Spexin (SPX) is a novel neuropeptide and adipokine negatively correlated with obesity and insulin resistance. A recent study investigated expression and regulatory function of SPX in the hypothalamus and pituitary; however, the effect on ovarian function is still unknown. The aim of this study was to characterize the expression of SPX and its receptors, galanin receptors 2 and 3 (GALR2/3), in the human ovary and to study its in vitro effect on granulosa cells (GC) function. Follicular fluid (FF) and GC were obtained from normal weight and obese healthy and diagnosed with polycystic ovarian syndrome (PCOS) women. Expression of SPX and GALR2/3 in the ovary was studied by qPCR, western blot, and immunohistochemistry. The level of SPX in FF was assessed by enzyme-linked immunosorbent assay. The in vitro effect of recombinant human SPX on GC proliferation, steroidogenesis, and signaling pathways  was analyzed. Moreover, GC proliferation and estradiol (E2) secretion were measured with and without an siRNA against GALR2/3 and pharmacological inhibition of the above kinases. The results showed that both the SPX concentration in FF and its gene expression were decreased in GC of obese and PCOS women, while the protein expression of GALR2/3 was increased. We noted that SPX reduced GC proliferation and steroidogenesis; these effects were mediated by GALR2/3 and kinases MAP3/1, AKT, and STAT3 for proliferation or kinases MAP3/1 and PKA for E2 secretion. The obtained data clearly documented that SPX is a novel regulator of human ovarian physiology and possibly plays a role in PCOS pathogenesis. We observed decreased spexin (SPX) levels in granulosa cells (GC) and follicular fluid collected from obese and polycystic ovarian syndrome women, and we noted an inhibitory effect of SPX on GC proliferation and steroidogenesis.  RLIG1, previously known as C12ORF29) gene, which is located on chromosome 12 and consists of six exons and five introns. This gene encodes a SPX prepropeptide of 116 amino acids, while an active neuropeptide is built from a 14-amino-acid polypeptide [Spexin (SPX), a novel neuropeptide and adipokine, was discovered in 2007 using a bioinformatics method based on a hidden Markov model . In humaypeptide . Structuypeptide  or reducypeptide , 9, and ypeptide . Moreoveypeptide  and pancypeptide . SPX actypeptide .Fsh) gene expression [Some evidence also indicated a close relationship between SPX and reproduction, by describing its expression in tissues of the hypothalamus–pituitary–gonads (HPG) axis . Its prepression . HoweverSpx transcript was decreased in the ovary of letrozole-induced PCOS rats [Interestingly, recent studies suggest that SPX may be a novel key player in the pathophysiology of polycystic ovarian syndrome (PCOS); the serum level of SPX is inversely associated with androgens and metabolic profiles in PCOS women . Also, oCOS rats . In the COS rats . ApproxiCOS rats , and it COS rats . BesidesCOS rats , while iCOS rats . All PCOCOS rats . Thus, tCOS rats . Levels COS rats  and adipCOS rats  were decCOS rats  and visfCOS rats , suggestCOS rats .Thus, we hypothesize that SPX and GALR2/3 are expressed in human ovarian cells and the follicular fluid (FF) of women and that SPX directly regulates GC function. Hence, in the present work, we investigated (i) gene and protein expression of SPX and GALR2/3 in GC of normal weight and obese healthy women and diagnosed with PCOS, its immunolocalization in the human ovary, as well as SPX levels in FF; (ii) the in vitro effect of SPX on GC proliferation and steroidogenesis; and (iii) the molecular mechanism of SPX action by GALR2/3 silencing and pharmacological inhibition of kinases: MAP3/1, AKT, and protein kinase A (PKA), as well as signal transducer and activator of transcription 3 (STAT3).The study was conducted according to the principles set out in the Declaration of Helsinki. Informed consent was obtained from each participant, and the study protocol was approved by the Institutional Review Board .2) or obese (BMI > 30 kg/m2). Characterization of patients is presented in Studied patients were recruited among women at 21–41 years (32 ± 4.7) admitted to the referral Centre for Reproductive Medicine of Tours University Hospital (2011–2022) for infertility requiring in vitro fertilization (IVF) assistance. The ovarian stimulation protocol and IVF, which were the same for all patients included in the study, were described previously . Patientg for 10 min) to separate cell remnants from FF. Then, FF was stored at −80°C for later analyses. Human GC were isolated by 20 min of centrifugation at 400 × g on a two-layer discontinuous Percoll (Cytiva) gradient  in 10% fetal bovine serum (FBS) in McCoy (Sigma-Aldrich) medium (The FF and primary human luteinized GC were obtained from the cumulus–oocyte (Oo) complexes collected during Oo retrieval as part of the IVF procedure. Fluid collected after punctuation was centrifuged (400 × ) medium  to remov2/5% CO2. After 24 h, the medium was replaced with fresh medium containing 1% FBS, and cells were starved for 24 h to reduce effect of hormones or growth factors presented in FBS.Human GC were obtained as described above from patients. In addition, we used the KGN steroidogenic human GC-like tumor cell line expressing functional FSH receptors  . KGN werExperiment 1: to investigate the effect of SPX on GC proliferation after 24 h of starvation, GC were treated with SPX  at doses of 0.1–100 nM [−8 M; Merck) [PCNA) mRNA levels or boiled in Laemmli buffer for 4 min for the protein expression of PCNA.; Merck)  and SPX Experiment 2: to study the role of SPX in GC steroidogenesis and GALR2/3 expression, cells were treated with SPX at doses of 0.1–100 nM for 48 h in the presence of A4 (0.1 mol/L) and IGF1 or FSH alone or with the addition of SPX (1 nM). Next, the culture medium was collected to investigate progesterone (P4) and estradiol (E2) levels, while cells were washed in PBS and stored at −80°C for mRNA quantification of steroidogenic acute regulatory protein (STAR), cytochrome P450 family 11/17 subfamily member A1 , 17β-hydroxysteroid dehydrogenase (HSD17B), 3β-hydroxysteroid dehydrogenase (HSD3B), and aromatase (CYP19A1) or boiled in Laemmli buffer for 4 min for the protein expression measurement of steroidogenic enzymes and GALR2 and GALR3 receptors.Experiment 3: to study the molecular mechanism of SPX action on GC, firstly we analyzed kinase phosphorylation patterns. Briefly, KGN cells were incubated with SPX (1 nM) for 1, 5, 15, 30, 45, and 60 min. Subsequently, cells were washed in PBS and boiled in Laemmli buffer for 4 min for the pMAP3/1/MAP3/1, pAKT/AKT, pSTAT3/STAT3, and pPKA/PKA protein expression.Experiment 4: in the next part of the experiments, cells were pre-treated for 1 h with pharmacological inhibitors of MAP3/1 , AKT , or STAT3 , and PKA , respectively. The doses of inhibitors were based on our previous papers [s papers . SubsequExperiment 5: finally, we investigated GALR2/3 involvement in SPX action on GC proliferation and steroidogenesis. To validate the efficiency of silencing, KGN were incubated for 24 h in DMEM without FBS and then transfected with GALR2/3 or negative control siRNA  using lipofectamine RNAiMAX (Thermo Fisher Scientific) according to the manufacturer’s instructions. After an additional 24 h of incubation, GALR2 and GALR3 gene and protein expression were assessed. According to transfection efficiency, we selected a dose of 20 pM for subsequent experiments. Subsequently, after 24 h of incubation with GALR2 or GALR3 siRNA, we added SPX (1 nM) for an additional 48 h. Next, alamarBlue (Invitrogen) was added for cell proliferation measurement, or culture medium was collected for E2 concentration analysis.−ΔΔCt method.RNA extraction was performed with TRIzol Reagent according to the manufacturer’s procedure. Subsequently, RNA and cDNA quantity were evaluated by measuring absorbance at the 260- and 280-nm wavelengths by spectrophotometry . ReverseCell lysis, western blotting, electrophoresis, and transfer were performed as we described previously . ProteinTo determine the SPX level in FF and steroids in cultured GC, ELISA kits for SPX , P4, and E2 (DRG Instruments GmbH) were used. The limit of assay sensitivity was 0.11 ng/mL for SPX, 0.045 ng/mL for P4, and 9.714 pg/mL for E2. The inter- and intra-experimental coefficients of variation were, respectively, <10% and <15% for SPX, <9.96% and <6.99% for P4, and <9.39% and <6.81% for E2. Samples were run in duplicate within the same assay. Absorbance was measured at the 450 nm wavelength for SPX or the 405 nm wavelength for steroids using a Varioskan LUX reader (Thermo Fisher Scientific).Ovary serial sections Biomax;  from norTo determine GC proliferation, the alamarBlue stock solution was aseptically added to wells in amounts equal to 10% of the medium incubation volume. Subsequently, after 2 h of incubation with alamarBlue, the fluorescence was determined at the 530- and 590-nm wavelengths using a Varioskan LUX reader (Thermo Fisher Scientific).P <0.05, and detailed P-values were added in Results are shown as mean ± SEM. One-way and two-way ANOVA followed by post hoc tests were used. Results were not adjusted for age or any other factor. All data were also tested for the assumptions of normality (Shapiro–Wilk test) and homogeneity of variances (Levene test). Statistical analysis was performed using GraphPad Prism 8 (PRISM) software, significance was checked at the level SPX gene expression was decreased in GC of obese, PCOS normal weight, and PCOS obese subjects compared with normal weight women by 3.7, 4.13, and 7.33 folds, respectively (P < 0.05). The transcription level of GALR2 was stable between groups. Gene expression of GALR3 was increased in GC of obese, PCOS normal weight, and PCOS obese compared to normal weight by 1.66, 2.25, and 1.56 folds, respectively (P < 0.05). At the protein level, we observed that GALR2 expression was elevated in GC of PCOS normal weight and obese compared to normal weight women. Expression of GALR3 was increased in GC of obese and PCOS obese compared to normal weight women (P < 0.05). There is no available anti-SPX antibody for western blot; therefore, its level was not analyzed.We noted that P < 0.05). Moreover, we detected an SPX signal and both receptors GALR2/3 in GC, theca cells (Tc), Oo, and surrounding cumulus cells . Both GALR2 and GALR3 protein expression was elevated compared to normal weight control (P < 0.05).The decreased transcript level of PCNA mRNA level, which was inhibited by SPX at 1, 10, and 100 nM (P < 0.05). Besides, SPX at all investigated doses inhibited PCNA protein levels in KGN cells (PCNA gene expression (P < 0.05).As shown in GN cells . As we nGN cells , but redP < 0.05). In addition, SPX decreased PCNA transcript levels at doses of 10 and 100 nM in GC of normal weight and PCOS obese women and at doses of 1, 10, and 100 nM in obese and PCOS normal weight women (P < 0.05). As shown in P < 0.05). It was confirmed by analysis of PCNA transcript levels. In addition, we observed no effect of SPX on FSH-induced cell proliferation, whereas in GC of normal weight women, we noted a decrease in PCNA expression after SPX with FSH (P < 0.05).In human primary GC, we showed that SPX at 10 and 100 nM decreased cell proliferation significantly in all investigated groups after 24 h (P < 0.05). Interestingly, SPX at doses of 1 and 10 nM decreased E2 secretion (P < 0.05), while no effect on IGF1- and FSH-induced E2 secretion was observed (As shown in observed .P < 0.05). Furthermore, we noted an inhibitory effect of SPX on E2 secretion by GC in women of all studied groups: at 100 nM in the normal weight group, and at 10 and 100 nM in the obese, PCOS normal weight, and PCOS obese groups (P < 0.05). Moreover, no effect of SPX was induced in response to both IGF1 and FSH on P4 , while no effect on transcript levels of HSD3B, HSD17B, and CYP19A1 was demonstrated. Moreover, we observed that SPX (1 nM) decreased both IGF1- and FSH-induced CYP11A1 and CYP17A1 mRNA expression (P < 0.05).We noted that in KGN cells, SPX decreased the gene expression of As shown in HSD3B transcript levels in GC of the normal weight, obese, and PCOS obese groups and at doses of 10 and 100 nM in the PCOS normal weight group (P < 0.05). SPX had an inhibitory effect on CYP19A1 expression at 10 and 100 nM in the normal weight, PCOS normal weight, and PCOS obese groups and at doses of 1, 10, and 100 nM in GC of obese women. Furthermore, in GC of normal weight women, we noted that SPX decreased the IGF-induced HSD3B level, whereas it had no effect in the response to FSH (P < 0.05).In primary human GC, we observed that SPX at 1, 10, and 100 nM decreased P < 0.05). We noted that SPX at 1 nM modulated phosphorylation of the following kinase pathways in a time-dependent manner: at 1, 5, 15, 30, 45, and 60 min, it stimulated the phosphorylation of MAP3/1 and reduced the phosphorylation of PKA, STAT3, and AKT (P < 0.05).We showed that SPX at 1, 10, and 100 nM elevated GALR2 protein levels, whereas all investigated doses inhibited GALR3 expression  (P < 0.05). This observation was partly confirmed on the protein level except at a dose of 10 pM (P < 0.05). Finally, both siRNA and pharmacological inhibitors PD98059, AG490, and LY294002 added along with SPX reduced the SPX inhibitory effect on GC proliferation (P < 0.05), while both siRNA and inhibitors PD98059 and KT5720 added along with SPX reduced the effect of SPX on E2 secretion (P < 0.05). We also observed that both siRNA and kinase inhibitors added alone had no effect on GC proliferation or E2 secretion.Next, the efficiency of GALR2/3 silencing was checked: on the mRNA level, siRNA for The present study was the first to demonstrate expression of the SPX/GALR2/GALR3 system in human GC. We observed decreased levels of SPX in GC and FF of obese and PCOS women, in contrast to the expression of galanin receptors. In addition, we confirmed our hypothesis that SPX affects human GC function and we noted a negative in vitro effect of SPX on GC physiology including steroidogenesis and proliferation via activation of GALR2/3 receptors and kinases MAP3/1, PKA, STAT3, and AKT, which indicate that SPX may be a novel modulator of GC physiology and closely linked with PCOS.GALR3 transcript was increased, but the GALR2 level was stable in GC of obese and PCOS women, while on the protein level, the expression of both receptors was elevated. Differences between the gene and protein levels may be explained by complex and diverse post-transcriptional mechanisms involved in converting mRNA to protein not yet sufficiently defined to be able to calculate protein concentrations from mRNA [Galr2/3 transcript increased in mouse subcutaneous adipose tissue [Galr2/3 expression in hypothalamic neurons of mice [Galr2 expression in proopiomelanocortin rat neurons [Galr3 expression in the pituitary of female rats [Our data showed, for the first time, decreased expression of the SPX transcript in human GC collected from obese women and those diagnosed with PCOS. Thus, we can confirm that ovarian cells are able to produce SPX and change its level in FF, as was noted previously for other adipokines such as omentin . Our datrom mRNA . Our obse tissue  and rat e tissue . In addi of mice . Moreove of mice . In addi neurons , while Eale rats .We observed immunolocalization of SPX and GALR2/3 in GC and Tc, as well as Oo and Cc, which is in agreement with the previous data that describe its expression in rat ovaries. In rats, SPX immunoreaction was mainly cytoplasmic in thecal, luteal, and interstitial cells of the ovary  showed nThe proliferation of GC is an important process in ovarian physiology necessary for proper folliculogenesis and even Oo growth . During HSD3B and CYP19A1 mRNA expression in human GC, whereas in a KGN model, SPX decreased STAR, CYP11A1, and CYP17A1, with no effect on HSD3B, HSD17B, and CYP19A1 transcripts. As is well known, HSD17B participates in A4 conversion to testosterone, so its overexpression may be linked with addition of A4 to the medium, which is necessary for E2 synthesis. An increased A4 concentration is connected with PCOS, in which we observed a decreased SPX level [CYP19A1 mRNA in KGN. In addition, as previously shown, primary human GC respond more strongly to IGF1 or FSH in P4 secretion than KGN cells [In the next step, we investigated the effect of SPX on steroidogenesis because proper synthesis of steroid hormones is crucial for follicle growth, ovulation, corpus luteum formation, and hormonal homeostasis in the body . Our datPX level . An addiPX level . InteresGN cells . There aGN cells , and thuGN cells , which iLepr) in mouse liver [It is previously known that SPX participates in regulation of body energy metabolism via activation of galanin receptors, improving lipolysis and fatty acid oxidation via GALR2 signaling in mouse liver  and inhise liver , and vasse liver . Therefose liver . Moreovese liver . In our se liver , thus inse liver  and Mailse liver  showed tse liver .In summary, our data first showed decreased SPX levels in GC and FF of PCOS and obese women. In addition, SPX negatively influenced GC function by inhibiting cell proliferation via GALR2/3 and MAP3/1, STAT3, and AKT, and E2 secretion via GALR2/3 MAP3/1, and PKA, which is a feature of PCOS connected with inhibited ovulation and changes in hormones homeostasis. In light of these findings, SPX appears to be a novel modulator of GC physiology and could represent a relevant player in PCOS pathogenesis. However, further studies are needed to characterize the role of SPX in the whole ovary because, as previously described for vaspin, its effect in the porcine ovarian follicles on kinase phosphorylation varies depending on whether it was cultured in co-cultures of GC and Tc or in monocultures . In addiSupplementary_Table_1_ioad108Click here for additional data file.Supplementary_Table_2_ioad108Click here for additional data file.Supplementary_Table_3_ioad108Click here for additional data file.Supplementary_Table_4_ioad108Click here for additional data file.


As an important part of the stomach, gastric antrum secretes gastrin which can regulate acid secretion and gastric emptying. Although most cell types in the gastric antrum are identified, the comparison of cell composition and gene expression in the gastric antrum among different species are not explored. In this study, we collected antrum epithelial tissues from human, pig, rat and mouse for scRNA-seq and compared cell types and gene expression among species. In pig antral epithelium, we identified a novel cell cluster, which is marked by high expression of AQP5, F3, CLCA1 and RRAD. We also discovered that the porcine antral epithelium has stronger immune function than the other species. Further analysis revealed that this may be due to the insufficient function of porcine immune cells. Together, our results replenish the information of multiple species of gastric antral epithelium at the single cell level and provide resources for understanding the homeostasis maintenance and regeneration of gastric antrum epithelium. The online version contains supplementary material available at 10.1186/s13619-023-00171-w. As an important digestive organ, the stomach secretes acids and enzymes, performs the function of food storage and digestion, and kills harmful microorganisms. Structurally, the human stomach can be divided into corpus and antrum, which show differences in epithelial cell type and function , pit progenitor cell, progenitor cell, basal gland mucous cell (AQP5), proliferative cell , chief cell (PGC), tuft cell , endocrine cell  and parietal cell  . BGMCs were uniformly distributed among four species, but F3+ cells were unique to pig  staining, and found that the length of antrum glands in pig is similar to that in human Fig. SA. Moreovse Fig. SB and C. B) Figs. D. FurtheM5 Fig. SD. Two ceTo better analyze the gastric antrum of the four species, we performed PCA analysis and found that the intra-species differences of pig gastric antral epithelial cells were minimal among the four species Fig. D. In theNEDD4L  enrichment analysis revealed that genes specifically and highly expressed in F3sis Fig. E. It is CD74  Fig. A. The ceMKI67, BIRC5, TOP2A and PCNA were highly expressed in pig T cells and B cells, while the immune-related genes IL7R, CD7 and CXCR6 high in human  in pig gastric antral epithelium, which highly expressed AQP5, F3, CLCA1 and RRAD. Due to the limitation of scRNA-seq depth, further functional analysis of this cell cluster was impossible. We have also tried to investigate the potential function of F3+ cells in an organoid system. However, pig antral organoids predominantly consist of proliferative cells, and F3 expression was not detected due to the specific culture conditions requiring high levels of Wnt3a. As F3+ cells express the markers of serous cells in submucosal glands of pig lung  with prior approval of the ethics committee of The First Affiliated Hospital of Nanjing Medical University, Nanjing (2017-SR-171.A2). Anonymized samples  of Tsinghua University (19-YGC). Bama miniature pigs were used in this study from Beijing Farm Animal Research Center . The experimental protocols were approved by the Animal Ethics Committee of the Institute of Zoology, Chinese Academy of Sciences (IOZ20180061).The antrum tissue was extracted from four adult human, three adult mice (10 weeks), three adult rats (3 months old) and three adult pigs (6 months old). Fragments of the gastric antrum region were isolated from different species. The digestion protocol of the gastric epithelial cells was varied in species. The antrum fragments of human, mouse, rat and pig antrum was incubated with 20 mM EDTA digestion for 25 min at 4 °C. Then, the gastric glands from these species were scraped from tissue and collected. Then for human, mouse and rat antrum were followed by Tryple (Invitrogen) digestion for 10–15 min at 37 °C. For pig antrum, the epithelial cells were incubated with 10,000 U/mL collagenase IV (Thermo Fisher), 30 mg/ml dispase II (Roche), and 1 M hepes (MACKLIN), 2500 U/ml DNase I (KeyGEN) in Advanced DMEM F12 for 15 min at 37 °C. After filtering with 40 μm strainer and stained with propidium iodide , PI-negative cell cells were sorted by FACS (Beckman). Single cells were loaded onto the single cell chip from 10X genomics Chromium Single Cell 3′ Solution. The cDNA library was constructed according to instruction and sequenced by Illumina Novaseq 6000 sequencer  with paired-end 150-bp reads.The antrum tissue was cut from stomach of these species and washed by cold PBS for 5–6 times to remove the contaminant. After incubation with 20 mM EDTA for 25 min at 4 °C, gastric glands were carefully scraped and collected. Then, after centrifugation (3 min at 1000 rpm), the gastric glands were embedded into Matrigel (BD Biosciences) and seeded on 24-well plate. After polymerization, the culture medium was added. Advanced DMEM/F12 was supplemented with 2 mM GlutaMAX, 1 mM N-acetylcysteine, 1X N2, 1X B-27 and penicillin/streptomycin to prepare a basal medium . The organoid culture medium for human and mouse antrum included 50 ng/mL EGF (Peprotech), 100 ng/mL Noggin (Novoprotein), 500 ng/mL R-spondin-1 (Novoprotein), 5 μM CHIR-99021 (Selleck), 10 nM Gastrin (TOCRIS), 100 ng/mL FGF10 (Novoprotein), 10 μM SB431542 (Selleck) and 10 μM Y-27632 (Selleck) in basal medium. The organoid medium for rat and pig antrum was supplemented with 30% wnt3a conditional medium. Growth medium was replaced every 3–4 days.For TNFα stimulation, organoids derived from human, mouse, rat and pig antrum were prepared and cultured in 24-well plate. Then, after 2 days treatment of 10 ng/mL TNFα, organoids were removed from Matrigel and lysed for RNA isolation.The gastric tissue was fixed using 4% formalin overnight and subsequently embedded in paraffin. To prepare the sections for analysis, 5 μm thick sections were deparaffinized using a series of graded alcohols and isopropanol. The sections were then subjected to H&E staining using a commercial H&E staining kit (Beyotime). Briefly, the sections were stained with hematoxylin solution for 6 min and followed by treatment with 1% acid alcohol for 2 s. Subsequently, the sections were stained with eosin for 2 min using the eosin solution provided in the H&E staining kit .Immunofluorescence was performed as previously described , rabbit anti-AQP5 antibody , rabbit anti-Ki67 , mouse anti-PCNA , mouse anti-HK-Atpase-β , rabbit anti-E-cadherin , rabbit anti-CD74  and mouse anti-E cadherin . FITC-conjugated UEAI lectin  and Lectin GS-II conjugate with Alexa Fluor 647 .The total RNA from organoids was extracted by RNeasy Mini Kit (Qiagen). The cDNA was obtained by 1 st Strand cDNA Synthesis Super Mix (Novoprotein). Then, real-time PCR reactions were performed using qPCR SuperMix Plus (Novoprotein) in triplicates on a LightCycler 480 (Roche). The primers of selected gene were shown in Table SAfter total RNA extraction and then subjected to high-throughput sequencing on an Illumina Novaseq PE150 platform. RNA-seq was carried out with two biological replicates.https://asia.ensembl.org/biomart/martview/efb2456d7ea6a4d37b6a2a9f03499a88). Other three species were compared to human and a high-quality ortholog genes list was extracted. To account for gene paralogs and gene-duplication events, an aggregated table of “meta-genes” was created. Each meta-gene may include all gene symbols homologous to one human gene. For each organism, read counts were combined across all manifestations of each meta-gene. Finally, we sorted out 14,331 orthologous genes across 4 species, including 13,343 “1–1-1–1” orthologous genes and 988 “1-many” genes.To compare transcription between species, we first created a gene ortholog list using the human genes as the reference. We download homologous gene lists from Ensemble BioMart , and Cell Ranger (v3.1.0) . Variable genes were detected using “FindVariableFeatures”. We used “FindIntegrationAnchors” to combine the scRNA-seq libraries of the four species. The scaled gene expression data were projected onto principal components (PCs). The first 30 PCs were used for non-linear dimensionality reduction using Uniform Manifold Approximation and Projection (UMAP). Clustering was performed using the “FindNeighbors” followed by the “FindClusters” functions. Marker genes for each cluster have been identified using “FindAllMarkers” function.The four batches of scRNA-seq data from human, pig, rat and mouse were subjected to batch correction as described previously  tool with default parameters. PCA analysis were performed using R software.To identify signature genes of each cell types, functions “FindAllMarkers” and “FindMarkers” in Seurat were used. The function “FindMarkers” was used for identification of signature genes by comparing the cell type of interest to another specific group of cells. Functional enrichment analysis was performed using the online software DAVID  with default parameters.RNA-seq reads were aligned to the human and mouse genomes available in Ensembl (release 95) using HISAT2 (v2.1.0) , and AQP5 labeling antrum stem cells (C) in the antrum. Scale bar: 100 μm. Fig. S2. A graphical abstract showing the main workflow of this study. Schematic of stomach anatomy and cross-species scRNA-seq analysis in human, pig, rat and mouse. Dashed box indicates the gastric antrum epithelial region selected for scRNA-seq in all species. Fig. S3. scRNA-seq analysis reveals the landscape of epithelial cells in gastric antrum in human, pig, rat, and mouse. A The quality information of scRNA-seq from each species. B scRNA-seq analysis of gastric antral epithelium of human, pig, rat, and mouse as visualized by UMAP. C Violin plots show the range of genes identified by scRNA-seq in each species. D Expression levels of marker genes in each cell type. Pit mucous cell , basal gland mucous cell (AQP5), proliferative cell , chief cell (PGC), tuft cell , endocrine cell  and parietal cell . Color from gray to red indicates relative expression levels from low to high. Fig. S4. Distribution of F3+ cells in the pig antrum. A F3+ cells in the pig antrum glands, extending from the top to the bottom. B Expression of F3 and GSII in the pig antrum glands. Scale bar: 100 μm. C Heatmap of differentially expressed genes between BGMCs and F3+ cells. Fig. S5. The antrum epithelial cells of pig express high levels of immune response genes. A Expression of CD74 in the gastric antrum epithelial tissues of human, pig, rat, and mouse. B Heatmap shows the expression level of immune response genes in gastric antrum epithelial organoids of four species through bulk RNA-seq. C Heatmap shows the expression of immune function genes in gastric antrum epithelial organoids. D Heatmap shows the highly expressed genes in organoids of human, pig, rat, and mouse (left). The change trend in each module is shown in the line chart on the right. E Venn diagram indicates the up-regulated gene number of organoids treated with TNFα in four species. Fig. S6. T cells and B cells in pig antrum show high proliferation and low immunity compared to those in human antrum. A Dot plot showing scaled expression level  and percent of expressing cells (point diameter) of marker genes in each cell cluster. B The cell ratio of immune cells  in human and pig, based on scRNA-seq. C Dot plot showing scaled expression level  and percent of 8 expressing cells (point diameter) of immunity genes (left) and proliferating genes (right) in each cell cluster of human and pig. D, E Function enrichment analysis of highly expressed genes in B cells (D) and T cells (E) of human and pig. Fig. S7. Proliferative signal in antrum glands of human and pig A Expression of MKI67 in the antrum of human and pig. B Expression of PCNA in the antrum of both human and pig. C Quantification of MKI67+ and PCNA+ cells in nonepithelial cells per view in panels (A) and (B). Scale bar: 100 μmAdditional file 2: Supplemental Table S1. Cell number and gene counts of four species scRNA-seq libraries in Fig. SAdditional file 3: Supplemental Table S2. The cell ratio of each cell type in the gastric antral epithelium of the four species in Fig. Additional file 4: Supplemental Table S3. Bulk RNA-seq shows the FPKM of genes that have higher expression in pig gastric antrum in Fig. Additional file 5: Supplemental Table S4. FPKM of genes related with activation of T cells and B cells in pig organoids of control and TNFα treatment in Fig. Additional file 6: Supplemental Table S5. The cell ratio of each cell type in human and pig in Fig. SAdditional file 7: Supplemental Table S6. The list of each immune family in Fig. Additional file 8: Supplemental Table S7. Shows information about the human antrum samples.Additional file 9: Supplemental Table S8. Shows quantitative PCR primers.


Kiwifruit is a climacteric fruit, in which the accumulation of flavor substances mainly occurs at the postharvest ripening stage. However, the dynamic changes in metabolite composition remain poorly understood. Here, targeted multi-platform metabolome analysis based on GC-MS and UPLC-MS/MS and enzyme activity analysis were performed at different postharvest ripening stages of kiwifruit. A total of 12 soluble sugars and 31 organic acids were identified. The main soluble sugars are sucrose, glucose and fructose, which exhibited similar variation tendencies along with the extension of ripening. The main organic acids are citric acid, quinic acid and malic acid, which showed different variation patterns. A total of 48 energy metabolites were identified, which were classified into two groups based on the content variation. The content of substances related to the respiratory metabolic pathway decreased gradually along with postharvest ripening, and there was obvious accumulation of downstream products such as amino acids at the late ripening stage. A total of 35 endogenous hormones were identified, among which seven cytokinins were highly accumulated at the later stage of softening. We further investigated the dynamic changes in the activities of 28 ripening-related enzymes. As a result, the activities of 13 enzymes were highly correlated with changes in starch, total pectin, and soluble sugars, and those of seven enzymes were closely associated with the change in firmness. In conclusion, this study comprehensively describes the dynamic changes in soluble sugars, organic acids, hormones, energy substances, and ripening-related enzyme activities during kiwifruit postharvest ripening, and provides a theoretical basis for the postharvest quality improvement of kiwifruit. Actinidia spp.) is an economically important and popular fresh fruit originating from China and currently cultivated globally , β-amylase (β-Amy), starch phosphorylase (SP), starch debranching enzymes (SDBE), sucrose synthase (SUS), sucrose phosphate synthetase (SPS), acid invertases (AI), neutral invertases (NI), hexokinase (HK), and phosphofructokinase (PFK) have been reported to be involved in sugar production . FirmnesMetabolomics is an important part of systems biology that can be used to identify and quantify endogenous small-molecule metabolites in organisms or biofluid samples . In thisActinidia chinensis cv. Jinyan) samples were collected from Fengxin County Doctor Kiwifruit Base , Yichun City, Jiangxi Province, China. Fruit with uniform size were harvested at 180 d after pollination and immediately transported to Jiangxi Academy of Science, which were then stored at 20 °C and sampled from 0 to 12 d to represent different ripening stages. The flesh free of skin and seeds was cut into small pieces, rapidly frozen in liquid nitrogen and then stored at –80 °C for further metabolome and enzyme activity analysis. Three biological replicates were performed for each experiment, with each replicate consisting of 12 fruit.Kiwifruit  fruit using the GY-4 fruit firmness tester  fitted with an 8-mm plunger and GY-4 holder. Soluble solid concentration (SSC) was measured using a digital hand-held refractometer . The content of titratable acid was measured using the standard method . Starch and total pectin content were determined using the assay kits , following the instruction of the previously described method. A total of 28 enzymes related to ripening were determined in this study, and all enzymes were extracted under ice-bath and detected by corresponding assay kits  was employed for GC-MS analysis of soluble sugars. Helium was used as the carrier gas at a flow rate of 1 mL/min. Injection was made in the splitless mode and the injection volume was 2 μL. The oven temperature was held at 70°C for 1 min, then raised to 112°C at 30°C/min and held for 3 min, raised to 175°C at 15°C/min and held for 1 min, raised to 190°C at 3°C/min and held for 2 min, raised to 240°C at 35°C/min, raised to 280°C at 10°C/min and held at the temperature for 2.5 min. All samples were analyzed in the selective ion monitoring mode. The ion source and transfer line temperature were 230°C and 240°C, respectively.After the sample was thawed and smashed, 0.10 g of the sample was mixed with 1 mL of 70% methanol/water. The sample was vortexed for 3 min at 2500 r/min and centrifuged at 12000 r/min for 10 min at 4°C. About 600 μL of supernatant was taken and put into a new centrifuge tube and then placed in –20°C refrigerator for 30 min, Then, the supernatant was centrifuged again at 12000 r/min for 10 min at 4°C. After centrifugation, 200 μL of supernatant was used for organic acid determination directly, and another 200 μL of supernatant was passed through Protein Precipitation Plate for energy metabolite determination.Endogenous hormones were extracted according to previously described method . Frozen The sample extracts were detected using a UPLC-ESI-MS/MS system. The analytical conditions were as follows: for organic acid, ACQUITY HSS T3  column; solvent system, water 0.05% formic acid (A), acetonitrile with 0.05% formic acid (B). The gradient was started at 5% B (0 min), increased to 95% B (8-9.5 min), finally ramped back to 5% B (9.6-12 min); flow rate, 0.35 mL/min; temperature, 40°C; injection volume: 2 μL. For energy metabolites, ACQUITY UPLC BEH Amide ; solvent system, water with 10mM Ammonium acetate and 0.3% Ammonium hydroxide (A), 90% acetonitrile/water 27(v/v) (B). The gradient was started at 95% B (0–1.2 min), decreased to 70% B (8 min),50% B (9–11 min), finally ramped back to 95% B (11.1–15 min); flow rate, 0.4 mL/min; temperature, 40°C; injection volume: 2 μL. For endogenous hormones, Waters ACQUITY UPLC HSS T3 C18 ; solvent system, water with 0.04% acetic acid (A), acetonitrile with 0.04% acetic acid (B); gradient program, started at 5% B (0-1 min), increased to 95% B (1–8 min), 95% B (8–9 min), finally ramped back to 5% B (9.1–12 min); flow rate, 0.35 mL/min; temperature, 40°C; injection volume, 2 μL.® 6500+ LC-MS/MS System, equipped with an ESI Turbo IonSpray interface, which was operated in both positive and negative ion modes and controlled by Analyst 1.6.3 software. The ESI source operation parameters were as follows: ion source, ESI+/-; source temperature 550°C; ion spray voltage (IS) 5500 V(Positive), –4500 V (Negative); curtain gas (CUR) was set at 35 psi, respectively.Linear ion trap (LIT) and triple quadrupole (QQQ) scans were acquired on a triple quadrupole-linear ion trap mass spectrometer (QTRAP), QTRAPBased on the self-established metabolite database MWDB (Metware database) and the public metabolite information database, the primary and secondary mass spectrometry data were qualitatively analyzed. The soluble sugars, organic acids, and endogenous hormones were analyzed using scheduled multiple reaction monitoring (MRM). Data acquisition was performed using Analyst 1.6.3 software (Sciex). Multiquant 3.0.3 software (Sciex) was used to quantify all metabolites. Pearson’s correlation analysis was performed using the R software.Actinidia chinensis cv. Jinyan). Since our objective is to uncover the complex changes in metabolites during kiwifruit postharvest ripening, the kiwifruit fruit were picked at 180 DAP and then stored at 20 °C for ripening. During the postharvest ripening, the flesh color remained pale green in phase I, and gradually changed to faint yellow from phase II to phase III  for Actinidia chinensis cv. Jinyan, including nine monosaccharides and three disaccharides  for LC-MS/MS analysis. A total of 35 endogenous hormones were identified, including one abscisic acid (ABA), one ethylene, one strigolactone, three gibberellins, six jasmonic acids, six auxins and 17 cytokinins (enoic acid (an average of 28.08 ng/g). Interestingly, the accumulation level of these three hormones showed no significant change during postharvest ripening. Nine hormones exhibited significant changes during postharvest ripening. The contents of dihydrozeatin (DZ), isopentenyl-adenine-7-glucoside (IP7G), isopentenyl-adenine-9-glucoside (IP9G), isopentenyladenine (IP), and 2-Methylthio-cis-zeatin riboside (2MeScZR) stayed at low levels from 0 to 6 d, and showed sharp increases from 8 to 12 d. The contents of dihydrozeatin-7-glucoside (DHZ7G) and dihydrozeatin-10-glucoside riboside (DHZROG) gradually increased in phase I and phase II, and then rapidly grew in phase III (10 to 12 d). 3-oxo-2-(2-(Z)-Pentenyl) cyclopentane-1-butyric acid (OPC-4) and isopentenyladenosine (IPR) showed similar variation patterns in content with a particularly high accumulation at 2 d of ripening Figure 4During the postharvest ripening of kiwifruit, changes in the activity of 28 enzymes were analyzed, among which 16 enzymes were related to sugar and organic acid metabolism Figure 5The α-AF activity rapidly decreased from an initial value of 308.86 U/g to 226.89 U/g at 1 d, and was then stable throughout the ripening. The β-1,3-Glucanase  activity always remained at very low levels (3.18~4.41 U/g) during postharvest ripening. The β-GAL, PG and PME activities were high in phase I and phase II, and then sharply declined from phase III. β-GLU activity first showed a rapid increase from 4 to 7 d, and then dramatically decreased to the initial level value at 9 d. The 1-amino-cyclopropane-1-carboxylate oxidase (ACO) activity sharply increased from 4 to 6 d, and then grew at a moderate rate and reached the peak at 9 d. The catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD) activities showed similar variations, decreasing sharply to low levels at 3 d, 5 d and 6 d, respectively, and then tended to be stable. XET activity showed an alternating pattern of increasing and decreasing. The CE activity sharply decreased from an initial value of 875.57 U/g to 381.19 U/g at 4 d, and then gradually increased to 565.31 U/g at 7 d, followed by continuous decreases.Pearson’s correlation analysis demonstrated that the activities of AI, NI, SOD and POD were positively correlated with the firmness and contents of starch, total pectin, and citric acid, but negatively correlated with SSC and fructose content , tricarboxylic acid (TCA) cycle and pentose phosphate (PPP) pathway skeleton substances and their downstream products (Respiration is the energy source of postharvest life activities, but it also plays a negative role in fruit quality maintenance. Energy status has been reported to be involved in the ripening and senescence of many horticultural crops . In thisproducts Figure 3Plant hormones are a kind of endogenous organic compounds with physiological activities, and play irreplaceable roles in fruit development and ripening, though their contents are generally very low . Many exThe softening process of kiwifruit is mainly accompanied by starch and pectin degradation, soluble sugar accumulation, organic acid degradation and cell wall disassembly, and involves a series of associated enzymes . In thisPG is a key enzyme in pectin degradation, cell wall disassembly and fruit softening. It exhibited a high activity in softening phase I and phase II, which decreased in the later softening stage of ‘Jinyan’ kiwifruit. This result seems to be somewhat contradictory to the report that PG activity increased at the late stage of ‘Hayward’ ripening , but is Actinidia kolomikta (The activities of protective enzymes such as POD, SOD and CAT that eliminate free radicals were also significantly correlated with starch, total pectin, sucrose, fructose and firmness. However, their activities reached the peak in the initial softening stage, which is contrary to the results of olomikta . One posThe original contributions presented in the study are included in the article/XW conceived the study, participated in its design and coordination, performed the experimental measurements, processed the experimental data, interpreted the data, and drafted and revised the manuscript. JM and ZG participated in study design and coordination, performed the experimental measurements, processed the experimental data, interpreted the data, and drafted and revised the manuscript. ML, XZ and XN performed the experimental measurements and helped in sampling. XG, YL and LC processed the experimental data and helped in sampling. All authors contributed to the article and approved the submitted version.


Dyella sp. strain GSA-30, a predominant endophytic bacterium of Dendrobium plants. The genome consists of a circular 5,501,810-bp chromosome with a G+C content of 61.4%. The genome was predicted to harbor 6 rRNA genes, 51 tRNA genes, and 4,713 coding sequences.We report a complete genome sequence of  Dyella is one of the predominant bacterial taxa inhabiting the inside Dendrobium roots  and the GridION X5 system . For MiSeq sequencing, a sequencing library was prepared using the Nextera DNA Flex library preparation kit (Illumina), and paired-end (2 × 256-bp) reads were obtained. Default parameters were used for all software unless otherwise specified. The raw sequencing data  were processed using fastp v.0.20.1  selected sequence reads that were >3,000 bp long with a >90% identity match to the Illumina short reads, which generated a total of 86,368 reads (696 Mb), with an N50 value of 9,850 bp.A single colony of strain GSA-30 was incubated in 1/5-strength tryptic soy broth  at 25°C for 24 h, with shaking at 120 rpm. The cultured cells were harvested by centrifugation and then lysed with lysozyme and achromopeptidase . Genomicde novo genome assembly, the processed short and long reads were coassembled using the Unicycler v.0.4.8 pipeline  and DRR420784 (Nanopore).The complete genome sequence and annotations for


FTN increased when RBCs decreased  and hepcidin-25 increased . Limiting erythropoiesis to maintain hemoglobin levels induces RBC reduction in hemodialysis patients, resulting in increased hepcidin-25 and FTN levels. Hepcidin-25 production may prompt an iron shift from RBC iron to FTN iron, inhibiting iron absorption even with continued FCH intake.Oral ferric citrate hydrate (FCH) is effective for iron deficiencies in hemodialysis patients; however, how iron balance in the body affects iron absorption in the intestinal tract remains unclear. This prospective observational study  was conducted at 42 hemodialysis centers in Japan, wherein 268 hemodialysis patients without inflammation were enrolled and treated with a fixed amount of FCH for 6 months. We assessed the predictive value of hepcidin-25 for iron absorption and iron shift between ferritin (FTN) and red blood cells (RBCs) following FCH therapy. Serum iron changes at 2 h (ΔFe2h) after FCH ingestion were evaluated as iron absorption. The primary outcome was the quantitative delineation of iron variables with respect to ΔFe2h, and the secondary outcome was the description of the predictors of the body’s iron balance. Generalized estimating equations (GEEs) were used to identify the determinants of iron absorption during each phase of FCH treatment. ΔFe2h increased when hepcidin-25 and TSAT decreased (−0.459, −0.643 to −0.276,  Patients undergoing hemodialysis lose 1.5–3.0 g of iron annually due to dialysis and periodic laboratory evaluations , while tFTN is an index of stored iron , but itsFTN correlates strongly and positively with hepcidin-25, an iron regulatory hormone, as measured using surface-enhanced laser desorption/ionization–time-of-flight mass spectrometry, liquid chromatography–tandem mass spectroscopy (LC-MS/MS), and enzyme-linked immunosorbent assay ,10,11. TMoreover, whether long-term FC administration induces an iron overload remains unknown. The plateauing of FTN levels at 6 months despite continued FC administration may be related to the strict regulation and saturation of iron absorption  or the gA total of 268 patients were included in the R-OIAT . Betweenn = 149), 1500 mg (n = 101), or 2250 mg (n = 18) of FCH, no significant interaction between the amount of FCH and the exposure time was observed for all iron variables; this means that three independent groups changed similarly to each other with respect to time .The clinical measurements on the day of R-OIAT testing at M0, M3, and M6 are summarized in  to time . Althougp = 0.000] and increased by 0.648 μg/dL per 1 % decrease in Log TSAT . Hb levels were excluded because of collinearity with respect to RBCs based on the formula Hb = RBC × MCH. In the three datasets of iron markers per patient at M0, M3, and M6 (n = 804), there were significant negative correlations of ΔFe2h with hepcidin-25  were used to identify the determinants of ΔFe2h during each phase of FCH treatment: M0, M3, and M6. ΔFe2h was affected by hepcidin-25 and TSAT . Log ΔFe4/μL decrease in Log RBC ; by 1.667 ng/mL per 1 pg/cell decrease in Log MCH ; by 0.372 ng/mL per 1 % decrease in Log TSAT ; by 0.754 ng/ml per 1 ng/mL decrease in Log FTN ; and by 0.353 ng/mL per 1 IU/week increase in Log ESA . In the three datasets of iron markers per patient at M0, M3, and M6 (n = 804), there were significant correlations between hepcidin-25 and ESA : P-1 , P-2 , P-3 , and P-4 . FTN gradually increased only in 63 cases (23.5%) during both 3-month intervals  whose ΔFTNM3-M0 was negative were positive with respect to ΔFTNM6-M3. Similar negative correlations were observed between the changes in the first and second 3-month periods with respect to hepcidin-25, Hb, and RBCs . Each datum was classified into four groups, G-1, G-2, G-3, or G-4, according to the RBC value at start points M0 or M3; RBC ≤ 300: 300 < RBC ≤ 350, 350 < RBC ≤ 400, and RBC > 400 × 104/μL, respectively. Furthermore, each case was classified into G-a when each ΔRBC3M was negative and into G-b when ΔRBC3M was positive. The start and end points were vectorized as the mean values of MCH and RBCs , was reduced to 11.6 g/dL when reducing ESA and resetting RBCs to 400 × 104/μL (point B). During this period, the FTN level increased because the RBC iron capacity decreased, and the corresponding amount of iron shifted to FTN iron. When FCH administration continued, MCH increased with iron absorption, and Hb levels easily exceeded 12 g/dL . If ESA was reduced again and RBCs reset to 350 × 104/μL, the Hb level improved to 11.4 g/dL (point D) with another increase in the FTN level. When RBC is ≤350 × 104/μL, there is little risk of Hb being ≥12 g/dL even if FCH therapy is continued because there is an upper limit against MCH, which falls normally within the range of 27–33 pg  × time [M0 vs. M3 vs. M6]) was used to analyze the effects of FCH on iron variables. Univariate correlations between variables were assessed using Pearson’s correlation test. After adjusting for independent variables, GEEs were used to identify the determinants of iron absorption during each phase of FCH treatment: M0, M3, and M6; the B coefficients with their 95% CI and the corresponding


The association between lipid metabolism disorder and carcinogenesis is well-established, but there is limited research on the connection between lipid metabolism-related genes (LRGs) and lung adenocarcinoma (LUAD). The objective of our research was to identify LRGs as the potential biomarkers for prognosis and assess their impact on immune cell infiltration in LUAD.We identified novel prognostic LRGs for LUAD patients via the bioinformatics analysis. CYP27A1 expression level was systematically evaluated via various databases, such as TCGA, UALCAN, and TIMER. Subsequently, LinkedOmics was utilized to perform the CYP27A1 co-expression network and GSEA. ssGSEA was conducted to assess the association between infiltration of immune cells and CYP27A1 expression. CYP27A1’s expression level was validated by qRT-PCR analysis.CYP27A1 expression was decreased in LUAD. Reduced CYP27A1 expression was linked to unfavorable prognosis in LUAD. Univariate and multivariate analyses indicated that CYP27A1 was an independent prognostic biomarker for LUAD patients. GSEA results revealed a positive correlation between CYP27A1 expression and immune-related pathways. Furthermore, CYP27A1 expression was positively correlated with the infiltration levels of most immune cells.CYP27A1 is a potential biomarker for LUAD patients, and our findings provided a novel perspective to develop the prognostic marker for LUAD patients.The online version contains supplementary material available at 10.1186/s12865-023-00572-1. Based on the GLOBOCAN 2020 estimates of cancer mortality and incidence, lung cancer continues to be a major contributor to cancer-related mortality and is the prevailing form of cancer worldwide . Lung adAn increasing body of research has demonstrated the crucial involvement of aberrant metabolic reprogramming, such as mitochondrial oxidative phosphorylation , cholestWe retrieved the LUAD-reltaed dataset from the Cancer Genome Atlas (TCGA) database to identify prognosis-related LRGs. Among these LRGs, we focused on investigating the role of CYP27A1, a gene with unclear function in LUAD. We conducted prognosis analysis, gene set enrichment analysis (GSEA), and immune infiltration analyses to further examine the significance of CYP27A1 in LUAD.The RNA-seq (FPKM) data and clinicopathological information of LUAD patients were downloaded from the TCGA database. The dataset consisted of 59 adjacent noncancer samples and 535 tumor samples. Furthermore, mRNA profiles obtained from Gene Expression Omnibus (GEO) including GSE41271, GSE11969, and GSE30219 were downloaded and utilized as validation datasets for lung cancer patients.LRGs were obtained from the lipid metabolism-related data sets  Table S.The limma package in R was utilized to identify the DEGs between the tumor samples and adjacent noncancer samples (p.adj < 0.05 and ∣logFC∣ ≥ 1) . The volThe survival package was applied to screen PRGs from TCGA-LUAD based on a p-value < 0.05. The Venny tool was employed to identify the overlapping set of LRGs, DEGs, and PRGs. Subsequently, these differentially expressed prognosis-associated LRGs were visualized on a forest plot using the ggplot2 package.https://cn.string-db.org/) for building the protein–protein interaction (PPI) network. The result was visualized using Cytoscape software (version 3.2.1). The cytoHubba plugin of Cytoscape software was employed to identify the core gene (CYP27A1) based on its degree value. In TIMER database, we used the “DiffExp module” to assess the CYP27A1 expression in pan-cancer. The UALCAN database is an interactive, user-friendly, and comprehensive database that allows researchers to rapidly analyze gene and protein expression in various solid tumors [www.tnmplot.com).The differentially expressed prognosis-associated LRGs were uploaded to the STRING database  and lung cancer cell lines  were obtained from the Cell Bank of Chinese Academy of Sciences. These cells were cultured in RPMI-1640 medium, supplemented with 1% penicillin and streptomycin, and 10% fetal bovine serum . The cultures were maintained at 37℃ in a 5% CO2 humidified atmosphere.–ΔΔCt method. The primers can be found in Supplementary Table SRNA extraction from the cells was carried out using TRIzol reagent . Purified RNA 2 µg) was utilized for cDNA synthesis using a cDNA synthesis kit . Subsequently, qRT-PCR was conducted in a PCR System . The CYP27A1 expression level was quantified using the 2 µg was up-value of less than 0.05 was considered statistically significant.The statistical analysis of data was conducted using the R software (version 3.3.3). The differences between tumor samples and adjacent noncancer samples were compared using the Wilcoxon signed-rank test. The receiver operating characteristic (ROC) analysis of CYP27A1 was performed using the pROC package of R. A As presented in Fig. As shown in Fig. p < 0.01, Fig. p < 0.05, Fig. p < 0.05, Fig. p < 0.05, Fig. p < 0.05, Fig. As presented in Fig. p = 0.015, Fig. p = 0.015, Fig. p = 0.03, Fig. P = 0.001, Fig. p = 0.021, Fig. Kaplan–Meier analysis showed that decreased expression of CYP27A1 was significantly related to poor overall survival  of CYP27A1 was 0.936 Fig. A. BesideAccording to Fig. We used ssGESA to analyze the infiltration of immune cells, and we observed that aDC, B cells, CD8 T cells, cytotoxic cells, DC, eosinophils, iDC, macrophages, mast cells, neutrophils, NK CD56bright cells, NK cells, T cells, Treg, Th17 cells, Th1 cells, TFH, and pDC were increased, whereas Th2 cells were decreased in high-CYP27A1 subgroup compared to the low-CYP27A1 subgroup , macrophages , DC , mast cells , eosinophils , pDC , TFH , T cells , cytotoxic cells , Th1 cells , aDC , neutrophils , CD8 T cells , B cells , TReg , NK cells , Th17 cells , Tem , and NK CD56bright cells . CYP27A1 expression was negatively correlated with Th2 cells . Furthermore, the scatter plot also exhibited the correlation between CYP27A1 expression and various immune cell types , whereas no significant difference was observed in the CD8 T cell, CD4 T cell, macrophage, and neutrophil subgroups   compared with 16HBE cells (01) Fig. .Fig. 11CLUAD has been considered a malignant tumor for its poor prognosis, refractory features, high mortality, and high incidence , 20. It CYP27A1, known as sterol 27-hydroxylase, is an enzyme belonging to the cytochrome P450 oxidase family and is predominantly expressed in liver tissue. It mainly catalyzes the hydroxylation step, regulates vitamin D3 metabolism, and sustains cellular cholesterol homeostasis , 30. NotThe tumor microenvironment is composed of immune cells, endothelial cells, and stromal cells, and it can provide insights into the effectiveness of immunotherapy and patients' prognoses , 40. AccDespite suggesting that CYP27A1 may serve as a valuable prognostic biomarker for LUAD patients, it is important to note its inherent limitations. Notably, all survival analysis data relied on public datasets, necessitating the need for validation in additional clinical cohorts. In addition, sufficient clinical samples need to be collected to validate CYP27A1 expression.In summary, our study suggested that low CYP27A1 expression is linked to a negative prognosis in LUAD patients, and it is also associated with immune infiltration levels in LUAD. Consequently, CYP27A1 has the potential to serve as a prognostic marker for LUAD patients, providing a foundation for further investigation into its role in the development and progression of lung cancer.Additional file 1: Table S1. The list of LRGs.Additional file 2: Table S2. Sequences of primer used quantitative real-time PCR. Figure S1. Validation of the prognostic value of CYP27A1 in independent datasets. Prognostic analysis of CYP27A1 in GSE41271 dataset (A), GSE11969 dataset (B), and Kaplan-Meier plotter (C). Figure S2. Validation of the diagnostic value of CYP27A1 in independent datasets. ROC curves of CYP27A1 in TNMplot.com analysis platform (A), GSE11969 dataset (B), and GSE30219 dataset (C). Figure S3. Immune cell infiltrates analysis of CYP27A1 in GSE11969 dataset. (A) The histogram presents the proportion of 24 immune cell types between the CYP27A1 low expression group and CYP27A1 high expression group. (B) The histogram presents the Stromal sore, Immune score, and ESTIMATE score between the CYP27A1 low expression group and CYP27A1 high expression group. (C) Correlation analysis between 24 immune cell types level and CYP27A1 expression in GSE11969 dataset.


Increasing evidence has reported that N6-methyladenosine (m6A regulatory factors and cancer stem cells (CSCs) of HCC to establish a clinical tool for predicting its outcome. First, we concluded that the expression level of m6A regulatory factors was related with the stemness of hepatocellular carcinoma. Subsequently, we gained a ten hub regulatory factors that were associated with prognosis of hepatocellular carcinoma by overall survival (OS) analysis using ICGC and TCGA datasets, and these regulatory factors included YTHDF1, IGF2BP1, METTL3, IGF2BP3, HNRNPA2B1, IGF2BP2, RBM15B, HNRNPC, RBMX, and LRPPR. Next, we found that these ten hub m6A regulatory factors were highly expressed in CSCs, and CSCs related pathways were also enriched by the gene set variation analysis (GSVA). Then, correlation, consensus clustering and PCA analysis were performed to reveal potential therapeutic benefits of HCC. Moreover, univariate Cox regression (UNICOX), LASSON and multivariate Cox regression (MULTICOX) analyses were adopted to establish HCC prognosis prediction signature.In our study, we comprehensively analyzed the connection between mFour regulatory factors RBM15B, LRPPRC, IGF2BP1, and IGF2BP3 were picked as valuable prognostic indicators.In summary, these ten hub regulatory factors would be useful therapeutic targets for HCC treatment, and RBM15B/LRPPRC/IGF2BP1/IGF2BP3 prognostic indicators can be used to guide therapy for HCC patients.The online version contains supplementary material available at 10.1007/s00432-023-05045-x. In addition, we collected 23 m6A regulatory factors in this study and selected m6A differential regulatory factors (DEGs) from patients with high-mRNAsi and low-mRNAsi for further study in TCGA dataset. Furthermore, we selected m6A DEGs that had prognostic value to be candidate genes in both TCGA and ICGC . We found that these hub m6A regulatory factors were highly expressed in liver cancer stem cells (LCSCs) using scRNA-seq data (GSE149614) and RT-qPCR. GSVA analysis also showed that the hub m6A regulatory factors’ expression was associated with the CSCs related pathways. Moreover, we performed the analyses of correlation, function, Consensus, PCA, survival, and ROC to investigate the biological functions and mechanisms of these regulatory factors in HCC patients, highlighting the importance of these candidate hub regulatory factors. In addition, we observed the prognostic role of m6A regulatory genes in HCC, and build a prognostic model in ICGC, and verified it in TCGA. Finally, the overall survival of HCC patients could be better estimated using the prognostic model. In summary, our work suggests that the m6A regulatory factors are a potential prognostic indicator for HCC patients.Giving the RNA-seq data available online, we tried to analyze whether the expression patterns of mThe data of gene expression data and clinical annotations were gained from ICGC and TCGA datasets. Two cohorts were enrolled in our work: TCGA-LIHC (371 samples) and ICGC-LIRI-JP (243 samples). For mRNA expression data, FPKM-normalized, log2-transformed data were gained, respectively, from web sites Genomic Data Commons Data Portal  (RRID: SCR_014514), ICGC Data Portal (RRID: SCR_021722). Clinical annotations in ICGC with 232 HCC patients and in TCGA with 240 HCC patients were also downloaded for further analysis. The data of Copy number variation (CNV) were gained from TCGA. In addition, the scRNA-seq (GSE149614) of HCC was downloaded from Gene Expression Omnibus (GEO) (RRID: SCR_005012) , including 8 writers   in TCGA were identified for further study.The m6A differential regulatory factors in TCGA and 13 m6A regulatory factors DEGs in ICGC, we figured out the potential prognostic m6A differential regulatory factors by Survival analysis and Kaplan–Meier curves using the “survival” R package (adjusted p < 0.05). The R package “survminer” and a two-sided log-rank test were used to identify the optimal cutoff value. To gain more accurate results, a Venn plot was used to obtain the overlapped prognostic m6A different regulatory factors in either TCGA or ICGC. Finally, ten shared hub regulatory factors were left for further analysis.Among 17 mscRNA sequence data of different sites of HCC was downloaded, including ten HCC patients from four relevant sites: primary tumor, metastatic lymph node, portal vein tumor thrombus (PVTT) and non-tumor liver tissue. After aggregation of the primary tumor data of the 10 patients  flow separation method  with 10% fetal bovine serum and 1% penicillin/streptomycin. Hep3B and Huh7 suspension cells (Hep3B SP and Huh7 SP) were cultured in HAM with 2% B27, 20 ng/ml EGF, 4 ng/ml bFGF, and 1% penicillin/streptomycin. Cells were cultured in a 5% CO2 and 37 °C incubator.Single-cell suspensions (Hep3B SP and Huh7 SP) were prepared and incubated with CD24 antibody , EPCAM antibody , and CD133 antibody  for 30 min in 4 °C, followed by flow cytometry analysis. LCSCs (LCSC1 and LCSC2) were prepared and incubated with ALDH antibody  for 30 min in 37 °C, followed by flow cytometry analysis.Total RNA was extracted using TRIzol reagent  based on the manufacturer’s protocol. cDNA synthesis was operated using the PrimeScript™ Reverse Transcriptase kit . The primers in Table S1 and Table S2 were used to perform qPCR.6A regulatory factors to divide HCC patients into various subgroups and study the gene expression patterns in the corresponding subgroups. After performing consensus clustering cumulative distribution function (CDF) for k = 2 to 9 in both TCGA and ICGC, k = 2 was shown and chosen for further study. To verify the significance of the cluster results of ten hub m6A regulators, we performed survival analysis and clinical information in TCGA and ICGC datasets.R package “ConsensusClusterPlus” and “PCA” was used to determine the function of ten hub mp < 0.05 and logFC > 0.1 was considered as statistically significant, and we got the top 100 different pathways between 2 models in KEGG and top 30 different pathways between 2 models in HALLMARK with “limma” R package.R package “GSVA” was used to perform GSVA enrichment analysis, getting different biological processes between stratified subgroups. GSVA, using a non-parametric and unsupervised method, is a common way to estimate the variation in biological process activities and pathways in the samples of gene expression dataset. We obtained function sets of “c2.cp.kegg.v7.4.symbols.gmt” and “h.all.v7.4.symbols.gmt” from MSigDB dataset. Adjusted 6A regulatory factors (adjusted p < 0.05) was performed to confirm prognostic genes in ICGC. The LASSO analysis (adjusted p < 0.05) was applicated to construct a prognostic mode at the least and best risk factors. Then using the MULTICOX Analysis, we chose four regulators to build a prognostic risk signature. Finally, survival analysis, ROC analyses and risk score distribution in both TCGA and ICGC datasets were performed to verify the prognostic model.UNICOX Analysis of ten candidate mR “rms” to combinate this prognostic signature with relevant clinical information.We performed nomogram analyses with 6A regulatory factors were finally identified in our work. mRNAsi index was utilized to analyze liver hepatocellular carcinoma (LIHC) cases in TCGA, which was selected to quantify the stem-like indices and well-calculated stemness index for HCC patients. We divided the LIHC patients into high-mRNAsi and low-mRNAsi group based on the median data of mRNAsi index. It has been confirmed that the expression level of m6A regulatory factors is correlated with CNV, and the change of CNV may be one of the main reasons causing the expression disorder of m6A regulatory factors   by overall survival (OS) analysis in 20 m6A regulatory factors. After determining the shared regulatory factors in both TCGA and ICGC, ten hub regulatory factors were selected .To investigate the correlation between m6A regulatory factors and the LCSCs which is known as tumor-initiating cells and is a small subpopulation of malignant tumor cells with stemness characteristics  LCSCs, 3_Negative (CD24−EPCAM−CD133−) liver cancer cells and other cells, respectively  LCSCs and 3_Negative (CD24−EPCAM−CD133−) liver cancer cells by flow cytometry in both Hep3B and Huh7 cells , then we discovered that the expression of these ten m6A regulatory factors were highly expressed in 3_Positive (CD24+EPCAM+CD133+) LCSCs from Hep3B and Huh7 cells by RT-qPCR  , and with worse survival status (adjusted p < 0.001)  Fig. E, while 01) Fig. G. We con6A regulatory factors, correlation analysis was conducted that ten hub regulatory factors exhibited strong correlation with each other with strict criteria (adjusted p < 0.05) in TCGA and ICGC . These five regulatory factors, including RBM15B, LRPPRC, IGF2BP1, RBMX, and IGF2BP3, were all oncogenes with hazard ratio (HR) > 1  Fig. A, B. We 05) Fig. C. As sho6A RNA modifications can be modified by “writes” and removed by “erases”  ranking third in cancer deaths worldwide is a serious disease  for establishing prognostic model. RBM15B, RNA-binding protein, performs as a key regulator of m6A methylation of RNA. Jaffrey SR’s team demonstrated that RBM15 and related RBM15B interacted with WTAP to form the complex to target mRNA and also were critical for XIST-mediated gene silencing Below is the link to the electronic supplementary material.


The mixtureof 2- and 3-(tert-butyl)-6-(2-methoxyethyl)-6H-indoloquinoxaline exhibits a lowreduction potential (−2.01 V vs Fc/Fc+), high solubility(>2.7 M in acetonitrile), and remarkable stability (99.86% capacityretention over 49.5 h (202 cycles) of H-cell cycling). This anolytewas paired with N-(2-(2-methoxyethoxy)-ethyl)phenothiazine(MEEPT) to achieve a 2.3 V all-organic NARFB exhibiting 95.8% capacityretention over 75.1 h (120 cycles) of cycling.Redox flow batteries(RFBs) are a promising stationaryenergy storagetechnology for leveling power supply from intermittent renewable energysources with demand. A central objective for the development of practical,scalable RFBs is to identify affordable and high-performance redox-activemolecules as storage materials. Herein, we report the design, synthesis,and evaluation of a new organic scaffold, indolo[2,3- Onepromising technology to help stabilize the latter is low-cost grid-scaleenergy storage that can help balance energy demand with energy production.5 Redox flow batteries (RFBs) are a promising solution for grid-scaleenergy storage and store electrical energy in the form of chemicalenergy within flowable anolytes and catholytes, which circulate fromseparate storage reservoirs through an electrochemical cell for chargingand discharging.9 RFBs offer ease and economic feasibility of scale-up, as well asdecoupling of energy and power.10 Aqueous-based vanadiumRFBs are currently the state-of-the-art commercial systems, exhibitingexcellent lifetimes and energy efficiencies.12 However, the accessible voltage of aqueous redox flow batteriesis limited by the thermodynamic potential window of water (between1.1 and 1.6 V), which constrains energy and power density.13 Given these limitations, along with concernsabout cost, sustainability, and potential environmental issues, itis necessary to explore other types of RFBs.15 Nonaqueous redox flow batteries (NARFBs) offer a wider operatingwindow (up to 5 V with MeCN), and modern organic synthesis allowsfor the tailoring of redox-active organic molecules (ROMs) to meetthe stability, potential, and solubility demands of NARFBs.20 However, identifying ROMs with high stability, high oxidation /low reduction potential, and high solubility that can leverage the nonaqueoussystem’s wide operating window remains challenging for NARFBs.21The burning of fossil fuels continuesto impact global warmingthrough the generation of greenhouse gases, underscoring the necessityof adopting renewable energy sources such as wind and solar.27 anolytes,38 and bipolar molecules.45 These include several elegant examples of novel anolytes;38 however, only a few of them leverage the wide potential window ofnonaqueous solvents by reaching reduction potentials more extremethan −1.9 V (vs Fc/Fc+)  and high solubility but only moderate electrochemical cycling stability.35 Benzophenone-containing scaffolds also exhibitlow reduction potentials (−2.26 V vs Ag/Ag+) andgood solubility but maintain only moderate cycling stability.32 Therefore, developing organic electrolytes withreduction potentials at the extreme ends of the electrochemical windowof acetonitrile (<−1.9 V Fc/Fc+) along with highstability remains a significant unmet challenge, especially when consideringthe solubility requirements necessary to achieve high energy density.21 This is due to generally unfavorable trade-offs between redox potentialand stability. Anolytes with lower potentials often deliver high-energycharged intermediates that are more basic and/or nucleophilic, resultingin decomposition through protonation as well as addition reactionsinvolving electrolyte and solvent.46In recent years, there has been significant progress in thedevelopmentof new ROM scaffolds for catholytes, Fc/Fc+) 1. The 2,N-atoms would allow us to both stabilize the charged intermediatewhile also adjusting the reduction potential to more negative values.Overall, this should enable the development of high-energy-densityanolytes with improved stability and low reduction potentials. Herein,we report a new anolyte scaffold, indoloquinoxaline,based on these design principles, that exhibits high stability andlow reduction potential via delocalization via charge throughout theextended π-system while still maintaining a low reduction potential.Further molecular engineering has resulted in an anolyte with remarkablyhigh solubility , high stability (0.0028% fade per hour (H-cell cycling);0.056% fade per hour (flow cell cycling)), and a low reduction potential(E1/2 = −2.01 V vs Fc/Fc+).To tackle this challenge, we hypothesized thatextending the π-conjugationsystem of an anolyte while simultaneously incorporating π-donor 47 Therefore, electron-richatoms must be incorporated into the conjugated π-system to adjustthe reduction potential, while additional functional groups must alsobe incorporated to improve solubility.The challenge we soughtto overcome in achieving highly stable electrolytes for NARFBs isthat the simple expansion of a conjugated π-system, a commonlyemployed approach for enhancing the electrochemical stability of organicanolytes, generally comes at the cost of less negative reduction potentialsas well as reduced solubility due to strong π–πstacking interactions.z orbital of the nitrogenatom with the lone pair electrons on nitrogen has the correct orbitalsymmetry to participate in electron delocalization and to expand conjugatedπ-systems. Second, this donation can enhance the electron densityof the entire π-system, which should result in more negativereduction potentials. Third, this atom can serve as a synthetic handlefor incorporating side chains, facilitating the development of solublederivatives. Guided by these concepts, we selected quinoxaline asthe starting point to test our proposal. As shown in 48 and phenazine derivatives52 have been developed for aqueousRFBs. Quinoxaline-based scaffolds show excellent performance in aqueoussystems but suffer from the inherent voltage limitations of aqueoussolvent. A nonaqueous system (Vocv = 2.2V) featuring a quinoxaline derivative (3) overcomes thevoltage limitation of aqueous systems; however, low stability is observed.53 On the other hand, phenazine derivative 4, which has an expanding π-system, exhibits both moderatereduction potential (−1.72 V vs Ag/Ag+) and stability,with excellent solubility as an anolyte.54The incorporation ofnitrogen atoms, which are electron-rich trivalent π-donors,offers a potential solution to the aforementioned issues. First, weexpect that the pb]quinoxalineas a newmotif for NARFB anolytes, inspired by these earlier works and ourown concept for improving stability and lowering the reduction potential and O-phenylenediamine (7a) , followed by methylationwith iodomethane to give the target anolyte in 95% yield .A 5 mM solution of 5a in 0.5 M TBAPF6/MeCNwas tested using the three-electrode method with a glassy carbon workingelectrode (0.071 cm2) at a scan rate of 100 mV/s. 5a exhibits a first reversible reduction at E1/2 = −1.97 V vs Fc/Fc+ and a secondirreversible reduction at Epc = −2.64V vs Fc/Fc+  compared with phenazine (9), which has its firstreversible reduction at E1/2 = −1.60V vs Fc/Fc+   as a model compound to examine ourinitial hypothesis. Densityfunctional theory (DFT) calculations employing the TPSSh-D4 functionalwere validated by comparison to the measured reduction potential of 5a/5a•–, quinoxaline(8/8•–), and phenazine(9/9•–). Usingthis computational protocol (detailed in the Supporting Information), the reduction potentials in acetonitrile werecalculated to be −1.98, −2.04, and −1.54 V vsFc/Fc+, respectively , furthercorroborating these findings on the interplay of the size and electronicproperties of the π-system and their substantial effects onthe reduction potential.With these electrochemical results in hand, weselected 6-methyl-ectively 3b, which5a and the singly occupied molecular orbital(SOMO) of 5a•–  are shown in 5a confirms that the pz atomic orbital of the nitrogen has the correct orbital symmetryto participate in electron delocalization, which helps expand theconjugated π-system and stabilize the charged intermediate.The change in NBO charges upon reduction of 5a to •–5a and the condensed Mulliken spindensities of •–5a  of D) and the heterogeneous electron-transfer kinetics(k0), are critical for the performanceof RFBs. We investigated both D and k0 of 5a through two experimental methods:CV with varying scan rates from 25 to 500 mV/s . To determine the accurate diffusion coefficient (D) and the heterogeneous electron-transfer kinetics (k0) of 5a,55 weconducted an LSV experiment using a three-electrode rotating diskelectrode (RDE) setup with a glassy carbon working RDE (D). The diffusion coefficientof 5a was determined to be 1.7 × 10–5 cm2/s using the Levich equation, which is higher thanthat of other low-potential anolytes such as N-methylphthalimide(8.4 × 10–6 cm2/s).56 Further analysis was performed using Koutecky–Levichplots (k0) of 5a. The obtained k0 value of 5a was 1.5 × 10–3 cm/s , which is comparable to that of N-methylphthalimide(2.5 × 10–3 cm/s).56 Notably, the Nicholson method yielded an estimated heterogeneouselectron-transfer constant of 5a as approximately 5.0× 10–3 cm/s , which significantlydiffers from the result obtained through the LSV test.55 The determined diffusion coefficient and rateconstant demonstrate that the new scaffold possesses good kineticproperties.The electrochemicalkinetics of ROMs, including the diffusion coefficient.In these experiments, 5 mL of 5 mM solution of 5a in0.5 M TBAPF6/MeCN is placed in the working electrode sideof an H-cell separated with a fine glass fit. Initially, the counterelectrode side of the cell contains 5 mL of 0.5 M TBAPF6/MeCN. 5a is reduced to 5a•– at a constant rate (−5 mA) to a voltage limit of 350 mV lowerthan the E1/2 of 5a to maximizethe state of charge (SOC), and then the current is reversed (+5 mA)to regenerate 5a. This cycling was repeated to evaluatethe stability of 5a. As shown in 5a exhibited only a 9.18%capacity fade over 202 cycles (46.8 h) with an average Coulombic efficiencyof 100% throughout the cycling. We also compared the cycling stabilityof quinoxaline (8) and phenazine (9) usingthe same assay (9) exhibited a 26.3% capacity fade over202 cycles (35.8 h), while quinoxaline (8) exhibiteda 50.4% capacity fade after only 12 cycles (2.0 h). After 202 cycles(5.1 h), the capacity fade of quinoxaline (8) increasedto 98.6%. These results demonstrate that incorporating the electron-richtrivalent π-donor N-atom into the expandedconjugation system can indeed significantly improve cycling stabilitywhile simultaneously pushing the reduction potential closer to theedge of the reduction window of acetonitrile.Electrochemical cycling stability is a crucialparameter for ROMs,and we evaluated the cycling stability of me assay 4d. Phenab]quinoxalinescaffold, with a focus on enhancing solubility and H-cell cyclingstability. Previous studies have suggested the use of tetraalkylammoniumgroups and glycol ethers to enhance the solubility of ROMs.57 We first incorporated the solubilizing groupsinto the core through N-alkylation. Ammonium salt(5b) and glycol ether derivatives 5c–e were synthesized through our convergent synthetic route in excellentyield . Incorporatingtetramethylammonium groups significantly improved the solubility of 5b to 0.63 M in acetonitrile, which is almost 20-fold greaterthan that of 5a . This improvement may be due to stabilizingcharge–charge interactions between the ammonium salt and theradical anion. The different lengths of glycol ether substitutionsdid not affect the reduction potential, which remained at −1.97V vs Fc/Fc+ for 5c, 5d, and 5e .Encouragedby these results, we proceeded to study the structure–propertyrelationships for this class of anolytes in order to identify next-generationderivatives based on the indoloquinoxaline core . Interestingly,the DFT calculations reveal that the π-system is further expandedvia hyperconjugation with orbitals from both the tert-butyl and N6-substitution side chain . We further investigated the electrochemicalkinetics of 5h using both LSV and CV. The diffusion coefficient(D) was 1.2 × 10–5 cm2/s, and the kinetic rate constant (k0) was 9.6 × 10–4 cm/s through LSV analysis. Bothof these values are comparable to other ROMs used in NARFBs.56With the knowledge gained from these structure–propertystudies, we aimed to incorporate the solubilizing and stabilizinggroups together in a single scaffold. As such, we synthesized twoderivatives, 5h in hand, we sought totest its performance in a flow battery.To do so, we first needed to identify a compatible catholyte. We exploredthe phenothiazine derivative MEEPT (10),24 which has a first oxidation potential of 0.32 V vs Fc/Fc+ and exhibits high cycling stability and solubility, as apotential catholyte. To initially assess the compatibility between 5h and 10, a mixed solution of 5 mM 5h and 5 mM 10 in 0.5 M TBAPF6/MeCN was subjectedto a static H-cell cycling experiment where 5h is cycledwith 5h•–, while 10 remained electrochemically neutral throughout. The anolyte 5h displays improved cycling stability in the mixed solutionas measured by the discharge capacity and Coulombic efficiency ofcycling between 5h and 5h•– shown in 62 The 202nd cycle shows almost the same SOC (91%) andsimilar charge–discharge performance as the 9th cycle .With the optimal anolyte th cycle 6b. The pth cycle 6c or theth cycle 6d. Furth5h as an anolytein a flow cell battery with 10 as thecatholyte using a mixed electrolyte solution of 5h and 10. During the charge–discharge process, the electrochemicalreaction for this flow battery system is depicted in 5h and 50 mM 10 in 0.5 M TBAPF6/MeCN(7.0 mL each side) to limit the potential impact of crossover drivenby a concentration gradient. The electrolyte solutions were chargedand discharged at a constant current density of 10 mA/cm2 until reaching cutoff voltages of 2.68 and 1.98 V  at a flow rate of 10 mL/min.The capacity utilization reached 66.1% in the steady flat state afterinitial equilibrium by the tenth cycle . However, the discharge capacitysignificantly decreased after 330 cycles, reaching only 31.0% by the400th cycle , with substantialvolume discrepancy in the reservoirs, presumably arising from thedifferences of pressure/viscosity of the anolyte and catholyte thatresult in preferential mass transfer from the anolyte to the catholytesolution.62 Impedance analysisconducted on the flow cell post-400 cycles showed an increase in resistance.62 Post-cycling CV analysis of diluted electrolyte solutions (100 μLdiluted to 1.0 mL) revealed no significant concentration change ofthe ROMs in either the anolyte or catholyte side of the cell , suggesting that the capacity losswas mainly due to the battery failing to charge and not as a resultof ROM decomposition.Finally, we evaluated the performance of th cycle 7b. The C5h and 10 electrolytesolution in 0.5 M TBAPF6/MeCN. The electrolyte solutions(7.5 mL per side) were charged and discharged at a constant currentdensity of 20 mA/cm2 until reaching cutoff voltages of2.73 and 1.70 V at a flow rate of 20 mL/min. In this case, the capacityutilization reaches 72.8% after the initial equilibrium at the tenthcycle, achieving a steady flat state . Impedance analysisconducted on the flow cell revealed a substantial increase in resistanceafter the 200th cycle.63 Post-200 cycles,CV analysis of diluted electrolyte solutions (50 μL dilutedto 1.0 mL) indicated that there was less than a 5% concentration lossin either the anolyte or catholyte. The flow cell battery was rebalancedafter 200 cycles, and the battery was run for another 20 cycles withthe same parameters, with the capacity recovering to 91.7% at the205th cycle . These observationssuggest that the capacity loss was mainly due to the buildup of chargeand/or concentration gradients in the cell that create flow cell resistanceand which result in prematurely reaching the cell cutoff potentialand not as a result of the loss of the ROM. Rebalancing the cell alleviatesthese gradients and allows for a return to higher discharge capacities.The battery demonstrated extraordinary capacity retention comparedwith other reported high-performance NARFBs.62 We further conducted the flow cycling of the mixed 5h and 10 electrolyte solution at a higher concentration. However, the materialutilization and battery system are likely to be constrained by theion viscosity and diffusivity in the 0.5 M TBAPF6/MeCNelectrolyte.58 Overall, the results ofthis study show the potential of 5h as a highly promisinganolyte for NARFBs with competitive solubility, reduction potential,and cycling performance.Encouraged by these results, we proceeded to testa higher concentration(100 mM) of the mixed at state 7c, whileb]quinoxalineas a new anolyte scaffold for NARFBs. Our approach involved expandingthe conjugated π-system with a trivalent π-donor nitrogenatom fusion and incorporating the mixed tert-butylcompound as a design principle that could potentially be applied toother material designs. To identify structure–property relationships,we synthesized a library of indoloquinoxalinederivatives through a convergent synthetic route and evaluated theirelectrochemical properties and solubilities. Among these derivatives,2- and 3-tert-butyl-6-(2-methoxyethyl)-6H-indoloquinoxaline (5h) wasidentified as the best anolyte due to its low reduction potential(E1/2 = −2.01 V vs Fc/Fc+), high stability ,and high solubility (greater than 2.7 M in acetonitrile). 5h paired with MEEPT (10) was deployed to a prototypeflow battery, achieving a 2.3 V battery with a 2.68 Ah/L capacity.The battery maintained 95.8% capacity retention and demonstrated an average utilization of 75.5%.In summary, we havedesigned indolo[2,3-