This systematic review aimed to collect the relevant historical and current literature to produce an informed analysis of the acute effects on cardiorespiratory and haematological factors following whole blood donation (~ 470 ml) during exercise. Testing the hypothesises that blood donation produces either no changes (Null) or produces significant changes  in haematology, Four databases of medical and science orientations were searched with terms sensitive to connections regarding exercise, blood donation (400–500 ml)/haematology, -1∙min-1) and a medium effect size (-0.26). No statistical significance was present at the mean meta-analysis level, also the case for heart rate, time to exhaustion and power. A mean reduction was seen in haemoglobin (- 1.05 g.dL-1), haematocrit (- 3.71%) and red blood cells (- 0.44 Mio μL-1), very large effect size was observed  and statistical significance .Following scrutiny of 48 research papers by two independent assessors 8 experimental studies were included. Four studies showed a mean reduction for difference in Although individual studies show that  Currently in the UK ~ 470 ml of blood is collected from donating a single unit  with bloA number of confounding reasons have been attributed to the progressive decline in new blood donors, including an increase in exotic holidays and tattoos ,4 both oThere are consequences to BD such as decrements in blood/plasma volume (B/PV) and haemoglobin (Hb). While the BV returns to normal within 24–48 hours , due tomax) [Ex) [2 content >99% of O2 is transported by Hb [The biological responses to acute BD are well documented, indeed early work from Karpovich and Millman  highlighporaries  showed at (Wmax)  and timeax) [Ex) ,19,20. Ted by Hb .Currently the Cochrane Database regarding systematic review  shows noThe systematic review was carried out from guidance of Systematic Reviews  and by uFrom the beginning of December 2016 to the end of January 2018, Pubmed, Web of Science, SPORTDiscus and Scopus were used to obtain literature from the early 1900’s to January 2018, due to the databases being medical and science orientated. Search terms were created in order to be sensitive to all possible connections regarding exercise, blood donation/haematology, l et al. ) were Pu"blood donation” OR "blood collection" OR "blood withdrawal" OR "blood centre" OR "Blood center" OR "blood service" OR "blood bank" OR "blood transfusion" OR "phlebotom*" OR "plasma don*” OR “blood volume” OR “blood donor*”"sport" OR "exercise" OR "physical endurance" OR "hiking" OR "cycling" OR "athletic" OR "training" OR "working out" OR "work out" OR "strenuous activity" OR “VO2max” OR “maximal aerobic power” OR “Oxygen carrying capacity”“men” OR “man” OR “male” OR “sportsman” OR “sportsmen” OR “woman” OR “women” OR “female” OR “sportswomen” OR “Sportswoman” OR “athlete” OR “adult” OR “healthy” OR “humans” OR “people” OR “fit”Restricting the publications to English and using the Population, Interventions, Comparators, Outcomes and Study designs (PICOS) strategy enabled studies to be selected accordingly . Studies that were accessible as conference abstracts were excluded, as were blood expansion studies, studies assessing muscular strength and studies involving participants > 66 years and < 17 years in age. The age range selected was according to blood transfusion services in the UK .The final studies selected for the systematic review were rated with an adapted scoring method  accordinTo ensure that the studies selected were of good quality, two assessors (DJ and DG) individually assessed the texts for eligibility according to the exclusion and inclusion criteria and additionally according to the previously mentioned COSMIN threshold.Using the spreadsheet software package Microsoft Excel, Microsoft Corp, Washington, USA (2011) a database was formed with the haematological and cardiorespiratory/respiratory variables extracted from the evaluated studies for analysis.2max, maximum heart rate (MaxHR), maximum aerobic power output and time to exhaustion were all considered for inclusion in the systematic review, since they were the most widely reported variables relating to haematological and cardio-vascular responses and regarded according to their mean and standard deviation pre and post donation results. The post donation values were classified according to time frames, which included immediately, 2 hrs, 24–48 hrs, 48–72 hrs, 7 days, 14 days, 21 days and 28 days. However, for the purpose of this evaluation the systematic review focused on 24–48 hrs for two reasons. Firstly, the time period had sufficient data to analyse and secondly the time period is closest to being straight after donation and suggested by the NHS [The variables of Hb, haematocrit (Hct), RBC’s, VO the NHS  and Amer the NHS  to be ap the NHS  suggest d and 95% confidence intervals were calculated for each study. Cohens d (standardized difference in means) is expressed as the difference between two (raw) means divided by the pooled standard deviation (SD) of the groups (M1 –M2 / SD) [d are evaluated as, very large > 1.3, 0.8–1.3 (large), 0.5–0.8 (medium), < 0.2–0.5 . The mean Cohens d value was calculated by individual studies being weighted by the variance of the data, thus expressed as Cohens M2 / SD) . Effect Siwi)Σwi  or MeanCI2 = 0%) of the main variable (VO2max) was assessed, and a Limits of Agreement plot showed that the two assessors were considered to be in agreement , 8 studies were deemed suitable for inclusion in the systematic review following the COSMIN check, with the publication dates of those included ranging from 1997–2016 as highlighted in All 8 studies included were experimental in nature, incorporating a before and after blood donation approach, with only the Meurrens, et al.  study usThe majority of the participants were male (91%) and the mean age of all who took part was 23.9 ± 1.5 with a mean height of 179.2 ± 3.4 cm and a mean mass of 76.4 ± 5.9 Kg.The exercise mode for all studies was cycle ergometer, with a protocol that induced exhaustion and thus , et al.  and Krip, et al. , which wGordon, et al.  has subm, et al.  study.-1∙min-1 (-1∙min-1). With values ranging from 40 ± 4.0 [-1∙min-1 [The participants athletic descriptions  included-1∙min-1  (when co40 ± 4.0  to 64.1 -1∙min-1 .-1∙min-1), with a small effect size, -0.26  and confidence intervals of -1.97 to -0.03. Of the remaining studies all had small Cohen’s d effect sizes, but no statistical significance.e, -0.26 . No statd effects across all research too . No statistical significance is present at the mean meta-analysis level due to the 95% CI passing through 0 .TEx pre and post donation evidence was recorded from five studies , which aporaries  study TEmax pre (329.7 ± 42.4) and post (329.5 ± 45.7) donation evidence could only be gathered from one study [Wne study  and the .dL-1) across four relevant studies, with a medium effect size produced . No statistical significance is present at the mean meta-analysis level due to the 95% CI passing through 0 . Gordon, et al. [d effects were moderate to high across all the studies. Burnley, et al. [Hb pre and post donation evidence was recorded from five studies , across , et al.  showed a, et al. , Gordon,, et al.  and Hill, et al.  were notd, -1.16). Statistical significance is not present at the mean meta-analysis level due to the 95% CI passing through 0 . All studies show large effect sizes and statistical significance.Hct pre and post donation evidence was recorded from four studies . Across -1) and a very large mean effect size . Statistical significance is present at the mean meta-analysis level due to the 95% CI being placed notably to the left of 0 . All studies show large to very large effect sizes and statistical significance.RBC’s pre and post donation evidence was recorded from three studies . Across 0) or produces significant changes (H1) in haematology, d ± 95% confidence intervals appears to accept the Null hypothesis, as the line passes through “0” and thus is not statistically significant; this is also the case for HR, TEx and Wmax. For the blood variables the alternate hypothesis is accepted only for RBC’s, rejecting the Null hypothesis, as the mean Cohen’s d ± 95% confidence intervals favour donation.Based on the hypothesis stated that blood donation produces either no changes  RBC’s, Hct and Hb values were significantly reduced. Where data allowed there were three studies ,18,32 inO2/100mL . This wocreasing ,19,20. T-1 for 18–60 yrs and 30 ml.kg-1 for over 60 yrs [One issue worth noting is that only one study  controllr 60 yrs . Therefor 60 yrs  and muscr 60 yrs  particulp < 0.01) before the second donation, and a value of 41 ± 5 μg/l (p < 0.001) was observed prior to the third donation, It is not known in some of the studies if the participants are new or regular donors, iron status according to ferritin levels could aid in indicating normal levels ). This might be important to help provide insight on differing results between studies.Although in many of these studies Hb, Hct and RBC’s were the considered blood variables only two studies ,34 consiFurther consideration when comparing studies should be given to the heterogeneous mix of participants, for example a study declares the participants to be trained athletes , but faiing ACSM  guidelining ACSM  study reing ACSM  and assoThe only study in this systematic review to use a randomized controlled trial (sham bleed) was that of Meurrens and colleagues  and hencd, -1.93 for VO2max and -6.01 for Hb., if they were included in the meta-analysis.Further analysis showed that with the exception of HR, Meurrens and associates  would haHowever, the pooling of robust high quality randomized controlled studies with lower quality uncontrolled designs is not recommended and would possibly lead to type I errors.In summary, it is clear from this systematic review that there are not enough high-quality papers to draw any definitive conclusions, regarding cardiorespiratory outcomes following BD. Although we have an understanding from individual study results of the raw data that S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOC)Click here for additional data file.


Bubalus bubalis) makes a major contribution to the global agricultural economy in the form of milk, meat, hides, and draught power. The global water buffalo population is predominantly found in Asia, and per head of population more people depend upon the buffalo than on any other livestock species. Despite its agricultural importance, there are comparatively fewer genomic and transcriptomic resources available for buffalo than for other livestock species. We have generated a large-scale gene expression atlas covering multiple tissue and cell types from all major organ systems collected from three breeds of riverine water buffalo  and used the network analysis tool Graphia Professional to identify clusters of genes with similar expression profiles. Alongside similar data, we and others have generated for ruminants as part of the Functional Annotation of Animal Genomes Consortium; this comprehensive transcriptome supports functional annotation and comparative analysis of the water buffalo genome.The domestic water buffalo ( Bubalus bubalis) has a world population of approximately 200 millionThe domestic water buffalo . We generated over 21 billion raw sequence reads which mapped to 18,730 unique genes. The dataset was used to support annotation of transcribed sequences in the new buffalo genome assembly . Here, wEthics approval was obtained from The Roslin Institute’s and the University of Edinburgh’s Protocols and Ethics Committees. All animal work was carried out under the regulations of the Animals (Scientific Procedures) Act 1986.® or snap frozen in liquid nitrogen. Bone marrow, alveolar lavage, and peripheral blood mononuclear cells (PBMCs) were collected and cryopreserved at −155°C for subsequent culture and RNA extraction. Viable cell counts were performed using Trypan blue (Gibco). All cell viabilities were >90%. Bone marrow was flushed from the posterior ribs with RPMI-1640 containing 5 mM EDTA, filtered through a 100-µm cell strainer (Corning) then pelleted by centrifugation (400 × g for 5 min). Red blood cells were removed by lysis for 5 min at room temperature in RBC lysis buffer (BioLegend) then washed in phosphate buffered saline (PBS). Alveolar lavage was performed by removing the lungs and trachea, then flushing the lungs with PBS through an endotracheal tube. The lavage was then filtered through a 100-µm cell strainer (Corning) then pelleted by centrifugation (400 × g for 10 min). Alveolar macrophages were isolated from alveolar lavages by culturing them overnight in complete medium  supplemented with 104 U/ml rhCSF1 at 106 cells/ml in six-well plates. The following day, non-adherent cells were removed with the media, and remaining alveolar macrophages were collected in TRIzol (Ambion). PBMCs were isolated from whole blood by centrifuging at 1,200 × g for 15 min (no brake) to obtain buffy coats. The buffy coat was then diluted in an equal volume of PBS + 2% FCS then layered over Lymphoprep (Axis-Shield) and centrifuged at 1,200 × g for 25 min (no brake). The mononuclear cell fraction was collected and washed in PBS, then red blood cells removed by lysis as detailed above. Bone marrow-derived macrophages (BMDMs) and monocyte-derived macrophages (MDMs) were obtained by culturing bone marrow cells or PBMCs, respectively, at 106 cells/ml on sterile bacteriological plastic in the presence of recombinant human colony-stimulating factor  for 10–11 days. To capture inducible innate immune effector genes, BMDMs were stimulated with 100 ng/ml lipopolysaccharide (LPS) derived from Salmonella enterica serotype Minnesota . Tissues from the major organ systems were dissected into small pieces (100 mg) and collected into RNAlaterTotal RNA was isolated from 220 tissue and cell samples  and mRNA library preparation . Briefly, ribosomal RNA (rRNA) was depleted from samples for total RNA-Seq, using biotinylated, target-specific oligonucleotides with Ribo-Zero rRNA removal beads. Following purification, the RNA was fragmented and first-strand cDNA synthesis performed. The RNA template was then removed, and a replacement strand was synthesized incorporating dUTP in place of dTTP to generate double-stranded (ds) cDNA. The incorporation of dUTP quenches the second strand during the subsequent PCR amplification step as the polymerase will not incorporate past this nucleotide. The ds cDNA was purified; then, the 3’ ends adenylated, and indexing adapters ligated to both ends before PCR enrichment of the library. For the TruSeq Stranded mRNA libraries, poly-A-containing mRNA was purified from total RNA using poly-T oligos attached to magnetic beads. From this point, the mRNA library protocol did not differ from the protocol for total RNA library preparation. The libraries were quality controlled using an Agilent Bioanalyzer DNA 1000 Chip and quantified by qPCR before hybridization onto a flow cell. TruSeq Stranded total RNA-Seq and mRNA-Seq libraries were sequenced using an Illumina HiSeq 2500 sequencer at depths of >100 million and >25 million 125-bp paired-end reads per sample, respectively.The sequence data for the buffalo atlas were processed using two different methods, one alignment-free and one alignment-based, as described in Using both methods together, we progressively revised the Kallisto index and updated expression-level estimates accordingly. This iterative “multi-pass” approach to Kallisto has been described previously  and usedB. bubalis assembly UMD_CASPUR_WB_2.0 . To aid in the presentation of findings, standardized placeholder IDs were—if unavailable—assigned to each gene, transcript, and exon model. These IDs are assigned arbitrarily and are of the form geneX, rnaY, and exonZ, respectively, where X, Y, and Z are numeric. IDs are available via the University of Edinburgh DataShare portal (http://dx.doi.org/10.7488/ds/2292).For the “first pass,” we ran Kallisto on all samples, using as its index the complete set of 45,402 predicted transcripts for the draft de novo into putative transcripts. Transcripts were retained only if they showed coding potential  transcription  and consp ≤ 1e-25  for every exon, the longest ORF is on the same strand; b) the last ORF terminates in a stop codon, rather than simply because the ORF remains open until the end of the exon; c) although the ORF of every internal exon does not have to span the entire exon length (because there may be noise in the placement of the exon/intron boundary), no internal ORF contains a stop codon ; and d) the peptide, concatenated from the set of translated ORFs, is ≥50 amino acids in length. These peptides were then aligned against the NCBI non-redundant (nr) peptide database v77  using bl ≤ 1e-25 .Bison (bison), Bos , Camelus (camel), Capra (goat), Ovis , Pantholops (antelope), or Vicugna  sources are listed in http://hdl.handle.net/10283/3356).Conservative criteria were applied to parse these alignments. For a novel transcript model to be retained, ≥ 5 alignments were required, at least one of which is to a gene model from a ruminant genus [Using this “third pass” index, on average 60–70% of the known buffalo (UMD_CASPUR_WB_2.0) protein-coding genes were detectably expressed  in all tissues  under accession number PRJEB4351. These data were generated to provide reference RNA-Seq data as part of the International Water Buffalo Genome Project . The datExpress3D; r ≥ 0.80, a gene-to-gene network graph was constructed connecting 15,752 nodes (genes) with 1,851,403 edges (correlations between nodes). The Markov cluster algorithm (MCL) (Expression data were represented as average transcripts per million (TPM) per gene per tissue. To visualize the data, we used the network analysis tool Graphia Professionalhm (MCL)  was usedhm (MCL) . Clusterhm (MCL) .https://www.ebi.ac.uk/biosamples/samples/SAMEG326824). RNA-Sequencing data were deposited in the European Nucleotide Archive (ENA)https://www.ebi.ac.uk/ena/data/view/PRJEB25226). All experimental protocols are available on the FAANG consortium websitehttp://ftp.faang.ebi.ac.uk/ftp/protocols.Sample metadata for all tissue and cell samples, prepared in accordance with Functional Annotation of Animal Genomes (FAANG) Consortium metadata standards , were deThe complete “third pass” expression atlas, including samples derived from , is avaiThe core of this dataset was derived from four 6-month old Mediterranean buffalo. From these animals, we collected tissues from all major organ systems and, wherever possible, collected biological replicates from each sex. These tissue samples were supplemented with immune cells from two additional animals of the same breed. Collectively, the Mediterranean buffalo contributed 164 samples to the atlas. We also collected the same set of tissues from our Indian buffalo cohorts which, due to restricted availability, were older (5–7 years old). Biological replicates  were collected where possible. The Indian animals contributed 56 samples to the atlas. A number of immune cell types were sampled, including different subsets of macrophages and their progenitors . Previous projects in several species have indicated that macrophages are a rich source of novel mRNAs . A complTwo types of library were generated to capture the expression of the largest diversity of RNA species possible, ribo-depleted total RNA, and (polyA) mRNA. These two library types were sequenced at different depths: total RNA at >100 million paired-end read depth and mRNA at >25 million paired-end read depth, generating approximately 21 billion raw reads in total.We selected a wide range of tissues for the atlas to obtain the largest diversity of transcripts possible, in addition to integrating 30 RNA-Seq libraries from a previous study . As we have done for atlas projects on other species  and partial correlation and information theory (PCIT) have been used by others to perform gene co-expression analysis in livestock species . We have species , the corp = 6.39 × 10−22), “regulation of RNA metabolic processes” , and “regulation of gene expression”  (AGO2), the catalytic component of the RNA-induced silencing complex (RISC), and casein kinase 1 alpha 1 (CSNK1A1), the inhibitory kinase of AGO2. CSNK1A1 initiates the AGO2 phosphorylation cycle, required to enhance the specificity of miRNAs for their target (The content of the top 50 clusters is summarized in × 10−18) Table 1.r target .p = 6.67 × 10−29) and cilium assembly (p = 9.07 × 10−29) (cluster 2), male gamete generation (p = 7.50 × 10−14) and spermatogenesis (p = 7.50 × 10−14) (cluster 4), nervous system development (p = 2.50 × 10−20) and generation of neurons (p = 2.82 × 10−17) (cluster 5), and muscle structure development (p = 4.59 × 10−8) and regulation of heart contraction (p = 1.19 × 10−6) (cluster 12).Most of the smaller clusters contained genes whose expression was restricted to an organ system. Some clusters were specific to a single tissue or cell type, while others were clearly associated with a biological or cellular process. In many cases, the likely function of genes within any of the clusters can be inferred from their cell type enrichment or the known function of well-annotated genes within the clusters. These include organ system and tissue-specific clusters for genes expressed predominantly in the brain , heart (clusters 12 and 66), and reproductive system . More specifically, certain clusters were enriched for the biological process GO terms of cilium organization . Variation in other tissues may result from sex-specific effects, phase of oestrus cycle in the females, different husbandry , and other factors. These differences could be explored further with a larger set of replicates. Nevertheless, in this analysis, clear, logical associations of gene expression patterns were found in spite of some differences between replicates, as presented below.p = 2.12 × 10−11), “regulation of cytokine production” (p = 2.60 × 10−11), and “positive regulation of defense response” (p = 1.63 × 10−10). Genes in this cluster include those encoding pro-inflammatory cytokines IL1A, IL1B, IL6, and IL8 and toll-like receptors TLR2 and TLR4 and the arginine metabolizing enzymes arginase (ARG2) and nitric oxide synthase (NOS2). The expression of ARG2 and NOS2 differs in buffalo macrophages from human, mouse, pig, and sheep and is more similar to cattle gene expression as previously described , “regulation of immune system process” (p = 6.67 × 10−5), and “collagen metabolic process” (p = 1.20 × 10−3).We sampled several immune tissue and cell populations to identify genes that might be associated with disease resistance and resilience traits. We identified two main macrophage clusters (clusters 19 and 20) from the atlas data, each enriched for a particular macrophage subset. Genes in cluster 19 showed the highest expression levels in alveolar macrophages (AM) with many of the genes encoding well characterized macrophage-specific proteins. Genes in this cluster were enriched for GO terms including “immune system process” (escribed . A separig atlas . In sheen in AMs . Genes ip = 6.87 × 10−5), “porphyrin-containing compound metabolic process” (p = 9.05 × 10−5), and “tetrapyrrole metabolic process” (p = 9.17 × 10−5). Genes in this cluster include those encoding some of the key red blood cell transcription factors, GATA1, GFI1B, and KLF1. Genes for members of the heme biosynthesis pathway were also expressed in this cluster, including ALAS2, FECH, HMBS, UROD, and UROS. In addition, the solute carrier genes SLC4A1 and SLCO4C1 were predominantly expressed in buffalo bone marrow cells. By inference, many of the genes within these clusters that currently lack a functional annotation are likely to have an immune function.Cluster 23 contains genes with expression peaks in bone marrow and spleen and both LPS-stimulated and unstimulated BMDMs. Biological process GO terms enriched in this cluster include “protoporphyrinogen IX metabolic process” , “mitotic cell cycle” (p = 1.80 × 10−44), and “cell cycle process” (p = 5.60 × 10−42). These genes cluster together because they have higher expression in tissues with a relatively high proliferative index, such as the small intestine, Peyer’s patches, and the bone marrow.Cluster 10 was enriched for genes with GO terms including “cell cycle” (n = 44) were common to both buffalo and sheep clusters. Of the remaining genes, 47 were only present in buffalo cluster 21, and 111 genes were only present in sheep cluster 13. Genes shared by both species include the keratin genes KRT5, KRT15, KRT23, KRT78, and KRT80 and the peptidoglycan recognition protein genes PGLYRP3 and PGLYRP4. Expression of these peptidoglycan receptor proteins has previously been described in the GI tract of other mammals such as mice, humans, and pigs , “regulation of microvillus organization” (p = 1.02 × 10−2), and “regulation of cell projection size” (p = 1.45 × 10−2). This cluster includes genes expressed in the crypt-villus axis of the small intestine, such as BMP5, ATOH1, and VIL1, along with the mucin-encoding genes MUC3A and MUC12.Cluster 26 was enriched for genes expressed in the small and large intestines, although with highest expression in the former. Genes expressed in this cluster are enriched for the GO terms “brush border assembly”  from large gene expression atlas projects has added a further layer of complexity to the genome and regulation of gene expression. The ENCODE project has annotated approximately 16,000 lncRNAs in the human genome. More recently, lncRNAs have been annotated in livestock and large animal species such as sheep, goat, cattle, pig, and horse . We deted cattle . ExpressMost of the lncRNA clusters were tissue- or organ system–specific. The largest lncRNA cluster (cluster 1) showed co-expression of lncRNAs in a single buffalo embryo and embryo pool. lncRNA cluster 6, a relatively small cluster containing only 39 lncRNAs, also showed co-expression in the embryo, along with the occipital lobe and longitudinal dorsal muscle. This expression pattern reflects the involvement of lncRNAs in the regulation of gene expression during development  Act 1986.RY, LL, SG, SK, AA and DH contributed conception and design of the study; SB performed data analysis and curation; RY, LL, AJ, SS, SJ, VD, ZL, DI, KS, JW and DH collected the samples. LL, RY, AJ, SS, SJ and VD performed the experiments. RY, LL, SB and DH analysed the results. DH, AA, SK and SG secured funding and supervised the project. RY wrote the first draft of the manuscript; LL, SB and DH wrote sections of the manuscript. All authors contributed to manuscript revision, read and approved the submitted version.http://www.bbsrc.ac.uk) and Indian Department of Biotechnology Grant BB/L004623/1 , also BBSRC Institute Strategic Program Grants: BBS/E/D/20211550 , BBS/E/D/20211552  and BB/P013732/1 . Edinburgh Genomics is partly supported through core grants from BBSRC (BB/J004243/1), NERC (http://www.nerc.ac.uk) (R8/H10/56) and the Medical Research Council (MRC) (https://www.mrc.ac.uk) (MR/K001744/1). KMS and DAH receive funding form the Mater Foundation, Brisbane, Australia.This work was supported by a joint Biotechnology and Biological Sciences Research Council (BBSRC) (The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


People vary in their capacity to learn and retain new motor skills. Although the relationship between neuronal oscillations in the beta frequency range (15–30 Hz) and motor behaviour is well established, the electrophysiological mechanisms underlying individual differences in motor learning are incompletely understood. Here, we investigated the degree to which measures of resting and movement-related beta power from sensorimotor cortex account for inter-individual differences in motor learning behaviour in the young and elderly. Twenty young (18–30 years) and twenty elderly (62–77 years) healthy adults were trained on a novel wrist flexion/extension tracking task and subsequently retested at two different time points . Scalp EEG was recorded during a separate simple motor task before each training and retest session.Although short-term motor learning was comparable between young and elderly individuals, there was considerable variability within groups with subsequent analysis aiming to find the predictors of this variability. As expected, performance during the training phase was the best predictor of performance at later time points. However, regression analysis revealed that movement-related beta activity significantly explained additional variance in individual performance levels 45–60 min, but not 24 h after initial training. In the context of disease, these findings suggest that measurements of beta-band activity may offer novel targets for therapeutic interventions designed to promote rehabilitative outcomes. As the Imaging studies have revealed considerable experience-dependent plasticity of sensorimotor cortex representations during motor skill acquisition . LearninHere, we explored the neurophysiological mechanisms associated with individual differences in short-term motor learning behaviour using EEG. We included both young and elderly subjects in order to maximise inter-subject variability, because (i) alterations in beta oscillations have been seen with ageing , and ii. Specifi22.1Twenty young  and cognitive functioning . Since sleep has been shown to affect motor memory consolidation , on both2.2The experimental design is illustrated in Electroencephalography (EEG) recorded during the performance of a simple wrist flexion/extension task was used to assess changes in pre-movement (resting) and movement-related beta activity before (Pre), immediately after (Post1) and 24h after (Post2) the initial training phase. By recording beta oscillatory activity during the performance of a separate task, not used for training, but which employed comparable motion features (flexion and extension), it was possible to investigate the generic properties of brain activity and their relation to motor learning. The simple wrist flexion/extension task is known to induce clear movement-related changes in beta activity that are distinct and separate in time . This is2.3All tasks were performed with the non-dominant hand resting in an instrumented wrist rig (modified from ). The ri2.3.1Subjects were required to continuously track a circular target (in yellow) that moved back and forth along a fixed arc through a predefined sequence of 12 positions A. The miEach block consisted of two sequences, one random and one repeated sequence presented in randomised order, with a 3s stationary target between both. The repeated sequence was identical throughout initial training (40 blocks), and retest sessions  and randomly selected from a pool of 57 difficulty-matched sequences. Each random sequence was encountered only once; however, the same set of difficulty-matched sequences was used across subjects. Subjects were instructed to move their wrist so as to shift the red wrist cursor to match the movement of the target as ‘accurately and smoothly as possible’.t = 0.94, p = 0.072). The individually determined target velocity with which subjects were subsequently trained on the continuous tracking task was applied to all sessions and did not significantly differ between young (mean velocity ±SD = 55.38 ± 6.92 deg/s) and elderly subjects (mean velocity ±SD = 50.78 ± 9.41 deg/s) .Prior to the training, the average velocity with which the target moved along the arc was individually determined in order to ensure that the task was of equal difficulty for everyone at the beginning of the training and left enough room for improvement in performance. For this purpose, we implemented an adaptive staircase procedure, which, on any given trial, adjusted (increased/decreased) the target velocity dependent on the subject's preceding performance until a pre-specified criterion range was reached. On average, subjects reached the criterion in 14.4 ± 4.5 trials and there was no difference in the number of trials required between groups  was provided at times when the subject positioned the wrist cursor inside the circular target. In addition, at the end of each block, subjects were made aware of their change in motor performance by presenting a score on the screen. Prior to the start of training, subjects received explicit verbal information regarding the presence of a repeated sequence along with a random sequence in every block. However, they were not shown the repeated sequence. To determine the time point at which participants gained explicit knowledge of the repeated sequence, after each block they had to decide (forced-choice) which of the two sequences within each block the repeated sequence was - i.e. tell the experimenter whether it was the first or second sequence they tracked within the block. The trajectories of the target and subject's wrist cursor did not leave a residual trail on the screen and hence, subjects could not visualize the entire target sequence.2.3.2r > 0.8), we report only reaction time and movement time.The EEG measures we used as explanatory variables of motor learning were acquired separately from the learning task using a simple visually-cued wrist flexion and extension task . During 2.4Scalp EEG  was continuously recorded at 2084Hz using 64 electrodes mounted on an elastic cap (waveguard EEG cap) according to the international 10–20 EEG system. The impedance was kept below ≤5kΩ and the EEG signal was referenced to Cz during recording. The timing of the visual cue (blue target) in the motor task was marked in the simultaneous EEG recording, with separate markers for each condition . Surface electromyography (EMG) using bipolar electrodes in a belly-tendon montage placed on the wrist extensor  and flexor  muscles monitored movements of the non-dominant hand.2.52.5.1i (wi) from the target position (ti), and serves as a composite measure of temporal and spatial measurements of time lag and distance as calculated using the following equation:N is the total number of time samples of the sequence in each block. Thereby, smaller RMSE values reflect better motor performance.Motor performance on the continuous tracking task, was parametrized by Root Mean Square Error (RMSE), an established measure implemented by other motor learning studies . RMSE caRMSE was calculated for repeated and random sequences separately and averaged across each block of the training and retest sessions. As the beginning and end of individual training and retest sessions might not be representative of actual motor performance (e.g. due to warm-up decrement at the beginning or fatigue at the end) , a lineaThe analysis then concentrated on six time points in order to assess changes in motor performance across time: first block of training (T0), last block of training (T1), first block of retest1 (T2), last block of retest1 (T3), first block of retest2 (T4), and last block of retest2 (T5). As outlined above, various processes can occur during time periods in which the task is not practised (i.e. between T1 and T2 or T3 and T4), such as dissipation of temporary effects (e.g. fatigue or boredom)  and moto2.5.2http://fil.ion.ucl.ac.uk/spm) and additional scripts written in Matlab . The raw EEG signal was first offline re-referenced to the average signal across all electrodes, bandpass filtered between 5 and 100Hz, additionally filtered with a 50Hz notch filter to reduce line noise contamination, and downsampled to 300Hz. Data were epoched from −1 to 9s relative to visual cue onset (0s). Poorly performed trials (see section p > 0.1) or groups . Artefact-free EEG time-series from each single trial were decomposed into their time-frequency representations in the 5–45Hz range with frequency steps of 0.1Hz. A 7-cycle Morlet wavelet was used for the continuous wavelet transformation. Power (P) was averaged across trials and rescaled in order to show changes relative to the corresponding pre-movement baseline period (-1–0s prior to cue onset), expressed as percentage of this baseline power (Pref):Pre-processing and time-frequency analysis of EEG data during the performance of the simple motor task were performed using SPM12 . These electrodes were selected based on prior findings showing that the most prominent task-related changes in beta activity were observed in these electrodes when performing the exact same simple motor task . These bTo select time-frequency windows of interest that were orthogonal to potential differences between conditions (flexion versus extension) when the simple motor task was performed , we averaged over conditions, sessions, and subjects for each group separately. We then chose specific time-frequency windows based on peak changes in beta activity in time-frequency maps of the bilateral sensorimotor regions, which revealed clear movement-related beta-band (15–30Hz) activity in two distinct time windows of interest. This information was used to optimize the alignment of constant duration (1s) and width (15Hz) time-frequency windows to capture maximum MRBD (1–2s relative to cue onset), occurring between cue onset and movement termination, and PMBR , which emerges after movement cessation. This was done for young and elderly subjects separately because of known age-related reduction of beta peak frequency . Indeed,Subsequently, for each individual subject, percentage decrease (MRBD) and increase (PMBR) in beta power were extracted from the respective 1s time windows and averaged for each EEG session  for the pre-selected electrodes over each hemisphere. The absolute pre-movement (resting) baseline beta (BB) power from −1 to 0s relative to cue onset was also obtained and assessed for age-related differences and training-related changes.In total, 6 different beta parameter estimates were used for subsequent analyses: pre-movement baseline beta (absolute power), MRBD (relative power) and PMBR (relative power) from contra- and ipsilateral sensorimotor cortices, respectively. Importantly, these EEG measures of resting and movement-related beta-band power have previously been shown to have high intra-subject reliability , a prere2.6To assess how motor tracking performance changed over time, we performed a repeated-measures ANOVA, with ‘group’ (2 levels: young vs elderly) as between-subject factor and ‘sequence type’ (2 levels: repeated vs random) and ‘time’ (5 levels: T0 vs T1 vs T2 vs T3 vs T4) as within-subject factors. Additionally, to ensure comparable baseline performance and thus, allow for direct comparison between age groups, a repeated-measures ANOVA of motor performance at T0 (baseline) was employed.Since beta oscillations have been shown to be altered with ageing  and motoPost hoc Bonferroni-adjusted t-tests were performed whenever main effects and interaction effects were detected in the ANOVAs. Prior to ANOVAs and post hoc t-tests, Kolmogorov-Smirnov test was used to affirm normal distribution of the data. Results were considered significant if p-values were below 0.05. All data presented in the text and tables are represented as mean ± SD unless stated otherwise. Statistical analyses were performed using SPSS  and custom-written Matlab routines.A Greenhouse-Geiger correction was applied whenever Mauchly's test indicated a lack of sphericity. 2.6.1Finally, a multiple linear regression approach was employed in order to investigate whether spectral power measures of beta-band activity relate to individual differences in the extent of motor learning, accounting for multicollinearity between neurophysiological  and motoSignificant correlations raise the potential for beta power measures to serve as predictors of learning outcome. To avoid overfitting and evaluate the predictive strength of each regression model, a leave-one-out cross-validation (LOOCV) approach was employed . This cr3As expected, young and elderly subjects differed in aspects of upper limb motor ability and cognitive function . In addi3.1F = 0.047, p = 0.830] or repeated and random sequences , nor an interaction effect   = 63.14, p < 0.001, effect size ƞp2 = 0.637] and ‘sequence type’ , but no effect of age . In addition, a significant ‘time x sequence type’ interaction was found . Post hoc analyses were performed to separately assess changes in motor performance with initial training (online) and following a shorter (retest1) or longer (retest2) time delay during which subjects did not practice the task (offline).A repeated-measures ANOVA on motor performance revealed a significant main effect of ‘time’  (t(37) = 0.69, p = 0.489], indicating that improvements in motor performance primarily occurred via a sequence-specific learning effect which appeared to be unaffected by ageing.During the training phase, motor performance improved over time (T0 vs T1) irrespective of age, but these improvements were different between repeated and random sequences and varied considerably between individuals [= 0.443] C. This w3.1.2t(37) = 3.17, p = 0.003, effect size pƞ2 = 0.215] and random  = 4.71, p < 0.001, effect size pƞ2 = 0.382] sequence, indicating a boost in performance early after initial training (45–60 min) (t(37) = 10.91, p < 0.001], but also the random sequence  = 5.31, p < 0.001]. Again these changes in motor performance greatly varied between individuals as indicated by the range of performance changes.After establishing that young and elderly subjects showed a comparable ability to learn, next motor performance at retest1 was examined. During the short time delay between the end of the initial training and the retest1 session (T1 vs T2), motor performance significantly improved without further training for both the repeated  C. Overalt(37) = -1.21, p = 0.236], significant performance decrements (i.e. overnight forgetting) of ∼13% were observed for the repeated sequence (t(37) = -5.79, p < 0.001, effect size pƞ2 = 0.478] (t(37) = 10.87, p < 0.001] and random sequence  = 7.87, p < 0.001].Lastly, changes in motor performance, without practice, at 24 h (retest2) after initial training were assessed. Performance significantly deteriorated from T3 to T4 irrespective of age, but dependent on the type of sequence. While motor performance on the random sequence was retained overnight  = 0.02, p = 0.896; MT: F = 1.14, p = 0.293] nor the return movement towards the initial start position . Average spectral changes in contralateral and ipsilateral sensorimotor cortices in response to wrist movement are shown in All subjects were able to perform the simple motor task during EEG recording and there were no significant differences in movement kinematics between age groups for either the movement towards the target  and ipsilateral  sensorimotor cortex which returned back to pre-training levels on day 2 .Absolute beta power during the pre-movement (resting) baseline period was significantly affected by age, with elderly subjects exhibiting higher beta power in both contralateral and ipsilateral sensorimotor cortices  = 12.93, p = 0.001, effect size ƞp2 = 0.264; ipsilateral sensorimotor cortex: F = 8.12, p = 0.007, ƞp2 = 0.184], but a significant linear reduction in the magnitude of MRBD across sessions was only found in the ipsilateral hemisphere .Averaged beta power changes during movement (MRBD) and after movement cessation (PMBR) in both sensorimotor cortices and topographic maps are shown in Post hoc analyses showed that this decrease in PMBR across sessions was restricted to the ipsilateral sensorimotor cortex and elderly subjects only . In line with this, inspection of the topographical distribution of PMBR , including young and elderly subjects to naturally vary inter-subject differences.t(37) = 4.76, p < 0.001; T1: β = 0.74, t(37) = 9.30, p < 0.001], we found that pre-training MRBD in ipsilateral sensorimotor cortex significantly accounted for performance at T2 on the repeated sequence   = 5.28, p < 0.001], but also post-training PMBR  from contralateral sensorimotor cortex  = -3.70, p < 0.001] was associated with motor performance on the random sequence  was related to spectral power measures after accounting for the effect of prior motor performance. Interestingly, beyond the influence of motor performance, sleep quantity [sequence .4In the present study, we have tested for age-related differences in visuomotor learning and in the characteristics of movement-related beta oscillations. Firstly, we found that the degree of short-term motor learning was comparable between young and elderly individuals. Secondly, we found age-related differences in beta oscillations, such that older individuals exhibited higher pre-movement baseline beta power and greater MRBD, but no differences in the magnitude of PMBR. Lastly, we found that movement-related beta oscillatory dynamics could account for different aspects of performance levels amongst all subjects shortly (45–60 min) after but not 24 h after visuomotor learning. Specifically, better performance of the repeated sequence shortly after training (T2) was related to smaller pre-training MRBD in ipsilateral motor cortex, whereas better performance of the random sequences at T2 was related to greater post-training PMBR in contralateral motor cortex, suggesting different mechanisms in learning repeated and random sequences.Healthy ageing has been argued to reduce the ability to learn new motor skills  or exertWhile young and elderly individuals showed comparable visuomotor learning, their cortical beta oscillations during an independent motor task were significantly different. Older subjects exhibited higher pre-movement baseline beta power and greater MRBD, consistent with prior literature . InteresA small number of studies have reported changes in beta oscillations in the sensorimotor cortex in the context of motor learning, reporting greater MRBD and PMBR after training . It has Having looked for age-related changes in learning and beta dynamics, we next wanted to understand whether variability in beta dynamics could account for variability in learning. Here, we employed a regression approach with LOOCV, to examine for variables that might predict performance at T2 and at T4. Performance at T2 and T4 were, as expected, strongly dependent on the subject's initial performance , was not associated with beta oscillatory measures. One potential explanation for this lack of relationship may be that other factors have important implications for motor skill retention. For example, sleep has been suggested to play a fundamental role in retention of motor learning, with a wide belief that it benefits motor memory consolidation . InteresA number of limitations are worth discussing in more detail. For example, while motor sequence learning has been shown to elicit widespread activity changes in the cortical-striatal network , the curIn conclusion, the current findings imply that accessible measurements of beta activity reflect meaningful individual differences in the motor system that can be utilized in basic research and clinical studies. Movement-related beta desynchronization and post-movement beta rebound explained additional variability in individual post-learning performance differences. Given the complexity of the human nervous system, it might not be surprising that cortical oscillations may be only one of several factors important for motor learning. Notwithstanding, EEG/MEG studies of cortical dynamics in humans have the potential to bridge the gap between cellular and behavioural accounts of cortical plasticity . In the There is no conflict of interest.


Dear Editor,1. However, its molecular identity, architecture, and function remained unclear. Of the three distinct integral membrane proteins populating the nuclear pore membrane, only pom152 (of yeasts) or gp210 (of multi-cellular organisms) contain a sufficiently large ‘trans’ domain (over 100 kDa) that could form such a belt  of the nuclear envelope has been detected with electron microscopyelt Fig. .Fig. 1El2 to predict tertiary structures of yeast pom152 and its multi-cellular ortholog, gp210, we first identified ten and fifteen, respectively, immunoglobulin-like (Ig-like) folds which extended over much of these proteins’ large trans domain  of the thermophilic yeast Chaetomium thermophilum in insect cells and purified Ctpom152FL with detergent extract. Incubation of purified Ctpom152FL with chymotrypsin revealed a large stable fragment  and having lost 14 of its C-terminal residues  was examined by negative-stain EM using uranyl acetate. The electron micrographs showed beaded strings of 37 ± 4 nm, with each bead measuring ~4 nm in length and ~2 nm in width   showed that it behaves as a monomer of 130.3 ± 9.6 kDa  Fig. . Size-exkDa Fig. , close ttrans regions of Ctpom152 could oligomerize into lumenal ring. We used purified Ctpom152FL, but removed much of the detergent  are unable to oligomerize, these data strongly suggested that the longer beaded structures might arise by head-to-tail oligomerization of the trans domains.Strikingly, in up to an estimated 10% of images (over 2000 images), full-length res Fig. , measurires Fig. . BecauseChaetomium thermophilum and Saccharomyces cerevisiae. Indeed, both Ctpre-Ig and Scpre-Ig immediately downstream from the TM sufficiently precipitated CtIg10 and ScIg10, respectively. The remarkable agreement thus strongly suggests that yeast pom152, independent of other poms (pom34 and Ndc1), is capable of assembling into a complete ring.Intriguingly, both pre-Ig and Ig10 are amongst the most conserved regions between pom152 homologs  bears striking structural similarity to titin, an abundant protein in sarcomeres that fulfills a number of mechanical functions with the most notable one as a passive visco-elastic spring7. The existence of an elastic ring in lumen thus could provide the pore membrane with the counter force to maintain its integrity8.Why should NPC require such a structure? As the only conduit between nucleus and cytoplasm, dilation of the central channel to accommodate oversized particles could destabilize the pore membrane. Intriguingly, the 9 was published, the results of which were both overlapping and divergent with those of our present paper. Based on 3D reconstruction of negative-stain EM, Upla et al.9 reported that full-length Scpom152 consists of two distinct domains: (1) a large “head” group  , and (2) a “lumenal” domain consisting of nine beads in a rigid conformation, with the first one much longer than the remaining eight, all distinctly smaller than the head group . In contrast, our EM structures showed ten beads of about equal size in a highly flexible conformation  of another, whereby linking multi-trans domains into a single ring , not a constituent of the ring3. Better precision in the ‘head group’ boundary determination, negative stain in the absence of detergent, and higher resolution in 3D reconstruction will be needed in order to resolve the differences between our models.While preparing our manuscript, a paper by Upla et al.ion Fig. , and theion Fig.  and S2, ing Fig. . SurprisSupplementary Information


Incubation of the digested fraction for 24 h didn’t exert any effect on cellular viability, while a dose- and time-dependent cytotoxicity was observed after 48 h and 72 h of incubation for all the berries analyzed. Our results suggest that the approach proposed in this work may represent a rapid tool for evaluating and identifying new berries with increased phytochemical bioavailability, highlighting their antiproliferative agents after an in vitro digestion.Berry fruits are rich in nutrients and polyphenols, providing potential health benefits. Understanding the factors that affect their bioavailability is becoming of utmost importance for evaluating their biological significance and efficacy as functional food. In this study, the phytochemical composition and the total antioxidant capacity of different varieties of five berries  were evaluated after an in vitro gastrointestinal digestion process. The cultivar of each berry that showed the higher content of total phenols and flavonoids was selected to study its cytotoxic effect on human hepatoma cells. Digestion resulted in a high reduction ( Rubus sp.), blackcurrant (Ribes nigrum), blueberry (Vaccinium corymbosum), raspberry (Rubus idaeus), and strawberry (Fragaria x ananassa), which are usually consumed in fresh and processed forms in the human diet all around the world. The principal group of phytochemicals in berry are polyphenols, comprising flavonoids , stilbenes, tannins, and phenolic acids, which are reported to strongly contribute to the health effects of berry consumption against human diseases [The importance of diet on human health has been widely recognized worldwide. It is commonly accepted that the regular consumption of plant-based food is strongly correlated with a high intake of bioactive compounds that play a crucial role in the prevention of a wide range of diseases, such as cancer, cardiovascular disorders, and other chronic degenerative pathologies, as well as with the general health benefits they provide ,2,3. Berdiseases ,7,8. In diseases ,10.Bioavailability is a complex process which depends on many factors, including the release of nutrients/phytochemicals from the food matrix, their digestive stability, and their efficiency of transepithelial passage . BecauseIt is well known that berry polyphenol composition is highly influenced by the genotype: each type of berry and each type of cultivar have different profiles and contents of bioactive compounds ,18,19,20The aim of the present study was to assess the bioacessability of different cultivars of five berries  using an in vitro digestion procedure that mimics the physiochemical and biochemical conditions encountered in the GI tract. In particular, we evaluated and compared the phytochemical composition  and the total antioxidant capacity  and Ferric Reducing Antioxidant Power (FRAP) assays) of the different digested samples, taking into account the “IN” and the “OUT” fractions, which represent the “serum-available” and the “colon-available” fractions, respectively. In addition, the cultivar of each berry that showed the higher content of total phenolic compounds and flavonoids was selected to test their cytotoxic effects on human hepatoma cells (HepG2), the most used cellular model for in vitro cytotoxicity studies given the simplicity of its use, culture and relatively low cost compared to primary human hepatocytes.In the present work, the phytochemical composition of the different berries was analyzed after the in vitro digestion process. p ˂ 0.05) were found between the diverse berries and between the “IN” and the “OUT” fractions of each berry. In particular, the OUT samples always presented the highest contents of TPC, Flavo, and ACY than the IN samples, in most cases with double values (p ˂ 0.05). Significant differences (p ˂ 0.05) total phenolic contents (TPC), followed by strawberry and raspberry; the lowest concentration (p ˂ 0.05) was registered for blueberry. Black currant also presented the highest (p ˂ 0.05) flavonoid content (Flavo), followed by blueberry and blackberry; the lowest contents (p ˂ 0.05) were found for raspberry and strawberry. Again, black currant had the highest (p ˂ 0.05) contents of anthocyanins (ACY), followed by blackberry, raspberry, strawberry, and blueberry. Black currant showed the highest value of total antioxidant capacity (TAC) (p ˂ 0.05), measured by TEAC assay, followed by raspberry (p ˂ 0.05), and by blackberry and strawberry, which showed similar values; the lowest value was found for blueberry (p ˂ 0.05). With FRAP method, black currant possessed the highest TAC (p ˂ 0.05), followed by strawberry and blackberry; blueberry and raspberry presented the lowest ones (p ˂ 0.05). In summary, black currant was the berry with the highest contents of polyphenols and the highest TAC for IN fractions. Regarding the “IN” fractions, blackberry and black currant possessed the highest (p ˂ 0.05) of TPC, followed by black currant and strawberry (p ˂ 0.05); the lowest contents (p ˂ 0.05) were registered for blueberry and raspberry. Blueberry presented the highest (p ˂ 0.05) content of Flavo, followed by blackberry, black currant, and strawberry; the lowest content (p ˂ 0.05) was found for raspberry. As the “IN” fractions, black currant had the highest (p ˂ 0.05) content of ACY, followed by blackberry, raspberry and strawberry; the lowest content was found for blueberry (p ˂ 0.05). Black currant showed the highest TAC (p ˂ 0.05) measured by TEAC assay, followed by blackberry and raspberry, which presented similar values; blueberry had the lowest (p ˂ 0.05) values. With the FRAP method, the highest values were found for strawberry and black currant, followed by blackberry (p ˂ 0.05), blueberry (p ˂ 0.05) and raspberry which showed the lowest (p ˂ 0.05) concentration.Concerning the “OUT” samples, blackberry possessed the highest content (p ˂ 0.05) were also found between the diverse cultivars of each berry (p ˂ 0.05) in both the “IN” and “OUT” fractions. Among black currant, “Ben Finlay” presented the highest content of total phenolic and flavonoid compounds (p ˂ 0.05) in the “IN” and “OUT” samples, while the highest (p ˂ 0.05) content of ACY were found for “Ben Starav” “IN” and “OUT” extracts. “Misty” cultivar was the blueberry with the highest (p ˂ 0.05) content of TPC and Flavo (p ˂ 0.05) in both the “IN” and “OUT” fractions, while “Georgiagem” presented the highest content of ACY. For raspberry, “Glen Ericht” was the cultivar with the highest content of TPC and Flavo in both “IN” and “OUT” fractions, followed by “Tulameen” variety. Finally, among strawberry, “Romina” presented the highest content of TPC and Flavo, while AN00.239.55 the highest content of Flavo. Interestingly, “Bianca” showed the highest (p ˂ 0.05) content of TPC and Flavo, together with “Romina” and “AN00.239.55,” respectively.Significant differences (ch berry . In partp ˂ 0.05).In addition, significant differences were outlined also between the IN and OUT fractions of each variety . In partThe total antioxidant capacity of the different cultivars of each berry was evaluated after the in vitro gastrointestinal digestion process by the TEAC and FRAP assays .p ˂ 0.05) were outlined among the different varieties of each berry and between the “IN” and “OUT” fractions of each variety. In particular, for raspberry “Loch Ness” showed the highest TAC (p ˂ 0.05) measured by TEAC and FRAP assays in the IN fraction, while R. brigantinus and R. vagabundus presented the highest (p ˂ 0.05) values in the “OUT” fraction. “Ben Finlay” and “Ben Starav” showed the highest TAC (p ˂ 0.05) measured with the two methods both in the “IN” and “OUT” samples for black currant; “Misty” and “Glen Ericht” were the variety with the highest (p ˂ 0.05) TAC, both in the “IN” and “OUT” fraction, for blueberry and raspberry respectively. As for the phytochemical characterization, significant differences  of TAC measured with the two methods both in the “IN” and “OUT” extracts; these high values can be due to the high levels of ellagitannins present in this variety. In addition, the “OUT” samples always presented higher concentrations than the IN samples, confirming the strong correlation between the phenolic content and the total antioxidant capacity of food matrices.Surprisingly, On the basis of results obtained for the phytochemical composition, the “IN” fraction of a cultivar of each berry was selected for the in vitro study: “Loch Ness” for blackberry, “Ben Finlay” for blackcurrant, “Misty” for blueberry, “Glen Ericht” for raspberry, and “Romina” for strawberry .The “IN” samples were evaluated for their antiproliferative activity on HepG2 cells. Cell viability was analyzed after 24 h, 48 h, and 72 h of exposure to media containing increasing levels of digested berry extracts (0–5000 µg DW/mL) using the MTT -2,5-diphenyltetrazolium bromide) assay .Results showed a dose- and time-dependent cytotoxic effect of the “IN” fractions: after 24 h of incubation, they did not exert any effect on cellular viability at any concentrations, while after 48 h of incubation, cell vitality began to decrease at the concentration of 500 µg/mL especially for blackcurrant, blackberry and raspberry. At 72 h, cell viability decreased for all the berries analyzed, especially at higher concentrations. In particular, after 48 h of incubation, the most cytotoxic effects were registered for black currant (“Ben Finlay”) and strawberry (“Romina”), which led cell vitality near to 50% at 1000 µg/mL, followed by blueberry (“Misty”) and raspberry (“Glen Ericht”), which led the viability closer to 80%; the less cytotoxic berry was blackberry (“Loch Ness”), with a viability of about 90% at 1000 µg/mL. As expected, a similar trend was found after 72 h of incubation: strawberry (“Romina”) and black currant (“Ben Finlay”) were again the most cytotoxic berries , followed by raspberry (52% of viability at 1000 µg/mL); blackberry and blueberry exerted the weaker effect berries . Berries are well known to possess a wide range of phytochemicals such as flavones, flavonols, anthocyanins, and phenolic acids ,7,8, whiIt is widely accepted that the antioxidant power of fruits strictly depends on the presence of efficient oxygen radical scavengers, such as vitamin C and phenolic compounds. Indeed, highly reactive species such as polyphenols act in plants as antioxidants and protective agents against several sources of damage . In the last years, the capacity of these compounds to scavenge free radicals and/or limit their formation has been accepted as the main mechanism through which they could counteract oxidative stress, preventing the onset and development of degenerative diseases ,34. HoweCancer is one of the leading causes of death worldwide, and about 14.1 million of new cancer cases and 8.2 million of cancer deaths occurred in 2012 . Many st2,2′-Azinobis(3-ethylbenzothiazolne-6-sulfonic acid) diammonium salt, ferrous sulphate and all other reagents and solvents were purchased from Sigma-Aldrich Chemie GmbH . F. vesca—white fruit and of “Sabrina,” an international cultivar from a Spanish breeding program. The plants were grown in open field conditions using the standard cultivation conditions described in [The study was performed on strawberry fruits of “Romina” and AN00.239.55 and AN07.216.60, a cultivar and 2 advanced selections of from the Ancona University breeding program , a cloneribed in . Ripe frSamples of black currant cvs. Ben Finlay, Ben Maia, Ben Starav and Big Ben, all from the breeding program at the James Hutton Institute, Dundee, Scotland, were harvested at full ripeness from unirrigated open field plots grown under standard cultivation conditions. Samples were frozen immediately after harvest to await analysis. For Rubus berries, samples of the red raspberry cvs. Glen Ericht (bred in Scotland) and Tulameen (from Canada) were collected during the peak cropping season from breeding plots grown under polytunnels at the James Hutton Institute, using standard commercially based cultivation methods. Additionally, samples from the Scottish breeding lines 00123A7, 0304F6 and the yellow fruited 2J19 were also collected. All plots were grown under standard cultivation conditions. For the blackberry cv. Loch Ness from James Hutton and the Rubus species R. brigantinus and R. vagabundus, samples were collected from open field plots grown under standard cultivation conditions at full ripeness at National Institute for Agrarian and Veterinary Research Experimental Farm, Odemira. In Vaccinium, the cvs. Biloxi, Misty and Georgiagem were all Southern Highbush types were collected from open field plots grown under standard cultivation conditions at full ripeness at National Institute for Agrarian and Veterinary Research Experimental Farm, Odemira.The in vitro digestion of berry samples was performed as previously described by McDougall et al. . BrieflyFor phytochemical characterization and TAC determination the extracts obtained after the in vitro digestion process were resuspended in Milli-Q water containing 0.1% methanol and subjected to an ultrasonic bath for 10 min at room temperature prior to analyses.The TPC was measured by Folin-Ciocalteu method , TFC by The TAC of the berry digested samples was determined by two methods: the TEAC and the FRAP assays. 2S2O8 and maintained in the dark at 25 °C for 12 h before use. Previously to the analysis, the working solution was obtained by diluting the stock solution 1:50 with PBS buffer, pH 7.4. Then, 10 µL of alternatively blank, Trolox standard or MilliQ water diluted samples were added to 1 mL of the ABTS working solution into 1.5 mL eppendorfs. The mixture was vortexed for 20 s and after 1–3 min, the absorbance (A) was read at 734 nm, measuring the color inhibition of the ABTS radical.The TEAC assay was carried out according to the modified method of Re and co-workers . BrieflyMeanwhile, the FRAP assay was performed according to the protocol proposed by Deighton and co-workers (2000) . BrieflyEach sample was analyzed in three replicates and results are expressed as mM of Trolox equivalents (mM TEq). Data are reported as a mean value ± S.D. of four measurements.2. The cells were incubated for 24, 48, and 72 h with different concentrations of berry digested extracts (0–5000 µg DW/mL). HepG2 cells were kindly provided by the Biological Research Laboratory of the Sevilla University (Spain), and were grown in Dulbecco’s modified Eagle’s medium, supplemented with 10% fetal bovine serum, 100 IU/mL penicillin and 100 ug/mL streptomycin at 37 °C in a humidified atmosphere with 5% COCell viability was determined by the MTT assay, which is based on the reduction of tetrazolium salt, 3--2,5-diphenytetrazolium bromide, by intracellular dehydrogenases of viable living cells, leading to the formation of purple formazan crystals . After ip < 0.05 were considered statistically significant.Statistical analyses were performed using STATISTICA software . Data were subjected to one-way analysis of variance for mean comparison, significant differences were calculated according to HSD Tukey’s multiple range test. Data were reported as mean ± SD. Differences at Popularly consumed berries include blackberries, raspberries, blueberries, cranberries, raspberries, and strawberries. These soft fruits contain high levels of phenols that exert in vivo biological activities and can have complementary and overlapping mechanisms of action. In the last few years, several researchers have used in vitro digestion methods to analyze structural changes, and digestibility of foods, indicating that in vitro digestion systems are common and useful tools for food analyses. In the present work, we have compared the phytochemical composition and the total antioxidant capacity of different berries following the gastrointestinal digestion, and we have demonstrated that, although a large proportion of phenolics undergo transformation during digestion, berry polyphenols continue to exert antiproliferative effects. In particular, the most promising berry was black currant, which presented the higher content of polyphenols and total antioxidant capacity after in vitro digestion and consequently the highest cytotoxic effects on human hepatoma cells. However, the main limitation of the method here described is the complete lack of microbial transformation that occurs in the large intestine and is essential for polyphenols metabolism. In addition, further studies are needed to describe the impact of the digestion on the relative chemistries, to elucidate the mechanisms of transport and metabolism of these compounds, to evaluate the in vitro–in vivo correlations with well-defined systems, and to analyze the advantages and disadvantages of in vitro digestion models.


A survey of presences and absences of specific species across multiple biogeographic units (or bioregions) are used in a broad area of biological studies from ecology to microbiology. Using binary presence-absence data, we evaluate species co-occurrences that help elucidate relationships among organisms and environments. To summarize similarity between occurrences of species, we routinely use the Jaccard/Tanimoto coefficient, which is the ratio of their intersection to their union. It is natural, then, to identify statistically significant Jaccard/Tanimoto coefficients, which suggest non-random co-occurrences of species. However, statistical hypothesis testing using this similarity coefficient has been seldom used or studied.p-values and false discovery rates. The proposed estimation methods are orders of magnitude faster than the exact solution, particularly with an increasing dimensionality. We showcase their applications in evaluating co-occurrences of bird species in 28 islands of Vanuatu and fish species in 3347 freshwater habitats in France. The proposed methods are implemented in an open source R package called jaccard (https://cran.r-project.org/package=jaccard).We introduce a hypothesis test for similarity for biological presence-absence data, using the Jaccard/Tanimoto coefficient. Several key improvements are presented including unbiased estimation of expectation and centered Jaccard/Tanimoto coefficients, that account for occurrence probabilities. The exact and asymptotic solutions are derived. To overcome a computational burden due to high-dimensionality, we propose the bootstrap and measurement concentration algorithms to efficiently estimate statistical significance of binary similarity. Comprehensive simulation studies demonstrate that our proposed methods produce accurate We introduce a suite of statistical methods for the Jaccard/Tanimoto similarity coefficient for binary data, that enable straightforward incorporation of probabilistic measures in analysis for species co-occurrences. Due to their generality, the proposed methods and implementations are applicable to a wide range of binary data arising from genomics, biochemistry, and other areas of science. Specifically, for k=1,…,m,yi,k∼i.i.d.Bernoulli(pi) and yj,k∼i.i.d.Bernoulli(pj). Because this conventional definition is undefined if both binary vectors contain only zeros such that yi∪yj=0, we refine the definition of Jaccard/Tanimoto coefficientUnder the null model of independence, m trials . Four categories arising from presence-absence data are N1=yi∩yj,N2=yi∩(1−yj),N3=(1−yi)∩yj and N4=m−N1−N2−N3. From pi and pj, probabilities of those four categories are pipj,pi(1−pj),(1−pi)pj and (1−pi)(1−pj), respectively. Putting them together, N= is distributed according to a multinomial distribution, Multi,(1−pi)pj,(1−pi)(1−pj)).Following the definition of Jaccard/Tanimoto similarity coefficient in Eq. , we deriyi and yj are independent, thenIf N1+N2+N3. We observe that N1|N1+N2+N3 follows N1+N2+N3>0, we haveN1+N2+N3=0, we haveFirst, we compute conditional expectation given Therefore,This allows us to define the centered Jaccard/Tanimoto coefficient asThis accounts for expected values, naturally distinguishing negative and positive associations. Generally, we would like to measure the deviation of an observed coefficient from an expected value, instead of simply looking at a magnitude of an observed statistics. Furthermore, this centered coefficient may be scaled by variance in order to span a pre-defined range.yi and yj are independent, a following statistical hypothesis testing is performed:To evaluate whether H0 is that the centered Jaccard/Tanimoto coefficient equals zero. Note that this is equivalent to that the conventional (uncentered) Jaccard/Tanimoto coefficient equals an expected value under independence. Therefore, although we propose and use the centered coefficient, this hypothesis testing is attributed to both uncentered and centered versions. Then, a p-value indicates a probability of observing a coefficient equal to or more extreme than an observed coefficient under the null hypothesis.The null hypothesis p-value, we derive the distribution of Jaccard/Tanimoto coefficient under the null hypothesis. In terms of N=, the Jaccard/Tanimoto coefficient can be expressed asTo obtain its pi and pj are known, the p-value is given by When pi and pj are usually unknown. Therefore, we define the centered Jaccard/Tanimoto coefficient by pi and pj respectively. Plug-in estimates of pi and pj for each configuration  separately.However, in practice, probabilities into Eq.  will resSo in this case, the critical region is defined as followswhere Results for comparison), we introduce an asymptotic approximation when m→∞. It may be useful when dealing with very large binary data, where computational power is a bottleneck. Denote by q1=pipj the probability that both yi and yj have ones, and by q2=pi+pj−2pipj the probability that only one of two vectors has one. Similarly, m→∞, we can estimate the variance:Because the exact distribution is computationally expensive  with N1+N2+N3+N4=m, such that Iε, we have following boundsThis can be quickly and accurately estimated by the measure concentration algorithm (MCA) with a known error bound . For eveIn addition, N= and N∼N′, if N′ can be obtained from N by moving one element to a different class. We construct the set Iε as follows.The idea behind the algorithm is that a multinomial distribution concentrates around its mode. Two possible states Iε contains only the mode of multinomial distribution. We find the mode by a simple hill climbing algorithm, which starts with a state close to the mean of the multinomial distribution and follows the direction of increasing probability until the maximum is reached. Because of unimodality, it is indeed a global maximum. In the next steps, we add the neighbors of states which were previously visited. The procedure is repeated until the total probability of set Iε reaches the desired value 1−ε. The details of the above method can be found in  re reAdditiAdditional file 3 Hypergeometric p-values of similarity among independent presence-absence vectors of m=200 with p=.5. We used a hypergeometric distribution [gt and plt can be “interpreted and reported as p-values”. The dashed red lines indicate theoretically correct Uniform distributions.ribution  to obtaiAdditional file 4 Scatterplot of marginal occurrences of 53 bird species and Jaccard/Tanimoto coefficients. As expected, we observe high correlation (Pearson correlation =0.43) between marginal occurrences and Jaccard/Tanimoto coefficients.Additional file 5 Histograms of conventional and centered Jaccard/Tanimoto similarity coefficients. The conventional (uncentered) Jaccard/Tanimoto coefficients are centered by their expected values under the independence assumption.Additional file 6 Comparison of p-values from the bootstrap and measure concentration algorithm (MCA). Both algorithms were applied on 1378 co-occurrences of bird species. The difference between estimated p-values from two methods is minimal with a mean squared deviation of 1.15×10−4. The diagonal red line indicates the identity.


Scientific Reports 10.1038/s41598-018-21483-x, published online 21 February 2018Correction to: This Article contained errors.As a result of a figure assembly error, in Figure 5b subpanel showing samples vps1Δ through vaps8Δ was duplicated for vps25Δ through vps31Δ and vps53Δ through vps63Δ, for methionine treated samples. This same methionine sample was correctly shown in the Supplementary Information File.Additionally, in the Supplementary Information file, as a result of labelling error, the label for vps32Δ through vps38Δ was duplicated for subsequent subpanel which instead should be labelled as vps39Δ through vps52Δ.These errors have now been corrected in the PDF and HTML versions of the Article, and in the accompanying Supplementary Information File.


Therefore, the main objectives of the present narrative review were to examine the effect of nutritional status on acute HR, and VO2 responses of children to exercise testing. For this purpose, we examined existing literature using PubMed, ISI, Scopus, and Google Scholar search engines. Compared with their normal-body mass index (BMI) peers, a trend of higher HRrest, higher HR during submaximal exercise testing, and lower HRmax was observed among overweight and obese children (according to BMI). Independent from exercise mode , exercise testing was metabolically more demanding  for obese and overweight children than for their normal-weight peers. Considering these cardiometabolic differences according to BMI in children might help exercise specialists to evaluate the outcome of a graded exercise test (GXT)  and to prescribe optimal exercise intensity in the context of development of exercise programs for the management of body mass.Although the beneficial role of exercise for health is widely recognized, it is not clear to what extent the acute physiological responses  and oxygen uptake (VO It has been reported that more than half of adults in the USA are either overweight or obese, and that high levels of body mass (BM) or body fat percentage (BF) are associated with increased risk for numerous diseases . High raFrom a physiological point of view, an increased BM might result from an excess of energy availability, which in turn might result from either increased energy intake, decreased energy expenditure, or a combination of both. Consequently, most of the research concerning the management of overweight and obesity focused on altering either nutrition intake and/or exercise levels . A revie2), metabolic equivalents (METs), lactate concentration, rate of perceived exertion, and heart rate (HR) [rest) and maximal values of HR (HRmax), e.g., the Karvonen method [max, which is an easy method to administer, but its weakness is in describing low intensities .Thus, information on exercise intensity is crucial to develop efficient aerobic exercise interventions for overweight and obese children. Exercise intensity might be measured by oxygen consumption (VOate (HR)  during an method , in whicmax by BMI (body mass index) during a GXT might influence the indirect criteria used to assess the attainment of VO2max.Despite the importance of exercise intensity in intervention programs for overweight and obese children, and the acknowledgment of HR as a measure of exercise intensity, limited data existed concerning acute HR responses to exercise in these population groups. It might be of great practical value to be aware of differences in acute HR responses of these groups compared to their normal-weight counterparts, because this information would assumedly contribute to a better prescription of exercise intensity and subsequently better development of exercise interventions to manage overweight and obesity. For instance, potential differences in HR−2), normal-weight (18.5–25 kg·m−2), overweight (25–30 kg·m−2), and obese (>30 kg·m−2) [Nutritional status reflects the energy balance, i.e., the relationship between energy intake (nutrition) and energy expenditure  . Assessi kg·m−2) ,13. Acco kg·m−2) ,15. Howe kg·m−2) , and tho kg·m−2) . Another kg·m−2)  defined  kg·m−2) ,21. Base kg·m−2)  defined  kg·m−2) , and Gov kg·m−2)  defined ght 18.5– kg·m−2, Testing aerobic capacity usually takes place either in a laboratory setting or in the field. In a laboratory, exercise testing is performed on calibrated equipment, which might be a treadmill ,27,28,29−1 on a treadmill [−1), but using a higher step bench (41.3 cm) [Laboratory testing typically includes either maximal or submaximal protocols. An example of maximal protocol is the Bruce protocol , which ireadmill ,26. An ereadmill ,35. Anot41.3 cm) ,34. Pate2, energy expenditure, and fat oxidation during exercise on a treadmill than on a cycle ergometer [It should be highlighted that the exercise mode might influence the differences in cardiometabolic responses between normal- and overweight participants in the studies under examination, because the body is supported on a cycle ergometer, in contrast to a treadmill or step, and this might attenuate the effect of BM. In this line, a study on a cycle ergometer reported similar cardiometabolic response to exercise between normal- and overweight children . Furtherrgometer . Anotherrgometer .2max has been considered as the golden criterion measure of aerobic capacity, which includes the recording of VO2 during a GXT usually on a treadmill or a cycle ergometer [−1), i.e., how much oxygen is transferred and consumed in the end of a maximal test, this measure has also been expressed relative to BM unit (mL·kg−1·min−1) in order to reflect the effect of body size on aerobic capacity [2max to consider which measurement unit is being implemented (L·min−1 or mL·kg−1·min−1).VOrgometer . In addicapacity . Thus, c2 depends on the applied model  of body composition [2 is scaled for BM when the whole body is considered. In addition to the traditional relative unit (mL·min−1·kg−1), another option is allometric scaling [−1·kg−0.67, mL·min−1·kg−0.71, or mL·min−1·kg−0.75 instead of mL·min−1·kg−1 [2 can be scaled for FFM when the tissue-system level in the body composition classification is considered [The use of relative units for VOposition . Accordi scaling  suggestin−1·kg−1 ,49. The n−1·kg−1 . Moreovensidered .2 responses to exercise during a GXT in groups differing for BMI. A further aim was to study differences according to BMI for other practically relevant cardiorespiratory parameters, such as HRrest, resting metabolic rate (RMR), and the respiratory quotient (RQ). Moreover, methodological issues concerning the exercise stimulus used in existing literature, such as exercise intensity  and mode , were examined.While the importance of exercise testing for the development of optimal training interventions for BM management is undisputable, there is no comprehensive review regarding differences in cardiometabolic responses by BMI groups during a GXT. Knowledge on such differences could be used by practitioners to design cohort-specific exercise testing protocols. Subsequently, data from these tests could be taken to deduce cardiorespiratory training zones. Therefore, the main aim of the present study was to examine the existing body of literature concerning cross-sectional studies that compared acute HR and VOn = 71) that were published in English only. In addition, studies were eligible for inclusion if they reported data on age, sex, number of participants, BMI, exercise protocol, and HR, and use at least two groups differing in BMI for the purpose of cross-sectional design [For the purpose of the present narrative review, we thoroughly examined existing literature using Scopus, PubMed, Google Scholar, and Clarivate Analytics search engines in December 2017. Keywords and syntaxes for the search engines were: (“heart rate” OR “oxygen uptake” OR “resting metabolic rate” OR “respiratory quotient”) AND  AND (children OR adolescents) NOT (adult OR women OR men). Inclusion criteria comprised studies (l design . Any stun = 8) were conducted in pre-pubertals and included both sexes. Unfortunately, these studies did not separate their findings according to sex. The remaining (n = 6) studies examined adolescents and reported sex-specific findings. Sample sizes ranged from 40 to 182 and whenever possible participants were classified in two groups .Our search identified 14 studies that applied cardiorespiratory exercise testing in children aged 6–18 years. Most studies (−1) (−1·min−1) VO2max   and lowe) VO2max  in overwlleagues  observedlleagues  recorded2max (L·min−1) for the overweight than for their normal-weight peers. Although Loftin and colleagues [2max in L·min−1 between BMI groups, VO2max in mL·kg−1·min−1 was 50% lower for obese girls than their normal-weight peers.In the study of Souza and colleagues , althouglleagues  showed s2max should be partially attributed to the relationship between BMI and BF. The magnitude of this relationship in children ranged from large to very large depending on sex and ethnicity [2max in absolute values but lower in relative to BM values than their normal-weight peers. On the contrary, overweight have lower relative VO2max as their body composition is less metabolically active since it consists of a higher BF.The negative effect of BMI on VOthnicity ,58, verythnicity  to almosthnicity . This clmax than their normal-weight peers, both in a GXT on a cycle ergometer  or a walk/run test (175 vs. 197 bpm) in the study of Norman and colleagues [Overweight had lower HRlleagues , and thelleagues . Maffeislleagues  found hilleagues  found lorest has been well discussed by many studies on overweight and obese children [rest in most of these studies has been measured in a seated position [rest includes electrocardiograph [rest than non-obese children among both boys  and girls (84.5 vs. 81.3 bpm). Charakida and colleagues [rest than their normal-weight peers . Norman and colleagues [rest to be higher in overweight (94 vs. 82 bpm) than in normal-weight children (14.5 years). Faria and colleagues [rest in obese children than in normal-weight children for girls , but not for boys (73.3 vs. 73.6 bpm). There was only one study that did not record differences between overweight and normal-weight children for boys  or for girls (93 vs. 93 bpm) [HRchildren ,62,63,64position ,62,63,65position ,64, and position . HR recoposition  to 15 miposition . The equdiograph ,64, bloodiograph ,26,62,65diograph ,63. Withdiograph  found thlleagues  found HRlleagues  showed ha) physical working capacity test in HR 170 bpm (PWC170) conducted on a cycle ergometer, in which power relative to BM (W·kg−1) was recorded, and (b) a 3 min step test, in which acute HR responses were recorded at the end of the test and at the end of the first minute of recovery. In a study on male handball players (15 years), normal-weight had similar PWC170 , HR at the end of the step test (140 vs. 145 bpm) and at the end of the first minute of recovery (96 vs. 99 bpm) than their overweight peers [170 in W and higher PWC170 in W·kg−1 than their overweight counterparts [170 in W·kg−1 for normal-weight and overweight participants  [170 consisted of submaximal cycling against predetermined resistances for three 3 min stages aiming to elicit HR between 120 and 170 bpm. Thus, the performance in PWC170 was dependent of HR; i.e., the lower the HR response to a given exercise intensity, the higher the PWC170. Consequently, the relatively low performance of overweight athletes in PWC170 might reflect their relatively high acute HR responses.Recent studies investigated differences in aerobic capacity between normal and overweight athletes ,69,70,71ctively) . The proRMR, usually measured by indirect calorimetry, is a major determinant of the daily total energy expenditure, and therefore, it is considered as a target-variable in any BM management program ,73. It hIndirect calorimetry also provides information about the nutrients’  oxidation, which can be quantified using the RQ, i.e., the ratio of the carbon dioxide removed from the body divided by the oxygen consumed in the tissues . Typical2 variation [2max in the examined cohorts. Furthermore, it would be recommended for strength and conditioning coaches prescribing exercise that aerobic exercise should be less (in terms of duration and/or intensity) in overweight and obese children and adolescents than in their normal-weight peers in order to induce similar cardiometabolic acute responses. We were able to show that different measurement units  influence the variation of VO2max according to BMI. Furthermore, since overweight children achieved lower HRmax during GXT than their normal-weight peers, this should be considered in the evaluation of the indirect criteria used to assess the attainment of VO2max.It should be highlighted that, although all ethnicities were considered during the search in the databases, it was acknowledged that most studies were conducted in Caucasian populations. With regards to ethnicity, differences have been observed in body composition and energy expenditure among ethnic groups  . Moreoveariation ,82. Therrest and HR during submaximal exercise and lower HRmax was observed among overweight and obese children. Independent from exercise mode , exercise was metabolically more demanding for obese and overweight children than for their normal-weight peers. Findings from this study are of practical relevance for practitioners working in the field of cardiorespiratory exercise testing in youth. Test data can be used to develop adequate training programs for BM management in youth. Based on the findings of this review, strength and conditioning coaches working with children and adolescents varying for BM and BF should be aware about the increased cardiometabolic cost induced by aerobic exercise in those being overweight or obese compared to their normal-weight peers.Compared with their normal-weight peers, a trend of higher HR