics, including the Caribbean and Amazon basin17. Notably, the magnitude of precipitation decline during the most intense rainfall reduction events suggested by the Itzamna record of ~−50% is consistent with model results of peak precipitation reduction in the Caribbean region associated with AMOC slowdown16.Progressive precipitation decline in the YP (this study), Central America19 would then cause a reduction in low latitude rainfall16. The North Atlantic low latitude precipitation reduction by the end of S2 was intense enough to have likely played a counteracting role to AMOC slowdown. North Atlantic high salinity induced by intense low latitude precipitation deficits, as the Itzamna precipitation record suggests, would propagate to the high latitudes, increase upper ocean convection, and help resume AMOC, as proposed by previous studies59. A recent study that investigates the northward flow of warm water through the Florida Strait, from benthic foraminiferal δ18O records from sediment cores, does not find evidence of significant shifts in the Atlantic overturning circulation during H260. The implication of these findings by ref. We suggest that extreme drought conditions in the YP after ~24.5 ka BP was an inevitable pattern that followed high regional precipitation in the Caribbean and warm ocean anomalies in the North Atlantic, the latter possibly related to a positive AMO phase. North Atlantic warming and freshening combined would trigger massive iceberg discharges into the North Atlantic (i.e. H2) and the resulting meridional propagation of cooling via advection and air-sea interactions16. Tropical Atlantic cyclogenesis was also likely reduced during the last glacial and particularly during cool stadial episodes, when tropical convection and SSTs in the main developmental region were reduced61. Precipitation reductions in the Caribbean region during S2 could have thus been amplified by a lower potential of tropical cyclones to transfer moisture to higher latitudes62.The Arabian Sea and Cariaco Basin sediment reflectance values during S2 are the lowest of all stadial events, thus suggesting to be the wettest of all stadial events, and comparable to values observed during interstadials 9, 18 and 20 within these records. These observations suggest that the ITCZ was not particularly displaced south during S2. The evidence presented thus far implies that cooling associated with Heinrich events can significantly impact tropical and subtropical hydroclimate during stadials without involving a shift in the mean position of the ITCZ. In the specific case of S2, Atlantic cooling could have induced lower precipitation across the tropical Americas by decreasing the atmosphere’s moisture holding capacity and, by decreasing the intensity of tropical convection18O and δ18O-derived precipitation records that help characterize the magnitude and frequency of Caribbean hydroclimate variability on interannual and multidecadal time scales during a stadial event. Our study offers new evidence that precipitation across the American tropics declined progressively in close association with the onset and duration of Heinrich event 2. The geographical pattern and magnitude of tropical hydrological change during stadial 2 suggested by paleoclimate records, furthermore, are consistent with model results of AMOC slowdown. We propose that increased salinity in the Caribbean region driven by a precipitation deficit resulting from North Atlantic cooling associated with H2 played a crucial role in helping counteract AMOC slowdown. In light of the evidence provided, we suggest that tropical hydroclimate does not only respond to but also influences AMOC circulation during glacial intervals, in agreement with previous studies59.This work provides new high-resolution stalagmite δ18O on interannual time scales revealed by models22, while helping us understand the factors that control this relationship and those that may disrupt it, such as tropical cyclones63. Speleothems from tropical regions may represent our best chance to reconstruct low latitude precipitation variability and its sensitivity to shifts in climate boundary conditions (e.g. greenhouse gases) and processes internal to the climate system (e.g. AMOC).Lastly, we suggest that the Itzamna stalagmite precipitation estimates be considered as preliminary and not as an end result. We anticipate that modeling studies will help expand our understanding of the amount effect and the isotopic composition of precipitation during the last glacial and thus help test our precipitation inferences. The long-term monitoring of precipitation we are conducting will reveal the robustness of the link between tropical precipitation amount and precipitation δ24. Uranium and thorium isotopic measurements were conducted on a multi-collector inductively coupled plasma mass spectrometer (MC-ICP-MS), Thermo Fisher Neptune, at the High-Precision Mass Spectrometry and Environment Change Laboratory (HISPEC), Department of Geosciences, National Taiwan University26. A triple-spike, 229Th-233U-236U, isotope dilution method was employed to correct for mass bias and determine all uranium and thorium isotopic and concentration values in an off-line data reduction process developed by ref. 27 . Measured cave air temperature inside this chamber was 23 ± 1 °C thus reflecting 3 °C colder mean temperature than the annual mean air temperature in Playa del Carmen of 26 °C21. In June 2014 we initiated a weekly collection of drip waters from different stalactites in various chambers within the cave system. Results from 163 dripwater measurements taken between the year 2014 and 2016 indicate an average drip water δ18O composition of −3.7 ± 1.0‰ in Laberinto del Fauno. The observed drip δ18O variability was in tune with the seasonal cycle of precipitation consistent with a relatively short mixing time of drips23. The mean drip water δ18O value (−3.7 ± 1.0‰) is very similar to the annual amount weighted δ18O value (−4‰) of rainfall in Playa del Carmen during this interval of time (n = 13 months). Modern dripwater temperature in this chamber is 23 °C, based on 1.2 years of weekly measurements of two drips (n = 62 weeks). These observations suggest that it is unlikely for evaporation to significantly influence dripwater geochemistry at these sites. Measured Laberinto del Fauno dripwater and groundwater temperatures are similar to the cave air temperature (23 ± 1 °C). Similar cave air, dripwater and groundwater temperatures that are 3 °C colder than the mean annual surface air temperature suggests that dripwater temperature reflects cave air temperature and this in turn groundwater temperature because groundwater is present year round in the Rio Secreto cave system.We monitored relative humidity daily in two sectors of Río Secreto including at the stalagmite Itzamna collection site during two full years, from June 2014 to June 2016 (n = 5000 measurements using HOBO instruments). Relative humidity of 100% was recorded throughout this time. The cave floor is currently below the water table and thus provides a constant moisture source that is particularly retained in cave chambers. We recognize that these conditions were likely different during the last glacial when sea level and thus the water table in the cave were much lower than today. Cave relative humidity during the last glacial may have remained, however, close to 100% because of lower evaporation resulting from global cooling. In addition, we have monitored caves with no standing water inside in the northwest most arid region of the YP18O, and modeling studies, indicate that there is an amount effect on seasonal and interannual time scales in the Yucatan Peninsula23. We have previously characterized the seasonal amount effect between precipitation amount (P) and precipitation δ18O (dP) by monitoring rainfall amount and rainfall δ18O in the city of Cancún in the year 2012 and in Río Secreto in 201423. The amount effect on seasonal time scales in the YP is represented by the slope δP/ΔP = −0.0137 ± 0.0031‰/mm . The amount effect is statistically similar (80% CI) to that recorded in Veracruz, México (−0.0125‰ per mm), in San Salvador, El Salvador (−0.0124‰ per mm)65, Havana, Cuba (−0.0147‰ per mm) and Tuscaloosa, Alabama (−0.0132‰ per mm) . We currently have no means to assess the value of the amount effect in the YP during the last glacial time interval. The similar amount effect slope found in the northern Caribbean and Gulf of Mexico regions suggest that this parameter is relatively stable across different climate regimes. In order to include a measure of uncertainty regarding the amount effect, this study uses the full confidence interval of the amount effect slope measured in the northeast of the YP to calculate precipitation changes. The slope range (i.e. −0.0168 and −0.0106‰ per mm) well exceeds values observed in northern Caribbean and Gulf of Mexico locations today.Instrumental records of precipitation amount and rainfall δ18O composition closely reflects the annual amount-weighted δ18O composition of rainfall23. Applying the equation by Tremaine et al.32, we calculate the expected stalagmite δ18O composition precipitated under oxygen isotopic equilibrium conditions with cave dripwater annual temperature (23 °C), by using the local amount effect relationship characterized instrumentally (Y = −0.0137x − 0.9525), and 5-year monthly averages of precipitation amount . The equilibrium calculations yield a stalagmite δ18O composition of −4.1‰, which is within the variability range of the most recent section of Itzamna  spanning the Preclassic Period of Maya history (BCE 1037 to CE 397)23. The Itzamna record we present in this study has a mean δ18O composition of −3.1‰ ± 1.8‰ (2 SD), that is, 1.7‰ more positive than the mean δ18O composition of the younger section  is expected to remain unchanged. If precipitation amount changes on one given year, then precipitation δ18O would change according to the amount effect relationship. Precipitation estimates from stalagmite δ18O represent the average precipitation amount of one, two or the number of years our sample integrates. Depending on the site, seasonal dripwater δ18O could conceivably integrate the annual precipitation isotopic signal, as we observe in some drips from Rio Secreto, in which case, stalagmite δ18O would closely represent an annual precipitation δ18O signal integration , even when it is sampled on seasonal resolution. Because stalagmite δ18O per mil shifts are assumed to reflect similar shifts in precipitation δ18O, interannually, we can then estimate precipitation amount shifts from stalagmite δ18O anomalies calculated relative to a reference point. We maintain the local modern annual precipitation cycle but shift annual precipitation amount and therefore precipitation δ18O so that annual mean precipitation δ18O changes in accordance to the interannual δ18O precipitation anomalies reflected by the stalagmite30. Seasonality may produce precipitation amount biases on both directions, positive and negative, using this method. Summer precipitation to total annual precipitation on typical years today in the northeast YP range from a minimum of 60% to a maximum of 70% summer precipitation  for this reference value is calculated with the paleotemperature equation by ref. 18Oc-VSMOW)/(1000 + δ18Ow-VSMOW) and δ18OcVSMOW = 30.92 + 1.03092*(δ18Oc-PDB).We use the 5-year annual mean of precipitation (1998–2003) in Playa del Carmen of 1465 mm as the reference precipitation value for our estimates of precipitation change18O composition (δ18Ow-VSMOW) in Río Secreto is determined from assuming the annual δ18O composition of precipitation (amount-weighted) associated with 1465mm/yr . This assumption is supported by instrumental monitoring data as detailed above23. The last glacial annual δ18O composition of precipitation (amount-weighted) was determined from adjusting a 1.6‰ higher last glacial annual precipitation δ18O value relative to today, as suggested by global circulation models GCMs68. We want to point out that because few studies exist that investigate shifts in precipitation δ18O during glacial intervals, it is difficult to assess how certain/uncertain this adjustment of precipitation δ18O may be, although a minimum of ~1.2‰ positive shift in precipitation is expected as a result of the last glacial shift in ocean δ18O due to expansion of the continental ice sheets66. Evidently, interpretations of speleothem δ18O records from tropical regions would greatly benefit from increasing development of studies focused on isotope-enabled GCMs that target glacial conditions.Here the last glacial cave dripwater δ31 from the modern mean annual dripwater temperature of 23 °C. We note that, this Holocene-to-last glacial SST range also applies to the Arabian Sea, Indian Ocean and tropical Pacific31. We consider this 2 °C temperature range as uncertainty associated with our estimates of last glacial cave temperature. This yields a final dripwater temperature estimate ranging from 18 °C to 20 °C. The resulting equilibrium δ18O composition of calcite associated with last glacial conditions and 1465 mm/year ranged from −1.4‰ at 18 °C to −1.7‰ at 20 °C.The S2 temperature of dripwaters (t) was calculated by subtracting a tropical glacial cooling of 3–5 °C that is suggested by seven Atlantic tropical SST records18O anomalies were then calculated in reference to these two isotopic equilibrium values. Positive and negative δ18O anomalies would therefore indicate lower and higher precipitation relative to 1465 mm, respectively. Precipitation percent changes were then calculated based on the full confidence interval of the slope of the relationship between the amount of precipitation and precipitation δ18O (δP/ΔP = −0.0137 ± 0.0031‰ per mm), equivalent to the slopes −0.0106‰/mm and −0.0168‰/mm. As expected, the steepest slope will yield the lowest precipitation change associated to a given δ18O anomaly. As an example, a positive stalagmite anomaly of + 1‰ would be explained by shifting precipitation amount and therefore the annual cycle of precipitation δ18O  by −55% and −35%, using the slopes −0.0106‰/mm and −0.0168‰/mm, respectively. We note that the precipitation estimates associated with a stalagmite δ18O anomaly, for instance of +1‰, depend on the reference value. If we increased 50% the reference value 1465 mm to 2194.5 mm, then a +1‰ anomaly would be explained by annual precipitation amount reductions of −38% and −24% using the slopes −0.0106‰ per mm and −0.0168‰ per mm, respectively.Stalagmite δet al.32 because this equation applies to a broad range of temperature and cave environments. We explored the alternative paleotemperature equation by Kim and O’Neil69 and found that precipitation estimates not based on the steepest slope (−0.0168‰/mm) yielded precipitation declines in excess of 100%. Precipitation declines >100% would not support this equation, or suggest that the amount effect was similar or higher than −0.0168‰ per mm during S2. Alternatively, excess precipitation declines could indicate underestimation of the last glacial precipitation δ18O shift, underestimation of the magnitude of cooling, and/or calcite disequilibrium precipitation during peak drought. The last glacial precipitation δ18O shift that would explain the most positive stalagmite δ18O value (0.1‰) without resulting in precipitation declines in excess of 100% over the temperature and amount effect conditions applied is 2.4‰, which is 0.8‰ more positive than the value suggested by climate model results (1.6‰)68 and ~1.2‰ more positive than explained by a shift in ocean δ18O associated with the expansion of the continental ice sheets66. A larger precipitation δ18O adjustment is therefore unsupported by available model results and paleoclimate proxy records. Examination of available last glacial subtropical and tropical Atlantic sea surface temperature records 71, on the other hand, does not suggest Caribbean sea glacial cooling larger than 5 °C. Lastly, we cannot discard disequilibrium isotopic conditions during peak drought events induced by decreasing cave relative humidity. The atmospheric demand of moisture and thus evaporation, however, were lower during the last glacial due to regional cooling61, which would have helped maintain water vapor saturation conditions inside the cave.We used the paleotemperature equation by Tremaine et al.32, which applies to a broad range of cave temperatures and environments similar to Rio Secreto, and does not produce precipitation declines in excess of 100% across the range of temperatures and amount effect slopes applied in this study. Additional precipitation records and the long-term monitoring we are currently conducting in Rio Secreto, involving farmed calcite, will provide more definite support for our chosen paleotemperature equation.Based on the available evidence, we find stronger support for applying the paleotemperature equation by Tremaine In order to assess chronological uncertainty effects on our spectral results, we expand and contract the time scale over periods of interest and determine how this affects the duration of the dominant periods suggested by the spectral analysis Fig. . SpecifiSOMTable S1Table S2Table S3