N-demethylation of N-methylated (both mono- and di-methylated) arginine residues of histones and other proteins, including HSP70 (heat-shock protein 70), estrogen receptor α, and RNA helicase A. Here, we report MS- and NMR-based kinetic assays employing purified JMJD6 and multiple substrate fragment sequences, the results of which support the assignment of purified JMJD6 as a lysyl hydroxylase. By contrast, we did not observe N-methyl arginyl N-demethylation with purified JMJD6. Biophysical analyses, including crystallographic analyses of JMJD6Δ344–403 in complex with iron and 2OG, supported its assignment as a lysyl hydroxylase rather than an N-methyl arginyl-demethylase. The screening results supported some, but not all, of the assigned JMJD6 substrates and identified other potential JMJD6 substrates. We envision these results will be useful in cellular and biological work on the substrates and functions of JMJD6 and in the development of selective inhibitors of human 2OG oxygenases.JmjC domain-containing protein 6 (JMJD6) is a 2-oxoglutarate (2OG)-dependent oxygenase linked to various cellular processes, including splicing regulation, histone modification, transcriptional pause release, hypoxia sensing, and cancer. JMJD6 is reported to catalyze hydroxylation of lysine residue(s) of histones, the tumor-suppressor protein p53, and splicing regulatory proteins, including u2 small nuclear ribonucleoprotein auxiliary factor 65-kDa subunit (U2AF65). JMJD6 is also reported to catalyze  A)  .N-methyl lysyl and N-methyl arginyl demethylases  (B)  (B), but the cellular relevance of this remains unclear  B 4). Jm. JmN-metaldehyde B 5). In. InN-methyde (B) B, but thC) (R hydroxylase), JMJD7 (a lysyl C-3S hydroxylase), and the ribosomal oxygenases MINA53 and NO66 (both histidine-residue C-3S hydroxylases)  . A protoC) , 9. Othexylases) –12. Manyylases) ––12. Strulases) ––, 13, altN-methyl arginyl demethylase and lysyl C-5 hydroxylase activities (C)  with a consequently associated role in apoptosis  that is characteristic of the Fe(II) and 2OG-dependent oxygenases  , a predicted AT-hook motif (Lys283–Ser326), a potential SUMOylation site (Leu316–Asp319), and a C-terminal polyserine (poly-Ser) region   –17N-methpoptosis . Subsequpoptosis , 20, altpoptosis . Structuygenases , 20, 22.ygenases , 23. JMJygenases , 25, conFig. S1) . Human JFig. S1) .et al. (N-methyl arginyl demethylase (RDM) acting on mono- and symmetric/asymmetric di-methyl forms of arginine residues as observed in studies with isolated enzyme (B). JMJD6 is also reported to catalyze RDM reactions on N-methylated forms of heat-shock protein 70-kDa (HSP70)  , estroge (HSP70) , RNA hel (HSP70) , and the (HSP70) . Althoug (HSP70) , 31, 32.C) of the splicing regulatory (SR) proteins luc-7–like 2 (LUC7L2), cisplatin resistance-associated overexpressed protein (CROP), and u2 small nuclear ribonucleoprotein auxiliary factor 65-kDa subunit (U2AF65) (S)-stereochemistry (C) (R)-product  . JMJD6-chemistry C 16), c, cC) of -product . JMJD6 i-product . More re-product .JMJD6-knockout mice dying near birth due to growth impairment of multiple organs, including heart, brain, lung, kidney, and eye , and two C-terminally truncated variants, i.e. JMJD6 comprising residues 1–362 (JMJD6Δ363–403) and residues 1–343 (JMJD6Δ344–403) . Circular dichroism (CD) spectroscopic analyses imply similar secondary structure content for each of the three JMJD6 variants .Because our objective was to investigate the catalytic reactions catalyzed by isolated JMJD6, the activity of which can be compromised due to oligomerization , 31, we 267–278 substrate . The apparent binding constant (DKapp) of 2OG was determined using CPMG-edited NMR . mKapp values for 2OG were determined using the standard hydroxylation assay procedure and were 31, 24, and 45 μm for JMJD6FL, JMJD6Δ363–403, and JMJD6Δ344–403, respectively , consistent with Mantri et al. . In the presence of the LUC7L2267–278 substrate with JMJD6Δ344–403, JMJD6Δ363–403, and JMJD6FL, these values increased to 1.8, 8.4, and 3.6 μm succinate, respectively . Thus, under both assay conditions, succinate formation for JMJD6Δ363–403 and JMJD6FL was higher than JMJD6Δ344–403, indicating a possible role of the C-terminal poly-Ser region in enhancing catalysis and/or of active protein stability. However, given the role of the poly-Ser region in oligomerization  solution being added prior to reaction, with the same outcome, i.e. with the poly-Ser region containing proteins being more active . Given that JMJD6Δ363–403 was the most active and stable variant tested, further assays were conducted with it.Hydroxylation assays using the reported LUC7L2ubstrate  revealedited NMR ; the KDai et al.  who reporization  and the Δ363–403 under standard assay conditions: H3R2(me2s)1–25, AR(me2s)TKQTARKSTGGKAPRKQLATKAA GKGGKGLGKGGAKRHRKVLRDNIQGIT GKGGKGLGKGGAKRHK-biotin . When treated with JMJD6, hydroxylation of K4histone3, K9histone3, K14histone3, K5histone4, and K8histone4 was observed , consistent with the MALDI results. Note, we did not accrue any evidence for JMJD6 catalyzed hydroxylation of arginine residues as reported for JMJD5 1–30 .Three histone peptides with symmetrically di-methylated arginine residues, all of which have been reported as JMJD6 RDM substrates , 40, werKQLATKAA ; H4R3. Furthermore, when a histone peptide monomethylated at Lys9 (H3K9me11–17) was tested with JMJD6Δ363–403, a +16-Da mass shift was observed, implying hydroxylation and not demethylation . This observation also suggests JMJD6 does not catalyze histone lysyl demethylation, consistent with an earlier report (9(me1) compared with Lys9 was relatively low , which suggests that under our assay conditions JMJD6 prefers to hydroxylate unmodified lysine residues and provides evidence that JMJD6-catalyzed lysyl hydroxylation has the potential to be affected by Nϵ lysine modifications.Evidence for JMJD6H3K9me11– was test469) is demethylated by JMJD6 as observed by MS .HSP70 has been reported as a JMJD6 substrate wherein the mono-methylated arginine residue  . Time-course assays were then performed , with peptides displaying ≥25% hydroxylation after 6 min in kinetic studies  . To inve studies .267–278 were as follows: mKapp, 51.0 μm; kcat, 106 × 10−4 s−1; and kcatm/Kapp, 208 × 10−6 μm−1·s−1. Of the tested U2AF65 peptide fragments, U2AF6521–35  was found to be a better substrate than U2AF6530–46  and U2AF6555–70  . Other peptides tested, e.g. from the SR protein CROP, gave similar kinetic parameters . Of the SRSF11 fragments tested, JMJD6Δ363–403 hydroxylated SRSF11358–372 with a relatively high efficiency . With RBM39 (RNA-binding protein 39), hydroxylation levels were found to vary with measured mKapp values ranging within 56.0–99.0 μm . Of the tested RBM39 fragments, RBM3931–42 was substantially more efficiently hydroxylated than the others tested, with mKapp 56.0 μm and kcatm/Kapp 455 × 10−6 μm−1·s−1. These results are consistent with the proposal that JMJD6 is promiscuous with respect to its lysyl hydroxylase activity in cells , suggesting possible hydroxylation of Lys171. Assays with the alanine variant pVHL166–177K171A and with WT pVHL166–177 in the presence of a JMJD6 inhibitor, 2,4-pyridine dicarboxylic acid ,BFig. S24). LC-MS/MS analysis of JMJD6Δ363–403-treated pVHL166–177 provided further evidence for pVHL Lys171 hydroxylation .The apparent promiscuity of isolated JMJD6 with RS domains of SR proteins prompted us to test the potential of other reported JMJD6 substrates. The von Hippel-Lindau protein (pVHL) has been reported as a potential JMJD6 substrate  and was N-demethylation of methylated  Arg260 of ERα and thereby regulates methylated ERα function in response to estrogen (260 (MKGGIRKDRR(me2s/a)GG) were tested with JMJD6Δ363–403, and ERα demethylation was not observed . Interestingly, a +16-Da mass shift, corresponding to hydroxylation, was observed for both peptides . In light of the results with histone peptides, we considered it possible that JMJD6 catalyzes hydroxylation of either or both of the lysine residues (Lys252 and Lys257) in the ERα sequence. Assays using ERα peptides with unmodified Arg260 also revealed JMJD6Δ363–403-dependent hydroxylation . Hydroxylation was ablated by alanine substitution ERα251–262K252A, ERα251–262K257A, or by addition of the JMJD6 inhibitor 2,4-PDCA4 . These results suggest Lys252 and Lys257 of ERα are possible targets for JMJD6 hydroxylation and are further evidence that JMJD6-catalyzed hydroxylation is possibly regulated by other post-translational modifications.Based on Western blot analysis, it has been reported that JMJD6 catalyzes estrogen . Peptide382 .JMJD6 lysyl hydroxylase activity has also been associated with post-translational modification of the tumor-suppressor protein p53, wherein the target residue is Lys382 . Assays Δ344–403 in the presence of Fe(II) and 2OG was performed in an anaerobic glove box as reported for FIH ..Δ344–403Δ344–403·Fe·2OG crystals belong to the same space group (P21) with similar unit cell dimensions to that reported by Mantri et al. (Table S1). The structure was solved by molecular replacement using PDB code 3K2O as a search model  with no Ramachandran or side-chain conformational isomer outliers ) .The JMJD6i et al.  ) . However  core fold (B) characteristic of the 2OG oxygenases, which is located within the JmjC domain and harbours the Fe- and 2OG-binding residues. Importantly, the JMJD6Δ344–403·Fe·2OG structure reveals the geometry of the JMJD6 active-site coordination chemistry in the presence of its Fe cofactor and 2OG cosubstrate , a feature characteristic of most 2OG oxygenases (Asp is sometimes substituted with Glu or Gly) (C). JMJD6 His187 and Asp189 are located on the loop linking βII and βIII, whereas His273 is located on DSBH βVII (B). Mutagenesis studies reveal the importance of the Fe-binding residues in JMJD6 catalysis . Although the JMJD6Δ363–404·D189A variant manifests apparent low-level formation of succinate in the absence of substrate , succinate formation was not observed in the presence of LUC7L2267–278 within the limits of detection , implying the D189A variant does not support productive hydroxylation catalysis. This provides further evidence that substitution of the metal-binding residues of 2OG oxygenases does not always completely block catalysis; for example, in the case of FIH, it has been reported that substitution of the Fe binding aspartate to a glycine is insufficient to completely ablate hydroxylation activity  C. JMJD6 SBH βVII B. Mutageactivity .et al. (204 (βIV) and to make hydrogen-bonding interactions with residues Tyr131 (located immediately to the N terminus of βI), Thr184 (βII), and Asn197 (βIII) (131 and Thr184 were observed in 3K2O (204 (3LDB), as reported by Hong et al. . Note in the JMJD6Δ344–403·Fe·2OG structure, the 2OG C-1 carboxylate is trans to the distal His273 of the binding triad (His273JMJD6) rather than being trans to the proximal His187 (His187JMJD6), as is also observed in FIH, JMJD5, JMJD2A, and PHF8  structures  . Similar in 3K2O , whereinK2O . This is similar to other structurally characterized JmjC domain-containing proteins (B–E) and likely contributes to the ability of JMJD6 to bind the positively charged basic groups of its substrate lysyl side chain as well as other lysyl-/arginyl-residues in the  basic JMJD6 substrates, e.g. histones and RS domains of SR proteins.Analysis of the electrostatic surface potential  of the Je charge A. This iproteins , B–E andFig. S29), Hong et al. , with basic residues involved in these interactions, including Lys4, Lys7, Arg8, Arg48, Lys91, Arg92, Arg95, Lys111, Lys115, Lys144, Lys151, Lys154, Arg305, Lys307, and Arg310 .Following the observation of ordered sulfate molecules at conserved positions across positively-charged sites on the surface of JMJD6 , which has an additional PHD, and the JMJD2 (KDM4) JmjC KDMs . HomjC KDMs , appear e.g. due to the presence of targeting domains/proteins, knowledge of the types of reaction directly catalyzed by the 2OG oxygenase domain in vitro can assist in subsequent functional assignment work in vivo. Given its checkered history , we carried out studies on reported JMJD6 N-methyl arginyl “demethylation” and lysyl “hydroxylation” substrates . In our studies, we found no evidence that purified JMJD6 has N-methyl arginyl demethylase (RDM) activity (Table S2). Positive controls for RDM activity employing KDM4E (Table S2)  . In addig et al.  have rep . Lys382 of the tumor-suppressor protein p53 is reported to be hydroxylated by JMJD6 . Peptide fragments of two other biochemically important reported targets, i.e. pVHL and ERα . Although we did not observe JMJD6-catalyzed RDM activity on ERα as was reported .In addition to multiple SR domain substrates , we founby JMJD6 , and we  and ERα , 37, werreported , hydroxypVHL is a tumor-suppressor protein in kidneys, which has a crucial role in dioxygen dependent proteasome-mediated degradation of prolyl-hydroxylated forms of α-subunits of the transcription factor HIF in many animal cells , 51, 52.6-tagged human full-length JMJD6  was inserted into the pET28a(+) expression vector. Expression plasmids for two more variants  were prepared by inserting a stop codon after the desired site using site-directed mutagenesis (see Table S3 for primer sequences). JMJD6 variants were expressed in Escherichia coli Rosetta2(DE3) cells  and stored at −80 °C. Cell pellets were resuspended in lysis buffer , DNase I , and 0.5% Nonidet P-40). The lysates were loaded onto a 5-ml HisTrap column , equilibrated with binding buffer  using an AKTA purifier . The column was washed with wash buffer . JMJD6 was eluted with elution buffer  using a linear gradient (0–100%). Based on UV-trace (280 nm) and SDS-PAGE analyses, fractions with purified JMJD6 were pooled and concentrated to 2 ml using a membrane filter (30-kDa molecular mass cutoff membrane). Concentrated protein was loaded onto a Superdex 200 size-exclusion column , pre-equilibrated with size-exclusion buffer , for further purification. The desired fractions  were concentrated to 25–30 mg/ml, then flash-frozen in liquid nitrogen, and stored at −80 °C. Catalytic mutants of the variant JMJD6Δ363–403 were prepared by site-directed mutagenesis (see Table S3 for primer sequences) and were purified by following the same purification procedure as for WT.DNA encoding for the N-terminal His3) cells , 23. Celm phosphate buffer, pH 8.0. Spectra were acquired using a quartz cuvette with a 0.1-cm path length, between 260 and 185 nm at 0.2 nm·min−1 increments, a response time of 1 s, and a data pitch of 0.5 nm. Spectra were averaged over four scans and corrected for solvent background. To investigate secondary structure content, the CD secondary structure deconvolution method was applied to the data, which were accessed using the DICHROWEB server (CD spectra were acquired using a Jasco J-815 spectrometer (Jasco). Protein solutions were buffered with 10 mB server , 54.m JMJD6, 100 μm (NH4)2Fe(SO4)2·6H2O (Sigma), and 400 μml-sodium ascorbate (Sigma) were mixed in deuterated Tris-d11 (Sigma), pH 7.5, in a 1.5-ml Eppendorf tube. Substrate (either only 500 μm 2OG or a mixture of 500 μm 2OG and 100 μm LUC7L2267–278) was added to initiate the reaction. The mixture was immediately transferred into a 2-mm NMR tube, and the acquisition of 1H spectra was started after 3.5–5 min.2OG turnover assays employed a reported procedure . 10 μm Jm 2OG and 200 μm Zn(II) were mixed in deuterated Tris-d11, pH 7.5, and the 1H NMR signals for 2OG were recorded at 700 MHz (DKapp) were measured using obs represents change in an observable NMR parameter from the titration; Δtotal represents the total change of the monitored NMR parameter; [L]0 represents the titrated ligand concentration; and [P]0 represents the protein concentration. Typically, a 5–10% error was allowed in the curve-fitting process.20 μ 700 MHz . Titratix − (τ − 180°y − τ − 90°y − τ − 180°y − τ)n − acquisition) was applied (n = 6); acquisition time 2.94 s; relaxation delay 2 s; number of transients 128. Water suppression was achieved by presaturation 2Fe(SO4)2·6H2O (Sigma), 400 μml-sodium ascorbate (Sigma), and 500 μm disodium 2OG (Fluka). After 30 min, the reaction was quenched by an equal volume of 1% (v/v) aqueous formic acid (Sigma). In a 96-well MALDI plate (Waters), 0.8 μl of CHCA  (1 μg in 0.1 ml of CHCA solvent) and 0.6 μl of the quenched mixture were placed in a well. After drying, the samples were analyzed by MALDI-TOF MS using a reported procedure 2Fe(SO4)2·6H2O (Sigma), 500 μml-sodium ascorbate (Sigma), and 1 mm di-sodium salt of 2OG (Fluka) for 1 h or more  and subsequent CID MS/MS spectra  of the 10 most intense peaks were acquired in the Orbitrap. CID fragmentation was performed at 35% of the normalized collision energy, and the signal intensity threshold was kept at 500 counts. ETD spectra  were acquired in the ion trap. PEAKS® 8.0  was used to analyze raw data. The raw MS files were searched against the respective protein sequences. NONE was selected as the protease. Demethylation (−14 and −28 Da) and hydroxylation  were set as variable modifications. The precursor mass tolerance was 15 ppm. The fragment mass tolerances for CID and ETD were set to 0.8 Da. All spectral assignments were manually validated.Samples were desalted using a ZipTip (Millipore) and then analyzed using a NanoAcquity-ultraperformance liquid chromatography system (Waters) connected to an Orbitrap Elite mass spectrometer (Thermo Fisher Scientific), possessing an EASY-Spray nano-electrospray ion source (Thermo Fisher Scientific). Peptides were “trapped” on an in-house packed guard column  using solvent A (0.1% (v/v) aqueous formic acid) at a pressure of 140 bar. Peptides were separated on an EASY-Spray Acclaim PepMap® analytical column  using a linear gradient , flow rate, 300 nl/min). The separated peptides were electro-sprayed directly into the spectrometer operating in a data-dependent mode using a collision-induced dissociation/electron transfer dissociation (CID/ETD)-based method. Full scan MS spectra  at a concentration of ≥25 mg/ml (500–600 μm) was used. JMJD6Δ344–403·metal·ligand complexes were formed by incubating enzyme with the other components  on ice for ∼1 h. A PhoenixTM RE crystallization robot (Art Robbins Instruments) and a Minstrel-HTTM platform with CrystalTrekTM  were used to prepare and monitor crystallization trials. Crystals were grown using the sitting-drop vapor-diffusion method . Crystals were cryo-protected using a mixture of reservoir solution diluted to 25% (v/v) glycerol and cryo-cooled by plunging into liquid nitrogen. Diffraction data were collected at 100 K at the Diamond Light Source synchrotron. PHASER was used for molecular replacement using PDB code 3K2O (Crystallization trials were performed using commercially available broad screens followed by optimization. JMJD6n method  either in method . The optode 3K2O  as the sode 3K2O , 63.Δ344–403·Fe·2OG structure are deposited in the Protein Data Bank as code 6GDY.Coordinates and structure factors for the JMJD6M. S. I., M. A. M., R. C., and C. J. S. conceptualization; M. S. I. and M. A. M. data curation; M. S. I. and M. A. M. software; M. S. I. and M. A. M. formal analysis; M. S. I. and C. J. S. funding acquisition; M. S. I. and M. A. M. validation; M. S. I., J. G., A. K., and E. P. investigation; M. S. I. and M. A. M. visualization; M. S. I. methodology; M. S. I., M. A. M., and C. J. S. writing-original draft; M. A. M., R. C., and C. J. S. supervision; M. A. M. and C. J. S. project administration; M. S. I., M. A. M. and C. J. S. writing-review and editing; C. J. S. resources.


It is known that HRmax decreases with high altitude and the duration of the stay (acclimatization). At an altitude typically chosen for training  conflicting results have been found. Whether or not this decrease exists or not is of importance since the results of previous studies assessing hypoxic training based on HR may be biased due to improper intensity. By pooling the results of 86 studies, this literature review emphasizes that HRmax decreases progressively with increasing hypoxia. The dose–response is roughly linear and starts at a low altitude, but with large inter-study variabilities. Sex or age does not seem to be a major contributor in the HRmax decline with altitude. Rather, it seems that the greater the reduction in arterial oxygen saturation, the greater the reduction in HRmax, due to an over activity of the parasympathetic nervous system. Only a few studies reported HRmax at sea/low level and altitude with patients. Altogether, due to very different experimental design, it is difficult to draw firm conclusions in these different clinical categories of people. Hence, forthcoming studies in specific groups of patients are required to properly evaluate (1) the HRmax change during acute hypoxia and the contributing factors, and (2) the physiological and clinical effects of exercise training in hypoxia with adequate prescription of exercise training intensity if based on heart rate.The use of exercise intervention in hypoxia has grown in popularity amongst patients, with encouraging results compared to similar intervention in normoxia. The prescription of exercise for patients largely rely on heart rate recordings (percentage of maximal heart rate (HR Intermi2) at a specific power output is similar at sea level and altitude  exposure to a high altitude such as encountered during mountaineering  and/or inspired oxygen fraction (%). A classification was first completed to select articles reporting HRmax data were collated from 81 publications involving healthy subjects and 5 publications involving patients , a systematic assessment of hypoxic intervention was not done.2max could not be fully explained by the reduction in arterial oxygen content (CaO2)  is usually associated with lower HRmax  = −0.0024 × altitude (m) + 0.73. Hence, a 1,000 m gain will reduce HRmax by 1.7 bpm. This is in agreement with, e.g., the 1.9 bpm per 1,000 m found in young subjects by Wehrlin et al. and with the 9 bpm decrease of HRmax observed at 4,300 m  = 116–0.0057x . Compared to our findings, this model tends to underestimate the decrease at low altitudes and overestimate the decrease at high altitudes . For a 20 years old subject, this represents a decrease of 2.5% (assuming HRmax = 200 bpm in normoxia). For a 70 years old subject, this represents 3.3% (assuming HRmax = 150 bpm in normoxia). As older subjects already have cardiac limitations, this further decrease may result in an insufficient HR to maintain performance and a tendency to reach exercise intolerance at the suggested exercise target HR.The large variability in the decrement in HRmax with altitude , the decrement in HRmax appears a little more pronounced for untrained than trained subjects  = −0.0026 × altitude (m) + 1.2486 and HRmax (bpm) = −0.0025 × altitude (m) + 1.4263, respectively. However, this observation is based on studies using different testing and hypoxic conditions and should be viewed with caution. Also, the definition of the “untrained” and “trained” states by the authors has not been harmonized as it should be , the trend is completely different with a paradoxical grseater decrease in HRmax at the lowest reported altitude  limiting the relevance of this finding. Interestingly, in one study with heart failure patients, an unexpected increase in HRmax of 8 bpm was reported at 3454 m compared to 540 m  variability exists. But this decrement should be clearly specified, as it has been previously reported in a review paper, which focused on the use of exercise training in hypoxia that hypoxia trigger an increase in both basal and maximal HRmax, which is contradictory to the current observation  . The absolute HR were identical in both normoxic and hypoxic groups in the study of Bailey et al. , an overestimation of 3 bpm (2.8%) and 5 bpm (2.8%) of target HR for moderate (40% HRmax) and vigorous (90% HRmax) intensity exercise, respectively, would have been observed for an exercise training session at 2,500 m. At 3,000 m, it would have been 4 bpm (3.5%) and 6 bpm (3.5%), respectively. Focusing only on the altitude gain ranging from 2,500 to 3,500 m  and 4 bpm (2.3%) for moderate and vigorous exercise, respectively. Also, resting HR increases under hypoxia due to increase sympathetic and decrease parasympathetic activity  and 3 bpm (2.2%) for moderate and vigorous intensity calculated from HRR. Using the data presented in Figure max group 50-59 ml/min/kg, the overestimation is roughly the same for each given example. However, using the data presented in Figure max is very close to the predicted HRmax indirectly derived from the age. But such derived HRmax could lead to large error in the prediction  for submaximal and maximal HR could be considered as high, since they have been reported to be greater than 0.9, the higher the HR, the lower the variation  and therefore also depends on the duration of hypoxic exposure. It is not known if over the course of a training program HRmax decreases in the same way, even if unlikely (a huge difference between daily exposure on one side and 3-5 sessions of 30-90 min per week exists in terms of hypoxic exposure). Hence, much remains to be done in this field and forthcoming studies with appropriate designs need to be conducted to answer questions in both the physiological and clinical area. In the first category, the effects of hypoxia on HRmax  amongst specific populations have to be better addressed, with a specific focus on sex and age. Also, it is of importance to better assess these effects in specific pathologies (in particular cardiovascular and metabolic diseases), as well as determining potential interaction with drugs. The difference between normobaric and hypobaric hypoxia should also be addressed. In all of these situations, the specific impact of SaO2 and the autonomic nervous system should be taken into consideration. In the second category, a thorough evaluation of the potential superiority of exercise training in hypoxia over normoxia on relevant outcomes need to be done with a well-controlled design that involves accounting for the placebo effect and an adequate prescription of exercise training intensity based on heart rate. Under conditions of hypoxic exercise training, the long-term effect of hypoxia exposure on HRmax and the potential need to adjust the relative HR target should also be addressed as well as the need to account for chronotropic effects of drugs. In some years, a review similar to the present one would be very instructive.A body of scientific literature exists on the evaluation of passive exposure and/or exercise training in altitude/hypoxic environment in healthy subjects. Despite this, debates still exists on the benefits and physiological effects of hypoxic training. Nevertheless, the use of exercise training in hypoxia has grown in popularity with patients. Studies have provided encouraging results, but the effectiveness and potential superiority of hypoxic training over normoxic training remains to be established. To achieve this, the exercise training programs performed by the experimental and control groups should be comparable to allow a rigorous evaluation of the isolated hypoxic stimulus. The best metric to quantify the exercise training load needs to be specified, but the prescription of exercise for patients largely rely on HR recordings. This review underlines that HRLM: Lead author, study writing. The manuscript presents clearly results, honestly, and without fabrication, falsification, or inappropriate data manipulation. Results of the present study do not constitute endorsement by ACSM.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


TBX18 to the left ventricular apex in the CAVB rats resulted in ectopic ventricular beats within days, achieving a de novo ventricular rate faster than the slow atrioventricular (AV) junctional escape rhythm observed in control CAVB animals. The model offers new opportunities to test therapeutic approaches to treat chronic and severe CAVB which have previously only been testable in large animal models.Complete atrioventricular block (CAVB) is a life-threatening arrhythmia. A small animal model of chronic CAVB that properly reflects clinical indices of bradycardia would accelerate the understanding of disease progression and pathophysiology, and the development of therapeutic strategies. We sought to develop a surgical model of CAVB in adult rats, which could recapitulate structural remodeling and arrhythmogenicity expected in chronic CAVB. Upon right thoracotomy, we delivered electrosurgical energy subepicardially via a thin needle into the atrioventricular node (AVN) region of adult rats to create complete AV block. The chronic CAVB animals developed dilated and hypertrophied ventricles with preserved systolic functions due to compensatory hemodynamic remodeling. Ventricular tachyarrhythmias, which are difficult to induce in the healthy rodent heart, could be induced upon programmed electrical stimulation in chronic CAVB rats and worsened when combined with β-adrenergic stimulation. Focal somatic gene transfer of  The subsequent slow AV junctional escape rhythm is inadequate to support CAVB patients’ hemodynamic needs, requiring the implantation of an electronic pacemaker device5. If left untreated, the ventricles of CAVB patients are susceptible to spontaneous and drug-induced QT prolongation7, which often precipitates to life-threatening arrhythmias such as torsades de pointes10. An animal model of CAVB would be ideal for studies aimed at understanding mechanisms of catastrophic ventricular tachyarrhythmias11, as well as developing therapies to mitigate arrhythmogenic events in CAVB13. We and others have developed large animal models of CAVB17, but those models are resource-exhausting and not widely available for standard benchtop research. Transgenic mouse models can exhibit spontaneous AV block19, but their degree and persistence of AV block are unpredictable, as CAVB is an adverse side effect of the transgene modification rather than a direct effect. Surgical models of CAVB have been documented in rodents23. However, we found these methods difficult to reproduce and adopt independently. One approach of injecting 70% ethanol into the AVN24, is hindered by a limited number of ablation attempts, as repeated doses of alcohol lead to global heart dysfunction and systemic complications, thus reducing survival. Other approaches require the use of custom-engineered, rodent-sized radiofrequency (RF) ablation catheters23, impeding widespread implementation in conventional laboratories.Complete atrioventricular block (CAVB) is a major cardiac conduction disorder, in which the transmission of an electrical impulse from the atria to the ventricles is completely inhibited25. Here, we present a long-term survival CAVB model in rats achieved via subepicardial delivery of electrosurgical energy into, and the subsequent fibrosis of, the AVN region. CAVB was achieved immediately upon ablation of the AVN and was stable for >4 weeks. The CAVB animals exhibited electrical abnormalities, including spontaneous and inducible ventricular tachyarrhythmias, and progressive ventricular remodeling, evidenced by increased stroke volume and ventricular hypertrophy with preserved ejection fraction at week 4. Notably, our chronic CAVB model revealed striking age and sex differences in survival rates, in which all males and 3-month old females died within the first 72 hours of creating CAVB, suggesting that the slow junctional escape rhythm is insufficient for supporting male and 3-month old female rats.We sought to develop a rodent model of CAVB that requires only a routine set of surgical instrumentation, yields a high success rate in 6-month old female rats, persists long-term (4 weeks), and recapitulates ventricular arrhythmias that are often manifested in CAVB patientsTBX18, a concept we have previously demonstrated for converting chamber cardiomyocytes to induced pacemaker cells27. Direct intramyocardial delivery of TBX18 into the left ventricular apex of chronic CAVB rats revealed emergence of ectopic ventricular beats at a rate higher than the slow AV junctional rhythm of the control animals. The TBX18-induced ventricular pacing is the first demonstration of the technique’s feasibility and disease-modifying potential, when the biologic is delivered after chronic CAVB had been established.We also sought to reverse the severe CAVB-induced ventricular bradycardia by focal somatic gene transfer of We attempted to disrupt AVN conduction by focal ablation with electrical energy. We elected to use an electrosurgical unit over electrocautery, because electrosurgery delivers high-frequency electrical energy, traveling beyond the tissue-electrode contact site. On the other hand, electrocautery, which delivers heat only, is limited to burning tissues at the contact site. Initial trials of electrical energy delivery by direct contact of an electrosurgical pen on the AVN region caused an epicardial scar that remained largely superficial. This failed to generate reproducible CAVB. In order to deliver electrical energy subepicardially, we employed a thin needle of a 0.3 mm diameter Fig. . This neThe following steps were taken prior to delivering electrosurgical energy: The bent distal tip of the ablation needle was advanced into the epicardial surface, posterior to the fat pad and posterolateral of the aorta, and pointing toward the left ventricular apex. This maneuver often elicited skipped ventricular beats, transient AV dissociations indicative of mechanical disruption of AVN or high His bundle conduction, and/or premature ventricular complexes (PVCs) Fig. . Parallep = 0.49). However, the male rats weighed significantly more at 504 ± 15 g compared to the age-matched female rats weighing 372 ± 63 g . We asked if the mortality in the males was strictly due to sex difference, and performed CAVB in 3-month old female rats weighing 271 ± 16 g. The 3 month old female rats also expired in 72 hours after CAVB induction , but slower than the 6-month old female rats . Subcutaneous injection of isoproterenol during the post-op recovery period transiently increased the slow junctional rhythm of the 3-month old animals, but did not aid in the survival of those animals beyond three days post-op. To learn if the differences in the acute survival rates CAVB animals may be due to developmental stages rather than to sex difference per se, we examined the normal compact AVN areas near the central fibrous body of 6-month old female rats, 6-month old male rats, 3-month old female rats, and 3-month old male rats (n = 3 for each group). The compact AVN region near the central fibrous body was distinctively smaller in the 3-month old rats of both sexes compared to that of the 6-month old rats . Likewise in male rats, the mean area of the AVN was 0.052 ± 0.028 mm2 in 3-month old, compared to 0.177 ± 0.034 mm2 in 6-month old males . No significant difference was found in AVN area between age-matched male and female rats . Immediately upon CAVB, the ventricular rate of the 6-month old male rats was 106 ± 15 bpm, statistically similar to that of the 6-month old female rats at 123 ± 39 bpm  or PVCs Fig.  were obsTBX18, converts chamber cardiomyocytes to induced-pacemaker cells27. Focal delivery of TBX18 into the ventricular myocardium gave rise to ectopic ventricular beats in both small27 and large12 animal models, providing evidence for a transcription factor-based biological pacemaker. Although our porcine model of CAVB closely mimicked clinical CAVB31, our previous small animal model of ventricular bradycardia relied on transient AV dissociation resulting from non-specific, cholinergic suppression of AV conduction in anesthetized rodents32. Using the current rat model of chronic CAVB, we focally delivered an adenoviral vector expressing TBX18 (Adeno-TBX18) into the left ventricular apex of 6-month old female rats upon confirming stable and complete AV block at 1 week after ablation surgery  control animals  resolved two distinct peaks in the heart rates that lasted beyond 1 week post-delivery; one peak at a rate similar to the slow junctional rhythm of the control animals, and a second peak at a faster ventricular rate . Surprisingly these younger, smaller male rats showed a significantly higher mortality rate compared to their older counterparts , indicating an additional age-dependent effect on mortality. Further investigation showed a similarly increased mortality rate in 3-month female rats with CAVB . In both sexes, 3-month old rats were shown to die of ventricular bradycardia and sudden cardiac arrest  hearts containing a smaller AV nodal area, have significantly slower ventricular rates than their older counterparts following AV ablation. As shown in the ECG data  was applied following induction of anesthesia to prevent corneal drying. Monopolar electrosurgical current was delivered to the AVN region via an active electrode connected to a high frequency electrosurgical generator in a coagulation mode . A reusable dispersive grounding pad electrode , serving as the return electrode, was placed on the back of the rat. The back of the rat was shaved to minimize electrical resistance between the animal and grounding pad. We found that a larger surface area grounding pad reduced the resistance and increased electrical current, thereby reducing the voltage necessary to achieve the same delivered power. Smaller ground pads or poor contact between the skin and the return electrode significantly reduced the effectiveness of AVN ablation and generated excessive heat at the skin-ground pad contact site, leading to severe skin burns. In order to ensure a sufficient skin-ground pad interface, we found that application of ultrasound electrode gel between the skin and ground pad significantly increased the effectiveness of electrosurgical AVN ablation. During surgery, body temperature was maintained at 37 °C with a water blanket . Carprofen (5 mg/kg) and Buprenorphine SR (1 mg/kg) were given subcutaneously for analgesia. Atropine (0.05 mg/kg) was given intramuscularly to reduce pulmonary secretion. Upon ablation of the AVN, the thoracic cage was repaired with a 4-0 polyglycolic acid absorbable suture  and the lungs were fully inflated for two seconds to avoid pneumothorax immediately before closing the thoracic cavity. External thoracic muscles were repaired layer by layer with 4-0 absorbable suture. Skin was sutured with 4-0 monofilament polypropylene non-absorbable suture . The isoflurane ventilation was reduced to zero after completion of the surgery. Once spontaneous breathing was evident, the endotracheal tube was removed. If excessive blood loss occurred (>2 mL), 2 mL of 0.9% sodium chloride solution was administered subcutaneously. Carprofen (5 mg/kg) was administered subcutaneously as a post-surgical analgesic at 24, 48, and 72 hours after surgery.Sprague Dawley rats  were anesthetized in an induction chamber with 5% isoflurane in 100% oxygen at a constant flow rate of 2 L/min for 6 minutes. Endotracheal intubation was performed with a 14-gauge, 57 mm long intravenous catheter. The animals were ventilated with a respirator  at 85 respirations per minute with a 2.5 ml stroke volume. Anesthesia was maintained in 2% isoflurane mixed with 100% oxygen throughout the surgery. Sterile lubricating eye ointment  were recorded on anesthetized animals with a BioAmp (FE135) signal amplifier, a PowerLab 8/35 digitizer and analyzed with LabChart Pro . Baseline ECGs were acquired just after intubation under anesthesia with 2% isoflurane. A partial right thoracotomy was performed in the third intercostal space to expose the right atrium and aorta. After retracting the thymus and removing pericardium, the right atrial appendage was partially ligated and the right atrium laterally retracted so as to avoid excessive tissue damage or bleeding during ablation. This maneuver exposed the epicardial aspect of atrioventricular nodal area, landmarked by the characteristic fat pad consistently located between the aortic root and the medial wall of the right atrium. The negative electrode for lead II was replaced with the electrode connected to the ablation needle for epicardial electrogram. This was achieved by attaching the electrode of a surface ECG cable  to the proximal end of a 0.3 mm diameter, 5 cm long ablation needle  in the abdominal cavity according to the manufacturer’s instructions. Lead I was obtained by positioning the electrodes on the left and right latissimus dorsi muscles. Lead II was obtained by positioning the electrodes between the suprasternal fossi and left lower thoracic cage. The electrical signals were transmitted to SmartPad  and analyzed with LabChart Pro .Echocardiography was performed immediately before the surgery, then serially at one week and one month post-surgery with Vevo 2100 High Frequency ultrasound imaging system  and analyzed with Vevo Imaging Workstation. Inter-ventricular septal thickness (IVS), LV posterior wall thickness (LVPW), and LV internal diameter (LVID) were measured in short axis during systolic and diastolic phases on M mode imaging. From these measurements, LV end diastolic volume (LVEDV), LV end systolic volume (LVESV), LV fractional shortening (LVFS), LV ejection fraction (LVEF), and approximated LV myocardium mass were calculated.29. Pacing thresholds were determined, and stimulation was delivered at a 1 ms pulse width at twice the capture threshold. An S1 drivetrain of 10 stimuli  was applied followed by an extra stimulus (S2) starting at a coupling interval of 80 ms and by 1 ms decrements until the effective refractory period was reached. Another extra stimulus (S3) followed S2, decremented by 1 ms until the ventricular effective refractory period was reached. After this, a train of programmed stimulation with three extra stimuli after S1 (S2–S4) was performed until a ventricular arrhythmia was induced. If the rat failed to develop ventricular arrhythmia with 3 extra stimuli (S1–S4), the animal was deemed non-inducible.Ventricular arrhythmias were induced on five CAVB rats one month after CAVB creation. Animals were anesthetized with 5% isoflurane and placed on a mechanical ventilator after intubation. Anesthesia was maintained with 2% isoflurane during programmed electrical stimulation (PES). The right jugular vein of the anesthetized CAVB rat was cannulated with a 21-gauge polyethylene tubing which was navigated into the right ventricle. Using the polyethylene tubing as a guide sheath, a platinum wire was inserted through the lumen of the tubing into the right ventricular cavity until ventricular electrical potentials could be detected. PES was performed with current stimulus isolator  with or without isoproterenol  following our previous protocolThe heart from seventeen rats were harvested, fixed in 10% formalin for 24 hours and paraffin-embedded for histopathological examination of the AVN region. The animals were grouped as follows: 3-month old normal male (n = 3), 3-month old normal female (n = 3), 6-month old normal female (n = 3), 6-month old normal male (n = 3) and 6-month old female with CAVB (n = 5). The paraffin-embedded tissue samples were sectioned at 5 µm thickness. Masson’s trichrome staining was performed to examine the native AVN structure and subsequent tissue necrosis post-electrosurgical energy delivery. Staining was performed according to manufacturer’s protocol . Stained sections were scanned with Hamamatsu Nanozoomer . We measured the fibrotic area from upper margin of IVS to lower margin of IAS including the annulus ring of the mitral valve. The mitral valve leaflet was not included. Fibrotic area was measured by manually drawing a region of interest (ROI) around the circumference of blue collagen tissue. ROI area was measured using NDP.view2 software.TBX18-IRES-zsGreen1 (n = 4) or GFP (n = 4) to the heart. For each animal, 1 × 108 fluorescence forming units (ffu) of the adenoviral vector was injected in 100 µl of volume into the left ventricular apex of the heart. A telemetry device was implanted immediately after injection of the viral vector.Upon creating CAVB, the animals were allowed to recover from the right thoracotomy and monitored for one week to confirm stable CAVB. Upon validating stable CAVB, the animals underwent a partial left thoracotomy in the fourth intercostal space to deliver an adenoviral vector expressing either All data are expressed as mean ± standard deviation (SD) at a 95% confidence limit. For longitudinal comparison of continuous variables such as mean heart rates, weight, and echocardiographic parameters, the statistical significance was tested using repeated-measures ANOVA with subsequent Bonferroni multiple comparisons test. Statistical analysis was performed using SPSS version 23.0 .Supplementary figure 1Supplementary video 1Supplementary video 2


RNA binding protein (RBP) plays an important role in cellular processes. Identifying RBPs by computation and experiment are both essential. Recently, an RBP predictor, RBPPred, is proposed in our group to predict RBPs. However, RBPPred is too slow for that it needs to generate PSSM matrix as its feature. Herein, based on the protein feature of RBPPred and Convolutional Neural Network (CNN), we develop a deep learning model called Deep-RBPPred. With the balance and imbalance training set, we obtain Deep-RBPPred-balance and Deep-RBPPred-imbalance models. Deep-RBPPred has three advantages comparing to previous methods. (1) Deep-RBPPred only needs few physicochemical properties based on protein sequences. (2) Deep-RBPPred runs much faster. (3) Deep-RBPPred has a good generalization ability. In the meantime, Deep-RBPPred is still as good as the state-of-the-art method. Testing in A. thaliana, S. cerevisiae and H. sapiens proteomes, MCC values are 0.82 (0.82), 0.65 (0.69) and 0.85 (0.80) for balance model  when the score cutoff is set to 0.5, respectively. In the same testing dataset, different machine learning algorithms (CNN and SVM) are also compared. The results show that CNN-based model can identify more RBPs than SVM-based. In comparing the balance and imbalance model, both CNN-base and SVM-based tend to favor the majority class in the imbalance set. Deep-RBPPred forecasts 280  and 265  of 299 new RBP. The sensitivity of balance model is about 7% higher than the state-of-the-art method. We also apply deep-RBPPred to 30 eukaryotes and 109 bacteria proteomes downloaded from Uniprot to estimate all possible RBPs. The estimating result shows that rates of RBPs in eukaryote proteomes are much higher than bacteria proteomes. After RBPs have been identified, CLIP-related experimental technologies14 are applied to reveal the binding sites in RNAs. Also, many computational methods have been proposed to predict interaction of protein with RNA18 and RBPs25. RBP predictors can predict the RBPs, and then CLIP-related techniques can further reveal RNAs interacting with these RBPs. However, previous computational methods only considered only part features or known RNA binding domain (RBD) which plays a significant role in RBPs prediction. So, we proposed RBPPred integrating as much as features to address this problem22. Benchmarking on datasets shows that RBPPred is better than other approaches. But RBPPred runs slowly because it requires to run blast against a huge protein NR database to generate PSSM matrix. However, the prediction speed is important because a large number of RBPs are still unknown in many species. To overcome this shortcoming, we present Deep-RBPPred which is based on deep learning.RNA binding proteins (RBPs) play important functions in many cellular processes, such as post-transcriptional gene regulation, RNA subcellular localization and alternative splicing. With significant function in biology, many high-throughput experimental techniques have been developed to identify new RBPs in human, mouse, S. cerevisiae and C. elegans32. For predicting protein binding sites in RNA sequence, DeepBind32 is the first CNN-based model to predict the binding affinity. Deep-rbp29 and iDeep31 are two deep learning methods which both take RNA structure into consideration. These methods outperform the conventional approaches in term of prediction accuracy. However, deep learning algorithm is still not applied to RBPs prediction. In Deep-RBPPred, we apply a deep convolutional neural network instead of SVM. Since CNN-based method requires to input a fixed length feature vector, two solutions are handled to meet this requirement. The first solution is to pad all the sequences to fixed length sequences, and then one-hot encoding is used to encode the sequences. The second solution is to design the features by hand. It is not appropriate to predict RBPs with the padding solution because the length of RBPs varies over a wide range . Based on this consideration, we employ the hand-designed features which are proved effective to represent RBPs in RBPPred. Unlike RBPPred, we only employ physicochemical features including hydrophobicity, polarity, normalized van der Waals volume, polarizability, side chain’s charge and polarity. These features are used to train the weights of 11 layers convolutional neural network with Tensorflow33. Deep-RBPPred presents comparable results to RBPPred but is significantly more efficient in the testing. And it also only needs few physicochemical features.In recently years, deep learning technology has been used in many aspects in bioinformatics and proved as a power tool22. Here we just simply describe the generating process. The positive samples are collected from the Uniprot database34, which is retrieval with GO term’RNA binding’ to search this protein database because the Uniprot database includes RBPs with x-ray crystal structures and RBPs identified by high-through experiment. For the negative samples, we took the approach from SPOT-stru35. The negative sequences are collected from PDB, by using PISCCES36 with sequence identity cutoff 25%, sequence length between 50 and 10,000 and resolution of X-ray better than 3.0 Å. The collected sequences are then mixed together so that the redundant proteins are removed with sequence identity of 25% by psi-cd-hit in the CD-HIT package37. Finally, the training set includes 2780 RBPs and 7093 non-RBPs.In order to train our deep learning model, we employed the training set used in the RBPPred. The details of generating the training set have been described in RBPPredThe training set consisting of different amount of RBPs and non-RBPs is known as an imbalance training set. The classification algorithm tends to favor the majority class when it is trained in the imbalance dataset. So, we randomly select 2780 non-RBPs to generate the balance dataset together with 2780 RBPs.22. However, only the identical sequences between the training and the testing set are removed. This may lead to a bias result caused by the redundance between training and testing set. So, we remove the homology sequences by CD-HIT. The testing and training set are mixed together to be clustered by CD-HIT with sequence identity cutoff 30%. Then all the sequences are discarded from testing set if they are in the same cluster with the training sequences. This can ensure the testing sequences are independent with training set. For one cluster, we only select the sequence provided by CD-HIT to ensure a non-redundant testing set. We finally collected 488 sequences including 239 negative samples and 249 positive samples, which are composed of 72 RBPs and 13 non-RBPs for A. thaliana, 129 RBPs and 164 non-RBPs for H. sapiens, 48 RBPs and 62 non-RBPs for S. cerevisiae. Comparing to the previous testing dataset including 2546 sequences, 2058 sequences are discarded for the redundance.For testing our deep learning model, we used the testing set from RBPPred37. But the evolutionary information and predicted secondary structure are discarded due to the computational time. The solvent accessibility is also discarded. At last, a 148-dimensional vector is encoded to represent each protein sequence including the properties of hydrophobicity, normalized van der Waals volume, polarity and polarizability, charge and polarity of side chain. We expand the dimension of feature vector to 160 with the expanded feature values assigned to 0 due to the CNN network architecture. Finally, we collect a total 160-dimensional feature vector to represent a protein sequence, as shown in Fig. 22. The program encoding the feature vector is extracted from the RBPPred software package.The protein is encoded to a feature vector by the approach described in RBPPredThe performance is evaluated by sensitivity (SN), specificity (SP), accuracy (ACC) and Matthews Correlation Coefficient (MCC) which are defined as following:38 with tensorflow. In Fig. 39 which randomly discards some neurons in the training phase. The dropout probability is set to 0.5. The final layer is the Softmax layer which is used to classify RBPs or not. The output of this model is a probability score which describes the probability of an RBP. All the activation functions in neurons are ReLU40. All the weights in neurons are added a L2 regularization operation. The L2 regularization losses are added to the final loss function. Adam optimizer is employed to minimize final loss consisting of cross-entropy between the label and probability score and L2 regularization loss of neurons. In this architecture, the number of trainable variable is 480,930. In training process, the learning rate is set to 0.0001.Deep-RBPPred is a Convolutional Neural Network (CNN)To avoid the overfitting and estimate an appropriate epoch of our models in the whole training sets, we perform the 10-fold cross-validation on the balance and imbalance training set. As shown in Fig. th epoch and imbalance model of 242th epoch are selected as final models. The training loss of final balance/imbalance model is 0.15/0.17, which is almost equal to loss of the 10-folds validation process /3), which is much better than average SP of 0.62 ((0.56 + 0.64 + 0.65)/3) for the imbalance model. For predicting RBPs in the testing dataset, the SVM-imbalance model achieves an average of SN 0.94 ((0.90 + 0.93 + 1.0)/3), which is much higher than average SN of 0.82 ((0.83 + 0.81 + 0.83)/3) for the balance model. Indeed, the SVM models trained on the balance or imbalance model have an effect on the non-RBPs prediction. That is, the balance model has a better/worse predicting ability in RBPs/non-RBPs than the imbalance model. This effect is not significant in CNN when comparing with SVM. As shown in Table 22.Deep-RBPPred is also tested and compared to other models on the testing set. Total three predictors are compared. The first approach is RBPPred, which is developed by our group previously. The second approach is RNApred which employees the amino acid composition or PSSM to predict RBPs. The third method is SONAR which integrates protein-protein interaction network and other features to predict the RBPs. The result of SPOT-Seq-RNA is not shown here because it has been compared with RBPPredAs shown in Table 22. 280 and 265 of 299 new RBPs are correctly predicted by Deep-RBPPred-balance and Deep-RBPPred-imbalance, but only 260 RBPs are predicted by RBPPred22. Deep-RBPPred performs better than RBPPred. One protein (Uniprotid: P0DOC6) can’t be calculated by RBPPred for that no protein sequences can be found by Blast. We also collect the 130 experimently determined human RBPs published in Wen and the co-workers’ work42. RBPPred correctly predicts 24 of 130 RBPs, while Deep-RBPPred-imbalance and Deep-RBPPred-balance correctly predict 63 and 92 RBPs respectively. These results indicate that Deep-RBPPRed has better predicting ability than RBPPred.To test the predicting ability of Deep-RBPPred on new RBPs, we collect 299 new RBPs created between 2015-05-24 (consistent with RBPPred) and 2017-09-27 from Uniprot. In this section, only the RBPPred is compared because that the RBPPred have been proved to have better predicting ability than other methodsRunning time is an important metric to measure a model. We list the computational time of Deep-RBPPred in Table E. coli. Finally, we filter out 109 bacteria and 30 eukaryote proteomes from all the bacteria and eukaryote proteomes.Deep-RBPPred is applied to estimate the RBPs in 139 reviewed proteomes for 109 bacteria and 30 eukaryote species. There are two problems in the Uniprot proteome dataset. Firstly, reviewed and un-reviewed sequences are both included in the Uniprot. The un-reviewed sequence may not be a real protein. So, the reviewed proteomes are used in the prediction. The second problem is that almost all reviewed proteomes are incomplete. For example, truepera radiovictrix (proteome id: UP000000379) only contained one reviewed sequence. These two problems can result in a bias prediction. In order to select some appropriate proteomes, we filter the proteomes with the number of sequences. For eukaryote species, the amount is set to 1/10 of S. cerevisiae. For bacteria, the number is set to 1/10 of The results of prediction are shown in Fig. 2. It may lose the RBPs binding to the non-coding RNA.In this study, we develop two RBPs predicting models  based on CNN which only need hydrophobicity, normalized van der waals volume, polarity and polarizability, charge and polarity of side chain of protein sequence. Comparing with SVM models, we show that the CNN-based model performs better than SVM-based model. In comparing the balance and imbalance model, both the CNN-based and SVM-based classification show a preference for the major class. The result from the testing dataset shows that our deep learning models perform as good as RBPPred which is the best model so far. More importantly, Deep-RBPPred needs fewer features than RBPPred. Deep-RBPPred was then applied to estimate RBPs in 139 reviewed proteomes from the Uniprot dataset. The result shows that the RBPs rate in the bacteria is smaller than the eukaryote proteome. Deep-RBPPred-imbalance predicts 14,744 RBPs for the whole reviewed human proteomes. This number is almost 10-fold more than the number of the RBPs identified by high through experiments. This may be caused by these high throughput experimental limitations. For example, “Interactome Capture” only identifies the RBPs which bind to mRNA43 are added to avoid overfitting in the architecture of our deep learning. The process of 10-cross validation (Fig. th epoch. The process of training (Fig. In general, deep learning methods are applied in a large-scale data. A classic application of CNN-based methods is to classify the image. In this application, data augmentation approaches are used to enlarge the number of samples. And a large dataset may reduce the risk of deep learning model in overfitting. In Deep-RBPPred, we remove the redundant sequences as other researches have done. The process can be regarded as the opposite of data augmentation process in image recognition. In addition, L2 regularization and dropout layerSupplementary Information


Among the known triterpenes, β-d-glucopyranosyl 2α,3β,6β-trihydroxyolean-12-en-28-oate is reported for the first time in the Combretaceae, while bellericoside and asiatic acid are described for the first time in the genus Combretum. The structures of the isolated compounds have been established on the basis of spectral techniques . Their in vitro antifungal activities against standard strains of Candida albicans, C. krusei and Cryptococcus neoformans were also evaluated in this work.Two new triterpene glucosides, β- The 1H-NMR spectrum of 1 showed six aliphatic methyl singlets at δ 0.85, 0.87, 0.97, 1.06, 1.18 and 1.54 and a broad singlet at δ 5.38 assignable to an olefinic hydrogen. The 13C and DEPT NMR spectra exhibited signals for six methyls, eleven methylenes (two oxymethylenes), eleven methines  and eight quaternary carbons (one olefinic and one ester carbonyl carbon), of which six were attributed to a sugar unit and 30 were consistent with an triterpene aglycon moiety. The presence of a Δ12-double bond, already inferred from the broad singlet at δ 5.38 ppm in the 1H-NMR spectrum was corroborated by resonances at 122.7 and 144.1 in the 13C-NMR spectrum, assigned to C-12 and C-13, respectively, of an olean-12-ene-type skeleton  assignable to diastereotopic hydroxymethylene hydrogens, which in turn showed cross-peak correlations with a carbon signal at δ 65.7 in the HSQC spectrum. This information, along with an upfield shifted methyl carbon signal at δ 24.1 ascribable to C-23 and a downfield quaternary carbon resonance at δ 44.0 attributable to C-4 strongly suggested the location of this third hydroxyl substituent at C-24 - ; 1H-NMR: δ 4.33 ; 3.54 ; 5.38 ; 3.16 ; 3.69 ; 4.42 ; 1.54 ; 0.97 ; 1.06 ; 1.18 ; 0.87 ; 0.85 ; sugar signals: δ 6.29 ; 4.00 ; 4.18-4.45*  *overlapping signals; 13C-NMR: δ 47.8 (C-1); 68.6 (C-2); 85.7 (C-3); 44.0 (C-4); 56.5 (C-5); 19.3 (C-6); 33.4 (C-7); 40.0 (C-8); 48.3 (C-9); 38.3 (C-10); 24.1 (C-11); 122.7 (C-12); 144.1 (C-13); 42.1 (C-14); 28.2 (C-15); 23.4 (C-16); 47.0 (C-17); 41.7 (C-18); 46.2 (C-19); 30.7 (C-20); 34.0 (C-21); 32.5 (C-22); 24.1 (C-23); 65.7 (C-24); 17.3 (C-25); 17.4 (C-26); 26.0 (C-27); 176.4 (C-28); 33.1 (C-29); 23.6 (C-30); sugar signals: δ 95.8 (C-1’); 74.1 (C-2’); 78.9 (C-3’); 71.1 (C-4’); 79.3 (C-5’); 62.3 (C-6’).β-Arjunolic acid (2) and Asiatic acid (7) as a mixture: colorless amorphous powder; 1H- and 13C-NMR data in accordance with those of an authentic sample and with the literature [2: 13C-NMR: δ 47.6 (C-1); 68.8 (C-2); 78.2 (C-3); 43.6 (C-4); 47.9 (C-5); 18.5 (C-6); 32.8 (C-7); 39.8 (C-8); 48.1 (C-9); 38.4 (C-10); 23.6 (C-11); 122.4 (C-12); 144.8 (C-13); 42.2 (C-14); 28.2 (C-15); 23.9 (C-16); 46.6 (C-17); 41.9 (C-18); 46.3 (C-19); 30.9 (C-20); 34.1 (C-21); 33.2 (C-22); 66.4 (C-23); 14.3 (C-24); 17.3 (C-25); 17.5 (C-26); 26.1 (C-27); 180.2 (C-28); 33.2 (C-29); 23.7 (C-30). Compound 7: 13C-NMR: δ 47.6 (C-1); 68.8 (C-2); 78.2 (C-3); 43.6 (C-4); 48.2 (C-5); 18.5 (C-6); 32.8 (C-7); 40.0 (C-8); 47.6 (C-9); 38.3 (C-10); 23.6 (C-11); 125.5 (C-12); 139.2 (C-13); 42.2 (C-14); 28.6 (C-15); 24.8 (C-16); 48.0 (C-17); 53.5 (C-18); 39.4 (C-19); 39.3 (C-20); 31.0 (C-21); 37.4 (C-22); 66.4 (C-23); 14.3 (C-24); 17.4* (C-25); 17.4* (C-26); 23.8 (C-27); 180.6 (C-28); 17.3* (C-29); 21.3 (C-30) *interchangeable signals.terature ,17. CompArjunglucoside II (3) and Quadranoside IV (8) as a mixture: colorless amorphous powder; 1H- and 13C-NMR data in accordance with those of an authentic sample and/or with the literature [3: 1H-NMR: δ 4.25* ; 4.28* ; 5.43 ; 3.19 ; 3.72 ; 4.22* ; 1.07 ; 1.10 ; 1.16 ; 0.90 ; 0.88 ; sugar signals: δ 6.33 ; 4.21 ; 4.22-4.46*  *overlapping signals; 13C-NMR: δ 47.6 (C-1); 68.8 (C-2); 78.1 (C-3); 43.5 (C-4); 48.0 (C-5); 18.4 (C-6); 32.7 (C-7); 39.9 (C-8); 47.7 (C-9); 38.3 (C-10); 23.8 (C-11); 122.7 (C-12); 144.0 (C-13); 42.1 (C-14); 28.1 (C-15); 23.2 (C-16); 46.9 (C-17); 41.6 (C-18); 46.0 (C-19); 30.6 (C-20); 33.8 (C-21); 32.4 (C-22); 66.3 (C-23); 14.2 (C-24); 17.5 (C-25); 17.6 (C-26); 25.9 (C-27); 176.4 (C-28); 32.9 (C-29); 23.5 (C-30); sugar signals: δ 95.6 (C-1’); 74.0 (C-2’); 78.8 (C-3’); 71.0 (C-4’); 79.2 (C-5’); 62.1 (C-6’). Compound 8: 1H-NMR: δ 4.25* ; 4.28* ; 5.43 ; 2.52 ; 3.72 ; 4.22* ; 1.07 ; 1.11 ; 1.20 ; 1.10 ; 0.92 ; 0.88 ; sugar signals: δ 6.27 ; 4.21 ; 4.22-4.46*  *overlapping signals; 13C-NMR: δ 47.9 (C-1); 68.8 (C-2); 78.1 (C-3); 43.5 (C-4); 48.1 (C-5); 18.4 (C-6); 33.0 (C-7); 40.1 (C-8); 47.8 (C-9); 38.2 (C-10); 23.7 (C-11); 125.9 (C-12); 138.3 (C-13); 42.4 (C-14); 28.5 (C-15); 24.5 (C-16); 47.7 (C-17); 53.2 (C-18); 39.2 (C-19); 39.0 (C-20); 30.7 (C-21); 36.6 (C-22); 66.3 (C-23); 14.2 (C-24); 17.3 (C-25); 17.5 (C-26); 23.6 (C-27); 176.1 (C-28); 17.2 (C-29); 21.1 (C-30); sugar signals: δ 95.6 (C-1’); 73.9 (C-2’); 78.8 (C-3’); 71.1 (C-4’); 79.1 (C-5’); 62.1 (C-6’).terature ,13,21. CBellericoside (4): colorless amorphous powder; 1H- and 13C-NMR data in accordance with the literature [1H-NMR: δ 4.07 ; 4.30* ; 5.42 ; 3.18 ; 4.24 ; 4.86 ; 3.97 ; 4.61 ; 1.13 ; 1.14 ; 1.16 ; 0.87 ; sugar signals: δ 6.32 ; 4.20 ; 4.25-4.44* ; 4.02  *overlapping signals; 13C-NMR: δ 47.8 (C-1); 69.0 (C-2); 79.7 (C-3); 47.8 (C-4); 48.2 (C-5); 19.2 (C-6); 32.5 (C-7); 40.0 (C-8); 48.3 (C-9); 38.1 (C-10); 23.3 (C-11); 122.7 (C-12); 144.1 (C-13); 42.1 (C-14); 28.1 (C-15); 24.1 (C-16); 46.9 (C-17); 41.7 (C-18); 46.1 (C-19); 30.7 (C-20); 33.7 (C-21); 33.1 (C-22); 64.3 (C-23); 62.8 (C-24); 17.3 (C-25); 17.4 (C-26); 26.0 (C-27); 176.5 (C-28); 33.0 (C-29); 23.6 (C-30).terature . 1H-NMR:Chebuloside II (5): colorless amorphous powder; 1H- and 13C-NMR data in accordance with the literature [1H-NMR: 4.43 ; 4.25 ; 5.10 , 3.17 ; 4.04 ; 4.40 ; 1.74 ; 1.78, 3H, s, H-25; 1.71 ; 1.16 ; 0.86 ; 0.85 ; sugar signals: δ 6.27 ; 4.20 ; 4.28 ; 4.30 ; 4.00 ; 4.40 and 4.45 ; 13C-NMR: δ 50.1 (C-1); 69.0 (C-2); 78.2 (C-3); 44.5 (C-4); 48.7 (C-5); 67.5 (C-6); 41.0 (C-7); 39.4 (C-8); 48.8 (C-9); 38.1 (C-10); 24.0 (C-11); 124.2 (C-12); 143.5 (C-13); 42.7 (C-14); 28.2 (C-15); 23.4 (C-16); 47.0 (C-17); 41.8 (C-18); 46.2 (C-19); 30.7 (C-20); 34.0 (C-21); 32.4 (C-22); 66.1 (C-23); 15.9 (C-24); 18.8 (C-25); 19.0 (C-26); 26.0 (C-27); 176.4 (C-28); 33.0 (C-29); 23.6 (C-30) .terature .1H-NMR: d-glucopyranosyl 2α,3β,6β-trihydroxyolean-12-en-28-oateβ- (6): colorless amorphous powder; 1H- and 13C-NMR data in accordance with the literature [1H-NMR: δ 4.30 ; 3.40 ; 4.82 , 2.50 ; 5.50 ; 3.19 ; 5.54 ; 1.44 ; 1.76 ; 1.71 ; 1.68 ; 1.23 ; 0.92 ; 0.88 ; sugar signals: 6.27 ; 4.18-4.45 ; 4.00 ; 13C-NMR: δ 50.0 (C-1); 68.7 (C-2); 84.0 (C-3); 39.5 (C-4); 57.0 (C-5); 67.5 (C-6); 41.2 (C-7); 40.6 (C-8); 48.6 (C-9); 38.3 (C-10); 23.9 (C-11); 123.2 (C-12); 143.5 (C-13); 42.7 (C-14); 28.1 (C-15); 23.4 (C-16); 46.9 (C-17); 41.7 (C-18); 46.2 (C-19); 30.6 (C-20); 34.0 (C-21); 32.4 (C-22); 29.1 (C-23); 18.5 (C-24); 18.7 (C-25); 19.1 (C-26); 26.0 (C-27); 176.3 (C-28); 33.0 (C-29); 23.5 (C-30); sugar signals: δ 95.7 (C-1’); 74.0 (C-2’); 78.6 (C-3’); 71.1 (C-4’); 79.1 (C-5’); 62.0 (C-6’).terature . 1H-NMR:Bellericoside (4) and d-glucopyranosyl 2α,3β,23,24-tetrahydroxyurs-12-en-28-oateβ- (9) were obtained as a mixture: colorless amorphous powder. Compound (9): 1H-NMR (pyridine-5d): δ 5.45 ; 3.18 ; 4.05 ; 4.30* ; 4.24 ; 4.90 ; 3.95 ; 4.62 ; 1.15 ; 1.19 ; 1.10 ; 0.91 ; 0.87 ; sugar signals: δ 6.30 ; 4.20 ; 4.25-4.44* ; 4.02  *overlapping signals;. 13C-NMR (pyridine-5d): δ 47.4 (C-1), 69.0 (C-2); 79.7 (C-3); 47.8 (C-4); 48.0 (C-5); 19.2 (C-6); 33.5 (C-7); 40.2 (C-8); 48.2 (C-9); 38.0 (C-10); 23.9 (C-11); 125.9 (C-12); 138.4 (C-13); 42.4 (C-14); 28.6 (C-15); 24.6 (C-16); 47.8 (C-17); 53.2 (C-18); 39.3 (C-19); 39.1 (C-20); 30.7 (C-21); 36.7 (C-22); 64.3 (C-23); 62.9 (C-24); 17.3 (C-25); 17.4 (C-26); 23.7 (C-27); 176.2 (C-28); 17.5 (C-29); 21.2 (C-30); sugar signals: δ 95.7 (C-1’); 74.0 (C-2’); 78.8 (C-3’); 71.2 (C-4’); 79.1 (C-5’); 62.3 (C-6’).Betulinic acid (10): colorless amorphous powder; 1H- and 13C-NMR data in accordance with those of an authentic sample and with literature [1H-NMR (pyridine-5d): δ 3.47 ; 3.55 ; 4.78 ; 4.96 ; 1.24, ; 1.02 ; 0.83 ; 1.07*; 1.08* ; 1.80  *interchangeable signals; 13C-NMR (pyridine-5d): δ 39.3 (C-1), 28.3 (C-2); 78.2 (C-3); 39.6 (C-4); 56.0 (C-5); 18.8 (C-6); 34.9 (C-7); 41.2 (C-8); 51.0 (C-9); 37.6 (C-10); 21.3 (C-11); 26.2 (C-12); 38.7 (C-13); 42.9 (C-14); 31.3 (C-15); 32.9 (C-16); 56.7 (C-17); 47.8 (C-18); 49.8 (C-19); 152.5 (C-20); 30.3 (C-21); 37.6 (C-22); 28.7 (C-23); 16.4 (C-24); 16.5 (C-25); 16.5 (C-26); 15.0 (C-27); 178.9 (C-28); 110.0 (C-29); 19.5 (C-30).terature ,17. 1H-NQuadranoside I (11): colorless amorphous powder; 1H- and 13C-NMR data in accordance with the literature [1H-NMR: δ 4.25 ; 3.43 ; 4.81 ; 5.50 ; 4.76 ; 4.90 ; 1.76 ; 1.45 ; 1.58 ; 1.78 ; 1.04 ; sugar signals: 6.42 ; 4.22 ; 4.27 ; 4.35 ; 4.06 ; 4.38-4.45 ; 13C-NMR: δ 50.4 (C-1), 69.0 (C-2); 84.1 (C-3); 40.7 (C-4); 56.6 (C-5); 67.9 (C-6); 42.4 (C-7); 40.7 (C-8); 51.7 (C-9); 38.6 (C-10); 21.4 (C-11); 26.2 (C-12); 37.5 (C-13); 43.0 (C-14); 30.2 (C-15); 32.2 (C-16); 57.0 (C-17); 49.9 (C-18); 47.4 (C-19); 150.9 (C-20); 30.8 (C-21); 36.8 (C-22); 28.8 (C-23); 19.0 (C-24); 19.3 (C-25); 17.0 (C-26); 15.2 (C-27); 174.9 (C-28); 110.0 (C-29); 19.4 (C-30); sugar signals: δ 95.4 (C-1’); 74.3 (C-2’); 78.8 (C-3’); 70.9 (C-4’); 79.3 (C-5’); 62.2 (C-6’).Candida albicans (ATCC 90028), C. krusei (ATCC 6258) and Cryptococcus neoformans (ATCC 32045). The antifungal activities were determined using microbroth dilution assays in 96-well microplates, in duplicate, following the guidelines of the Clinical and Laboratory Standards Institute (CLSI) [The following strains from the American Type Culture Collection (ATCC), Rockville, MD, USA were used for the antifungal evaluations: e (CLSI) . The low


We contrasted the event-related brain potentials (ERPs) to visual narratives depicting an explicit event, an action star, or a “noise” panel of scrambled lines. Both action stars and noise panels evoked large N400s compared to explicit-events (300–500 ms), but action stars and noise panels then differed in their later effects (500–900 ms). Action stars elicited sustained negativities and P600s, which could indicate further interpretive processes and integration of meaning into a mental model, while noise panels evoked late frontal positivities possibly indexing that they were improbable narrative units. Nevertheless, panels following action stars and noise panels both evoked late sustained negativities, implying further inferential processing. Inference in visual narratives thus uses cascading mechanisms resembling those in language processing that differ based on the inferential techniques.Research in verbal and visual narratives has often emphasized backward-looking inferences, where absent information is subsequently inferred. However, comics use conventions like star-shaped “action stars” where a reader  Inference has been a primary focus of studies of discourse  posits that a narrative structure operates in parallel to semantics, where it organizes meaning at a discourse level  implicate similar mechanisms in visual narratives as in language processing Cohn . When enInformation extracted from the visual surface then activates semantic memory to process the meaning of the immediate representation in relation to what came before in the sequence. This process is indexed in ERPs by the N400, a negative deflection that peaks around 400 ms after the onset of a word or image  narratives  and descriptive words (Punch!) in action stars, which were both attenuated compared to anomalous words, suggesting that they were both sufficient as event-cues given the context of the prior visual sequence , third panel (5), fourth panel (13), and fifth panel (40). Action star sequences substituted an action star panel for the explicit Peak panels. Because action star panels can have less visual information than explicit panels, we therefore designed action star panels with a similar degree of visual complexity as our explicit Peak panels. We calculated the “gray value” of all pixels across all explicit Peak panels (M = 213.2) and designed three action star panels with similar values (M = 213.0). These three action star panels were distributed randomly across sequences within the action star sequence types. Our final sequence type then created “noise” panels by selecting subdivisions of action star panels (via a grid and iterated circular pixel selections), and then rotating these subdivisions randomly such that no discernable representational information was conveyed, though the quantity and character of the visual lines remained the same. Action stars were used as the base for noise panels rather than explicit panels in order to ensure they remained asemantic, and also involved similar line segments. Noise panels had a grey value comparable to other critical panels (M = 213.0).From these strips, we created three sequence types, as in Fig. These 60 sequences were counterbalanced into three lists using a Latin Square Design such that participants viewed each sequence only once, but across lists all participants viewed all sequences in all conditions. An additional 96 fillers, half of which contained sequencing discontinuities, were used to introduce additional heterogeneity into the experimental stimuli.F-values above 3.2 for our within-subjects design. All participants gave their informed written consent prior to the experiment and the study was approved by the Tilburg University School of Humanities and Digital Sciences Research Ethics and Data Management Committee. Participants were right-handed, taking no psychiatric medications, with no history of head trauma, and with normal or corrected-to-normal vision. Prior to experimentation, participants filled out the Visual Language Fluency Index (VLFI) questionnaire which assessed their frequency of reading and drawing visual narratives like comics, along with experiencing other media like movies and written books. The VLFI score generated by this assessment has been a consistent predictor of individual differences in visual narrative comprehension . Although statistical power was not computed a priori, a power analysis in G*Power indicated that with 3 conditions in a sample of 24 participants, to achieve a medium effect size of 0.25, it would require The experiment was conducted in a soundproof chamber, where a participant sat in a chair across from a computer screen. Lights in the chamber were turned off, except for backlighting behind the screen used to prevent a flashing effect of stimuli on the screen that could induce blinks. We used PsychoPy2 ?”.EEG was recorded using a Brain Products ActiChamp system at a sampling rate of 250 Hz and high cutoff filter of 70 Hz. EEG recordings were made with 32 channel Standard actiCAPs, referenced online to electrode Fz. Eye movements and blinks were monitored using electrodes placed beneath the right eye and beside the left eye. Electrode impedances for all electrodes were kept below 10 kΩ. We analyzed the data using the ERPLAB plugin for EEGLAB in MATLAB , critical panel position (p = 0.095), or their interaction (p = 0.210).Trials with excessive blink or muscle artifact were isolated and removed. Across conditions at the critical panels, 6% (range 3–8%) of trials were rejected per participant, an average of 1.25 trials . A 3  × 2  ANOVA showed no significant differences in the rejection rates across sequence types . Additional analyses in epochs of 0–100 ms and 100–200 ms investigated the potential for early, stimulus-driven physical differences at the critical panels. A broad coverage of the scalp was examined using five regions of interest which each averaged the amplitudes across four electrodes. As in Figs. Behavioral results were compared using a repeated-measures ANOVA with three levels of Sequence Type , with post hoc tests using a Bonferroni correction. Finally, to investigate any possible influence of comic reading experience, we used Pearson's correlations with an alpha level set to 0.05 between VLFI scores and ratings and the mean amplitude differences averaged across all electrode sites at the critical and subsequent panels.F = 12.54, p < 0.001. Explicit sequences  were rated as more comprehensible than sequences with action stars  or noise panels , all ts > 4, all ps < 0.005, but these latter types did not differ from each other (p = 1). Nevertheless, all sequences were rated as comprehensible on the whole, rated above the midway point of 4 on a 1–7 scale . Finally, in open response post-test questionnaires, 35% of participants commented on observing action stars, while 33% noticed noise panels and that they differed from action stars , including one who drew a noise panel.Analysis of participants’ ratings suggested differences in the sequences’ comprehensibility, Fs < 2.7, all ps > 0.079, all η2p < 0.105). No significant differences arose in the 100–200 ms epoch.We first analyzed ERPs at the critical panels, depicted in Fig. Fs > 7.6, all ps < 0.001, all η2p > 0.25) and in the right posterior region, F = 3.3, p < 0.05, η2p = 0.13. Pairwise comparisons suggested that noise panels evoked greater negativities than both explicit panels and action stars in the central and anterior regions .In the 200–300 ms epoch, a main effect of Sequence Type arose in the central region and interactions in the peripheral regions were found between Sequence Type and Hemisphere. Follow up ANOVAs in each region revealed main effects of Sequence Type in both anterior regions . Across central and anterior regions, pairwise comparisons showed a greater negativity indicative of an N400 appeared to action stars and noise panels than explicit panels , but no difference between action stars and noise panels.In the 300-500 ms epoch, main effects of Sequence Type appeared in both central and peripheral regions. An additional Sequence Type × Hemisphere interaction was followed by analyses revealing main effects in both anterior regions . Pairwise contrasts suggested that action stars evoked a greater negativity than both explicit and noise panels in the left anterior region , and a greater negativity than the noise panels alone in the right anterior region (p < 0.05).Later effects were first suggested in the 500-800 ms epoch by Sequence Type × Hemisphere and Sequence Type × Hemisphere × AP Distribution interactions in the peripheral regions. Main effects of Sequence Type were subsequently found in both anterior regions . Pairwise comparisons in the left anterior region suggested that noise panels evoked a frontal positivity that was close but did not exceed the threshold of significance compared to action stars (p = 0.050) and explicit panels (p = 0.058). In the right posterior region, post-hoc comparisons implicated a greater posterior positivity to action stars than noise panels (p < 0.05), which is more visible in the topographic maps of Fig. Additional differences were suggested in the 800–1100 ms epoch with an interaction between Sequence Type and Hemisphere. Follow up ANOVAs suggested main effects of Sequence Type in the left anterior and right posterior regions  and in the left posterior region of the 800–1100 ms epoch, F = 3.6, p < 0.05, η2p = 0.138. These differences arose because action stars and noise panels evoked a larger rightward posterior negativity than explicit panels , which extended into the left posterior for only noise panels compared to explicit panels (p < 0.05).At the panel following the manipulated, critical panel, no differences occurred between sequence types in the 200–300 ms epoch, but interactions between Sequence Type and Hemisphere appeared in the 300–500, 500–800, and 800–1100 ms epochs (Table r(22) = 0.47, p < 0.05, but when correcting for multiple comparisons this correlation was no longer significant. No significant correlations were found for sequences with action stars or noise panels, nor the differences between them. No significant correlations were observed between VLFI scores and ERP results.The analysis of expertise correlated only marginally with behavioral results. A positive correlation between ratings of explicit sequences and VLFI scores suggested that greater comic reading frequency lead to higher ratings, Inference has been a hallmark of the study of visual narrative processing. Here, we asked about such processing both for representationally impoverished action stars and noise panels and at the subsequent image. Our first apparent finding was that panels omitting information in a sequence elicit a large N400 effect compared to explicit depictions of an event. These N400s were evoked both by the highly conventionalized action stars and the not-conventionalized noise panels. That these inexplicit panels did not differ in amplitude of the N400 implies that they both trigger a greater demand for accessing semantic memory given the absence of overt representations. Under one interpretation, this N400 could indicate inferential processing, accessing the semantic features of the unseen information  when compared to onomatopoetic or event-descriptive words in lieu of explicit events in visual narratives  appear different than those observed at later epochs. In addition, despite differences prior to 300 ms, action stars and noise panels had similar amplitudes and latencies of the N400 on visual inspection, including topologically in its phasic ascent and descent. If such stimulus differences sponsored downstream effects, then these relative differences do not seem consistent across time windows in a sustained way  elicited larger LFPs than onomatopoetic sound effects (Pow!), regardless of congruity  that was greater than both action stars and explicit panels. In research on language, LFPs have been associated with violated lexical or semantic predictions, such as when a particular word is expected in the sentence, but participants are presented with a different, yet congruent word  or less conventional (noise panels) properties of these panels. However, the absence of depicted events in both seemed to sponsor similar attempts to reconcile this missing information. Altogether, these findings provide an initial look at the neurocognition of inference generation across sequential images, further demonstrating that inference must balance the implicit of what is omitted and the explicit of what is provided, even when what is shown remains inexplicit.


Plagiomnium ellipticum and Polytrichum formosum were also documented; proximal parts had higher levels of endopolyploidy than distal parts. Endopolyploidy is spatially and temporally differentiated in the gametophytes of endopolyploid mosses and follows a pattern similar to that seen in angiosperms.Somatic polyploidy or endopolyploidy is common in the plant kingdom; it ensures growth and allows adaptation to the environment. It is present in the majority of plant groups, including mosses. Endopolyploidy had only been previously studied in about 65 moss species, which represents less than 1% of known mosses. We analyzed 11 selected moss species to determine the spatial and temporal distribution of endopolyploidy using flow cytometry to identify patterns in ploidy levels among gametophytes and sporophytes. All of the studied mosses possessed cells with various ploidy levels in gametophytes, and four of six species investigated in sporophytic stage had endopolyploid sporophytes. The proportion of endopolyploid cells varied among organs, parts of gametophytes and sporophytes, and ontogenetic stages. Higher ploidy levels were seen in basal parts of gametophytes and sporophytes than in apical parts. Slight changes in ploidy levels were observed during ontogenesis in cultivated mosses; the youngest  parts of thalli tend to have lower levels of endopolyploidy. Differences between parts of cauloid and phylloids of  Arabidopsis thaliana (L.) Heynh.  Triton X-100, pH 7.0) [−1), propidium iodide (30 μg·mL−1), and with β-mercaptoethanol (2 μL·mL−1) as described in Goga et al. [P. undulatum, E. striatum), there is a small risk of misinterpreting the 2C peak as the 1C peak on FCM records.Samples for flow cytometry (FCM) were prepared according to a standard method by chopping plant material in 1 mL of general purpose buffer (0.5 mmol·L pH 7.0)  in a Pet pH 7.0) ,57. Aftea et al. . Samplesa et al. . The peaa et al.  and reprBased on the number of nuclei of the individual peaks of the FCM histograms, the endoreduplication index  of each gametophyte (reduced haploid phase) was calculated according to the following formula ,60: EI =1C, n2C, n4C, n8C, n16C… represents the number of nuclei of the respective ploidy levels. Tissues with an EI higher than 0.1 are considered endopolyploid [Since the sporophyte represents an unreduced diploid phase, the EI was calculated according to the formula:P. patens and P. drummondii). A two-way ANOVA test was used to analyze the spatial distribution of endopolyploidy in organs (study of P. ellipticum and P. formosum). Plots were visualized in ggplot2 ver. 2.2.1 [Results were evaluated in the statistical software R, version 3.6.1 . To testr. 2.2.1 .Atrichum undulatum, Brachythecium rivulare, Bryum moravicum, Dicranum scoparium, Eurhynchium striatum, Physcomitrella patens (laboratory culture), Plagiomnium ellipticum, Plagiomnium undulatum, Pohlia drummondii (laboratory culture), Polytrichastrum alpinum, and Polytrichum formosum. All the studied mosses had 1C, 2C, and 4C nuclei present in the gametophyte, except P. patens  values for gametophytes were recorded in B. rivulare , while the highest values were recorded in P. ellipticum   . It is w compare .A. undulatum, B. rivulare, B. moravicum, D. scoparium, P. alpinum and P. formosum) had developed sporophytes. In all cases, sporophytes had lower levels of endopolyploidy compared to gametophytes. Mostly 2C, 4C and 8C nuclei were represented in the analyzed sporophytes, with 8C nuclei absent only in the sporophytes of A. undulatum  to the highest values in D. scoparium   .P. formosum, A. undulatum and B. moravicum, and EI values were lower in sporophytes compared to gametophytes in these cases  were statistically significant between gametophytic and sporophytic tissues (whichever parts are considered) in se cases B.P. ellipticum and P. formosum, the later collected from locality near Kamenica  in all the species investigated except Kamenica B. In conB. rivulare, E. striatum, A. undulatum or P. drummondii, had cells of one dominant ploidy level; this could be 1C or 2C in gametophyte or 2C in sporophyte. Other endopolyploid cells were found often only at quite low levels. Other species, including P. formosum, P. unudulatum, D. scoparium or P. patens, showed a pattern of almost continuous increase or decrease of nuclei counts in subsequent ploidy classes. This resulted into almost equal proportions of two or three nuclei classes, as in case of P. formosum.To generalize our results, two within-tissue ploidy level distribution patterns were observed. Some species, such as P. formosum represented here by two spatially and timely different samples. While individuals lacking sporophytes collected in Milpoš (in 2018) were variable in three gametophytic parts, those with sporophytes and collected in Kamenica (in 2020) were not. This result points to the possibility that site or seasonal differentiation, genotype or population differentiation, or possibly sexual differentiation, may shape overall plant endopolyploidy level.Interestingly, we have found variable EI pattern in P. patens and P. drummondii were grown under laboratory conditions and were compared at three stages of development. In P. patens, 8C nuclei were observed in all parts of the moss (and stages) except for the apical portion developed in the third stage. In P. drummondii, 8C nuclei were recorded only in first stage of plants and the basal part of plants in both the second and third stages. In the other samples, the highest ploidy level was 4C. Generally, P. patens showed slightly higher EI values.To analyze changes in endopolyploidy in relation to organ or tissue age, P. patens in the first stage of analysis, and 2C nuclei were present in smaller proportions. Only a few dozen of 4C nuclei were detected (p < 0.05) but not for middle part of gametophyte  (The proportion of 1C nuclei was high in detected . Similardetected A. Statis > 0.05) .p < 0.001), but not for middle part of gametophyte   .P. formosum and P. ellipticum, were used to analyze the distribution of endopolyploidy within the cauloids and phylloids originating from different parts of the gametophyte. Both species had relatively high levels of endopolyploidization, with 1C to 8C nuclei present in their gametophytes. In the gametophytes of P. ellipticum, 16C cells were also represented in the basal and middle parts of the cauloids. In general, the degree of endopolyploidization in the cauloid and phylloids of both species decreased from base to apex. Plagiomnium ellipticum had a higher endopolyploidy level in both the cauloids and phylloids compared to P. formosum.Two mosses, In all three parts of gametophytes of P. formosum, 1C to 8C cells were represented irrespective of organ, cauloid or phylloids. These four cell categories were also present in the analyzed parts of all phylloids, except in the apical portion of the middle and apical phylloids of the gametophytes. Only three peaks were observed in these sections; the fourth peak, representing 8C nuclei, was absent. Most of the basal parts of the cauloids were composed of 4C nuclei; 2C and 8C nuclei were present in smaller amounts, and 1C cells were least abundant. 4C cells again dominated in the middle part of the cauloid, but the number of 1C nuclei dominated in the cauloid base .p < 0.001) and among organ parts   = 23.3; p < 0.001) were statisticaly significant, but interaction between them was not  = 0.8; p > 0.05). A Tukey post hoc test revealed significant pairwise differences between cauloid and all three types of phylloids, showing 1.17 up to 1.20 higher EI values, and between the basal and both the middle (- 0.23 EI) and apical parts of organs (- 0.35 EI).In phylloids, the 1C nuclei were most abundant, regardless of which part of the moss from which the phylloid was sampled. Within individual phylloids, a trend of decreasing ploidy level from base to apex was observed. While the number of 1C nuclei increased, there was a decrease in the number of 8C nuclei A, which P. ellipticum, five peaks in cauloids and three to four peaks in phylloids were detected by FCM. In addition to 1C, 2C, 4C, and 8C nuclei, 16C nuclei were observed throughout the cauloid except in the apical part  were not statisticaly significant, while differences among organ parts   = 38.1; p < 0.001) were. Interaction between them was not statisticaly significant  = 1.0; p > 0.05). A Tukey post hoc test revealed significant pairwise differences between the apical part of organs and both basal and middle portions .This species had relatively high EI values and similar pattern of variation for both cauloid and phylloids. Within these organs, endopolyploidy decreased from the basal and middle parts to the apical parts . DifferePhyscomitrella patens [Endopolyploidy, or increased ploidy in somatic cells beyond inherited organism ploidy level, is widespread in some plant groups, e.g., mosses and angiosperms, and has been reported to have various effects from the cellular to whole organism level. Recent studies have primarily focused on the study of endopolyploidy in higher plants or the model moss a patens ,63. To da patens ). TherefLevels of endopolyploidy vary depending on different factors, including the type of tissue or organ ,6. In anGametophytes are established in the life cycle of mosses before sporophytes ; therefoPlagiomnium ellipticum and Polytrichum formosum. While the part of the moss thallus from which organs were removed was always significant, the differentiation in EI between organs  was documented only in P. formosum. The variability of endopolyploidization is specific to each species. For instance, in P. formosum we have observed that the cauloid has much higher EI values compared to the phylloids from any location on the gametophyte. In contrast, P. ellipticum did not show this pattern of differentiation. It is necessary to analyze more moss species to generalize trends in endopolyploidy patterns, particularly in organs and their positions on moss thalli. Cytohistological techniques coupled with confocal microscopy may be beneficial.Divergences in eventual endopolyploidy levels were observed in individual organs and parts of sporophytes and gametophytes in the present study. Endopolyploidization in apical parts of gametophytes and sporophytes was lower than in basal parts and tended to decrease along these organs from base to apex. Although the effect of interaction between factors on endopolyploidy in different parts of moss organs (organ vs. part of an organ) was investigated in the present study, the results cannot be generalized yet. This topic was investigated in two different species, Physcomitrella patens, P. drummondii, B. moravicum, and P. ellipticum were characterized by replication of the whole genome in most cells in the gametophytes in the present study. In several samples, the first 1C peak was represented by very few or no nuclei, which may results into misinterpretation of FCM records [B. moravicum, which had developed sporophytes at the time of analysis, the dominant and often the first peak in gametophytes was identified as a 2C peak. This suggests that 1C cells may often be absent in the gametophytes of some moss species. This is very interesting because it suggests that almost all gametophyte cells may harbor a completely reduplicated genome. However, here we consider an alternative explanation of reduplicated genome. Endopolyploidy in mosses is poorly explored so far. Most data come from studies on the model moss P. patens. This species is characterized by a specific, tissue-dependent cell cycle. The protonema of this moss consists of two types of tissues, caulonema and chloronema, but only the latter form in young individuals. Most chloronema cells undergo DNA synthesis during the S phase of the cell cycle early after mitosis and are usually found “timely arrested” just before transition from G2 phase to M phase. Therefore, screening for nuclei ploidy levels in this moss revealed mostly 2C nuclei [1 and the S phase, the proportion of 1C nuclei is shown to increase in tissue FCM cytotyping. Later, as the cells of the caulonema age, DNA endoreduplication can be detected [2/M phase). Indeed, Bainard et al. [2/M arrest of the cell cycle may lead to misinterpretation of FCM data in genome size estimation. Although Bainard et al. [2/M phase. More detailed, future studies are needed to investigate this phenomenon in relation to endopolyploidy of mosses and further if the G2/M phase arrest of cells is ploidy-dependent. records ,46. In tC nuclei . Gradualdetected , confirmChenopodium quinoa Willd. [Trifolium pratense L. [Beta vulgaris L. [As in various organs and tissues, endopolyploidy changes during ontogenesis in an individual. Endoreduplication in cells can continue until maturation  and thera Willd. , Trifolitense L. , and Betgaris L. . P. drummondii and P. patens, a decrease in endopolyploidy from the base to the apex of gametophytes was demonstrated. In both species, higher ploidy levels were recorded in ontogenetically older parts of the thalli. The same patterns have been observed in higher plants [P. patens) of gametophytes may be alternatively the result of faster thalli growth via increasing cell division leading to the detection of a higher proportion of cells entering the M phase compared to other stages. The observed inconsistent patterns of endopolyploidy variation in the part of a gametophyte during ontogenesis found in two selected species invites further in-depth analysis of ontogenetic patterns in several mosses, preferably those with a large thallus.This phenomenon occurs not only in higher plants, but also in mosses, as documented in the present study. As exemplified by r plants ,57. A hiB. moravicum, P. patens, P. ellipticum, and P. drummondii). Nuclei that were in the baseline 1C state were of minimal proportions compared to those in the endopolyploid states.There were statistically significant differences in the levels of endopolyploidy between different parts of gametophytes and sporophytes in the studied mosses. In general, we observed higher degrees of endopolyploidization in gametophytes than in sporophytes. Based on the present study of 11 moss species, the level of endopolyploidy tends to be higher in basal parts of mosses than in apical parts. Also, endopolyploidy tends to decrease from basal to apical parts of the cauloids and phylloids. In addition, during analysis of endopolyploidy in selected moss species, it was found that some species replicated nearly all  of the nuclear DNA content in gametophyte cells (Research on endopolyploidy has so far been directed toward higher plants, although endopolyploidy is present in several moss species. As such, this group of plants is promising in terms of research on endopolyploidy as a part of adaptation to stress in plants or on the evolutionary patterns of endopolyploidy. Recent reports that endopolyploidy is common in mosses and in moss thalli and organs (, presentThe present study shows that certain cytological features associated with thalli development in mosses have just started to be explored, and that further elucidation of these features may help to better understand moss biology and evolution. Mosses are resilient and ubiquitous organisms and play an important role in several ecosystem processes, including net primary productivity, decomposition rates, above-ground microclimate modifications, and carbon and nutrient cycling . Bryophy