Genomic technologies can be subject to significant batch-effects which are known to reduce experimental power and to potentially create false positive results. The Illumina Infinium Methylation BeadChip is a popular technology choice for epigenome-wide association studies (EWAS), but presently, little is known about the nature of batch-effects on these designs. Given the subtlety of biological phenotypes in many EWAS, control for batch-effects should be a consideration.Using the batch-effect removal approaches in the ComBat and Harman software, we examined two in-house datasets and compared results with three large publicly available datasets, , and find that despite various forms of preprocessing, some batch-effects persist. This residual batch-effect is associated with the day of processing, the individual glass slide and the position of the array on the slide. Consistently across all datasets, 4649 probes required high amounts of correction. To understand the impact of this set to EWAS studies, we explored the literature and found three instances where persistently batch-effect prone probes have been reported in abstracts as key sites of differential methylation. As well as batch-effect susceptible probes, we also discover a set of probes which are erroneously corrected. We provide batch-effect workflows for Infinium Methylation data and provide reference matrices of batch-effect prone and erroneously corrected features across the five datasets spanning regionally diverse populations and three commonly collected biosamples .Batch-effects are ever present, even in high-quality data, and a strategy to deal with them should be part of experimental design, particularly for EWAS. Batch-effect removal tools are useful to reduce technical variance in Infinium Methylation data, but they need to be applied with care and make use of post hoc diagnostic measures.The online version contains supplementary material available at 10.1186/s13148-022-01277-9. Batch-effects can be defined as systematic differences between the measurements of different batches of experiments which artificially inflate within-group variances, thereby reducing experimental power and potentially creating false positive results. While high throughput genomic technologies are known to exhibit batch-effects, it is postulated they are also present in low throughput assays—it is the data resolution of high throughput technologies that offer the ability to identify and characterise them . Batch-eIn the instance of microarrays in particular, batch-effects often arise due to intra-batch differences in fluor labelling efficiency, dye bias (for two colour arrays), dye photobleaching, pipetting accuracy, buffer salt concentration, hybridisation temperature and time, array scanner variability and artefacts such as air bubbles in the hybridisation solution. As array scanning is not instantaneous, a time or position effect can also arise—with latter samples more subject to photodegradation or the damaging effects of ozone. It is known that Cy5 dye is more prone to photobleaching  and ozonAt a global level, methylation estimates based on the Illumina Infinium technology are known to have high assay reproducibility ; howeverWith Infinium methylation designs, probes designed for bisulphite-converted DNA bind to methylated and unmethylated alleles, which then allows for single-base extension with a labelled nucleotide across from the CpG site of interest. Subsequent staining of the extended template allows generation of a measurable fluorescence signal Fig. . There aIt is also common for a probe sequence to span other CpG sites before the site under inspection. Infinium I probe pairs are designed assuming that all CpG sites spanning the probe are the same state as the measured CpG site: all methylated or all unmethylated. So, we could expect reduced signal at loci that are partially methylated. Infinium II designs use degenerate bases throughout the probe at CpG cytosine positions. This reduces bias against partial methylation at the expense of probe uniqueness and issues with cross-hybridisation. As such, Infinium II designs are used where there are fewer CpG sites traversed by a probe. This also confounds probe type with biology, as the Infinium I design will be used more often within CpG islands. Considering the known technical biases of 450K and EPIC data, it is important to undertake normalisation to account for this. Normalisation methods can either be within-sample or between-sample methods. It is also common to include background correction and dye-bias correction as part of this process.Even with ideal experimental design and array normalisation, some residual technical noise will remain. It is common to use multi-variate techniques such as principal components analysis (PCA) to identify batch-effects and then to use specialised batch-effect removal software to adjust the data . Given tThere are caveats with batch-effect correction of methylation data. It is prudent to consider sources of sample-wise or feature-wise biological epigenetic variance which is potentially unrelated to the main experimental factor. If the source of variance has high population prevalence, it will often present by chance with unequal representation across each batch. If the biological variance is undeclared, batch-effect correction methods will naïvely mistake this as array feature technical variance and moderate batches with unequal representation towards the global mean. In DNA methylation studies, obvious sources of sample-wise biological variance are gender and cellular composition. In females, one of the X chromosome copies is inactivated  and therA further caveat is the choice of methylation metric. The quantification of methylation can be expressed as the log-transformed ratio of methylated over unmethylated signal (M) or the ratio of methylated over total (methylated plus unmethylated) signal (β) . It is iTo characterise batch-effects on Infinium Methylation BeadChip arrays, we took advantage of two of our in-house datasets studying the epigenetics of the developmental origins of health and disease (DOHaD) in neonates and employed two complementary correction methods; our batch-effect removal software, Harman , and theThe scale of these experiments and the careful experimental design allowed a great opportunity to study the nature of batch-effects on Infinium Methylation arrays. Our blocked design allows orthogonality between biological variance and technical variance giving us the best opportunity to identify and eliminate batch-effects. Importantly, this lack of confounding allowed us to best identify which probes are most susceptible to batch-effects and to characterise the factors contributing to them. To understand the reproducibly of our findings, we considered a further three large public datasets and for each of the five datasets, we generated sets of erroneously corrected and batch-effect susceptible probes and created a reference matrix for all 450K and EPIC probes. This reference matrix will allow investigators to identify erroneously corrected and batch-effect susceptible CpG probes in their own EWAS projects.For the EpiSCOPE study , DHA supSimilarly, the BFiN study  employedThe Infinium technology incorporates a number of control probe families to measure the efficiency and quality of the many steps in the protocol (the control classes are described by Illumina in their BeadArray Controls Reporter Software Guide document). Technical effects were evident across particular slides of both the EpiSCOPE and BFiN datasets. There was little commonality in the nature of these technical effects across the two datasets.Across the EpiSCOPE 450K data, we observed slides 9 and 17 had outlier probes for the staining controls with reduced fluorescence in the expected high intensity biotin beads Fig. a. Slide Within the BFiN EPIC data, a pronounced difference between each superbatch was observed. Slides 13–22 (the entirety of superbatch 2) had large increases in intensity for the Type I unmethylated control probes Fig. : Fig. S4Across the green Cy3) and red (Cy5) signal intensities, we observed notable dye bias on both the 450K and EPIC array designs. For Cy3, there was consistently lower mean fluorescence intensity and less variability than Cy5  typically had more or less Cy3 and Cy5 signal and a reduced fraction of positively detected probes .A total of 12 preprocessing methods were used to normalise the Infinium BeadChip data. Some of these methods incorporate dye bias correction within the process and some can accept data previously corrected for dye bias. The normalisation methods fall into three broad groups: raw preprocessing, within-array and between-array methods. Raw preprocessing directly translates Cy3 and Cy5 intensities into methylation and unmethylation signal, so there is no correction for probe design or dye bias. Within-array methods consider factors such as probe type and background correction and adjust each array individually. The six methods used were Subset-quantile Within Array Normalisation (SWAN) , ExponenFor the ten methods that process and return methylation and unmethylation channel data, we examined the removal of position or dye bias Fig. : Fig. S5For the between-array normalisation methods, we found Illumina preprocessing method scales all the fluorescence intensities from arrays towards an array from row 1. This scaling removes obvious position and dye bias from the data with a small amount of dispersion in array means remaining. Dasen combines background adjustment with a between-array normalisation method that is applied separately to methylated and unmethylated channels further subdivided into Type I and Type II probes. Dasen does not perform dye bias correction, so it is reasonable to also normalise data previously corrected by noob. Dasen moderated the means of all the arrays to be the same so no dispersion of BeadChip means remained. A large difference in fluorescence intensity still existed between the methylated and unmethylated channel but this disappeared with the use of Dasen in combination with noob. The ENmix authors developed a quantile normalisation method which can be run on ENmix corrected data. This hybrid ENmix-quantile normalisation approach, like the Dasen and noob combination, also equalised the methylated and unmethylated fluorescence intensities. Functional normalisation is typically coupled with prior noob background correction. The method extends quantile normalisation and only removes variation explained by a set of covariates associated with technical variation, such as the first two principal components of Infinium control probes. This PCA-based approach has similarities to Harman batch-effect removal but is more limited in scope. Functional normalisation returned results similar to Illumina preprocessing; however, there was less position bias.In summary, the use of preprocessing to remove probe type, background and dye bias was highly effective in removing much of the obvious glass slide position bias, with methylated and unmethylated signal largely equalised. The means of the methylated and unmethylated signals could be further moderated together using between-array normalisation methods.Unsupervised learning via principal component analysis (PCA) was used to examine global methylation patterns and determine the impact of different normalisation methods on the data, to gauge the influence of biological factors and to identify batch-effects Fig. . CoordinTo identify and remove batch-effects using Harman or ComBat, a batch variable needs to be declared to the algorithm, as well as sources of biological variance that the algorithm should seek to retain. The EpiSCOPE data PCA analysis illustrated that arrays are often separating in groups composed of the sets of 12 arrays on the same glass slide, so we may consider this to be a ‘batch’. The superbatch structure would be each of the six processing runs. With the balanced design of the experiment, there was a near equal representation of gender and DHA supplementation across each slide. For Harman, the experimental variable to keep was declared as a compound variable of gender with DHA supplementation, while with ComBat, gender and DHA supplementation were the two covariates specified in the linear model. For both batch-correction methods the largest source of technical variation to remove was slide number Fig. a, b. A mThe BFiN data PCA analysis showed the greatest structure in the data due to technical effects was the processing run Fig. d, e and As observed from PCA plots Fig. a, d, HarOn both the 450K and EPIC array formats, Type I probes were found to require far less batch correction than Type II probes Fig. . This fiIt is expected that normalisation methods accounting for bias due to factors such as colour, position and probe type should need less correction for variation across slides. The within-array preprocessing methods of ENmix, noob and the combination of noob and SWAN or BMIQ were effective in shifting probes requiring a moderate adjustment with raw preprocessing to the low adjustment group . For the between-array methods, the noob and Dasen combination or the ENmix-Quantile methods were effective at increasing the proportion of probes requiring low adjustment. The use of Dasen (without the addition of noob) was particularly effective in reducing the number of probes in the high adjustment group Table .For the remainder of our analyses, noob-normalised data were used. The noob method has good performance in correcting for batch-effect and underlies, or can be combined with, several other normalisation methods. It also makes few assumptions about the data and is a within-array method, so is suitable for experiments with high biological variation, where quantile normalisation might not be appropriate.The distribution of β at particular CpG sites may be modal in nature, which results in a clustered methylation pattern across samples. In practice, clustered methylation profiles can be due to technical or biological factors, and batch correction should ideally remove the former but preserve the latter. As biological variance to keep is declared per sample, rather than per feature, batch-effect removal software is prone to erroneously attributing methylation clustering to technical factors. When the distribution of biologically relevant clustered methylation is unbalanced across batches, then batch-effect removal software will inappropriately seek to converge the means of each batch. It is important to identify the CpG sites subject to such erroneous correction as this adjustment can profoundly destroy biologically meaningful clustering of the data. Which CpG sites naturally exhibit clustered methylation in populations is not well characterised, so a data-driven empirical approach was employed to find them.k-means clustering method was used to identify multi-modal features in noob-normalised data, with each cluster having at least 5 samples and a β difference between the cluster centroids of 0.1. When first defining the number of clusters for each probe, samples arising from slides with the greatest batch-effects  were set aside to reduce the impact of technical factors inflating the number of clusters. For each probe, the optimal number of clusters (k) was identified using Bayesian information criterion (BIC). Next, the previously removed samples were added back and clustering was undertaken again using the previously determined value for k. For each multi-modal probe (k > 1), the association between gender, batch, superbatch and cell composition was examined using statistical tests (described in Methods). Clustered methylation can often be due to allele-specific methylation (ASM), so for autosomal CpG probes with 2 or 3 clusters, we examined if the assortment across clusters fit with expectations from population genetics by employing a test for deviation from Hardy–Weinberg equilibrium (HWE). For all the described tests, a stringent FDR-moderated cut-off of p = 0.001 was used for establishing associations.To investigate, an optimal univariate X or Y chromosomes . Only 281 (1.3%) of probes clustered due to variability in the immune cell component, while a total of 1477 (6.6%) probes associated with batch and none with superbatch. The association with batch was expected to be low as the cluster discovery stage excluded the most batch-effect prone slides (further details in Methods). A total of 2011 (9.0%) of probes were cross-hybridising probes documented previously [For the EpiSCOPE 450K data  were also associated with gender in the EpiSCOPE data. Only 2 probes associated with batch (slide number), whereas 1481 associated with superbatch. A total of 1813 were cross-hybridising probes, and 476 remaining probes could not be associated with any of the factors considered.The distribution for the 80,752 clustered probes in the BFiN EPIC data was 76,041, 4588 and 123 for clusters of 2, 3 and 4, respectively  of features should be observed after correction. A simple reduction in total variance cannot be used as a metric, as batch correction may highly disrupt biologically meaningful clustering but will reduce the overall dispersion of the data. Instead, the metric needs to be generalised for probes with either a unimodal or multi-modal distribution. For this purpose, we created a cluster-aware dispersion metric.For the CpG features which form a multi-modal distribution, partial sums of squares were computed for each individual cluster using the dispersion from the mean for the members of a given cluster. The partial sums of squares were then collated across clusters to form a sample variance (as described in Methods). This modified calculation of sample variance will account for both the removal of assumed technical variance by Harman or ComBat and the preservation of a biologically meaningful clustering pattern. The log-base-2 of the ratio of sample variance precorrection over post-correction  was used as an empirical measure that batch correction was performing on multi-modal probes as intended. An LVR > 0 signifies that variance was inflated for a given probe after the application of the Harman or ComBat methods, whereas an LVR < 0 demonstrates that batch-effect correction is reducing the variance as intended.We observed that in instances of unintended removal of biologically meaningful methylation clustering Fig. , such asIn instances where a probe had batch-effects removed as intended, both the overall standard deviation (SD) was lower, as well as the LVR falling below 0. Figure The above examples illustrate the need for a discovery-based approach. We found the LVR statistic was particularly useful at identifying CpG sites having biologically relevant clustered methylation that should not be subjected to batch-effect correction (erroneously corrected probes). When applying the LVR statistic to identify probes prone to batch-effect (batch-effect susceptible probes), we found that fully methylated or unmethylated CpG sites often had very small corrections made to them by Harman or ComBat, but given the initial small variance, this resulted in large changes in ratio. The LVR statistic was combined with the mean difference between corrected and uncorrected data to correlate changes in variance and shifts in beta values Figs. , 8. A shTo classify erroneously corrected and batch-effect susceptible probes, we used a cut-off of 50% variance increase (log2(1.5), LVR = 0.584) or decrease (log2(1/1.5), LVR =  − 0.584), respectively, and mean β shifts of at least 0.01. How these cut-offs interacted with known clustered methylation associations was also characterised Fig. . As antiAnalysis of our unconfounded high-quality 450K and EPIC data established two sets of probes: one that was prone to batch-effect and another erroneously modified by batch-effect algorithms. It is useful to further explore the generality of these sets. Inclusion of further data from different studies and geographies may allow discovery of methylation clustering associated with less common SNPs or certain populations, and batch-effect susceptible probes needing significant correction in multiple datasets. To explore the universality of our findings, we searched for additional large 450K and EPIC datasets with these selection criteria: (1) hundreds of samples and an EWAS design, (2) with raw IDAT files in the public domain, having (3) the original Illumina Sentrix identifiers to enable the study of slide and positional effects, with (4) the experimental variable(s) and gender made known, such that biological variance to preserve can be declared to the batch-effect software, also (5) with reasonably subtle phenotype to make technical factors obvious and finally (6) the slide identifier and biological phenotype not being overly confounded.For the 450K array validation set, we selected an 845 participant (657 women and 188 men) methylation sub-study of peripheral blood as part of the European Prospective Investigation into Cancer and Nutrition , a molecular epidemiology project on diet and cancer . For EPIThe 450K EPIC-Italy cohort was divided across 72 slides. The control probes suggested a reduction in the quality of the data after slide 28, with many slides showing unfavourable control probe intensities across the broad range of sample dependant and independent control sets . In each of the three cases, the batch-effect variable specified was the slide identifier.The combination of mean β shift and LVR was used to identify probes shifted substantially by batch correction and also exhibiting appreciable decreases in LVR (batch-effect susceptible) and increases in LVR (erroneously corrected)  with cell composition in one or more of the datasets. This cell composition set was removed as erroneous correction due to unbalanced within-batch sample cell composition is particular to each study and driven by the nature of the biosample. In particular, the BFiN saliva samples and NOVI buccal swabs are a mixture of epigenetically distinct immune and non-immune cells, resulting in a large increase in probes having a multi-modal distribution. While the cell composition differences were modelled and declared to the batch-effect algorithm, this may not be sufficient to prevent erroneous correction in all instances.A total of 427,160 probes were cross-examined across the five datasets; this constitutes 452,453 probes common to all the datasets, less the 25,293 multi-modal distributed probes having a strong association  of probes are batch-effect susceptible in at least one of the datasets; however, only 15,094 (3.5%) are batch-effect susceptible in at least 4 of 5 datasets and 4,649 (1.1%) in all datasets examined  in at least one of the datasets, 1620 (0.4%) erroneously corrected in at least 4 of 5 datasets and 856 (0.2%) in all datasets examined  and has a multi-ethnic genetic background with 22% African American, 7% Asian and 7% Hawaiian or Pacific Islander background. However, the number of unique probes (144) was the lowest of all the five cohorts  of these are directly at the site of a SNP and another 20 (2.3%) have the measured CpG site within 10 bp of a SNP.With large EWAS designs, we suggest that beta values should be characterised empirically for clustering and for changes in variance before and after batch correction using the LVR statistic. However, this approach is not suitable for small studies as sufficient arrays are required to identify clusters. The need for larger datasets is magnified for ASM-associated clustering involving SNPs with small minor allele frequencies. Therefore, we provide reference matrices containing the LVR statistic and mean β differences  for all the arrays examined in this study , the number of CpG sites internal to the probe and probe melting temperature (Tm).Previously, Chen et al. identified a list of 29,233 probes in the 450K design which are highly homologous with 47–50 bases matching to a cross-reactive target . Often tp < 2.2e−16). Interestingly, the sets were enriched for those Type I probes having 2 or less internal CpG sites and Type II probes having no internal CpG sites  and 2901 (62.4%), respectively, of the probes universally considered batch-effect susceptible, whereas they were 27.4% and 72.6% of the total set of 427,160 probes. There is a significant bias towards Type II probes being batch-effect susceptible in all sets (Fisher exact A relationship between sensitivity to a batch-effect and probe melting temperature (Tm) could also be found for the EpiSCOPE and NOVI datasets in particular Fig. . While mIn summary, probe batch-effect susceptibility is multi-factorial in nature and was strongly associated with all the four factors examined. We note the low Tm set is largely different to the cross-hybridisation and multi-mapping sets, with only 198, 98 and 414 probes shared between the Benton, Chen and all sets, respectively. The set of batch-effect susceptible probes described here has overlap with the previously published sets described by Chen et al. and Benton et al. but is discrete.To gauge the impact in the literature of batch-effects on the outcomes of EWAS studies, a search was conducted across PubMed for appearances of the 4649 probes identified as batch-effect prone in all the 5 studies examined here. The R library easyPubMed (2.13) was used to query titles and abstracts in PubMed  for the In an EWAS considering Parkinson's disease, Moore et al.  listed cAll three examples had batch-effects readily observable via visual examination in the 5 datasets considered here. This illustrates the importance of plotting β ordered and coloured by slide number as a diagnostic to find potentially spurious associations.The Illumina HumanMethylation array is a popular epigenomic technology, and certainly the technology of choice for EWAS given the coverage, cost per unit and overall accuracy of the methylation calls. However, there are known small subsets of probes which are problematic and may give rise to false positive or negative associations , 38.Using high-quality data with a balanced-block design from the EpiSCOPE and BFiN cohorts, this study sought to identify which probes are prone to batch-effects, to investigate the factors that contribute to batch-effects and to characterise the effects of various preprocessing steps and batch-effect procedures. We found that batch-effects are predominantly linked to larger processing batches but using slide identifier as a batch variable is sufficient to capture and correct for batch-effect. Despite the arrays being run in service facilities by experienced operators using liquid handler robotics, multi-channel pipettes and other methods to control for uniformity, some batch-effects are persistent. There is also technical variance associated with position on each slide, but this can be largely managed by appropriate preprocessing methods.Across the two studies, we identified sets of batch-effect prone probes, the optimal preprocessing steps to reduce batch-effects and the factors that may have contributed to the technical variance observed in the data. The nature of the batch-effect was different in each dataset, with many of the troublesome probes not overlapping. To validate and further generalise our observations, we considered a further three large EWAS datasets from the literature. Consideration of all five datasets confirmed that the nature of the batch-effect was different in each experiment; however, there was a consistent set of 4,649 batch-effect prone probes that needed a high amount of correction. Alarmingly, we found three published EWAS studies that had reported one of these batch-effect prone probes as a top CpG site of interest.For future studies, to assist investigators in eliminating batch-effect prone probes we provide reference data characterising the batch-effects observed across the 2308 450K and EPIC arrays investigating in this current study. This reference data will have utility for anybody undertaking an EWAS. Acknowledging that the exact character of batch-effects is unique to each study, troublesome probes are not provided as a final list, rather a set of reference data specifying the moderation required for each probe across each of the five studies considered here. This matrix will allow simple identification of probes commonly exhibiting high levels of technical variance across multiple studies, including new studies.Also, as part of this investigation, we also uncovered and characterised a set of probes which should not be batch-effect corrected. These erroneously corrected probes have biologically meaningful clustering of methylation which cannot be declared a priori to current batch-effect removal tools, and this biological variance is erroneously attributed as technical variance. While it is common to remove probes associated with SNPs , we demoThis work also illustrates a process to minimise technical variation in methylation data. In agreement with prior recommendations, we suggest the first and foremost step to address this is careful study design, where the biological factors of interest are distributed across batches . Next, aMany comparisons of Infinium preprocessing methods exist in the literature. The value of this current comparison is the focus on technical variance in an EWAS context. EWAS often consider subtle biological phenotypes with small effect sizes, so technical variation (batch-effects) can be particularly troublesome. In studies with large between-group effects, such as cancer and normal tissue, some batch-effect can be tolerated as the biological variance is much greater than the technical variance. The metric used to compare preprocessing methods was maximal probe-wise β difference, a measure of residual technical variance remaining after processing. There was some overlap with the findings of previous comparisons. Shiah et al. compared 11 preprocessing methods on a large 450K prostate cancer dataset and considered technical replicate variances and differences, within-batch clustering and inter-array correlations. They found Dasen and noob to be preprocessing methods which minimised technical differences . Liu andIf batch-effect correction is to be employed after preprocessing, then multi-variate visualisation, such as PCA or multidimensional scaling, should be used to understand global patterns in the data and determine the largest sources of covariance. Also, as recommended by others , cell-coWe show that the ComBat and Harman batch-effect removal methods are largely comparable at the global scale. ComBat offers advantages in more complex model specification and allows for multiple categorical or ordinal variables, whereas Harman only allows a single categorical variable. Harman can remove or preserve multiple factors in one pass using compound variables. In principle, Harman should preserve more biological variance as it optimises for maximal preservation of biological variation when removing batch-effect. Consistent with the conservatism of Harman, we find that ComBat has more probes with maximal probe-wise β difference in the high moderation set (> 10% β moderation between batches). Over-correction can potentially introduce false positive findings. It has been found that while ComBat could remove contrived batch-effects introduced into randomly generated data, it also resulted in profound inflation of Type I error in certain use cases. In balanced or random designs, the degree of false positive results was reduced by increasing sample numbers. However, the unbalanced simulation showed increasing false positive results with increasing sample size . This isGiven the caveats and potential shortcomings identified here of applying batch-effect correction to EWAS data, some investigators may dismiss the use of batch-effect correction. However, if no correction is applied, this leaves a study open to false positives as a result of batch-effect. Investigators might consider using post hoc analyses, such as Cook’s distance (Cook’s D), instead of batch-effect correction to identify spurious associations driven by outlier datapoints with high leverage. Cook’s D is particularly effective at identifying spurious associations as a result of rare ASM events due to the large β change within individuals harbouring that SNP. However, batch-effects are typically more subtle with smaller changes in β and all the arrays within a batch moving as a group. Therefore, some spurious associations are likely to be missed by Cook’s D and other diagnostic tests which detect highly influential observations.Illumina Infinium BeadChips are empowering large epigenome-wide association studies in human populations. The technology is largely robust, but not ideal. We find that despite utilising various forms of bias removal and normalisation, some batch-effects persist. This residual batch-effect is associated with the day of processing, the individual glass slide and the position of the array on the slide. The individual array features most affected differed substantially across each of the five datasets considered. We also find probes that are erroneously adjusted by the correction procedure. We provide reference matrices of (1) CpG probes which are prone to high technical variance (batch-effect) and (2) CpG probes which are erroneously adjusted by batch-effect removal approaches. In addition, we suggest workflows and statistics which can help identify these two sets of probes in any moderately sized study.While it is important to limit technical variance and false positive results in a study, batch-effect removal approaches should be used with some caution and employ post hoc diagnostics to understand the impact of the correction and identify any erroneous correction of particular sets of probes. The best time to consider the control of technical factors is during the experimental design phase. If a study highlights differential methylation in probes requiring substantial correction, these putative CpGs should be validated by a second independent methylation quantification approach, such as next generation sequencing, pyrosequencing or MALDI-TOF mass spectrometry.Participant characteristics for DOMInO samples in the EpiSCOPE study with 450K methylation data are described in detail elsewhere , as is tThe EpiSCOPE HumanMethylation450 (450K) arrays were processed by the Australian Genome Research Facility Ltd (AGRF). DNA extracted from Guthrie card blood spots was bisulphite converted by the Zymo EZ DNA Methylation kit . All arrays with hybridised for 18 h at 48 °C with the oven temperature monitored with data loggers to ensure there were no temperature fluctuations during the hybridisation step. All arrays were scanned with same Illumina iScan® System. Extension and staining steps of the bead chip protocol were performed with a Tecan liquid handler robot.The BFiN cohort isolated DNA from infant saliva samples collected at birth using the Oragene OG-250 kit (Genotek). DNA was bisulphite converted and Human MethylationEPIC (EPIC) arrays processed at the Australian Cancer Research Foundation (ACRF) Cancer Genomics Facility in Adelaide, South Australia.For EPIC-Italy samples , DNA wasIn the NOVI study , genomicThe URECA  samples https://github.com/JasonR055/Batch_correcting_methylation_data). The EPIC-Italy and NOVI study originating data were downloaded from the Gene Expression Omnibus (GEO), with the Bioconductor GEOquery library (2.58.0) used to download the phenotype data and the raw IDAT files downloaded via FTP. All files were preprocessed and normalised using Bioconductor (3.12). The binary IDAT files were read into R using minfi (1.36.0) with preprocessing via the raw, SWAN, noob, Illumina and Functional normalisation methods implemented in minfi, the Dasen and BMIQ methods from the package wateRmelon (1.34.0) and ENmix from ENmix (1.26.6). Cell composition estimates as the authors of the EpiDISH package (2.6.0) used this for their reference generation. The ‘epidish’ method within the EpiDISH library was used to estimate the fractions of immune and epithelial component of the blood, saliva and buccal samples. We used the blood fraction and epithelial, fibroblast and immune component reference files supplied by the authors in their paper [All of the Infinium methylation data across the projects was reprocessed for this current work from raw IDAT files, with data analysis performed in the R statistical computing environment (4.0.3). All the scripts for the entire analysis are available in a Github repository (ir paper . BMIQ-noβ = Meth/(Unmeth + Meth)) or M values (M = log2(Meth/Unmeth)), Meth = 0 yields β = 0 and M =  − ∞, and Unmeth = 0 yields β = 1 and M = ∞. If both Meth and Unmeth signals are 0, then β and M are recorded as missing. The other preprocessing methods slightly moderate 0 values, yielding β approximating to 0 or 1 and non-infinite M values. For consistency across the preprocessing steps, values were modified to eliminate the generation of infinite M values. After normalisation, β were extracted and shifted from exactly 0 or 1, to approximate 0 or 1 by the ‘shiftBetas’ function in Harman. If both Meth and Unmeth signals were 0, these were changed to β = 0.5, such that M = 0 when transformed using the ‘logit2’ function of minfi. Missing β were also converted to β = 0.5 and upon logit transformation will become M-values of 0. This is consistent with the approach of SWAN. A very small amount (sd = 1e−8) of random normally distributed noise was also added, as features having every M-value exactly 0 will terminate ComBat with an error due to the variance also being 0. This strategy was also used for the EPIC array probe cg06180910, which was found to have every M value being 0.Small sets of probe values were also moderated to handle particular rare edge cases. For example, it is possible for raw, Illumina, Dasen and Functional normalisation to produce values of exactly 0 for one or both of the methylated (Meth) and unmethylated (Unmeth) signals. When processed into betas  and the ComBat function in the Bioconductor library sva (3.38.0) were applied to data resulting from each normalisation method. For each, the default settings were used. For Harman, the default confidence limit of 0.95 implies that Harman will remove technical variance across each slide, with the probably of also removing biological variance arising from gender and treatment effects on DNA methylation constrained to 0.05. Harman corrected PCA values were transformed back into corrected M matrices using the ‘reconstructData’ function. For both Harman and ComBat, the returned corrected M matrices were transformed into β values using the ‘ilogit2’ function in minfi.k). The data were then re-clustered with the top two values of k and specifying that each cluster must have at least 5 samples with a minimum distance between cluster centroids of 10% methylation (β difference of 0.1). The largest value of k meeting these criteria was retained. A total of 8 and 11 CpG probes on the 450K and EPIC arrays, respectively, had computed optimal values of k above 4. These were manually recoded as k = 4. Clustering was then repeated with the inclusion of all samples and using the optimal value of k for each probe.An optimal univariate clustering method provided in the ‘Ckmeans.1d.dp’ R library (4.3.3) was used to discover multi-modal features. In the initial cluster discovery step, to reduce the impact of technical effects inflating the number of clusters for each array feature, samples from the 450K slides 1, 5, 9, 17 and 25 were removed and similarly, slides 14–22 left out for the EPIC data. The Bayesian information criterion (BIC) statistic was used to select the two most optimal cluster numbers  procedure of Benjamini and Hochberg [p value < 0.001 was used to classify a probe as associated with a factor. This cut-off was determined after visual examination of the distributions of the returned p values. Modal probes were further annotated as being on chromosome X or the site of a common single nucleotide polymorphism (SNP). The ‘snp151Common’ table from UCSC was used for SNP annotation. This is table of SNPs from dbSNP (version 151) having a minor allele frequency of at least 1% in any of five super-populations. Also, matches to the list of potentially cross-hybridising as determined by Chen et al. [Modal CpG probes were examined for associations with several biological factors and batch-effect. To examine the association between cell composition and clustering, a simple linear model was used on the estimated proportions of neutrophils for blood data and total immune system cells for saliva or buccal swab data. The associations between clustering and gender, batch and superbatch were examined with Fisher exact tests. In the instance of superbatch and 450K data, Chi-square tests with simulated p values were used instead due to the computational limitations of Fisher exact on larger contingency tables. For autosomal CpG probes on with 2 or 3 clusters, departure from Hardy–Weinberg equilibrium was also examined using an exact test from the ‘HardyWeinberg’ R library (1.7.1). The Hochberg  implemenn et al.  were reck > 1), the sample variance was calculated by adding together the sum of squares for each cluster and then dividing by the total number of samples, less one.The sample variance in β for each probe was calculated for the original and Harman and ComBat corrected data. In instances where the methylation data for a given probe were clustered  was used to estimate the melting temperature (Tm) for each probe in the 450K and EPIC designs. This function uses the nearest-neighbour melting temperature estimates of Allawi et al.  but doesInfinium I has A and B probes, and the Tm for each was calculated and averaged. Infinium II probes will contain a degenerate R (purine) base opposite cytosine in a CpG context. So, Tms were calculated where all R bases were A or G, respectively. From these two Tm values, an average probe Tm was calculated.Additional file 1: Figure S1. EpiSCOPE study blocking plan. Across the 31 slides, 29 were completely balanced for gender with 6 male (coloured in powder blue) and 6 female (pink) replicates, while slides 30 and 31 were partially balanced with 5 females to 7 males and 5 females to 4 males, respectively. With regards to DHA supplementation, slides 1–23 and slide 30 were completely balanced with 6 replicates having DHA supplementation (square) and 6 controls (circle), with slides 24–29 having 5 controls to 7 DHA supplemented and slide 31, 5 controls to 4 DHA supplemented. Within a slide, the samples order was randomised to avoid correlation of position with gender or DHA supplementation.Additional file 2: Figure S2. Body Fatness in Newborns (BFiN) study blocking plan. Across the 22 slides, 15 were completely balanced for gender with 4 male (coloured in powder blue) and 4 female (pink) replicates. Slides 5, 6, 13, 14, 19 were partially balanced with 5 females and 3 males, while slide 12 had 3 females and 5 males. Slide 22 had the 3 remaining samples. The blocking was also structured by percentage bodyfat. As this variable is continuous, the samples were mapped to yield approximately equivalent distributions across slides. On the figure, the lowest, middle and upper tertiles of percentage bodyfat are represented by a downward-facing triangle, a lozenge and upwards-facing triangle, respectively. Within a slide, the samples order was randomised to avoid correlation of position with gender or percentage bodyfat.Additional file 3: Figure S3. Full set of control probes for the EpiSCOPE study. Further detail on the controls is provided by Illumina in the BeadArray Controls Reporter Software Guide document.Additional file 4: Figure S4. Full set of control probes for the BFiN study. Further detail on the controls is provided by Illumina in the BeadArray Controls Reporter Software Guide document.Additional file 5: Figure S5. BFiN fluorescence intensity slide positional effect is reduced with preprocessing methods. Infinium green (Cy3 dye) and red (Cy5 dye) fluorescent intensities are formulated into methylated (meth) and unmethylated (unmeth) signals. These meth and unmeth signals are used to calculate β and M values. If the 169 Beadchips in the BFiN set are grouped by row (R) position on the glass slide, there is evidence that the distribution of fluorescent intensities is associated with position. As for the EpiSCOPE dataset, this effect diminishes with preprocessing methods , estimated cell composition (Cell), chromosome X or Y location , remaining batch-effect after the most batch-effect prone slides were removed (Batch), a common single nucleotide polymorphism at the CpG site (SNP) or within 10 bp proximal (SNP_10 bp), cross-hybridisation prone (Crosshyb), gender (Gender) and probes in Hardy-Weinberg equilibrium (HWE). A proportion of modal probes could not be associated with any factor considered (Unknown). The two most common intersections were modal probes on the X chromosome and associated with gender (presumably as a result of X chromosome inactivation) and CpG sites at the site of a common SNP having ratios consistent with the Hardy–Weinberg principle for expected allele frequencies.Additional file 7: Figure S7. BFiN modal probe associations The upset plot for BFiN data. Refer to Additional file Additional file 8: Figure S8. Full set of control probes for the EPIC-Italy study. Further detail on the controls is provided by Illumina in the BeadArray Controls Reporter Software Guide document.Additional file 9: Figure S9. Full set of control probes for the NOVI study. Further detail on the controls is provided by Illumina in the BeadArray Controls Reporter Software Guide document.Additional file 10: Figure S10. Full set of control probes for the URECA study. Further detail on the controls is provided by Illumina in the BeadArray Controls Reporter Software Guide document.Additional file 11: Figure S11. Log-variance ratio and mean β shift plots for all five datasets. Refer to Fig. a), BFiN (b) as presented in Fig. c), NOVI (d), and URECA (e).Additional file 12: Figure S12. Intersection of batch-effect susceptible probes across the five datasets. The upset plot presents the number of batch-effect susceptible probes per dataset as well as their intersections. A total of 4649 probes were common to all datasets.Additional file 13: Figure S13. Intersection of erroneously corrected probes across the five datasets. The upset plot presents the number of erroneously corrected probes per dataset as well as their intersections. A total of 856 probes were common to all datasets.Additional file 14: Figure S14. Three batch-effect susceptible probes reported as top EWAS findings. The three probes, , show obvious batch-effect in all the five datasets considered. Each scatter plot compares methylation across slides (X axis) with the methylation β value (Y-axis). The datapoints are the totality of the arrays from each study, sorted and coloured by slide number. The panel is ordered column-wise from left to right as original, Harman-corrected and ComBat-corrected data. In each instance, the standard deviation (SD) of the data was reduced, the log-variance ratio (LVR) was considerably below 0 and the mean β shift (Shift) was greater than 0.01.Additional file 15. Table S1. Reference log-variance ratio and mean β shift values for the five datasets.


Background: General pathophysiological mechanisms regarding associations between fluid administration and intra-abdominal hypertension (IAH) are evident, but specific effects of type, amount, and timing of fluids are less clear. Objectives: This review aims to summarize current knowledge on associations between fluid administration and intra-abdominal pressure (IAP) and fluid management in patients at risk of intra-abdominal hypertension and abdominal compartment syndrome (ACS). Methods: We performed a structured literature search from 1950 until May 2021 to identify evidence of associations between fluid management and intra-abdominal pressure not limited to any specific study or patient population. Findings were summarized based on the following information: general concepts of fluid management, physiology of fluid movement in patients with intra-abdominal hypertension, and data on associations between fluid administration and IAH. Results: We identified three randomized controlled trials (RCTs), 38 prospective observational studies, 29 retrospective studies, 18 case reports in adults, two observational studies and 10 case reports in children, and three animal studies that addressed associations between fluid administration and IAH. Associations between fluid resuscitation and IAH were confirmed in most studies. Fluid resuscitation contributes to the development of IAH. However, patients with IAH receive more fluids to manage the effect of IAH on other organ systems, thereby causing a vicious cycle. Timing and approach to de-resuscitation are of utmost importance, but clear indicators to guide this decision-making process are lacking. In selected cases, only surgical decompression of the abdomen can stop deterioration and prevent further morbidity and mortality. Conclusions: Current evidence confirms an association between fluid resuscitation and secondary IAH, but optimal fluid management strategies for patients with IAH remain controversial. Identified citations had their titles and abstracts independently screened for the relationship between fluid therapy and IAH . We usedThe same two authors extracted the following data independently (as tabulated in the manuscript): (1) design and setting; (2) study participant diagnosis ; (3) type and amount of fluid administered; (4) IAP measurement in mmHg; (5) patient outcomes; (6) management/intervention of IAH or ACS.All relevant studies underwent a full-text assessment, and data were extracted into tables according to the study type/design. Studies and hypotheses on pathophysiological mechanisms are summarized as narrative text. One hundred and three of the 657 potentially relevant publications identified during the literature search were included .Among 764 unique citations, 103 studies enrolling 12015 critically ill adults, 107 critically ill children, and 104 animals met the inclusion criteria  5,18,19,118,119.From the analyzed and discussed studies, twenty included burn patients ,35,36,37Pooled analysis was not possible because of the heterogeneity in study populations and data, and the lack of details on IAP measurement techniques.Several above-cited studies have investigated the relationship between the volume of intravenous fluids administered and their effect on IAP. Most of these trials reported an association between the volume of intravenous fluids administered and the rise in IAP or the development of IAH.There are nine prospective studies in 434 burn patients ,24,25,26The reported prevalence of IAH ranged from 57.8% to 82.6% among patients with ≥20% total body surface area (TBSA) burned. Six of the nine studies reported ACS rates between 5.5 and 28.6% ,24,25,26A capillary leak is common in critically ill patients and leads to interstitial edema. This can be a particular problem in burn patients who require large volumes of intravenous fluid resuscitation. There is a significant correlation between IAP and resuscitation volume ,33,34. ABladder pressure measurements should be performed after infusion of more than 25 mL during the acute resuscitation phase . While IMortality rates in the prospective studies varied from 18% to 82.6% ,24,25,26Severe acute pancreatitis (SAP) is a disease with a 30% mortality rate and is characterized by a systemic inflammatory response, pancreatic necrosis, and multiple organ failure . ApproprThe incidence of ACS is lower when controlled fluid resuscitation is applied . This waThe type of intravenous fluid used is important in the prevention of IAH. Resuscitation with colloids resulted in less IAH compared with crystalloids . Using aEarly management of patients with SAP includes the initiation of CVVH to facilitate achieving a negative fluid balance and a subsequent reduction in IAH . AbdominIAH is associated with a poor prognosis and an increased need for surgical interventions with associated morbidity and mortality. The reported mortality rate varied between 7.3% to 31.6% .Trauma patients frequently pose a fluid resuscitation challenge since they often require rapid intravenous fluid administration to treat hypovolemia. This may include red cell concentrate (RCC) and platelets. Rapid fluid administration, together with reperfusion injury and activation of inflammatory mediators, leads to increased capillary permeability and an increased risk of developing IAH and ACS ,121. TheThe reported prevalence of ACS in the prospective studies varied between 8% and 36% (with a mean Injury Severity Score (ISS) range of 13–35) ,50,51,52Trauma patients that develop ACS, as a complication of massive volume loading, receive significantly more crystalloids and blood products . AggressBladder pressures should be checked routinely when resuscitation volumes approach 10 L of crystalloid or ten units of packed red cells . FollowiTrauma patients with ACS have more complications, mechanical ventilation, organ failure, and a longer length of stay. Mortality for this group varies between 6% and 54% ,52,120. Three prospective studies (188 patients) ,86,87, tThe observed incidence of IAH varied between 20 and 85%, and ACS developed in 25–28% of cases ,85. The In a prospective trial of 68 children, the replacement of crystalloid fluid resuscitation with albumin for refractory shock resulted in a smaller positive fluid balance, decreased morbidity, and improved outcomes . TreatmeDecompressive laparotomy (open abdomen with silo bag) has been previously successful in medical patients ,76. FluiACS is associated with a high mortality rate (52.8–77.4%) . MoreoveSix prospective studies  ,95,96,97Dalfino et al., showed how a positive fluid balance comprised one of three independent predictors for developing IAH (31.8%), together with baseline IAP and central venous pressure .There is a significant positive correlation between increased IAP with a positive fluid balance and decreased IAP with a negative fluid balance . A liberMakar et al., conducted an observational study in patients following open and endovascular repair of ruptured abdominal aortic aneurysms (rAAA). The results suggested that endovascular repair is associated with less intra-abdominal hypertension and host inflammatory response, less blood loss, blood transfusion, and total intraoperative intravenous fluid infusion compared to open repair . In 25 p2, massive fluid resuscitation and transfusions, severe hypothermia, and acidosis.Patients with high IAP have more frequent renal failure, delayed postsurgical weaning from mechanical ventilation, and worse outcomes . ReporteTwelve prospective studies see  5,104,1,115,116 The incidence of ACS varied between 2% and 12.9% ,106. TheFluid resuscitation and positive fluid balance are independent predictors for IAH . Body maMortality rates for IAH vary from 3 to 80% . The graWe found eleven animal studies, of which three were suitable, reporting on resuscitation and secondary IAH . Fluid rExisting studies and pathophysiological rationale support the association between fluid administration and IAH. However, current evidence does not allow clinicians to accurately identify specific fluid management strategies for patients with IAH. IAH often occurs in patients with sepsis, trauma, burns, and severe acute pancreatitis ,123,124.The origin of intravenous fluid therapy  dates baFluid movement through the microcirculation is partly determined by the imbalance between colloid osmotic and hydrostatic forces (Starling equation). Following this theory in IAH, an increase in microvenule blood pressure following venous compression reduces the difference in hydrostatic pressure, resulting in disturbance of microcirculatory fluid movement. The entire vascular endothelium is covered by the endothelial glycocalyx which consists of various proteoglycans, glycoproteins, and glycolipids. It which plays a vital role in the movement of fluids. The endothelial glycocalyx is semi-permeable to small molecules and ions and impermeable to molecules greater than 70 kDa ,130. TheExperimental models have confirmed that when maintaining a normal MAP of approximately 65 mmHg (using vasopressors), fluid movement and reduction of plasma volume are more pronounced when the capillary permeability is disrupted versus normal conditions . InteresThe incidence of ACS and IAH differs across various patient populations, but with a high mortality rate, regardless of the population.In severe burns, the systemic release of inflammatory and vasoactive mediators is responsible for a systemic capillary leak, intravascular fluid loss, and significant fluid shifts that should be managed with aggressive intravenous fluid resuscitation . The impSevere acute pancreatitis is associated with high mortality rates , and theIn patients with SAP, sepsis, septic shock, or severe trauma, shock-induced endotheliopathy (SHINE) is responsible for endothelial cell and glycocalyx damage . DisruptUnderstanding the different phases of intravenous fluid management  compared HES with Ringer’s lactate resuscitation in 41 patients with SAP. Resuscitation using colloids resulted in a lower IAP and reduced need for mechanical ventilation compared to those in which Ringer’s lactate was used . There iBalanced crystalloids may have advantages over 0.9% saline, possibly reducing inflammation, but no apparent effect on mortality or morbidity was demonstrated in patients with SAP ,154. TheSeveral studies  was able to keep the cumulative fluid balance in check with a significant drop in IAP, EVLWI, and rise in P/F ratio. This also resulted in faster weaning from the ventilator and improved survival compared to the matched control group [Only one retrospective study involving 114 patients incorporated IAP into the respiratory and fluid management concept. This study showed that using PAL treatment  resuscitation improves hemodynamics ,166,167.The 4 D’s of fluid therapy  should be considered during the administration of resuscitation fluids ,148. FluDecisions regarding the administration of intravenous fluids should be guided by functional hemodynamic measurements, such as pulse pressure or stroke volume variation. They should not be solely based on increased lactate, low MAP, or oliguria (<0.5 mL/kg/hour) ,170. WitAll of these factors should be carefully considered, to avoid the dangerous complications and vicious cycle of fluid accumulation, as illustrated in The ideal rate at which fluid is administered appears to depend on how much it takes to maintain perfusion, and thus there is no clear guidance from the available literature. This would largely depend on the systemic inflammation, rate of fluid extravasation out of the intravascular compartment, and effects on cardiac function. An RCT involving 60 patients with acute pancreatitis, but without organ failure, that received either aggressive (20 mL/kg bolus followed by 3 mL/kg/h) or standard (10 mL/kg bolus followed by 1.5 mg/kg/h) resuscitation with Ringer’s lactate solution. The rate of clinical improvement was more significant with aggressive hydration, and no patients developed signs of fluid overload . AnotherFluid requirements may be reduced by ascorbic acid, which has an apparent (osmotic) diuretic effect that may lead to hypovolemia and reduced inflammatory response . This waPeritoneal resuscitation (PR) corrected many of the physiologic derangements that lead to eventual organ dysfunction, including endothelial cell dysfunction, tissue ischemia, reduction in capillary blood flow, derangements in fluid exchange, and electrolyte handling, and increased inflammatory mediators. Studies in trauma patients have shown that PR was associated with accelerated abdominal closure, reduced abdominal complications, and reduced mortality . FurtherAlthough the literature search was broad, it was limited to those studies published in English. There were potential sampling errors in the search terms, and the search was limited to Scopus and PubMed. Negative studies are less likely to be published and hence would not have come to our attention during the literature search. The studies included were also heterogeneous in their sampled populations and data, making pooled analysis impossible. Future studies should broaden the search to include other languages.Final take-home messages on the relation between fluid resuscitation and IAH:There is a relationship between fluid resuscitation, fluid accumulation, and secondary IAH. This signal, from the limited number of RCTs, needs further confirmation.Crystalloids are associated with a more positive fluid balance and a greater likelihood of developing IAH compared to colloids or hypertonic solutions.Fluid resuscitation in IAH may preserve cardiac output, however, it does not prevent organ damage.Delivery of blood products in a 3:2 ratio of RCC: FFP (red blood cells: fresh frozen plasma) and 5:1 for RCC: platelets, may reduce MOF and infectious complications, and increase ventilator-free days .Fluid resuscitation leads to IAH and venous congestion (or venous hypertension), contributing to gut edema and diminished gut contractility.The relationship between fluid resuscitation, fluid accumulation, and secondary IAH holds in the setting of sepsis (capillary leak), severe burn injury, emergency surgery, and trauma with the presence of the deadly triad .Fluid removal with diuretics or CVVH may restore cumulative fluid balance and may reduce IAP. The time to initiate RRT in this setting remains unclear.Bladder pressure measurements should be performed after infusion of more than 25 mL during the acute resuscitation phase, and one should check for peak inspiratory pressures greater than 40 cm H2O.The presence of IAH is associated with a poor prognosis. The presence of ACS warrants escharotomy or surgical decompression of the abdominal cavity, while IAH usually responds to medical therapy .Intravenous fluid administration plays an essential role in developing IAH and ACS. Multiple pathophysiological mechanisms have been described, notably damaging the endothelial glycocalyx. Fluid balance has been identified as an independent risk factor in several clinical studies and can contribute to the development of IAH, venous congestion, gut edema, and diminished gut contractility. Evidence identifying the best resuscitation targets and management strategies regarding type, timing, and volume of fluids in patients with IAH is scarce. It is striking how there has been little advancement of new studies or data in recent years, as the bulk of the literature is more than five years old. Therefore, further research is required to improve insights into this topic.


Nepenthes x ventrata) on the germination of tomato (Solanum lycopersicum L.) seeds, elongation growth and cell viability of roots of tomato seedlings. The digestive fluid was collected from pitchers before feeding and four days after feeding; the pH and electrical conductivity of the fluid were determined. Undiluted and 50% fluids were used in the study. An inhibition of germination of tomato seeds, by around 30% and 55%, was respectively observed in 50% and 100% digestive fluids collected before and after feeding. Digestive fluid did not affect the root growth of tomato seedlings; a slight (6%) inhibition was only observed after the application of 100% digestive fluid from an unfed trap. The roots of the tomato seedlings treated with undiluted fluid were characterized by reduced cell viability. Reactive oxygen species (H2O2 and O2•−) were mainly localized in the root apex regardless of the used phytotoxic cocktail, and did not differ in comparison to control plants.The digestive fluid of pitcher plants is a rich source of enzymes and secondary metabolites, but its impact on higher plant growth and development remains unknown. The aim of the study was to determine the phytotoxicity of the digestive fluid of the pitcher plant ( Nepenthes x ventrata belongs to the Nepenthaceae family and is a natural hybrid of Nepenthes alata Blanco and Nepenthes ventricosa Blanco. This species is endemic to forests in the Philippines  were grown in the greenhouse under conditions of constant high humidity (60%) and temperature (28 °C); light was supplemented with sodium lamps to obtain a 16-/8-h day/night photoperiod. A mixture of acid peat, perlite and sphagnum moss was used as a growing medium and plants were watered with distilled water every other day. The traps of pitcher plants, immediately after opening, were covered with gauze to avoid contamination by accidental insects. Digestive fluid was collected from fed or unfed mature pitchers . Traps were fed with 40 μg hen egg white solution (1 µg µL−1) introduced with a pipette directly into a pitcher. Digestive fluids from fed traps were collected four days after feeding. The fluids (from fed and unfed pitchers) were shortly centrifuged , and the supernatants were transferred to the sterile tubes, frozen and used for biotests.Pitcher plants Before biotesting, digestive fluids from several traps were combined (fluid separately from fed and unfed traps) to maximize the volume of the phytotoxic cocktail. One portion of the fluid was boiled at 100 °C for 10 min (heat-treated fluid) and the rest was left untreated (crude fluid). Then, part of each fluid (heat-treated or crude) was diluted twice to obtain a 50% solution. The electrical conductivity and pH of phytotoxic cocktails were determined using a pH/conductivity meter .Solanum lycopersicum L. cv. Malinowy Ożarowski)  were surface sterilized with 0.5% sodium hypochloride for 10 min at room temperature. Then, seeds were rinsed three times with distilled water, and 8 seeds were placed on Petri dishes (ø 3.5 cm) filled with filter paper wetted with 2.5 mL phytotoxic cocktail or 2.5 mL distilled water (control). The culture was carried out in a growth chamber , in darkness at 20 °C for 3 days. Seeds were considered germinated when the radicle had emerged through the seed coat.Tomato seeds  were selected and transferred to Petri dishes (ø 3.5 cm) filled with filter paper wetted with 2.5 mL phytotoxic cocktails or 2.5 mL distilled water (control). Control seedlings and seedlings treated with digestive fluid were cultured in a growth chamber at 23/20 °C, 12-/12-h day/night regime, and a light intensity of 90 µmol PAR ma et al. . The roog at 4 °C, the supernatant was collected and absorbance was measured at 600 nm . For the positive control (100% cell damage), the roots were boiled for 10 min, cooled and then treated as described above. Three roots were used for one repetition. The concentration of the extracted dye was estimated from the standard curve prepared with Evans blue in 1% SDS and expressed as mg g−1 FW or % of cell damage. The data were means of three measurements from each of three sets of experiments.The viability of tomato root cells was determined using Evans blue staining . The who2O2 was carried out with 3,3′-diaminobenzidine (DAB) staining [−1) with 2 mM DMSO. Staining was carried out for 4 h at room temperature, in darkness.The histochemical localization of Hstaining . The roo2•− was performed according to Beyer and Fridovich [2•− was visualized as a deposit of a dark blue insoluble formazan compound.The histochemical localization of Oridovich  using niridovich . O2•− waImages of seedlings stained with DAB and NBT were taken with the TAGARNO FHD TREND digital microscope .Data were obtained in at least three independent experiments with at least three repetitions each. The plants for experiments were randomly selected from 25 individuals. Data were analyzed using Statistica Software. Mean values were calculated and SD was provided. After Anova, homogenous groups were evaluated using Fisher’s LSD post hoc test.2O2 and O2•−) distribution in the roots of tomato seedlings. The explanation of the phytotoxic potential of the digestive fluid requires further study, in which the compounds of the trap fluid, being mainly secondary metabolites, are determined prior to their use in phytotoxicity tests. The context of perturbation in ROS levels in acceptor plants as the target of digestive fluid action needs examination of the activity of the enzymatic antioxidants in the tissue of the acceptor plants.We demonstrated the negative, dose-dependent effect of the digestive fluid of the pitcher plant on tomato seed germination; whereas its impact on root elongation was less evident, but still significant. Application of the digestive fluid decreased cell viability but did not alter ROS (H


Lymph node (LN) metastasis is an important prognostic factor in colorectal cancer (CRC). We aimed to search for lymphatic vessels (LVs) in the lamina propria of 39 surgically resected in situ CRC, as well as to detect the presence of tumour burden in the regional LNs. We identified the presence of LVs in the mucosa of all tumours  using D240 immunostains. LNs were analysed by both H&E and a RT-PCR-based molecular method. All cases were pN0 with H&E, and the molecular assay detected the presence of low amounts of tumour burden in the LNs of 11/39 (28%) cases, with no clinical consequences at 1 to 5 years of follow-up. The amount of tumour burden in LNs has proven to be a prognostic factor. Despite the fact that pTis is considered to have little or no risk of LN metastasis, our results enabled to quantify the amount of tumour burden within LNs, which may help clinical management.Lymph node (LN) metastasis is an important prognostic factor in colorectal cancer (CRC). We aimed to demonstrate the presence of lymphatic vessels (LV) in the mucosa of in-situ (pTis) CRC, and of detectable tumour burden in regional LNs. This is an observational retrospective study of 39 surgically resected in situ CRCs. The number of LVs was evaluated in both pTis and normal mucosa using D2-40 immunostains. All LNs were assessed with both H&E and the One Step Nucleic Acid Amplification (OSNA) assay, and the results were correlated with clinicopathological features. D2-40 immunohistochemisty revealed LVs in the lamina propria of all pTis CRC (100%), being absent in normal mucosa. A median of 16 LNs were freshly dissected per patient, and all cases were pN0 with H&E. Molecular LN analysis with OSNA revealed the presence of low amounts of tumour burden in 11/39 (28%) cases (range 400 to 4270 CK19 mRNA copies/µL), which had no clinical consequences. This study demonstrates the presence of LVs in the lamina propria in 100% of pTis CRC, as well as the presence of low amounts of tumour burden in regional LNs, only detected by molecular methods. Given the prognostic value of LN tumour burden, its molecular quantification may help a patient’s clinical management. It has long been established that in situ colorectal carcinoma (CRC) has scant capacity for lymph node (LN) metastasis, which is supported by the hypothesis that the normal colonic mucosa is devoid of lymphatic vessels (LV) ,2. In adThe colonic mucosa has abundant capillary vessels in the lamina propria, ensuring a rich blood supply. Its lymphatic drainage is indirectly observed by the large number of LV in the submucosa. Nevertheless, LVs are not seen in normal colorectal mucosa. Fogt et al. used D2-40 immunohistochemistry (IHC) to seek for the presence of LV in the normal colonic mucosa, adenomas, and invasive carcinomas. They found that LVs were absent in normal colon mucosa, but present in the lamina propria of in situ and invasive carcinomas . The samThe One Step Nucleic Acid Amplification (OSNA) is an RT-PCR-based molecular assay for cytokeratin 19 (CK19) mRNA detection. It is a quantitative and highly sensitive method, useful for the diagnosis of LNs metastases and quantification of the amount of tumour burden in the LN compartment. This method of LN assessment has been validated for the analysis of sentinel LNs from breast carcinoma, as well as for LN staging in CRC ,8. In thThe purpose of our study was to demonstrate the presence of LVs in the colorectal mucosa of in situ CRC, and to determine both the capability of tumour cell seeding into regional LNs, and the ability to detect and quantify the amount of tumour burden within regional LNs.®, Eiken, Japan). Among all patients included, we selected all pTis CRC. LN analysis from the resected specimens was performed with both H&E and OSNA. This is a retrospective and observational study from a single institution for molecular identification of LN metastases. From May 2012 to October 2018, we included 312 stage I to III CRC patients submitted to surgery after a diagnosis of carcinoma or unresectable adenoma, in the context of population-based CRC screening program using the fecal immunochemical occult blood test (FIT) ” ,13, noneThe study was approved by the Ethics and Scientific Committee of our institution (Ref. HCB 2012/7324). All patients signed and kept a copy of the informed consent document for participation in the study after the nature of the research was fully explained. Another copy was kept with the patient’s clinical files, and a third copy was kept in the Biobank files of our institution.Immunohistochemical staining with CK19 , CAM5.2 , and podoplanin (D2-40)  antibodies was performed with the Ventana Benchmark Ultra  on 2-micron tissue sections placed on FLEX IHC microscope slides, according to the manufacturer’s protocol, with 20 min incubation for each primary antibody . Immunos2 [We assessed the presence and density of LVs in both tumours and normal mucosa on the D2-40-stained slides. All pTis slides were first scanned at low power with an optical microscope  to find the area of the tumour with the highest density of LVs. Then, an LV count was performed using the 20× objective lens, corresponding to an area of 0.785 mm2 ,16. OnlyWe counted the number of intratumour tumour buds (ITB) present in the lamina propria of pTis with cytokeratin immunostains, using the classification of the International Tumour Budding Consensus Conference (ITBCC), i.e., low TB , intermediate TB , and high TB  . We furtLNs from pericolic and intermediate levels (D1 and D2) of pTis CRC were freshly dissected within 45 min after surgical resection, and were not separated into stations. Fresh dissection was performed as described by Rakislova et al. . BrieflyThe OSNA assay is a PCR-based quantitative amplification of CK19 mRNA. It uses the RT-LAMP  at 65 °C without previous purification steps. It is a fast and standardized method used for routine sentinel LN analysis in breast carcinoma, which has also been validated for CRC LN staging ,8,9. Thehttps://documents.cap.org/protocols/ColoRectal.Bx_4.2.0.1.REL_CAPCP.pdf, accessed on 26 January 2023). Both pathologists and surgeons were blinded to the molecular OSNA results, which did not interfere with the patient’s clinical management.In all patients, pathological LN diagnosis (pN stage) was performed using conventional H&E analysis, according to the American College of Pathology/TNM-UICC protocols   and 59% were males. Tumours ranged in size from 0.4 to 5.5 cm. Tumours ≥ 2 cm were arbitrarily defined as big. All tumours were low grade and most  were on the right colon. The CK19 immunostain resulted in positives in all pTis CRC. Patients did not receive adjuvant therapy and were alive without disease between 1 and 5 years of follow-up. Clinical and pathological characteristics of all cases are described in D2-40 immunochemistry performed on normal colorectal mucosa demonstrated the absence of LVs in the lamina propria in all cases, but presence next to the muscle fibers of the superficial part of the muscularis mucosae, without reaching the base of the crypts. Abundant LVs were present in the submucosa a. When assessing the presence of LVs of in situ CRC using D2-40 IHC, we observed LVs in the lamina propria of all tumours . We next quantified the number of LVs present in each tumour, which ranged from 1 to 7. We arbitrarily defined two groups: low-LV density when containing 0–4 LVs and high-LV density when containing 5–7 LVs b. We onlp = 0.217 and p = 0.923, respectively).Intratumoural tumour budding (ITB) was assessed with CK CAM 5.2. We divided ITB into two groups, ITB-negative (Bd0) and ITB-positive (Bd1 and Bd2). Most cases, 76.9% (30/39) had no tumour buds and were classified as Bd0. Nine cases (23.1%) were listed as ITB-positive , seven hA total of 648 LNs were dissected from 39 cases, with a mean of 16.6 LNs per patient. 556 LNs were freshly dissected and 92 (14.1%) were found post formalin fixation. Fresh LNs were analyzed by both H&E and the OSNA assay. All patients were pN0 by H&E. OSNA detected the presence of tumour burden in the LNs of 11/39 (28%) cases, with low TTLs (range 400 to 4270 CK19 mRNA copies/µL). There was no significant correlation of OSNA positive cases with age, sex, location, and LV density .Regarding clinical outcome, all patients were alive without disease, with a median follow-up of 49.62 months (range 13–86 months).This is a novel molecular study demonstrating the presence of tumour burden in regional LNs at very early stages of CRC. In all cases LNs were negative with H&E analysis (pN0), and the presence of low amounts of tumour burden within LNs was detected only by molecular methods. We also observed the presence of LVs in the lamina propria in all in situ CRC. In situ CRC are non-invasive carcinomas, considered to have limited risk of LN metastasis . NeverthTo our best knowledge, this is the first study including a series of surgical specimens of in situ CRCs in which LN assessment has been performed with both H&E and molecular methods. Further, LNs from normal colons and rectums are normally small-sized. Similarly, LN metastases from early CRC are usually small and located in LNs of ≤5 mm, which are difficult to identify. In this regard, Aldecoa et al. demonstrated that those LNs which are more prone to harbour tumour burden are those from the lymphatic basin which drain the tumour, usually located close to the tumour . AnotherIn our series, the presence of a low quantity of tumour load in regional LNs of in situ CRC had no clinical significance. In this regard, it is important to emphasize that it has been demonstrated that the TTL correlates with the pN, and that the amount of tumour burden in the LNs, or TTL, has prognostic value. Yamamoto demonstrated that the TTL increases with the pN stage of CRC, having 1550 copies/µL for pN0 cases, 24,050 copies/µL for pN1, and 90,600 copies/µL for pN2 cases ,26. MoleOne limitation of our study is that we have used half of the LN for the OSNA assay and the other half for H&E analysis, which may have induced a tumour allocation bias. Despite that, some tumour burden was identified in the part of the LN used for molecular analysis. Another limitation is that there was no statistical association between budding and vessel density/higher tumour burden by OSNA, or other clinicopathological features. Given the number of cases in our cohort, the analysis is probably underpowered.In agreement with previous reports, we have also confirmed the presence of LVs in the lamina propria of pTis CRC. In addition, we have demonstrated that tumour cells from in situ CRC can seed the LNs, probably in the form of isolated tumour cells or small groups of cells, which confer no additional risk for these patients. The relevance of this study is that molecular assays enable to quantify the amount of tumour burden present in the LN compartment, which has been demonstrated to have prognostic value. In the setting of pTis CRC, the TTL can help patient’s clinical management.


Here, we present ICG-based SWIR fluorescence molecular imaging for the highly-sensitive optical detection of breast and skin tumours in mice. As SWIR fluorescent molecular-imaging probes, we synthesized ICG–antibody conjugates, which prepared from anti-HER2 antibody (Herceptin), anti-EGFR antibody (Erbitux), anti-VEGFR-2 antibody (Cyramza), and anti-PD-L1 antibody (anti-PD-L1 ab). The present SWIR molecular imaging probes specifically accumulated to the breast and skin tumours, and their SWIR fluorescence images (>1000 nm) showed 1.5–2.0 times higher contrast than NIR tumour images taken at 830 nm. We show that the SWIR fluorescence imaging using ICG–antibody conjugates can be used for the elucidation of expression level of cancer-specific membrane proteins, HER2, EGFR, VEGFR-2, and PD-L1 in vivo. We also show that the SWIR fluorescence imaging enables quantitative analysis of the change in the size of tumour treated with an anti-cancer drug, Kadcyla. Our findings suggest that the SWIR fluorescence molecular imaging using ICG–antibody conjugates has potential to use for the optical diagnostics of cancerous tumors in medical and clinical fields.Recently, shortwave-infrared  fluorescence imaging has attracted much attention due to the higher contrast and sensitivity with deeper penetration depths compared to conventional visible and near-infrared (NIR) fluorescence imaging. For the SWIR fluorescence imaging, the development of fluorescent probes emitting over 1000 nm is necessary. So far, a variety of SWIR fluorescent probes based on single-walled carbon nanotubes, quantum dots, rare-metal doped nanomaterials, and organic dyes have been developed. However, there are a very limited number of biocompatible SWIR fluorescent probes, which can be used to biomedical applications. Among NIR and SWIR fluorescent probes, indocyanine green (ICG) is the only fluorescent dye approved by US Food and Drug Administration (FDA) for clinical use. Although ICG has a fluorescence maximum at a NIR region ( We present indocyanine green (ICG)-based shortwave-infrared (SWIR) fluorescence molecular imaging for the highly-sensitive optical detection of breast and skin tumours in mice. At present, there are a few number of SWIR fluorescent probes that can be used to the biomedical and clinical applications.7Fluorescence imaging is widely used for the visualization of molecular and cellular structures through labelling with fluorescent probes 7 Among the organic-dye based fluorescent probes, indocyanine green (ICG) is the only fluorescent NIR dye approved by US Food and Drug Administration (FDA), which is used in clinical fields.8 Although ICG is a traditional NIR fluorescent dye with a fluorescence maximum at ca. 830 nm, ICG can emit in the SWIR region.7 ICG is a most popular NIR fluorescent probe for non-invasive deep tissue imaging in animals9 and humans.8 In the clinical field, ICG is employed for diagnostic investigations of hepatic function10 and ophthalmic angiography.11 Although ICG is a NIR fluorescent probe emitting at ca. 830 nm, recent research has shown that ICG can also be used as a SWIR fluorescent probe for non-invasive deep-tissue imaging over 1000 nm in mice7 and humans.12,13 However, there are only a few reports of ICG-based SWIR fluorescence molecular imaging to visualize cancerous tumours in living system.7In the last few years, organic-dye based fluorescent probes with the low cytotoxicity have been developed for deep-tissue imaging in the SWIR region.14 or HER2 (16 and programmed death-ligand 1 (PD-L1).17 EGFR and HER2 are transmembrane tyrosine kinase receptors that are overexpressed on the surface of most cancer cells. VEGFRs are signaling proteins which play important roles in the growth of blood vessels in tumours (tumour angiogenesis).16,18 PD-L1 is a transmembrane protein that is overexpressed in several types of cancers, where PD-L1 plays a major role to allow cancers to evade the host system.19 PD-L1 can also be used as a biomarker for tumour imaging.Owing to the lower light scattering and autofluorescence in the SWIR region, SWIR fluorescence molecular imaging using ICG is expected to offer higher signal to background signals compared to conventional visible and near-infrared fluorescence imaging. As ICG-based SWIR molecular imaging probes, we synthesized ICG–antibody conjugates, which are prepared from human epidermal growth factor receptors (EGFR or HER2 ), and va20 anti-EGFR antibody (Erbitux),21 anti-VEGFR-2 antibody (Cyramza),22 and anti-PD-L1 antibody (anti-PD-L1 ab).23 These monoclonal antibodies are used as antibody drugs of cancer therapy for breast and skin tumours in clinical fields. By using the ICG–antibody conjugates, we conducted NIR and SWIR fluorescence imaging of breast and skin tumours in mice. Here, we show that the signal to background contrast in the SWIR tumour imaging is 1.5–2 times better than that of the NIR tumour imaging. The high contrast tumour images in the SWIR region results from the lower tissue absorption/scattering and autofluorescence in the SWIR region. We also show that the high contrast SWIR imaging enables the visualization of the expression level of tumour-specific membrane proteins in vivo. Furthermore, we show time-course SWIR fluorescence imaging for tumour shrinking by treatment with an anti-cancer drug, ado-trastuzumab emtansine (Kadcyla).24 Our finding suggests that the SWIR fluorescence imaging using ICG–antibody conjugates has potential to apply to the optical diagnostic of cancerous tumours in humans.As tumour-targeting probes, we used four types of monoclonal antibodies such as anti-HER2 antibody (Herceptin),in vivo.25 Antibody can be labelled with many types of fluorescent dyes (e.g. amine-reactive and sulfhydryl-reactive dyes).26 Since there are many monoclonal antibodies for cancer diagnostics and therapy,27 we can easily prepare molecular imaging probes by labelling the antibodies with fluorescent molecules. For example, amine-reactive fluorescent dyes such as fluorescein-5-isothiocyanate (FITC) and sulfhydryl-reactive dyes such as fluorescein-5-maleimide bind to amino groups and sulfhydryl groups of antibody molecules, respectively.26 In this work, we employed N-hydroxysuccinimidyl ester (NHS) derivatives of fluorescent dyes, Alexa488 and ICG for labelling the lysine residues of antibody molecules (Fluorescent dye and antibody conjugates act as fluorescence molecular imaging probes olecules . These N−1 cm−1 (at 280 nm), 71 000 M−1 cm−1 (at 495 nm), and 147 000 M−1 cm−1 (at 800 nm), respectively.28,29 The labelling efficiency was 50% for Alexa 488-Herceptin and 89% for ICG–Herceptin conjugates. For other antibody conjugates, the labelling efficiencies of the Alexa 488 and ICG dye were summarized in Fig. S1The labelling efficiency was estimated from the absorption spectra of Alexa 488-Herceptin and ICG-Herceptin , where t30 and breast cancer cell (KPL-4)31 were implanted. A431 and KPL-4 cells are the cancer cells established from a human epidermoid carcinoma and a human breast tumour, respectively.30,31 To check the expression level of the membrane proteins, HER2, EGFR, VEGFR-2, and PD-L1, we first conducted western blotting analysis for A431 and KPL-4 cells -4 cells . The resNext, we conducted fluorescence imaging for A431 and KPL-4 cells. For the cellular imaging, we used visible-emitting Alexa488–antibody conjugates instead of ICG–antibody conjugates, because of the low sensitivity of a conventional fluorescence microscope in the NIR region (<700 nm). We prepared Alexa488–antiody conjugates with Herceptin, Erbitux, Cyramza, and anti-PD-L1 ab. Alexa488–Herceptin stained the membrane surface of KPL-4 cell, and its fluorescence was much stronger than that of A431 cells . In the 7ca. 0.5%.32 SWIR fluorescence images of a capillary filled with an aqueous solution (2 μM) of ICG–Herceptin are shown in Recent research has proven that ICG fluorescence emission over 1000 nm can be used for the non-invasive deep-tissue imaging of brain and lymph vasculatures.To check the light scattering in the SWIR region, we detected SWIR fluorescence passed through an agarose gel. Although the SWIR fluorescence of ICG was very weak compared to its NIR fluorescence, higher signal to background contrast of the SWIR fluorescence images was expected due to the lower tissue scattering and autofluorescence in the SWIR region  and S5†.31 to nude mice. The diameter of a tumour was ca. 5 mm ca. 5 mm . NIR andca. 5 mm . Immedia−2), significant tissue autofluorescence was observed in the NIR region, while almost no autofluorescence was observed in the SWIR region over 1000 nm  contrast of the SWIR tumour image was 1.5 times higher than that of the NIR tumour image . The lowm Fig. S5.7Furthermore, we examined the difference in the image contrast of breast tumours stained by other types of molecular imaging probes, ICG–Erbitux, ICG–Cyramza, and ICG–anti-PD-L1 conjugates . In all ca. 2 mm to 8 mm in diameter). SWIR fluorescence images of breast tumours were taken three days after the injection of ICG–Herceptin (ca. 2 mm in diameter) was clearly detected by SWIR fluorescence. Since tissue autofluorescence in the SWIR region above 1000 nm was very weak, detection sensitivity of breast tumours by SWIR fluorescence was very high enough to be able to detect early-stage cancers which sizes are less than a few millimeters.To evaluate the detection sensitivity of tumours by SWIR fluorescence, we conducted SWIR fluorescence imaging for the different-sized breast tumours  and proteins.34 Angiogenesis plays an important role in tumour growth, and the increase in neovasculatures is usually observed with increasing the size of the tumour.34 Non-invasive imaging of angiogenesis in tumours is important for early diagnostic and for image-guided management of therapeutic regimens.35Tumours induce blood vessel growth (angiogenesis) by secreting various growth factors  exists at the periphery of a tumour (ca. 10 mm in diameter) exists both at the periphery and the inside of the tumour .a tumour , while te tumour . These r24 Kadcyla is an antibody-drug conjugate which is used for HER2-positive cancer therapy. Kadcyla comprises anti-HER2 antibody (Herceptin) linked to the anti-mitotic agent emtansine, which is a tubulin polymerisation inhibitor that interferes with mitosis, inducing apoptotic cell death.37Finally, we conducted SWIR fluorescence imaging of a breast tumour (KPL-4) treated with Kadcyla (ado-trastuzumab emtansine).in vitro experiments have shown that Herceptin cannot inhibit proliferation of the HER2-positive KPL-4 cell.38HER2-positive breast tumours were stained by ICG–Herceptin (0.2 mg). SWIR fluorescence of the breast tumour was clearly visualized two days after the injection of ICG–Herceptin, where the size of tumour was about 5 mm in diameter . In the ca. 830 nm). Although the SWIR fluorescence emission of ICG is much weaker than its NIR fluorescence emission, ICG–antibody conjugates has enough sensitivity for the SWIR optical detection of small tumours, which size is less than a few millimetres. Furthermore, we demonstrate that the SWIR fluorescence imaging using ICG–antibody conjugates is useful for the elucidation of the expression level of cancer-specific membrane proteins such as HER2, EGFR, VEGFR-2, and PD-L1 in vivo. Our findings show that owing to its high contrast images, ICG-based SWIR fluorescence molecular imaging is highly sensitive compared to conventional ICG-based NIR fluorescence molecular imaging.In this paper, we describe ICG-based SWIR fluorescence molecular imaging for the optical diagnostics of cancerous tumours in mice. We demonstrate that SWIR fluorescence images (>1000 nm) of breast tumours using ICG–antibody conjugates show 1.5–2 times higher S/B contrast compared to the tumour images taken in the NIR region (e.g. breast tumours) in humans.We also demonstrate that the SWIR fluorescence imaging using ICG–antibody conjugates enables quantitative analysis of the change in tumour size. Since the fluorescence emission of ICG from the tumours is stable over one month, ICG-based SWIR fluorescence imaging can be used for the evaluation of the effect of anti-cancer drugs. The results of this work show that ICG-based SWIR fluorescence imaging would be useful for the optical detection of cancerous tumors as well as for the optical evaluation of anti-cancer drugs in preclinical research. We believe that ICG-based SWIR fluorescence imaging has potential to use for the optical diagnostics of cancerous tumours , respectively. Heceptin, Cyramza, and Kadcyla were purchased from Chugai Pharmaceutical Co., Ltd . Erbitux was purchased from Merk Serono. Anti-human PD-L1 antibody was purchased from Bio Cell. Normal human IgG was purchased from FUJIFILM Wako Pure Chemical Corp. (Japan). Glutathione-coated PbS QDs (Em: 1250 nm) were prepared by the literature method.36 Intralipid emulsion (20%) was purchased from Sigma-Aldrich. Breast tumour cells (KPL-4) were kindly provided by Dr Kurebayashi . Skin tumour cells (A431) were purchased from RIKEN cell bank. Nude mice  were purchased from SLC Inc (Japan).In vivo NIR fluorescence imaging was performed with a fluorescence system (Bruker MS-FX PRO). In vivo SWIR fluorescence imaging was performed with a home-built wide-field microscope system.4Absorption spectra were recorded with a spectrophotometer . Fluorescence spectra were recorded with a spectrofluorometer . Fluorescence imaging of cancer cells were performed with a fluorescence microscope . 2CO3) of antibody , 30 μL of a dimethyl sulfoxide solution of Alexa488–NHS or ICG–NHS was dropwisely added. The coupling reaction was performed for 30 min at room temperature. The dye–antibody conjugates were purified by using a size-exclusion column  to remove unreacted dyes.Alexa488–NHS ester (1 mg) or ICG–NHS ester (1 mg) was resolved to 1 mL of anhydrous dimethyl sulfoxide. To an aqueous solution (0.01 M NaEx: 760 nm/Em: 830 nm) of ICG was detected first, and then proteins were stained with Coomassie Brilliant Blue . Antibody molecules were reduced by dithiothreitol (DTT).ICG–antibody conjugates were run on a 5–20% polyacrylamide gel  in Tris-glycine-SDS buffer, 200 V for 40 min. NIR fluorescence (−1) were measured at the emission of 830 nm and at the excitation of 785 nm, respectively. SWIR fluorescence images of a capillary (1 mm in diameter) filled with ICG–Herceptin conjugates (1 mg mL−1) were measured using a solid laser (laser power 2.5 mW cm−2) with the excitation of 785 nm. Images are taken by using a long path (>1000 nm) and band path filters . NIR fluorescence images of a capillary (ca. 0.5 mm in diameter) through an agarose gel  were measured with an EMCCD camera  using a band path filter (820 ± 15 nm). The exposure time of the camera was 100 ms. SWIR fluorescence images of a capillary (ca. 0.5 mm in diameter) through an agarose gel  were measured with an InGaAs CMOS camera . The exposure time of the camera was 30 s.NIR excitation spectra and fluorescence spectra of ICG–Herceptin conjugates . The cell lysates (24 μg) were separated by electrophoresis on 5–20% Extra PAGE One Precast Gel  at 200 V for 45 min. The protein was transferred to PVDF membrane by a Trans-Blot Turbo Transfer System (BIO-RAD). The membranes were incubated in 5% skim milk for 1 h at room temperature to prevent nonspecific binding. Then, the membranes were incubated in primary antibodies against HER2 , EGFR , VEGFR-2 , PD-L1  or beta-actin  for overnight at 4 °C. After washing with TBST, the membranes were incubated with a 1 : 2000 dilution of secondary antibody  for 1 h at room temperature. After washing with TBST, bands were visualized by treating the membranes with ImmunoStar LD (FUJIFILM) according to manufacturer's instructions and detecting the bioluminescence with LAS-4000 (GE).The cells were lysed with RIPA buffer  for 15 min on ice and centrifuged at 10 000×KPL-4 and A431 cells were seeded to cell culture dishes  and incubated in Dulbecco's Modified Eagle Medium (DMEM) with 10% fetal bovine serum (FBS) for overnight at 37 °C. Alexa488–antibody conjugates were added to the cell and incubated for 10 min at 37 °C. Then, the cells were washed with PBS four times and filled with PBS. Fluorescence images were acquired with a fluorescence microscope . The excitation and emission filters were 470 ± 20 nm and 525 ± 25 nm, respectively.7 cells per mouse) was transplanted to the ventral region of 5 week old female BALB/c nu/nu mice. After several weeks, a mouse bearing a tumour less than 10 mm in diameter was selected for imaging. For tumour imaging, two hundred μL of an aqueous solution of ICG–antibody conjugates (1 mg mL−1) was injected into a tumour-bearing mouse via a tail vein. For the imaging of a breast tumour treated with Kadcyla, Kadcyla (0.2 mg) was intravenously injected to a breast-tumour bearing mouse two days after the injection of ICG–Herceptin. Then, the image of a breast tumour was taken 0, 3, 6, and 9 days after the injection of Kadcyla. All animal procedures were performed in accordance with the Guidelines for Care and Use of Laboratory Animals of RIKEN and approved by the Animal Ethics Committee of RIKEN.A suspension of KPL-4 or A431cells  of nude mice were taken by using an in vivo fluorescence imaging system . Exposure time of an imaging camera was 30 s. SWIR fluorescence images  of mice were taken by using a home-built imaging system with an InGaAs CMOS camera  Exposure time was 30 s. A solid laser (laser power 2.5 mW cm−2) was used as an excitation light source of 785 nm. SWIR fluorescence images are taken by using a long path filter (>1000 nm).NIR fluorescence images (There are no conflicts to declare.RA-010-D0RA04710D-s001