Chondrilla caribensis, which hosts symbiotic cyanobacteria and lives in low-light environments. Although the sponge is net heterotrophic at 20 m water depth, photosynthetically fixed carbon potentially provides up to 52% of the holobiont’s respiratory demand. When considering the total mixotrophic diet, photoautotrophy contributed an estimated 7% to total daily carbon uptake. Visualization of inorganic 13C- and 15N-incorporation using nanoscale secondary ion mass spectrometry (NanoSIMS) at the single-cell level confirmed that a portion of nutrients assimilated by the prokaryotic community was translocated to host cells. Photoautotrophy can thus provide an important supplemental source of carbon for sponges, even in low-light habitats. This trophic plasticity may represent a widespread strategy for net heterotrophic sponges hosting photosymbionts, enabling the host to buffer against periods of nutritional stress.The ability of organisms to combine autotrophy and heterotrophy gives rise to one of the most successful nutritional strategies on Earth: mixotrophy. Sponges are integral members of shallow-water ecosystems and many host photosynthetic symbionts, but studies on mixotrophic sponges have focused primarily on species residing in high-light environments. Here, we quantify the contribution of photoautotrophy to the respiratory demand and total carbon diet of the sponge  Mixotrophy is a widespread and important nutritional strategy in terrestrial and marine ecosystems , from auSponges are a highly successful group of benthic invertebrates, found in abundance from deep-sea to shallow-water marine ecosystems . They arOur understanding of the contribution of carbon fixation by cyanobacteria to sponge nutrition has typically focused on sponges that dwell in shallow, high-light environments, particularly coral reefs , where tAssessing the role of cyanobacterial carbon fixation to host nutrition is complicated by the fact that photosynthesis and translocation rates are not necessarily closely coupled . ManipulChondrilla caribensis and assessed whether the sponge host benefits from the autotrophic assimilation of inorganic carbon and nitrogen by cyanobacteria. This common Caribbean sponge hosts a high density of symbiotic microorganisms  and nitrogen (NH4+) by (i) cyanobacteria, (ii) other prokaryotes, and (iii) sponge cells over time, confirming the translocation of symbiont-assimilated nutrients to the host. This holistic approach enabled us to comprehensively assess the contribution of symbiotic cyanobacteria to the mixotrophic diet of a sponge residing in low-light environments.Here, we estimated the contribution of photosynthetic carbon fixation to the respiratory demand and total carbon diet of the coral reef sponge , sponge ), includongiarum . It is congiarum  and is cChondrilla caribensis forma hermatypica [2 (mean ± SD throughout unless otherwise stated), with at least 5 intact oscula (outflow openings). Sponge individuals were stored vertically in sheltered wire cages on the house reef (15 m water depth) for between 1–2 weeks prior to experimentation, ensuring photoacclimation of all sponges to a light profile mimicking irradiances on vertical surfaces at around 20 m depth (Supplementary Table n = 3) were collected in situ at around 20 m water depth and subsequently assessed for microbial community composition (see Supplementary Methods).This study was conducted at the Caribbean Research and Management of Biodiversity (CARMABI) Research Station on the Southern Caribbean island of Curaçao from October to December 2019. Individuals of the sponge matypica  (PoriferP–E) curves were constructed for C. caribensis by measuring net oxygen fluxes ex situ at 7 increasing irradiance levels of natural sunlight (between 0 and ~800 μmol photons m−2 s−1) (n = 4). Sponge individuals were incubated in individual airtight 2-L chambers [−2 s−1, E0) and then sequentially removing the PVC tube and layers of cloth, from 6 layers to none (see Supplementary Methods).Photosynthesis–irradiance , Pmax is the maximum gross photosynthetic rate, Ek is the saturating irradiance coefficient, and Rd is the dark respiration rate (measured at E0), which is negative as oxygen is consumed. All photokinetic parameters are given in Supplementary Table Rates of net oxygen consumption or production at each irradiance level were calculated using the linear slope of oxygen concentration, and fluxes expressed as μmol Ofunction :1\documeC. caribensis was constructed based on typical irradiances received on vertical reef surfaces at 20 m water depth. To achieve this, we combined the P–E curves and a daily ambient light profile at 20 m with in situ natural diet incubations to determine photoautotrophic and heterotrophic daily uptake rates of carbon.A daily mixotrophic carbon diet for P–E curves to obtain hourly gross oxygen fluxes, which were summed to give daily gross primary productivity rates (Pg). Daily net primary productivity rates (Pn) were calculated asR) is calculated from dark respiration rates . Oxygen fluxes were then converted to carbon fluxes using a photosynthetic quotient of 1.1 [−2sponge d−1. We acknowledge that the use of Rd to calculate R may have led to an underestimation of daily net primary productivity rates (Pn), as Rd was measured in darkness during the day. Separate incubations conducted in darkness during the day and at night showed that there was a small decrease in respiration rates at night (−1.15 ± 0.52 versus −0.94 ± 0.50 μmol O2 cm−2sponge h−1).Daily photoautotrophic carbon uptake rates were quantified for sponges residing on vertical surfaces. The light profile of a vertical surface at 20 m was derived from a model  that wasmentclass2pt{minimt of 1.1  and a ret of 1.1 –49), resC. caribensis was measured by incubating sponge individuals in situ in both dark and light conditions (n = 6 per condition). Natural diet incubations were conducted over one week in December 2019, between 10:00 and 12:00 h near station “Buoy 1”  at 10 m water depth. Sponges were incubated in airtight 2-L chambers and water samples (100 mL) were taken with acid-washed polypropylene syringes at t = 0, 5, 10, 20, and 40 min. For light incubations, chambers were wrapped in 2 layers of shade cloth to mimic maximal irradiance levels on vertical surfaces at 20 m . For dark incubations, chambers were wrapped in opaque cloth. Water samples were stored at 4 °C in the dark at the surface prior to processing within 5 h. Duplicate samples were taken for dissolved organic carbon (DOC) and live  particulate organic carbon (LPOC) (details in Supplementary Methods). A seawater only control was run daily (n = 3 per light condition). At the end of the experiment, sponges were imaged for surface area analysis using Image J (http://rsb.info.nih.gov/ij/), and tissue collected and stored at −20 °C before subsequent lyophilization and dry weight measurement.The net heterotrophic carbon diet of post hoc linear regressions did not show significant removal or release rates, uptake rates were set to 0. Hourly fluxes of DOC and LPOC obtained in the dark and in the light were each multiplied by 12 and then summed to calculate daily net rates of DOC and LPOC uptake, respectively (DOC24 and LPOC24).Initial net hourly DOC uptake rates by sponges were calculated by applying the previously described bi-exponential “2G model”, which describes uptake of the labile and refractory portion of DOM , 51. ForC. caribensis was estimated by summing daily carbon uptake from photoautotrophy (Pg) and net daily heterotrophy (DOC24 + LPOC24), expressed as μmol C cm−2sponge d−1. The standard deviation of the total mixotrophic diet was obtained by propagating the standard deviations of the underlying fluxes according to:Finally, the total mixotrophic diet of C. caribensis at the cellular level and assess metabolic integration between the microbiome and host, a pulse-chase experiment was conducted using isotopically labelled artificial seawater (ASW). Sponges were incubated with ASW enriched with 13C sodium bicarbonate  and 15N ammonium chloride  to a final concentration of 2 mM and 5 µM, respectively, as per Pernice et al. [−2 s−1 at midday, reflecting maximal irradiances received on vertical surfaces at 20 m depth). Sponges were then transferred to flow-through aquaria with non-labelled fresh running seawater for the 42-h chase period (see Supplementary Methods). Non-labelled sponges provided background enrichment values (t = 0) and sponges were also incubated with enriched ASW for 6 h in the dark. Four independent sponge replicates were sampled at each time-point , and 48 h). At each time-point, a subsample of tissue was removed with a sterile scalpel blade and fixed in 2.5% (v/v) glutaraldehyde + 1% (w/v) paraformaldehyde in PHEM buffer  and 9% (w/v) sucrose, pH 7.4), and the remaining “bulk” tissue transferred to pre-weighed cryovials and stored at −20 °C for subsequent bulk tissue stable isotope analysis (see Supplementary Methods).To visualize photosynthetic carbon fixation and ammonium assimilation by e et al. . SpongesFixed tissue samples were processed and embedded as per Hudspith et al. . Semithi15N by consuming the few remaining bacteria from the ASW medium that had incorporated 15N ammonium (13C enrichment was negligible). ROI were drawn over NanoSIMS 12C14N mass images, using 31P and SEM images as a reference to identify cell types. Extracted isotopic ratios (Rsample) were multiplied by a correction factor based on daily scans of Saccharomyces cerevisiae . Unlabelled sponge tissue (t = 0) was analyzed to obtain natural abundance stable isotopic ratios for each ROI category and 2 biological replicates were analyzed per time-point ), except for t = 48, where 3 replicates were analyzed. A total of 9421 cells were scanned  at the Centre for Microscopy, Characterisation and Analysis  following the methodology outlined by Hudspith et al. . Betweenh et al. ) and thePost hoc pairwise comparisons were made to determine which levels of factors were significant.Bulk stable isotope and extracted NanoSIMS data were analyzed in Primer v7  using thP–E curves were fitted and graphed using SigmaPlot (v. 14.5) and the change in irradiance over the course of a day on a vertical surface integrated against the fitted P–E curves using R (v. 4.0.3). Models used to calculate carbon uptake rates for individual replicates were run in Excel  and SPSS . Differences in net carbon uptake rates between dark and light incubations were analyzed using 2-tailed paired t-tests (SPSS). Significance was determined at the p = 0.05 level. Full statistical outputs are available in Supplementary Tables Plot v. 1.5 and thChondrilla caribensis displayed a photosynthesis–irradiance response typical of sponges hosting photosymbionts  indicate an efficient use of light at low photon flux rates. The average daily ratio of gross photosynthesis to respiration (P:R), which represents an index of the energetic budget over a diel cycle, was 0.35 ± 0.08. This sponge is therefore net heterotrophic at 20 m water depth, as indicated by P:R ratios <1. Accordingly, gross primary productivity did not have the potential to balance the respiratory demand of this sponge, with daily net primary productivity being −8.8 ± 4.4 μmol C cm−2sponge d−1 (−392 ± 195 μmol C g DW−1 d−1). However, carbon fixation via photosynthesis (gross primary productivity: 9.4 ± 4.1 μmol C cm−2sponge d−1) was estimated to contribute to the daily respiratory demand of the holobiont  dominated the heterotrophic diet of C. caribensis and provided 98% of the total organic carbon uptake, whereas live particulate organic carbon (LPOC) represented only 2% of the total uptake. Average removal rates of DOC were higher in the dark compared to the light, and the inverse was true for LPOC . When the contribution of photosynthetically fixed carbon was included, the daily total carbon uptake rate amounted to 139 ± 63 µmol C cm‒2sponge d−1, with photoautotrophy by cyanobacteria accounting for 7 ± 3% of the total carbon uptake , Gamma- (16%), and Alpha-proteobacteria (9%), with Ca. S. spongiarum accounting for 6% of the microbial community  < 0.01; Supplementary Table To visualize photosynthetic carbon fixation and trace its subsequent transfer, sponges were pulsed with od Figs.  and 5, dwer Fig. . Host ce13C after 48 h  < 0.05; Supplementary Table 13C-labelled cyanobacteria. Due to the 2-dimensional nature of NanoSIMS images, some of these enriched host cells may have contained engulfed cyanobacteria that were not visible. However, the relatively low proportion (21%) of enriched cells containing cyanobacteria suggests that phagocytosis of cyanobacteria by host cells was not the only mode of translocation. Furthermore, only 1 out of 19 enriched host cells in the inner sponge body contained an intracellular cyanobacterium during the chase period.The isotopic enrichment of cyanobacteria did not change during the chase period, and cells remained highly enriched in 8 h Fig. . There w13C-assimilation into the bulk tissue of C. caribensis during the dark control , confirming that enrichment during the light pulse was driven by light-dependent carbon fixation by symbionts rather than uptake via anaplerotic pathways. Dark fixation rates of the holobiont were on average 4.4 times lower than light fixation rates , all p(perm) > 0.05; Supplementary Table 15N enrichment of symbiotic microorganisms and cyanobacteria of the cortex and all host cells increased  > 0.05; Supplementary Table Ammonium assimilation was driven by the entire microbial community of ne Figs.  and 5. Mria Fig.  in the cnts Fig. , many hosed Fig. , but theStudies on the nutritional modes of sponges have predominantly quantified heterotrophy or autotrophy in isolation, hampering our understanding of their relative contribution to mixotrophy and how this strategy enables sponges to adapt to dynamic marine environments. Furthermore, our understanding of the role of photoautotrophy in sponges hosting photosymbionts is largely informed from species that are net phototrophic or live in high-light environments. Thus, a vast potential for photoautotrophy in net heterotrophic sponges that reside in low-light habitats and host photosymbionts has been overlooked. Here, we show that photoautotrophy supplements the diet of a sponge that dwells in lower light environments and can contribute significantly to the respiratory carbon requirements of the holobiont. Single-cell analysis confirmed that photosymbionts contribute to host metabolism, as photosynthetically fixed carbon was translocated from cyanobacteria to sponge cells, either via symbiont phagocytosis or the release and subsequent incorporation of photosynthates. We hypothesize that the contribution of photosynthetic carbon fixation to total sponge diet is underestimated in the many net heterotrophic sponges that host photosymbionts, and that mixotrophy is a widespread strategy for sponges residing in a range of illuminated shallow-water habitats, not solely restricted to high-light environments.C. caribensis predominantly resides in low-light reef environments, the transfer of fixed carbon from cyanobacteria to other members of the symbiosis can potentially offset the respiratory requirements of the holobiont by up to half  and shallow reefs  [Despite the fact that eed 130% –59). Moreed 130%  can proleed 130% . While meed 130% –28, quanhe other , and maym–2 s–1) , demonstm–2 s–1) , 28. Howm–2 s–1) , this reC. caribensis was met (and exceeded) by heterotrophy, with organic carbon providing an estimated 93% of total daily carbon uptake, indicating that these sponges are not carbon limited. The excess carbon and nutrients  provided by the ingestion of organic material can support growth, reproduction, and cellular turnover. Dissolved organic carbon accounted for 98% of the natural diet, which is comparable to previously reported contributions in shallow-water and deep-sea species [C. caribensis may have resulted from DOC release stimulated by the photosynthetic activity of symbiotic cyanobacteria, or diel variability in heterotrophic feeding, as some sponges exhibit plasticity in their feeding modes and can enhance heterotrophy in response to shading [The balance of the daily respiratory requirements of  species , 63, 64. species , pumping species , and the species . Uptake  species . Limited shading , 28 and  shading .C. caribensis, confirming that this sponge benefits from its photosynthetic symbionts. Phagocytosis of cyanobacterial cells was observed in NanoSIMS  are capable of fixing carbon via anoxygenic photosynthesis [C. caribensis. Chemoautotrophic carbon fixation pathways are also associated with members of the C. caribensis microbiome. The reductive tricarboxylic acid cycle in Nitrospirae [13C-assimilation by a small portion of the prokaryotic community during the dark control. Nearly all symbionts became enriched in 15N during the 6-h pulse, demonstrating the ubiquity of ammonium fixation pathways across diverse microbial taxa in C. caribensis. Furthermore, NanoSIMS images  and propose a more comprehensive approach to sponge nutrition, encompassing both autotrophy and heterotrophy, to better understand sponges’ trophic plasticity. Our understanding of the extent of sponge mixotrophy is currently hampered by a lack of physiological data. In the Caribbean, for example, over a third of sponges host photosymbionts , 87, butSupplementary MaterialData Set 1


We investigated the correlation between the DNA quality of archived FFPE heart tissue examined with the Illumina Infinium HD FFPE QC assay (Infinium QC) and Thermo Fisher’s Quantifiler Trio DNA Quantification kit (QuantifilerTrio), respectively, and the amount of usable DNA methylation data as measured by the probe detection rate (probe DR) obtained with the Illumina Infinium MethylationEPIC array. We observed a high correlation  between the QuantifilerTrio degradation index, DI, and the amount of usable DNA methylation data analysed with SeSAMe, whereas a much weaker correlation was observed between the Infinium QC and SeSAMe probe DR . Based on the results, QuantifilerTrio DI seems to predict the proportion of usable DNA methylation data analysed with the Illumina Infinium MethylationEPIC array and SeSAMe by a linear model: SeSAMe probe DR = 0.80–log10(DI) × 0.25.Archived formalin-fixed and paraffin-embedded (FFPE) heart tissue from autopsied individuals represents an important resource for investigating the DNA methylation of heart tissue of deceased individuals. The DNA quality of FFPE tissue from autopsies may be decreased, affecting the DNA methylation measurements. Therefore, inexpensive screening methods for estimating DNA quality are valuable.  However, DNA sequencing studies do not investigate tissue-specific or environmentally caused gene regulation in diseases2. However, environmental factors may also change the gene expression levels by affecting epigenetic mechanisms such as non-coding RNA, chromatin remodelling, histone modifications, and DNA methylation1. The most widely studied epigenetic phenomenon is DNA methylation, the covalent addition of a methyl group to primarily a cytosine nucleotide followed by a guanine nucleotide (CpGs).Environmental factors can lead to somatic mutations of the DNA sequence, as seen in cancer3. Most pathology and forensic pathology departments have extensive archives of FFPE tissue samples. The archived FFPE samples and clinical data represent enormous resources for tissue-specific disease research. Unfortunately, formalin-fixation of the tissue causes cross-linking between DNA and proteins and damages the DNA leading to short DNA fragments with nicks and other damages5. Breaking the cross-links requires harsh treatments resulting in further degraded and low-quality DNA for the subsequent analysis6.Biopsies from surgeries and autopsies have routinely been stored for decades as formalin-fixed and paraffin-embedded (FFPE) tissue7. To assess the DNA quality of the samples before the analysis with the EPIC array, Illumina developed a quantitative PCR (qPCR) based DNA quality assessment kit, the Infinium FFPE QC assay (Infinium QC) . EPIC array analyses are relatively costly experiments in person-hours and reagents compared to simple qPCR assays. Therefore, evaluating the DNA quality of tissue samples before EPIC array analysis is highly recommended. The QuantifilerTrio DNA Quantification Kit (QuantifilerTrio)  is another simple and inexpensive qPCR-based assay commonly used in forensic genetic laboratories to determine the quantity and quality of human DNA in biological trace samples.The Infinium MethylationEPIC assay (EPIC array)  is an array-based hybridization method for interrogating the methylation level at more than 850,000 sites in the genome. The method is widely used for DNA methylation analysis because of the high number of examined methylation sites for a reasonable priceminfi8 and SeSAMe9. Based on the data obtained with the EPIC array, Infinium QC, and QuantifilerTrio, analysed with minfi and SeSAMe, we developed prediction models for estimating the numbers of usable DNA methylation probes to evaluate the usability of FFPE samples for DNA methylation examination before carrying out more costly and time-consuming EPIC array examinations.We evaluated the correlation between the DNA quality measures of two qPCR assays, the Infinium QC and the QuantifilerTrio, and the amount of usable EPIC array probe data generated from FFPE heart tissue samples archived for 10–18 years. The DNA methylation data were analysed with the in silico analysis tools minfi and SeSAMe. minfi discarded 8.6–18.1% of the 862,927 CpG probes, while SeSAMe discarded 26.6–76.8%  , and SeSAMe: r2 = 0.01 (p > 0.05)  probes failed uniquely in one of the 36 samples, while 20 (0.013%) failed in all 36 samples. With SeSAMe, 58.329  probes failed in one of the 36 samples, while 68,393 (11.0%) probes failed in all 36 samples  also failed in at least one sample using the SeSAMe pipeline, and 49,806 (33.5%) probes failed in all 36 samples with the SeSAMe pipeline. When analyzing the samples with minfi, the odds was 3.91 times higher (p < 2.2 × 10−16) for a Type II probe to fail compared to a Type I probe, and it was 4.71 times the odds (p < 2.2 × 10−16) for a probe annotated to an Open Sea region to fail compared to a probe annotated to a CpG Island region. When analyzing the samples with SeSAMe, it was 1.51 times the odds (p < 2.2 × 10−16) for a Type I probe to fail compared to a Type II probe, and it was 2.69 times the odds (p < 2.2 × 10−16) for a probe annotated to an Open Sea region to fail compared to a probe annotated to a CpG island region (Supplementary Tables The p = 8.2 × 10−5) in samples of high quality compared to that of samples with low quality. Furthermore, we observed that samples of high DNA quality had a lower fraction of failing probes annotated to CpG Island region (p = 4.0 × 10−3) than the low DNA quality samples. For the probes failing with minfi, no statistically significant difference was found between the samples of high and low quality  and samples of low DNA quality (defined as samples with DI above the upper quantile). We found a statistically significantly higher fraction of failing Type II probes (minfi was r2 = 0.04 (p > 0.05), and with SeSAMe r2 = 0.17 (p = 0.01)   Fig. A.Figure 10(DI) and probe DR analysed with minfi was r2 = 0.43 (p = 1.3 × 10−4), and r2 = 0.75 (p = 8.7 × 10−12) with SeSAMe (Table 10(DI)  , corresponding to 766,372 usable probes, and a mean SeSAMe probe DR of 0.41 , corresponding to 351,024 usable probes , corresponding to 777,270 usable probes, and a mean SeSAMe probe DR of 0.55 , corresponding to 473,265 usable probes.The linear regression models presented above can be used to predict the probe DR. Heart tissue samples with Infinium QC ΔCt of, e.g., five are predicted to have a mean minfi probe DR of 0.91 , corresponding to 787,686 usable probes and a mean SeSAMe probe DR of 0.63 , corresponding to 541,313 usable probes , corresponding to 766,869 usable probes, and a mean SeSAMe probe DR of 0.45 , corresponding to 387,419 usable probes.Tissue samples of moderate quality with a QuantifilerTrio DI of, e.g., five are predicted to have a mean  0.90–0.9, 95% CI,10.This study aimed to examine whether the simple, inexpensive DNA quality screening methods Infinium QC and QuantifilerTrio could be used to estimate the quality of the EPIC methylation array data of archived FFPE tissue samples. The EPIC array investigates more than 850,000 CpG sites genome-wide and is rather costly and time-consuming. Thus, it is valuable to assess if the DNA to be examined is of sufficient quality for a successful examination with the expensive EPIC array. DNA quality assessment methods, including the two qPCR-based methods Infinium QC and QuantifilerTrio, are relatively inexpensive compared with the EPIC array. Illumina recommends using the Infinium QC for quality evaluation of FFPE tissue samples before EPIC array experiments. QuantifilerTrio is routinely used in many forensic genetic laboratories to ensure the accuracy and reproducibility of DNA typing. An inverse relationship has been demonstrated between qPCR assayed amplifiable DNA levels, the Ct value, and multiplex PCR SNP mini-sequencing success of FFPE tissue stored for 9–25 yearsminfi8 and SeSAMe9. SeSAMe is more restrictive than minfi, removing approx. 100,000 more probes than minfi using default settings. These probes are removed partly due non-unique mapping as described previously. SeSAMe removes particularly data that are technically questionable or flawed. Despite this difference, the probe DRs of minfi and SeSAMe were correlated with r2 = 0.55 (p < 10−6).We analysed the EPIC methylation array data with the commonly used in silico analysis tools minfi and SeSAMe. Both with minfi and SeSAMe, probes annotated to Open Sea regions had statistically significantly (p < 2.2 × 1016) higher odds of failing than probes annotated to CpG Islands. With minfi, Type II probes had higher odds of failing than Type I probes (p < 2.2 × 10−16), whereas the opposite was observed with SeSAMe, where Type I probes had higher odds of failing failed compared to Type II probes (p < 2.2 × 10−16). With SeSAMe, we found that the fraction of failing Type II probes was statistically significantly higher (p = 8.2 × 10−5) in high DNA quality samples (low DI) compared to that found in the low quality samples (high DI).We used the probe DR as the measurement for usable DNA methylation data. The probe DR is strongly influenced by the analysis method and the parameter settings. We used the standard settings of 11. The signs of body and tissue decomposition at autopsy before formalin fixation may give a rough estimate of the tissue’s suitability for DNA methylation analysis with the EPIC array. However, the information is not always readily available, particularly not for blocks of old FFPE tissue taken under unknown circumstances. We could not perform this kind of analysis because all heart tissue samples were taken from deceased individuals with no or very little clinical evidence of decomposition.We did not find any statistically significant correlation between storage time and the amount of usable DNA methylation data. There was a statistically significant correlation between storage time and Infinium QC ΔCt, but not with QuantifilerTrio DI. The inconsistent results may be due to the relatively short time between sample collection and analysis. It could also be due to the varying post-mortem DNA degradation before the forensic autopsiesminfi was r2 = 0.04 (p > 0.05), and when analysed with SeSAMe r2 = 0.17 (p < 0.05) (Table minfi was r2 = 0.43 (p < 0.05), and when analysed with SeSAMe r2 = 0.75 (p < 0.05)  while the prediction with Infinium QC with SeSAMe data was less informative . Illumina states that a ΔCt below five is sufficient for successful EPIC array analyses of FFPE tissue11. According to the prediction model of Illumina QC, a ΔCt = 5 would lead to a mean probe DR of 0.41 with SeSAMe data. When analysing the DNA methylation of fresh auricle tissue from cardiac surgery with the EPIC array using standard settings, we found that the average probe DR with minfi data was 0.91, and 0.86 with SeSAMe data (publication in preparation). These probe DR values correspond to those obtained with fresh auricular tissue with a Quantifiler DI close to 1. We previously decided to only examine FFPE heart tissue if the Illumina QC ΔCt ≤ 2 (unpublished). The decrease in QuantifilerTrio DI was associated with a larger decrease in probe DR for SeSAMe than minfi data, possibly reflecting that SeSAMe’s data analysis algorithm is more conservative than minfi’s. Other tools and pipelines for analysing DNA methylation array data have been published15. We expect the analyses with these tools will show similar correlations between the probe DR and the quality measures obtained with Infinium QC and QuantifilerTrio.Based on our data, we established regression models for predicting probe detection rates with Infinium QC ΔCt and QuantifilerTrio DI Fig. . The preThe DI of QuantifilerTrio, frequently used in forensic DNA typing of crime scene samples with compromised DNA, correlates better than the Infinium QC ΔCt with the proportion of usable EPIC array methylation probe data when examining FFPE tissue. The relatively cheap QuantifilerTrio performed better for pre-screening of archived FFPE tissue samples before examination with the more expensive EPIC array. A prediction model for the success of DNA methylation examination based on QuantifilerTrio results is presented.The study conformed to the Declaration of Helsinki and was approved by the Committees on Health Research Ethics in the Capital Region of Denmark (H-2-2012-017 and H-190084051). The biobank with the heart tissue samples is registered at the University of Copenhagen’s joint records of processing of personal data in research projects and biobanks (514-0725/22-3000), complying with the General Data Protection Regulation (Regulation (EU) 2016/679).Heart tissue was collected in the period 2003–2011 from deceased individuals autopsied at the Section of Forensic Pathology, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark (Supplementary Table DNA was extracted from five 20 µm tissue sections of each sample using the QIAamp DNA FFPE Tissue Kit (Qiagen) according to the manufacturer’s protocol with the modification of increasing the incubation time with proteinase K from 4 h to 16–20 h. The DNA concentration was measured using a Qubit 2.0 Fluorometer .A total of 500 ng DNA was bisulfite-treated using the EZ DNA Methylation kit (Zymo Research Corp) following the manufacturer’s protocol and eluted in 10 µL elution buffer. The eluate was prepared with the Infinium HD FFPE DNA Restore kit  according to the manufacturer’s protocol to repair the bisulfite-treated DNA. The level of DNA methylation was quantified with the Infinium MethylationEPIC Kit  following the manufacturer’s protocol. The prepared slides were scanned using the iScan System .Infinium QC. The quality of DNA from each sample was assessed with the Infinium HD FFPE QC kit  and an ABI 7900  following the manufacturer’s protocol. The qPCR cycle thresholds (Ct) were used to calculate the ΔCt = Ct(FFPE)–Ct(QCT), where Ct(FFPE) is the Ct of the FFPE heart sample, and Ct(QCT) is the Ct value of the Quality Control Template DNA (QCT) provided by Illumina. The primer set used is expected to generate an amplicon between 175 and 200 bp in length. Illumina considers DNA from FFPE tissue with a ΔCt below five eligible for further analysis with the EPIC array.The quality of DNA from each sample was assessed with the QuantifilerTrio DNA Quantification kit  and an ABI 7900  following the manufacturer’s protocol. QuantifilerTrio uses three primer sets  and a large (214 bp) autosomal amplicon, a Y-chromosomal amplicon (74 bp), and an internal PCR control amplicon (IPC). The ratio between the smaller and larger autosomal amplicons, called the degradation index (DI), was used to measure the DNA quality. A DI ≤ 1 indicates no degradation, a DI from 1 to 10 indicates moderate degradation or inhibition of the PCR, and a DI > 10 indicates severe degradation of the DNA or inhibition of the PCR .tidyverse package16. The raw iScan data (IDAT files) were imported into R using the Bioconductor17 packages minfi8 and SeSAMe9.The data analysis was conducted in the R statistical environment (R version 4.1.1.) using the minfi, the beta values were calculated from the red and green colour intensities (RGChannelSet object) with the getBeta function with no normalization. A detection p-value was calculated to indicate the signal quality at a given site. minfi calculated the detection p-value by comparing the total signal (methylated + unmethylated) for each probe with the background signal, estimated from the negative control probes. A small p-value indicates a reliable signal, whereas a high p-value indicates a poor-quality signal. Probes with detection p ≥ 0.01 were marked as failed and removed. Probes with common SNPs (SNPs found in dbSNP.137CommonSingle database) that may affect the CpG were removed by the function dropLociWithSnps as well as probes know to cross hybridise to multiple places in the genome7.With SeSAMe, the beta values were calculated using the function getBetas, applying its own normalization method ). In addition to discarding probes with detection p ≥ 0.01, SeSAMe also discards probes that hybridize with DNA fragments from loci giving incorrect DNA methylation levels9. Using the SeSAMeQC function, the loaded raw IDAT files were quality checked, and the number of removed probes (number_na_cg) for each samples was determined.With We defined the probe detection rate (DR) as:18 package was used to annotate probes as Type I or Type II and annotate the probes to CpG Islands and Open Sea regions.The IlluminaHumanMethylationEPICanno.ilm10b4.hg192) was calculated for the pairwise comparisons of probe DRs with Infinium QC ΔCt and QuantifilerTrio DI quality measurements. The plots were made with ggplot2 in R.Pearson’s correlation coefficient of determination (rlm function was used to determine the best fitting linear regression model for predicting the probe DR based on (1) the Infinium QC ΔCt data and (2) the best fitting log-linear regression model based on the QuantifilerTrio DI data obtained with minfi and SeSAMe, respectively.The fisher.test function was used to identify statistically significant differences between the failing and non-failing probes.The wilcox.test function was used to identify statistically significant differences between the failing probes of the top and bottom quantiles of samples, based on the QuantifilerTrio DI.The Due to autopsies being performed prior to 1 January 2012, informed consent was waived in accordance with the Danish Health Act and the Consolidated Act no. 1338 of 1 September 2020 on Research Ethics Review of Health Research Projects and Health Data Research Projects.Supplementary Information.


To review the current clinical evidence on advantages and risks of early weight bearing (EWB) after internal fixation for tibial plateau fracture., using PRISMA guidelines. The included studies were randomized controlled trials, prospective and retrospective observational studies, case reports. Data extraction was performed independently by 2 reviewers. Collected data were compared to verify agreement. Statistical analysis was not performed in this study.Data source: PubMed and Google Scholar from inception of database to 20 August 2021The literature search produced 174 papers from PubMed and 186 from Google Scholar, with a total amount of 360 papers. The two reviewers excluded 301 papers by title or duplicates. Of the 59 remaining, 33 were excluded after reading the abstract, and 17 by reading the full text. Thus, 9 papers were finally included in the review.EWB can be considered safe and effective in selected cases after internal fixation for tibial plateau fractures.Level of evidence Therapeutic Level III.The online version contains supplementary material available at 10.1186/s13018-022-03156-8. Tibial plateau fractures represent approximately 1.2% of all fractures in the adult population . Even ifTwo reviewers (MD and AS) independently identified studies by a systematic search of PubMed and Google Scholar from inception of database to 20 August 2021. The search strategy was structured according to the PICO (Population Intervention Comparison Outcome) method as follows: P “ AND I (“early weight bearing” OR “immediate weight bearing” OR “postoperative weight bearing”) AND O (“loss reduction” OR “rehabilitation” OR “return to work”). The two reviewers screened the titles and abstracts of the citations identified independently and in duplicate, and acquired the full text of any article that either judged potentially eligible. The inclusion criteria for the studies were: (a) English written papers, (b) all studies concerning early or immediate weight bearing in articular and/or partial articular tibial plateau fracture treated with ORIF, (c) all article types including case reports. The exclusion criteria were: (a) language of publication different from English (b) tibial plateau fractures treated non operatively, (c) tibial plateau fractures treated with external fixation, (d) extra-articular proximal tibia fractures, (e) animal research and biomechanical models, (f) book chapters.The present review was conducted in accordance with the 2009 Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement , and disagreement was resolved by consensus and discussed with another author (GC).Risk of bias was assessed on all the included studies in the quantitative analysis based on OHAT Risk of Bias Rating Tool for Human and Animal Studies. Domains were defined as selection bias, confounding bias, attrition/exclusion bias, detection bias and selective reporting bias and were rated as “The literature search produced 174 papers from PubMed and 186 from Google Scholar, with a total.amount of 360 papers. The two reviewers excluded 301 papers by title or duplicates. Of the 59 remaining, 33 were excluded after reading the abstract, and 17 by reading the full text. Thus, 9 papers were finally included in the review. Details of studies are described in Table Definitively Low” in 7 studies (77%), “Probably Low risk” for one study (11%) and not applicable for the case report. The risk of confounding bias was “Probably High risk” in 5 studies (55%) and “Probably Low risk” in 4 studies (44%). The risk of attrition/exclusion bias was “Definitively Low” in 2 studies (22%) and “Probably Low risk” in 6 studies . The risk of detection bias was “Probably Low risk” in 4 studies (44%), “Probably High risk” in 4 studies (44%) and “Definitely High risk” in 1 study (11%). Reporting bias was “Definitively Low” for 3 studies and “Probably Low risk” for 6 studies (66%)  with tibial plateau fractures treated with ORIF, divided the patients in two groups: the first one consisted of 60 patients with no weight-bearing or toe-touch weight-bearing for 6 postoperative weeks, the second one (30 patients) was allowed immediate weight bearing as tolerated. 51% of the patients had a Schatzker II tibial plateau fracture and the remainder were Schatzker I, IV, and VI fracture patterns. All patients had postoperative radiographs at first or second day post-surgery and after six weeks and three months. Only one patient of the weight bearing group had > 1 mm (4 mm) joint depression on the two follow up radiographs, with no worse clinical or functional outcome compared to the other patients. The author concluded that immediate weight bearing was not related with articular collapse or fixation failure and that patients with tibial plateau fractures should be allowed immediate full weight bearing on the operated limb after fracture fixation .In a retrospective study performed by Haak and collegues, involving 32 patients with partial articular tibial plateau fractures (AO type 41B) treated with locking plate osteosynthesis, the authors divided the patients in two groups: the first group  had indication for no weight bearing on the operated limb, the second  was allowed immediate postoperative weight bearing. No radiographic fracture displacement or implant failure was reported in any patient even in the last 6–8 weeks follow-up. The author concluded that allowing immediate weight bearing in partial articular tibial fractures treated by osteosynthesis with locking plate was possible and safe .Similarly, in a study conducted by Thewlis and colleagues involving 17 patients with tibial plateau fractures treated with ORIF (AO Type B-C), patients were prescribed isometric quadriceps exercise (before and after surgery), immediate postoperative full knee range of motion and weight bearing on the operated limb up to 20 kg for the first six weeks. Dynamic weight bearing in order to assess a ratio of limb loading (operated vs non operated) was conducted at 2, 6 and 12 weeks after surgery, Knee Injury and Osteoarthritis Outcome Scores (KOOS) were collected at 6, 12, 26, and 52 weeks after surgery and all patients were analyzed with plain radiographs immediately post-surgery and at 52 weeks. Fracture fragments’ migration or changes in knee stability and alignment was not noted in any patient at 52 weeks and the dynamic weight bearing performed at 2 and 6 weeks post-surgery demonstrated no correlation with knee-related Quality of Life at 52 weeks [Eggli and colleagues performed a prospective study on 14 patients (mean age 41 ± 27) with bycondilar tibial plateau fracture (AO type C) treated with double plating, with the addition of autologous cancellous iliac crest graft in 11 cases. All patients had preoperative antero-posterior (AP) and lateral view x-rays and computed tomography (CT) scans. The patients were evaluated at 8, 12, and 24 weeks, and at 1 year after surgery with clinical exam and both AP and lateral views. All patients were allowed immediate 10 kg weight bearing on the operated limb. All patients achieved union within 12 weeks and no patient experienced loss of fracture reduction .Thewlis and colleagues performed a prospective longitudinal study involving 9 patients with partial articular tibial plateau fractures (AO type B) treated with ORIF, allowing immediate weight bearing as tolerated. The mean age of all patients was 51.4. The aim of the study was to quantify the migration of bony fragments and the loads passing through the fracture construct using radioesterometric analysis. The patients were evaluated at 2, 12, 26, and 52 weeks after surgery. CT scans were taken postoperative and at one-year follow-up to assess maintenance of fracture reduction. Fracture migration was measured as the motion of the center of the fracture fragment relative to the center of the unfractured tibial plateau. Migration was defined acceptable if the articular surface subsided ≤ 3 mm during healing). The authors found that whilst peak loading during walking was not associated with fracture migration, average force, exercised during the stance phase of gait, was majorly correlated with fragment migration. Despite this finding migration was not higher than 3 mm in none of the patients .Solomon et al. described 7 Schatzker type II tibial plateau fractures  treated with subcondral screws and buttress plate. All patients were allowed partial weight bearing up to 20 kg using crutches for six weeks. In addition to traditional radiographs, radiostereometric analysis (RSA) and differentially loaded radiostereometric analysis (DLRSA) were performed at 2, 6, 12, 18, 26, and 52 weeks. Displacement of fractures fragments was < 1 mm in all patients, in both craniocaudal and mediolateral direction. The mean fracture fragment displacement in craniocaudal direction was −0.30 mm (−0.73 to 0.02) and 0.00 mm (−0.12 to 0.15) at 2 and 52 weeks respectively. The mean displacement in mediolateral direction was −0.08 (−0.73 to 0.36) and −0.01 (−0.16 to 0.11) at 2 and 52 respectively [As stated, faster recovery of full weight bearing and faster return to work and sport  might alp = 0.04) more severe fracture patterns (Schatzker type IV–VI). There were no statistically significant differences in terms of quality of life, pain and complication rates between the two groups, but patients with PWB reached full weight bearing earlier  and the number of patients who reached full weight bearing within 12 weeks was significantly higher in the PWB group . The authors concluded that permissive weight bearing after tibial plateau fracture was safe and lead to a significant reduction in time to reach full weight bearing without differences in terms of complications, pain and quality of life [Kalmet et al. evaluated a series of 91 patients with tibial plateau fractures in a retrospective cohort study with the aim to identify the differences in term of quality of life, pain and complications between patients with tibial plateau fractures with postoperative indication of permissive weight bearing  and patients with restricted weight bearing . In the PWB group patients had significantly  with tibial plateau fracture (AO type B-C) and divided them into 2 groups. In the first group (“Classic group”) the patients were treated with plate and screws according to the standard surgical technique. In the second group the patients were instead treated with a different approach, preserving the perforating vessels: Angiosome of Perforator-Sparing (APS). In both groups after surgery the patients were allowed full weight bearing and were encouraged to mobilize as early as possible routine preoperative CT scans were performed for all patients while postoperatively CT is only requested when quality of reduction is unclear on radiographs. The authors found no significant increase in wound complications or fixation failure in the second group compared to the “classic group”, despite the earlier and more aggressive rehabilitation process .In the literature few studies evaluate time to return to work and sport. Furthermore, the few studies considered did not associate rehabilitation protocols with EWB and didn’t compare the results with a delayed weight bearing control group. We found a case report of a 44 year old man with a lateral tibial plateau fracture (AO 41B2) diagnosed with CT scans and treated with highly impacted bone allograft and angular stable plate fixation. The patient was allowed immediate weight bearing on the affected limb and follow up was performed at 2 and 6 weeks and 3 and 12 months after surgery. There was no widening of the tibial plateau, no collapse of the articular surface, the patient at 6 weeks had 0–125 degrees of range of motion (ROM) and returned to work three months after surgery .n = 193) have a variable time of delayed weight bearing and do not consider EWB as a rehabilitation protocol. There is, therefore, lack of data on average time to return to work and sport.Robertson et al.  in theirThe retrieved papers also allow to understand the key role of early rehabilitation, which has a well-known role in recovery after fracture fixation and gains even more importance in association with EWB protocols. In all studies analyzed, patients returned to normal gait and early knee ROM without evidence of complications.However, the retrieved studies often did not give sufficient information about post-operative rehabilitation programs and when described there was a wide disparity of indications. In most studies early weight bearing seems to be reserved to young patients with simple fracture patterns , knee function before trauma and associated of intra-articular lesions. Furthermore, only in a few studies patients are divided according to fracture pattern and it is therefore difficult to establish the most suitable post-operative rehabilitation protocol for tibial plateau fractures based on the severity of the fracture pattern.Early weight bearing in tibial plateau fractures treated with internal fixation has shown comparable complications in terms of loss of reduction, mechanical failure and delayed healing with respect to restricted weight bearing protocols. The retrieved studies do not allow to draw definitive conclusions on time to return to work and sport activities, as well as greater autonomy in daily life activities and better motility. To accurately evaluate the safety of EWB we will need longer clinical trials with a greater number of patients and that more clearly define the indications or limitations of early weight bearing protocols.Additional file 1.PRISMA 2020 Checklist.


The extremely low cytotoxicity and excellent biocompatibility of T−CDs without light irradiation were tested using MTT and hemolytic assay. Further, T−CDs have been shown by in vivo experiments, using a mouse breast cancer cell line (4T1) subcutaneously injected in the back of the mouse buttock as a model, to effectively inhibit the tumor cell proliferation in solid tumors and show an excellent PDT effect. In addition, pathological sections of the mice tissues after further treatment showed that the T−CDs had no apparent impact on the major organs of the mice and did not produce any side effect lesions. This work demonstrates that the as−synthesized T−CDs has the potential to be used as a PS in cancer treatment.Photodynamic therapy (PDT) has become an emerging cancer treatment method. Choosing the photosensitizer (PS) compounds is one of the essential factors that can influence the PDT effect and action. Carbon dots (CDs) have shown great potential as photosensitizers in PDT of cancers due to their excellent biocompatibility and high generation of reactive oxygen species (ROS). Here, we used tea polyphenol as raw material for synthesized tea polyphenol carbon dots (T−CDs) that show dual emission bands of red and blue fluorescence and can efficiently generate hydroxyl radicals (OH) under mildly visible irradiation with a LED light (400–500 nm, 15 mW cm The type II mechanism is about energy transfer reaction, which produces singlet oxygen (1O2) ..2O2), anen (1O2) . Carbon en (1O2) ,10, supeen (1O2) , and manen (1O2)  who disca et al.  prepared2O2) to overcome the influence of the hypoxic tumor microenvironment on PDT therapy, and achieve high multimodal imaging and efficient in vitro/in vivo tumor PDT therapy. Instead of using CDs as a new generation of photosensitizers to take advantage of their advantages, post−modified photosensitizers frequently use them as carriers. Hence, developing CDs that absorb light in the red or near−infrared region without any post−processing and have high ROS generation capacity is worthy of further study.However, so far, only a few CDs have been reported in the literature to exhibit intrinsic ROS−generating capacity ,15. TherTea polyphenols are a general term for polyphenols extracted from tea, and their anti−mutation effect in vitro can effectively reduce the occurrence of cancer ,19. More−2). In vitro/in vivo experiments proved that it has a good PDT therapeutic effect under the LED irradiation. Furthermore, due to the metal−free property of T−CDs, the hemolytic test, cell activity test and histopathological section demonstrated that the T−CDs have excellent biocompatibility and extremely low cytotoxicity. Therefore, T−CDs reported in this paper has the potential to be used as a PS for performing type I PDT.Herein, inspired by the multiple excellent properties of tea polyphenols against cancer, water−soluble T−CDs with red emission were prepared by the solvothermal synthesis in formamide using citric acid and tea polyphenols as starting materials. Under different excitation wavelengths in the range of 360–620 nm, the T−CDs showed a broad absorption in the visible region and exhibited dual emission of blue and red fluorescence. More interestingly, we found that the T−CDs can efficiently generate hydroxyl radicals under the excitation of LED light  [−1, the stretching vibration of C=C and C=N bonds is attributed to the absorption peak [−1 may be attributed to the residual −OH of the polyphenol group in tea polyphenols [−1 may be attributed to the stretching vibration of C=O. In addition, the Raman spectra of T−CDs (2 hybrid carbon (1603 cm−1) and the D−band peak of sp3 hybrid carbon (1603 cm−1). Among them, the intensity ratio of D−band to G−band (ID/IG) is a standard method used to evaluate the degree of graphitization and amorphous, disordered carbon structure in carbon materials [D/IG of T−CDs is determined to be 0.978, which demonstrates the existence of abundant oxygen− and nitrogen−containing functional groups on the surface of T−CDs, which is consistent with the results of FT−IR. In addition, we determined the molecular weight (Mw) of T−CDs to be 60,739 daltons (Da) by gel permeation chromatography (GPC)  ; at 1635ion peak ; 1376 cmyphenols , while 1of T−CDs b exhibitaterials . Here, thy (GPC) . It is pTo analyze the element content in T−CDs and the chemical environment of each element in more detail, we performed XPS spectroscopy on T−CDs. The full XPS spectrum, as shown in 2 hybrid structure in T−CDs, respectively [As shown in ectively . Meanwhiectively . Figure ex = 360 nm) and 4.27% (λex = 610 nm), respectively  is a standard method to analyze the ability and species of reactive oxygen species produced by light−induced photosensitive materials ,34. The er light a. Howeveer light b. It caner light . We obse−1, proving that T−CDs have no significant cytotoxicity in the concentration range of 0–300 μg mL−1, which is suitable for further cell experiments.As mentioned above, T−CDs present excellent physical and chemical properties and have great potential in biological applications, with particular attention to cancer treatment. We first analyzed T−CDs’ biosafety for practical biological applications by MTT and hemolysis experiments. As presented in −1, the hemolysis rate of T−CDs is less than 5%. It was believed that the absorbance of the sample at a high concentration, the osmosis effect caused by this concentration, and some minor red blood cell damage contributed to the increase in hemolysis rate. In that case, the red blood cells rupture the release of hemoglobin, leading to the sample solution turning red. At the same time, Subsequently, fresh mouse blood was taken to evaluate the hematological toxicity of T−CDs. We used 4T1 cells to subcutaneously create a typical in vivo tumor model in the mouse buttocks and back in order to examine the in vivo photodynamic treatment effect of T−CDs. As illustrated in The tumor cells were extracted from mice after 14 days of therapy. T−CDs were further investigated for their biocompatibility as well as their potential to cause cellular and pathological changes in major organs as a result of PDT treatment . Histopathological analysis was performed using hematoxylin−eosin (H&E) staining ,35. As s−1) were co−incubated with HepG2 cells for 2 h, and the cell uptake capability were observed by laser confocal microscopy. Due to T−CDs good biocompatibility, low cytotoxicity, and bright fluorescence emission in the red region, we studied the application of T−CDs in the field of bioimaging. First, HepG2 cells were selected as the model for cell imaging. T−CDs , 5,5−dimethyl−1−pyrroline N−oxide (DMPO), 4−Amino−2,2,6,6−tetramethylpiperidine (TEMP) and 3−−2,5−diphenyltetrazolium bromide (MTT) were purchased from Aladdin Industrial Corporation . Formamide, methanol, acetone, and dimethyl sulfoxide (DMSO) were purchased from Sinopharm Group Chemical Reagent Co. Tea polyphenols were purchased from Zhongshan Huazhong Food Additives Co., Ltd. .−1; the cooling rate was 5 °C min−1. After the reaction has cooled, remove the dark brown T−CDs stock solution. Add 100 mL acetone to 30 mL of the above T−CDs reaction stock solution and sonicate for 20 min to make it thoroughly mixed (the addition of acetone will cause precipitation), and cool it in a −20 °C refrigerator overnight. The above solution precipitation was collected by suction filtration, and the precipitation was successively washed with acetone solutions containing 10%, 20%, and 30% methanol. The precipitates were dissolved repeatedly in a pure methanol solution, and the clear solution was collected until the solution was colorless. Finally, the collected methanol solution of T−CDs was rotary evaporated at a temperature of 45 °C to obtain a purified black T−CDs powder sample.It is synthesized from citric acid (CA) and tea polyphenols by a solvothermal reaction in the reaction system with formamide as a solvent. First, weigh 1.5 g anhydrous CA and 1 gtea polyphenol powder, add 30 mL formamide solvent, and sonicate for 10 min to thoroughly mix the reaction materials. Subsequently, it was transferred to a 50 mL autoclave, heated at 180 °C in a muffle furnace for 4 h, and the heating rate was set to 2 °C min−1 sodium nitrate solution as eluate at a flow rate of 1 mL min−1. Then the GPC curve was analyzed by the Breeze software. UV−Vis absorption and PL spectra were recorded using a UV−1800PC spectro−photometer and a fluorescence spectrophotometer . Fluorescence images were recorded using a confocal laser scanning microscope (CLSM) (Leica TCS SP8X). A classical MTT assay measures cytotoxicity by absorbance zymography .T−CDs morphology was characterized by TEM (JEM−2100), and the crystallinity and disorder of T−CDs samples were analyzed by confocal laser Raman spectroscopy (LabRAM HR800). Both X−ray photoelectron spectroscopy  and Fourier transform infrared spectroscopy (FTIR), utilizing a Nexus 870 FTIR  spectrometer, were employed to assess the structure and composition of the samples. The capture of free radical signals using Electron paramagnetic resonance (EMXnano) spectroscopy. The average molecular weight  and polydispersion index (PDI) of T−CDs were determined by the GPC  method with 0.1 mol L1O2 capture agent. Using pure water as a control, the ability of T−CDs aqueous solution to generate OH and 1O2 before and after irradiation was tested. A white light LED  was used as the excitation light source, and the illumination time was 12 min.Analysis of reactive oxygen species and their ability to generate T−CDs under light stimulation by EPR spectroscopy, using DMPO as the trapping agent for OH; TEMP as the 2 in an incubator at 37 °C. The cells were digested and passed through trypsin to keep the cells in good condition during the cell experiment.In the in vitro experiment, 4T1 cells, HUVEC cells and HepG2 cells were used as cell models. The cell culture medium was high−glucose DMEM medium , cultured in humid air containing 5% CO2 atmosphere . The T−CDs solutions were incubated for 24 h at various concentrations . Then, after incubating each well with 10 μL of MTT solution (5 mg mL−1) in the dark for 4 h, aspirate the solution from each well, add 150 μL of DMSO, and shake the mixture at room temperature for 5 to 10 min. Finally, use 563 nm as the detection wavelength and 630 nm as the reference wavelength to measure the absorbance in a microplate reader. Using MTT colorimetry, the impact of T−CDs on cell viability was evaluated. Aspirate the growth media and add it to each well after the cells have been incubated in a 96−well culture plate for around 12 h in a 5% CO–2) as the light source. Continue to culture the cells for another 12 h after exposing the 96−well plate to radiation for 12 min. A 96−well plate was used for each study, containing six replicate wells for each sample concentration.4T1 cells were chosen as the model for the in vitro PDT experiment following the MTT experimental methods mentioned above; however, 12 h after adding the T−CDs sample co−culture, an extra step was taken to pass a white light LED  for another 2  h incubation at 37  °C. The cellular fluorescence images were acquired after washing with PBS for 3 times on the laser scanning confocal microscope.HepG2 cells, selected as the cellular imaging model, were plated on 15  mm laser confocal dishes with an initial density of 6 × 10−1, the final volume of the solution is 400 μL, the negative control is red blood cells resuspended in In normal saline, the positive control is red blood cells resuspended in 0.5% (wt) Triton X−100; the above 10 centrifuge tubes were incubated at 37 °C for 2 h, centrifuged at 2000 rpm for 5 min to take pictures, and 100 μL of the supernatant was taken in a 96−well plate to measure the absorbance at 450 nm using a microplate reader. Calculated by the following formula:0: Sample absorbance; A1: Positive control absorbance; A2: Negative control absorbance)Take 500 μL of fresh mouse blood  and centrifuge at 2000 rpm for 5 min to remove the supernatant; resuspend the bottom red blood cells with 1 mL of normal saline, continue to centrifuge at 2000 rpm for 5 min to remove the supernatant, repeat 3–4 times until the supernatant is almost colorless, and finally, resuspend the red blood cells in 1 mL of normal saline. Take 50 μL of the above red blood cell suspension, and add T−CDs to the final concentration of 1, 2, 5, 10, 20, 50, 100, and 200 μg mL7 4T1 cells into the buttocks and back of each mouse. The mice were cultured for about 6–7 days under 12 h light and 12 h dark per day after injection, and tumor−bearing mice were used for in vivo imaging and in vivo PDT experiments after solid tumor growth and formation.Select female Balb/c mice , aged 4–6 weeks, weighing about 20 g as the model for animal experiments. Using 4T1 cells as cancer cells in a mouse solid tumor model, inject 100 μL of a cell suspension containing about 2–10 × 10−1 of T−CDs solution was injected into the tumor area of 1 group of mice. Then, the tumor area was irradiated with LED  for 12 min, and the control group was T−CDs were injected without light, PBS with light for 12 min, and PBS without light. Treatment was performed every two days, and changes in body weight and tumor volume of mice were recorded to evaluate the effect of treatment and the effect of treatment on the body weight of mice. Calculate the tumor size as follows:In vivo PDT experiment: 12 mice with relatively average tumor size were randomly divided into 4 groups. The in vivo PDT effect of T−CDs and control sample PBS was investigated. First, 100 μL of 200 μg mLAfter 14 days of treatment, the mice were sacrificed to obtain their organs  and soaked in 4% paraformaldehyde for preservation. Embed in paraffin, section thickness 4–6 μm. Sections were stained with hematoxylin and eosin (H&E) for histopathological evaluation to further assess T−CDs’ safety.In summary, the solvothermal method was successfully applied to prepared T−CDs with red and blue dual emissions by tea polyphenols compounds as the precursor. The surface of the T−CDs was rich in polyphenol groups through the introduction of tea polyphenols, and it had good dispersion in water and a biological medium. Additionally, hemolytic and MTT experiments showed that T−CDs exhibited high biocompatibility in vitro and minimal cytotoxicity (regular and cancer cell lines). EPR spectral analysis showed that T−CDs could efficiently generate ·OH under LED light stimulation. While using the 4T1 cells as the model, it can be seen that T−CDs could effectively inhibit the proliferation of cancer cells in both cell and solid tumor models, showing an excellent PDT effect. What is more, T−CDs had no obvious effect on the main organs of the mice and did not produce any lesions. Therefore, the T−CDs can be used as a type I PS for the PDT of cancer cells.


When high-energyradiation passes through aqueous material,low-energyelectrons are produced which cause DNA damage. Electronic states ofanionic nucleobases have been suggested as an entrance channel tocapture the electron. However, identifying these electronic resonanceshave been restricted to gas-phase electron-nucleobase studies andoffer limited insight into the resonances available within the aqueousenvironment of DNA. Here, resonance and detachment energies of themicro-hydrated uracil pyrimidine nucleobase anion are determined bytwo-dimensional photoelectron spectroscopy and are shown to extrapolatelinearly with cluster size. This extrapolation allows the correspondingresonance and detachment energies to be determined for uracil in aqueoussolution as well as the reorganization energy associated with electroncapture. Two shape resonances are clearly identified that can capturelow-energy electrons and subsequently form the radical anion by solventstabilization and internal conversion to the ground electronic state.The resonances and their dynamics probed here are the nucleobase-centereddoorway states for low-energy electron capture and damage in DNA. The anion resonances of thenucleobases, in particular, have been extensively studied throughisolated electron-nucleobase reactions.10 These have clearly identified the resonances and dissociative electronattachment pathways that exist, and have offered detailed mechanisticinsight into the chemical dynamics involved in the isolated nucleobase.However, how these observations relate to the aqueous environmentof DNA has remained elusive.11 Linkingthe bottom-up gas-phase work to top-down condensed-phase studies wouldprovide unprecedented insight into the primary processes in DNA. Tobridge these two approaches, complexity can be added incrementallyto gas-phase nucleobases using, for example, nucleobase-solvent clusters.However, this has been challenging in electron-spectroscopic experimentsbecause of the lack of mass-selection prior to the experiment.13 To overcome this challenge, we have shown that 2D anion photoelectronspectroscopy can probe electron-molecule resonances following opticalexcitation, offering new and complementary information to electronspectroscopy.15 More importantly, mass-selectionoffers a route to probing the effect of incremental solvation on electronicresonances.17 We now apply this methodologyto a radical nucleobase anion clustered with water molecules and uncoverhow the electron impact resonances evolve with increasing hydration,thus identifying the possible resonances and their dynamics responsiblefor nucleobase electron capture that constitutes the first step oflow-energy electron damage to DNA.When high-energy radiation passes throughaqueous media, includingwithin living organisms, low-energy (<20 eV) electrons are produced.4 Furthermore, the effect of micro-hydration ofpyrimidine resonances has been considered by computational methods.23 The isolated uracil radical anion, U–, is a dipole-boundanion in the gas-phase, where the excess electron is very weakly boundby the dipole-moment of the molecular core of U.24 Solvation substantially stabilizes the valence anionicstates and a single water molecule is sufficient to render the valencestate (π1*) as the lowest energy conformation.25 The stabilization has been studied using photoelectronspectroscopy for uracil-water clusters, U–(H2O)n, with n ≤7, which showed that increased hydration further stabilizes the valenceanion.27 However, extrapolation from such small n to larger sizes and the bulk is inappropriate. Hence,key physical quantities such as the vertical detachment energy, VDE,and adiabatic electron affinity, AEA, of the aqueous uracil anion,U–(aq), are not known. Moreover, becauseprevious experiments focused on a few distinct photon energies, theyoffered no insight into the location or dynamics of resonances thatare key to the radiation damage mechanism. Experiments by Kočišeket al. have measured the anionic products formed following electronimpact (<3 eV) of small U(H2O)n (and thymine-water) clusters and found that the gas-phasedissociative electron attachment channel to produce [U – H]− is suppressed in the cluster.12 Here, we study U–(H2O)n with n up to 10 to understand theevolution of electronic resonances with increased hydration, and wemeasure additional photoelectron spectra up to n =35 to determine the evolution of detachment energies. Together, theseoffer a detailed view of the energetics of electronic states in aqueoussolution that ties gas-phase work to the bulk.We focus on uracil, U, thesimplest of nucleobases and a proxyfor pyrimidines due to their similar electronic resonances.28 A sample of uracilwas heated to a temperature of 230 °C in the oven of a high-temperatureEven-Lavie valve.24 Nitrogen gas (Oxygen-Freegrade) at ∼5–6 bar was passed through this reservoirand expanded into vacuum to produce a seeded supersonic expansion.The experiment has been describedin detail previously.Uracil radical anions were produced using a ring-filament ionizer,which consisted of a thoriated tungsten wire filament  carrying a ∼5 A current. The filamentwas contained in a hollow stainless steel cylinder  with a ∼15 mm hole through the center and held at between−200 and −600 V (tuned to optimize anion production)to serve as an anode, which, combined with a grounded grid aroundthe central hole, accelerated the electrons produced by the filamenttowards the supersonic expansion that passed through the center ofthe hole.Figure S1. Packetsof mass-selected ions were subjected at the focal point of the spectrometerto light from a Nd:YAG pumped optical parametric oscillator , producing electrons which were collected using a velocitymap imaging photoelectron spectrometer.29 The images were reconstructed using polar onion peeling30 and calibrated using iodide. The resultant energyresolution was on the order of 5% of the photoelectron’s kineticenergy.The electron impact on the seeded gas jet producesa variety ofionic and neutral species, including anions, which were extractedusing a perpendicular time-of-flight mass spectrometer. A representativemass spectrum is shown in –(H2O)n wereproduced and mass-selected before beingintersected by nanosecond light pulses with photon energies, hv, ranging from 1.2 ≤ hv ≤5.2 eV. –(H2O)n with n = 2–4,6, 8, and 10. Each 2D plot is composed of several individual photoelectronspectra at 0.1 eV hv intervals that have been normalizedto their maximum intensity .Cold anionic clusters of U0 anionic ground state of U–(H2O)n to the S0 ground state of thecorresponding neutral cluster, and is in agreement with previous studiesat specific photon energies.27 The electron kineticenergy (eKE) increases linearly with hv with a unitgradient, as expected for such a process. As n increases,the onset of the direct detachment feature moves to higher hv indicating a larger electron binding energy (eBE = hv – eKE) for larger n. For n = 2 and 3, a second, parallel feature is seen in the top-leftcorner, which corresponds to detachment to the lowest excited tripletstate of the neutral with a S0-T1 gap of ∼3eV. The onset of this is also visible for n = 4.n > 10, 2D photoelectron spectroscopybecomes prohibitively time-consuming and we instead measured theirphotoelectron spectra at a single photon energy, hv = 3.6 eV. These photoelectron spectra are shown in n increasesfurther, so does the binding energy, but at a slower rate than forthe smaller clusters. Additionally, the spectral width increases withincreasing n.For clusters with 15 Indirect detachment can take two forms. Electrons can be emittedfrom the resonance by autodetachment, leading to changes in eKE andbroadening of signal in the 2D photoelectron spectra  and a Gaussianfunction (representing direct detachment) and then taking the ratioof their respective amplitudes . The result of this analysis is shown in 32 Therewill also be contributions from direct detachment channels at hv close to their onset and these have been omitted. Theobservation of distinct peaks in – and not to electron transferto the water cluster. Specifically, the fact that peaks do not shiftwith hydration is consistent with previous 2D photoelectron spectroscopystudies on micro-hydrated polycyclic aromatic hydrocarbon anions.17 Additionally, the peaks in hv range to justbelow the VDE43 and this range has been omitted in To determine the positionof the resonances moreprecisely, therelative contribution of thermionic emission at each udes see S2. The rudes see S2. The rudes see S2. The rudes see S2. The rhv ∼3.9 eV corresponds to excitation of π3* and resultsin a relatively sharp feature that is present for all six clustersstudied. The spectral profile of the π3* resonancewas fitted to a Gaussian function for each n andyields an average value for its center of hv = 3.89± 0.03 eV and a full-width at half-maximum of 0.34 eV.2* resonance, although it is less clearlydefined. The thermionic emission signal is present even at the lowestphoton energies used and even below the VDE, such that we cannot determinethe lower bound of the resonance. For the clusters studied, the relativeintensity changes significantly with increasing hv, but for all clusters shows a clear decline at ∼2.7 eV, whichcorresponds to the upper bound on exciting the π2* resonance. As such, the hv region marked in orangein 2* resonance is <1.5–2.7eV. Its spectral width of more than 1 eV in hydrated clusters is similarto that seen for electron attachment in the isolated nucleobase.7A second region of enhanced thermionic electron emission in –(H2O)m clusters upon electronimpact to U(H2O)n (where m ≤ n) instead of the formationof [U – H]− by dissociative electron attachmentas seen for bare U.12 While their experimentwould not be sensitive to anions decaying by thermionic emission,their observation of U–(H2O)m also necessitates the formation of ground stateanions, where stabilization is induced by the dissipation of energyinto the many modes of the cluster and/or H2O evaporation.Hence, the current experiments are complementary by probing the competingelectron evaporation channel, whilst importantly offering mass-selectivity.For n = 8 and 10, the contribution of thermionicemission from the π3* resonance diminishes n from Figure S3). The adiabatic electron affinity, AEA, for each clusteris estimated by considering the onset of each peak . The error in determiningthe VDE is on the order of ±0.05 eV. Using the VDE, AEA, andelectronic resonance positions for each n, an energylevel diagram for U–(H2O)n can be constructed, as shown in 0 ground state (defined as 0 eV).In additionto the resonance positions, we also determine the VDEof U–HOn from 2n, physical propertiescan be correlated to the cluster’s size and evolve linearlyas a function of n–1/3.45 Such a correlation appears to fit the data very well for U–(H2O)n<35. However, thegradient of VDE as a function of n–1/3 does not agree with that expected from continuum dielectric theoryin the bulk limit.45 This is predominantly becauseof a disregard for the volume of the uracil anion in the cluster.To account for this missing volume, the energy level diagram in n + ξ)−1/3, where ξrepresents the volume occupied by the uracil anion relative to thevolume a single water molecule, assuming a bulk solvated U–. A value of ξ = 4 produces a gradient in agreement with thedielectric sphere model .47 This choice ofξ is supported by considering the relative molar volumes ofU– and H2O as well as electronic structurecalculations (see Supporting Information for details),48 and the resulting gradient is also consistentwith other anion-water cluster studies.50 The lineartrend is expected for sufficiently large clusters, while small clustersmay be expected to deviate. In n = 2) showsthe greatest deviation to the linear trend and is not incorporatedinto the linear fits. Extrapolation of VDE as a function of (n + ξ)−1/3 to the bulk limit at n = ∞ −1/3 = 0) gives a VDE of U– in aqueous solution, VDE(aq) = 4.75 ± 0.20 eV. The error in determining VDE(aq) is predominantly associated with the choice of ξ(see Supporting Information) and selecting only larger clusters forthe linear fit )changes VDE(aq) by less than the error.For sufficiently large valuesof 2* and π3* resonances. Whilstwe only have data for relatively small clusters (n ≤ 10), the gradient as a function of (n +ξ)−1/3 for the π3* resonanceis similar to that of the VDE, offering confidence that the resonanceenergies can also be extrapolated to larger sizes. In agreement withrecent studies on the effect of hydration on polycyclic aromatic hydrocarbonanions,17 the excitation energies to the resonancesare invariant to cluster size, however, from the perspective of afree electron impacting the neutral (S0) molecule, theresonances become stabilized by an extent similar to that of the anionground state.16–(aq). Both theπ2* and π3* shape resonances arebound states in U–(aq), with the laterlying ∼0.85 eV below S0. More generally, – in the neutral geometry and hydration sphere. Theenergy difference between the two is the reorganization energy, λ.An estimate of λ can be obtained from the difference in VDE(aq) and AEA(aq), as highlighted in the Marcus-typeplot in n + ξ)−1/3 to a value of AEA(aq) = 3.53 ±0.20 eV, which compares well with a recent computed prediction of3.37 eV.51 Hence, from our experiment wefind that λ = 1.2 eV. The diverging gradients of VDE and AEAin n and is consistent with an increase in λ for largercluster sizes as the solvent reorganization naturally increases. Notethat we are not aware of any other experimental method by which thesefundamental physical properties can be determined for U–(aq). While liquid microjet photoelectron spectroscopycan determine VDE(aq), AEA(aq), and λ,52 it is not clear how these methods can be appliedto unstable radical anions such as U–(aq).It is important to recognize that thecurrent work considers theresonances within the anion’s geometry and hydration sphere.Vertical electron attachment on the other hand will lead to U53 as illustrated in 0 in the neutral geometry and hydration sphereis ∼2λ  higherin the neutral geometry than the anion geometry. Hence, the π3* resonance of U(aq) will be able to capture electronswith a vertical attachment energy, VAE(aq) ∼ 1.6eV (see Supporting Information). Similarly, the high-energy edge ofthe π2* resonance shifts to be above S0 in the neutral geometry so that it too is a resonance, which canbe populated by electrons with very low-energy (VAE(aq) ≲ 0.4 eV, see Supporting Information). Upon formation ofeither resonance, solvation will set in very rapidly 23 to accommodate the change incharge state of the nucleobase, which will dynamically shift the resonanceto lower energy. This would enable the π2* and π3* resonances to adiabatically evolve into bound states. Whilethe resonances are unbound in the present cluster studies, internalconversion can clearly take place to form the bound anion ground state resonances at energies>4 eV,21 although these would likelyhavea lower capture probability. Nevertheless, some evidence for sucha resonance is seen in hv >5 eV.Uracil is verysimilar to the other pyrimidine nucleobases, withboth thymine (T) and cytosine (C) having similar electronic resonancesin the gas-phase.2O)m clusters attached electrons over a relatively narrow rangeof <2 eV, which subsequently leads to evaporation of H2O molecules.12 This could be consistentwith excitation to the π2* resonance, however, astheir experiments have little control over cluster size, drawing directcomparisons is not possible. No other resonances were observed upto 3 eV electron energy. From 3* resonance is likely to lie at higher energy forsmall clusters , andwould therefore not be seen by their experiments. Moreover, signaturesof the π3* resonance may also not be visible if thermionicemission dominates over evaporation at the higher electron energies.Our findings are broadly consistent with those from Kočišeket al. who showed that neutral Un clusters. Both the π2* and π3* shape resonances, which are well-known from electron transmissionspectroscopy of isolated U, have been observed in the water clusters.A significant fraction of these resonances decay to form the groundstate anion in all clusters studied (up to n = 10).Extrapolation with increasing U–(H2O)n cluster size of the resonances,adiabatic detachment, and vertical detachment energies, offers a pictureof the energetics and available resonances in a bulk aqueous environment.We find that AEA(aq) = 3.53 ± 0.20 eV and VDE(aq) = 4.75 ± 0.20 eV and that the reorganization energy,λ ∼ 1.2 eV. The broad π2* resonancein isolated uracil is a bound state in the anion geometry, but thehigh-energy edge remains a resonance in the neutral geometry. As aresult, the π2* resonance can capture electrons withvertical attachment energies, VAE ≲ 0.4 eV, and rapid adiabatichydration dynamics drives the electron binding. The π3* resonance with VAE(aq) ∼ 1.6 eV remains unboundalong a larger fraction of the reorganization coordinate, but eventuallydoes become bound by 0.85 eV in the anion geometry. Recovery of theground electronic state of the uracil anion is observed in all studiedhydrated clusters, suggesting that even when the π3* is a resonance, internal conversion can compete to form a stableuracil anion. Hence, both the π2* and π3* resonances can capture electrons in the bulk aqueous environmentleading to the radical uracil anion in its ground electronic state.The electron captureresonances of uracilin a water cluster environmenthave been determined by 2D photoelectron spectroscopy of the mass-selectedanionic UOur results provide a new route to explore electron impact resonancesin complex environments. For uracil, we have determined the characterof the scattering channels  for the two lowestshape resonances in a bulk aqueous environment, providing a criticalstep towards identifying the resonances involved in the electron captureof DNA mediated by the nucleobases.


When analyzing large datasets from high-throughput technologies, researchers often encounter missing quantitative measurements, which are particularly frequent in metabolomics datasets. Metabolomics, the comprehensive profiling of metabolite abundances, are typically measured using mass spectrometry technologies that often introduce missingness via multiple mechanisms: (1) the metabolite signal may be smaller than the instrument limit of detection; (2) the conditions under which the data are collected and processed may lead to missing values; (3) missing values can be introduced randomly. Missingness resulting from mechanism (1) would be classified as Missing Not At Random (MNAR), that from mechanism (2) would be Missing At Random (MAR), and that from mechanism (3) would be classified as Missing Completely At Random (MCAR). Two common approaches for handling missing data are the following: (1) omit missing data from the analysis; (2) impute the missing values. Both approaches may introduce bias and reduce statistical power in downstream analyses such as testing metabolite associations with clinical variables. Further, standard imputation methods in metabolomics often ignore the mechanisms causing missingness and inaccurately estimate missing values within a data set. We propose a mechanism-aware imputation algorithm that leverages a two-step approach in imputing missing values. First, we use a random forest classifier to classify the missing mechanism for each missing value in the data set. Second, we impute each missing value using imputation algorithms that are specific to the predicted missingness mechanism . Using complete data, we conducted simulations, where we imposed different missingness patterns within the data and tested the performance of combinations of imputation algorithms. Our proposed algorithm provided imputations closer to the original data than those using only one imputation algorithm for all the missing values. Consequently, our two-step approach was able to reduce bias for improved downstream analyses.The online version contains supplementary material available at 10.1186/s12859-022-04659-1. Metabolomics refers to the comprehensive profiling of metabolite abundances, which are typically measured using mass spectrometry (MS) or nuclear magnetic resonance (NMR) spectrometry . While tThese mechanisms for missing data can be described in the context of three general frameworks. Sparsity resulting from mechanism (1), (2), and 3) are referred to as Missing Not At Random (MNAR), Missing At Random (MAR), and Missing Completely At Random (MCAR)  are refe. If the A technique for omitting missing data is to assess whether multivariate data missing values are MCAR or not, before omitting the values . HoweverIn recent years, many imputation algorithms have been developed to estimate data that are missing, but they tend to be optimal for a particular missing mechanism . CommonlIn this work we propose a novel Mechanism-Aware Imputation (MAI) algorithm that relies on first predicting the missing mechanism (MAR/MCAR versus MNAR) using a Random Forest classifier . Once miLet mentclass2pt{minimThe fit-transform approach is different from a traditional machine learning approach in that the new data that we wish to make predictions on is the starting data set. Moreover, the fit-transform approach draws complete data from the starting data set and transforms this complete subset into a structured data set to which we can apply traditional machine learning algorithms.To build our classifier, we first need to extract a complete data subset from input data mentclass2pt{minimAfter extracting our complete data subset entclass1pt{minimaEST, βEST, and γEST, in the mixed-missingness algorithm. The purpose of estimating these parameters is to ensure that when we impose missingness in the complete data subset the input data matrixEST ranges from 5% up to the total percent missing values in αEST ranges from 60% up to 80%, in increments of 5%.βEST ranges from 5% up to 60% in increments of 5%.γDefine the gridFor each entry in the grid in step 1, impose missingness with the MM algorithm according to specified values into Sort the rows of Calculate the proportion of missing values in each row of Calculate the Euclidean distance between the two vectors generated in step 4 and store the distance measurement.EST, βEST, and γEST parameter values corresponding to the smallest distance, as well as the distance value itself.After iterating over all the grid-values, store the αEST, βEST, and γEST parameters that correspond to the smallest distance.Repeat steps 2–6, 10 times and select the αTo estimate the mixed-missingness parameters of our data and impose missingness on the fully observed complete data subset One iteration of this algorithm is depicted in Additional file EST, βEST, and γEST parameters that correspond to the smallest distance from the grid search are then used to impose classified missingness on the complete data subset The αOur proposed algorithm used to estimate the MM parameters . For rows with a target of MCAR or MNAR, the metabolite abundance feature is defined as zero , we impute the missing values using a combination of two imputation algorithms; one algorithm imputes the MCAR classified values, and the other algorithm imputes the MNAR classified values. Figure p = 300 metabolites and n = 100 subjects. This complete subset is our original oracle data. As a second application, we consider another plasma metabolomics data set from COPDGene. In COPDGene Data Set 2, the fresh frozen plasma from patients in Phase I of COPDGene was profiled using untargeted LC–MS (C18+) and (HILIC+) metabolite quantification platforms [https://www.metabolomicsworkbench.org), with Project IDs PR000907 and PR000438 respectively. For the purpose of this work, we used versions of both data sets before any imputation was performed.To test our method, we use two real-world untargeted metabolomics data set from the COPDGene cohort . Chroniclatforms . After oAdditional file Using the imposed oracle data and the sample classified data we validate our random forest classifier using the following accuracy metric: proportion of true missingness-type predictions divided by the total predictions made. To avoid inflating accuracy, we omit the O (other) class when reporting accuracy, since we will always get 100% accuracy for this class.Single ImputationnsKNNQRILCMNAR Imputation Algorithms:BPCARandom ForestIterative nsKNNMCAR Imputation AlgorithmsWe implement different imputation algorithms that were recommended by Ni et al.  in orderIn a similar manner to a single imputation approach for linear regression with a randomly right-censored covariate , we deveThis method is similar to classical KNN , howevertune.sigma is used at the default value of 1, which corresponds to the case where the complete data distribution is Gaussian.This method uses a quantile regression approach for the imputation of left-censored missing values . We implBPCA uses expectation-maximization as well as a Bayesian estimation method to determine the likelihood of an estimated value . We implMissing values are imputed by iterative fits of random forest regression model. We implemented this algorithm in the R statistical language using the package missForest . We use We develop an iterative version of the standard NS-KNN . This meTo test the accuracy of each algorithm in different missingness scenarios, we selected four different γ scenarios, and fixed α and β to 30% and 70%, respectively. Recall that the α is the parameter that defines the boundary between the “high” versus “medium” and “low” average metabolite abundance groups, and the β parameter defines the boundary between the “medium” and the “low” average metabolite abundance groups. Note that due to the settings of the simulation method, once α is set there are no MNAR values introduced in the high abundant metabolites, we can change the definition of a high abundant metabolite by changing α which allows metabolites with larger mean abundances to be missing as MNAR. We introduced missingness patterns using the MM algorithm on the original oracle data with varying ratios of MCAR to MNAR values defined by our selection of γ values. These parameter values and their effects are displayed in Table We repeat the above procedure 50 times and report the means and standard errors of the normalized root mean square error (NRMSE) based on the true and the imputed values.In order to evaluate our proposed approach, for each missingness scenario, we apply the two-step MAI, and separately, each individual imputation algorithm approach across 50 repetitions and report the means and standard errors of the NRMSEs based on the true and the imputed values.The mean and median accuracies of the random forest classification model for the four simulated missingness patterns across 450 scenarios  are depicted in Table Table We evaluated effect of sample size (n) on the accuracy of the random forest classifier and tested for varying n with 30% total imposed missingness with fixed γ = 23%, α = 30%, and β = 70%  and (2) Best Possible Imputation .Figure Confidence intervals for the pairwise differences of mean NRMSEs for the three imputation methods did not include zero for the 10% total missing case  or non-omics data sets .The computational time of MAI is dependent on the size of the data set, the algorithms used in imputing the MCAR and MNAR classified missing values, and the total number of missing values present. For COPDGene Data Set 1 with 30% total missing it takes, on average, 2.2 min to impute MCAR values using random forest imputation and MNAR values using single imputation . In contrast, using Multi-nsKNN imputation for MCAR values and nsKNN imputation for MNAR values, it takes, on average, 1.7 min and 46.1 s for 30% total missing and 10% total missing, respectively. Computational time is measured on a MacBook Pro with MacOS BigSur, 2.9 GHz 6-Core Intel Core i9 processor, and 32 GB RAM.In this article, we propose MAI—a missing-mechanism aware two-step approach—which imputes missing data more accurately than standard imputation procedures. Incorporating a random forest classifier in step one, we first predict a missing mechanism for the missing values. Then in step two, we impute those missing values using the predicted missing mechanism-specific imputation algorithms. Such mechanism-aware imputations result in better estimation of the true, unobserved (missing) data in terms of higher statistical power and less biased estimates, and consequently, more reliable conclusions derived from downstream data analyses.https://gitlab.com/Dekermanjian/mechanismaware_imputation. We have also built a Bioconductor R package available at https://www.bioconductor.org/packages/devel/bioc/html/MAI.html. Links to both the R package and the REST API can also be found at Metabolomics Workbench: https://www.metabolomicsworkbench.org/tools/externaltools.php.We have developed MAI into a REST API at GitLab: Additional file 1. Additional algorithms detail, and additional simulation and sensitivity analysis results.