MVs also restored the level of IL-6 and IL-10 in lung homogenate. Additionally, PTEN/AKT and MAPK pathways were associated with the protection of MVs. Taken together, this study suggests MVs derived from hUCMSCs improve lung architecture and function in an antenatal LPS-induced BPD rat model by promoting AT2 cell proliferation and attenuating lung inflammation; thus, MVs provide a promising therapeutic vehicle for BPD treatment.Although it is known that exosomes derived from human umbilical cord mesenchymal stem cells (hUCMSCs) alleviate hyperoxic lung injury of bronchopulmonary dysplasia (BPD) in animal models, the role of microvesicles (MVs) derived from hUCMSCs in BPD is poorly defined. Furthermore, antenatal inflammation has been linked to high risk of BPD in preterm infants. The purpose of this study was to explore whether MVs derived from hUCMSCs can preserve lung structure and function in an antenatal lipopolysaccharide- (LPS-) induced BPD rat model and to clarify the underlying mechanism. We demonstrate that antenatal LPS induced alveolar simplification, altered lung function, and dysregulated pulmonary vasculature, which restored by hUCMSCs and MVs treatment. Furthermore, MVs were large vesicles with a diameter of 100-900 nanometers and mostly uptaken by alveolar epithelial type II cells (AT2) and macrophages. Compared with the LPS-exposed group, MVs restored the AT2 cell number and SP-C expression  Bronchopulmonary dysplasia (BPD) is a serious and common chronic lung disease of premature infants. It is caused by the imbalance between lung injury and repair in the developing immature lung . BPD is The cause of BPD is associated with a wide variety of risk factors . Historivia paracrine mechanisms, and MSC-derived conditioned medium revealed a comparable therapeutic effect [in vitro [Human umbilical cord mesenchymal stem cells (hUCMSCs), with low immunogenicity and easy accessibility, are effective for inflammatory disease treatment and regenerative medicine, which bring new hope to patients with BPD . In precc effect . As a mac effect , proangic effect , 28, andc effect . Besidesc effect —have beec effect , 32. Onec effect . Anotherin vitro . HoweverIn this study, we aim to explore whether MVs derived from hUCMSCs can preserve lung development and the underlying mechanism in an antenatal LPS-induced BPD rat model. We found that MVs derived from hUCMSCs were able to enhance alveolar development by promoting AT2 cell proliferation and ameliorating inflammation. Our findings provide insights into the paracrine effects of MSCs on the antenatal rat model of BPD.Sprague-Dawley (SD) rats were purchased from the Experimental Animal Center of Chongqing Medical University and maintained at the Animal Laboratory Center of Pediatrics, Children's Hospital of Chongqing Medical University. All animal procedures and protocols were approved by the Ethics Committee of Children's Hospital of Chongqing Medical University. The animals were housed under controlled temperature (22 ± 1°C) with a 12-hour day/night cycle with food and water ad libitum. Neonatal mortality was checked daily.μL per amniotic sac) for the control group or LPS (10 μg of Escherichia coli 055: B55 diluted with 50 μL NS per sac) for the antenatal BPD model. Two days following IA injections, cesarean section was performed on pregnant rats under general anesthesia. All the rat pups  in the injected amniotic sacs were delivered and then placed with foster mother rats.As shown in 5 cells per 100 mm dish and cultured for 48 hours in 10 mL DF-12 with 10% exosome-free FBS. The medium was collected and centrifuged at 4°C, 400 × g for 5 minutes and 1500 × g for 10 minutes to remove cells and debris. The supernatant was ultracentrifuged at 18000 × g for 30 minutes to pellet the MVs. The total protein concentration of the MVs was measured using BCA kit  as per the manufacturer's recommendations. The isolated MVs were stored at −80°C for later use and characterized by TEM  and Zetasizer Nano S90 .Exosome-free fetal bovine serum (FBS) was prepared overnight using ultracentrifugation at 4°C, 120000 × g for 12 hours. MVs were harvested from the medium of hUCMSCs, obtained from the Chongqing Stem Cell Engineer Research Center. Briefly, P4-P6 HUCMSCs were seeded at 1 × 10μL hUCMSCs (1 × 106 cells per pup) or MVs by intratracheal route, while the control groups received 40 μL of intratracheally administered NS. On PN14, the pups were anesthetized with an intraperitoneal injection of pentobarbital sodium (40 mg/kg). Then, the thoracic cavity was opened, and the lungs were perfused with cold PBS through the heart. The lungs were harvested for histological assessment. The hearts were weighed to determine RVI. Body weight was measured at birth, on PN7, and on PN14. Animals were randomized into different groups using table of randomized numbers. Treatments were administered in a blinded manner. In order to minimize the cage effect, pups among groups were divided and housed in 4-4 cages, with five to eight pups per cage.On postnatal day 7 (PN7), as illustrated in One 4 mm thick transverse section was taken from the midplane of the left lobe of the fixed lungs per animal and processed and embedded in paraffin wax. All the sections were stained with hematoxylin and eosin, and alveolarization was assessed by performing radial alveolar counts (RAC), secondary septa count, and median linear intercepts (MLIs) as previously described .μm at −20°C . Frozen sections and cells were then fixed with 4% PFA and blocked with 10% BSA. Subsequently, the samples were stained with anti-vWF antibody , washed, and incubated with goat anti-mouse Fluor cy3-conjugated secondary antibody . Cell nuclei were counterstained with DAPI for 15 minutes, and fluorescence was observed on a Leica laser confocal microscope . Five random images were captured at 200x magnification for quantification of vWF.Pulmonary vasculature was measured by immunofluorescence with von Willebrand factor (vWF). Fixed left lungs were embedded in glue  and cut with a microtome at 10 2O with the computer-controlled small-animal ventilator . LR and Cdyn were recorded every five seconds. Right ventricular hypertrophy was determined by the right ventricular index (RVI), which represents the weight of right ventricle relative to left ventricle+septum (RV/(LV + S)). Briefly, after removing the arterial and adipose tissue on the epicardium, we collected and weighed the left ventricle plus the interventricular septum and the right ventricle tissue by cutting along the edge of the ventricle and the interventricular septum.Lung function was determined in PN14 pups with a computer-controlled small-animal ventilator . Briefly, the rats were anesthetized with pentobarbital sodium (40 mg/kg), intubated following tracheostomy, and mechanically ventilated at a rate of 150 breaths/min, with a tidal volume of 8 mL/kg and a positive end-expiratory pressure (PEEP) of 3 cm Hμm thick cryostat sections on PN9 (48 hours after MV administration). The following primary antibodies were used as markers of alveolar epithelial type I cells (AT1), AT2, vascular endothelial cells, vascular pericytes, total macrophages, and smooth muscle cells: Aquaporin-1 , prosurfactant protein C , CD31 , NG2 , Iba-1 , and α-smooth muscle actin (α-SMA) , respectively. Then, Cy-3 dye-labeled IgG was used as the secondary antibody . Fluorescence was observed on Leica laser confocal microscopy , and at least five different visual fields were randomly selected from each sample.MVs were labeled with a DiO Green Fluorescent  as per the manufacturer's protocol. Immunofluorescence localization of donor MVs was performed on 10 The lung tissues were harvested in a lysis buffer (25 mMTris-HCl (pH 7.5), 137 mM NaCl, 2.7 mM KCl, and 1% Triton X-100) containing protease and phosphatase inhibitor cocktail . The protein concentration was measured using BCA protein assay reagent . Equal amounts of proteins were separated using SDS-PAGE and transferred to polyvinylidene difluoride membranes . The membranes were blocked with 5% skim milk in PBS containing 0.1% Tween 20 (PBS-T) for one hour and then incubated with the specified antibodies. Signals were detected using the ECL detection system .t-test was used for statistical comparisons between two groups, and a one-way analysis of variance (ANOVA) with Kruskal–Wallis/Dunns post hoc test was applied for significance testing among more than two groups. Investigators were blinded to experimental groups for histological analysis and physiological measurements. Statistical significance is indicated as follows: ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001. NS means no significance. Data are presented as mean ± standard error.Statistical analysis was performed with the GraphPad Prism software . A Considering that antenatal LPS injection could cause impaired alveolar structure and dysregulated vasculature to mimic human BPD features , we estaμm) in rats exposed to LPS were significantly less abundant than those in the NS group; however, the abundance of small vessels increased after hUCMSC treatment, compared with the LPS group . Subsequently, we determined whether MVs can be internalized into the MLE-12 cells (an AT2 cell line). MVs labeled with red fluorescence PKH26 colocalized with the green fluorescence signals of cytoskeleton stained with phalloidin, indicating the internalization of MVs into the AT2 cells , and NG-2-positive pericytes (2.4%)  .in vivo, we next investigated the effects of MVs on these two target cells. For AT2 cells, immunofluorescence staining of SP-C showed that LPS exposure decreased SP-C(+) cells, whereas MVs restored the number of SP-C(+) cells  have a protective effect on lung injury on BPD , 37, 38.In this study, we showed that the MVs derived from hUCMSCs enhanced alveolar development and alleviated lung inflammation in the IA-LPS BPD model, and this protection was associated with the PTEN/AKT pathway and the MAPK pathway. These findings also suggest that MVs are key paracrine therapeutic mediators of hUCMSCs and show potential for application in safe and effective cell-free therapy for BPD associated with antenatal factors.Many studies have shown that antenatal factors are strongly associated with susceptibility to BPD. However, the most commonly used animal model for BPD research involves exposure to postnatal hyperoxia; thus, it cannot reflect antenatal factors that influence BPD. Here, we used a rat model of BPD induced by intra-amniotic injections of LPS; LPS induced impaired alveolarization and diminished lung function, particularly mimicking BPD of preterm infants in humans , 40.Functions of EVs depend on their ability to interact with recipient cells to deliver their contents  . Our datAT2 cells have critical secretory and regenerative roles in the alveoli to maintain lung homeostasis . Our datAs another major target cell of MVs, lung macrophages are dominant immune cells in the inflammation . Our resIt has been shown that the proliferation of AT2 cells in lung injury is linked to abnormal expression of PTEN/AKT . As a maFurthermore, previous studies have shown that the antenatal exposure of preterm infants to infection and inflammation may result in adverse fetal consequences, such as BPD . ActivatSince exosomes received most of the attention, the effect of MVs is poorly understood before. Our results show that MVs have the potential to exert both proinflammatory and proproliferation actions, providing a detailed framework for the successful use of MVs as a strategy for BPD treatment. These interesting results deserve more research efforts in the future. Our study also has the potentiality to be applied on other repairing strategies with novel biomedical materials, like the Phosphorene or the Borophene .Although encouraged by these findings, we acknowledge several limitations of this study. First, the concentration and duration of LPS in amniotic sac, as well as intake of LPS in the lung, were not examined. Second, we only administered MVs in IA-LPS BPD model rats. Other studies have shown that exosomes have similar therapeutic effects as MSCs . Future In conclusion, we demonstrated that MVs derived from hUCMSCs restored lung architecture and function and improved RVH in the IA-LPS BPD model by promoting AT2 cell proliferation and attenuating lung inflammation. The underlying mechanism was associated with the PTEN/AKT pathway and the MAPK pathway. Our findings may offer a new perspective for the treatment of BPD by MVs.


Leymus chinensis on the physicochemical properties and structure of degraded soil after 3 years of cultivation and explored the bacterial and fungal drivers in root exudates by metabolomics and high-throughput sequencing. The results showed that root exudates increased soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP) and soil aggregates, and organic acids in root exudates reduced pH and activated insoluble nutrients into forms that are available to plants, such as available nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), and available phosphorus (AP). The cultivation of L. chinensis restored the diversity and richness of soil microorganisms and recruited potential beneficial bacteria and fungi to resist degraded soil stress, and L. chinensis also regulated the abundances of organic acids, amino acids and fatty acids in root exudates to remediate degraded soils. Spearman correlation analysis indicated that glutaric acid, 3-hydroxybutyric acid and 4-methylcatechol in root exudates attracted Haliangium, Nitrospira and Mortierella to the rhizosphere and dispersed the relative abundance of the harmful microorganisms Fusicolla and Fusarium. Our results demonstrate that L. chinensis enhances soil fertility, improves soil structure, promotes microbial diversity and abundance, and recruits potentially beneficial microorganisms by modulating root exudate components.Phytoremediation is an effective means to improve degraded soil nutrients and soil structure. Here, we investigated the remediation effects of  Healthy soil plays a key role in human survival. Unfavorable environmental factors and inappropriate human utilization  lead to the destruction of soil ecosystems and a sharp decline in soil quality  through Root exudates are complex in chemical composition and typically comprise sugars, amino acids, organic acids, and other secondary metabolites, and their composition and release rates vary with plant species and environmental factors . Root exPseudomonas fluorescens strains  Tzvel. was chosen as the target plant. It has a well-developed root system and strong capacity for reproduction. L. chinensis reproduces asexually through powerful rhizomes and exhibits a strong resistance to abiotic stress and a strong potential for phytoremediation (L. chinensis on the remediation of degraded soil fertility and structure. We aim to determine (1) how soil degradation affects the changes in soil bacteria, fungal communities and root exudate components and (2) how L. chinensis shapes microbial communities in response to degraded soil stress by regulating root exudates. We predicted that soil degradation would increase root exudate components. We also predicted that the changes in root exudate components would reshape soil microbial communities and enhance soil nutrients.In this study, ediation . We condL. chinensis was transplanted into the plot and cultivated evenly. The planting spacing was set as 30 cm, and the plot area was set as 5 m × 5 m. Each adjacent plot was an untreated plot as a buffer to minimize the crossover effect. Without fertilization and irrigation, the samples were harvested on September 3, 2020 after 3 years of complete natural recovery.The research was conducted at the Degraded Soil Restoration and Treatment Demonstration Base (126°26′04″E and 45°57′87″N) at Northeast Agricultural University, Heilongjiang Province, China . The areL. chinensis were carefully uprooted with a shovel, and the soil around the roots was removed by gentle hand shaking. The soil tightly adhering to the root surface within 3 mm was collected in a sterile self-sealing bag, and the soil far from the root surface was considered the non-rhizosphere soil. Rhizosphere soil contains abundant root exudates, which makes its properties different from those of non-rhizosphere soil , and the morphology and structure of the soil aggregates were observed by scanning electron microscopy (SEM) , and 1% agarose gel electrophoresis was used to detect quality and purity. The bacterial 16S rRNA gene was amplified using primers 338F (ACTCCTACGGGAGGCAGCAG) and 806R (GGACTACHVGGGTWTCTAAT) specific to the V3-V4 variable region. The fungal ITS rRNA gene was amplified using primers ITS1-F (CTTGGTTCATTTAGAGGAAGCTA) and ITS2 (TGCGTTCTTCATCGATGC) specific to the ITS1 region. The purified polymerase chain reaction (PCR) product was subsequently paired-end sequenced on the Illumina MiSeq platform . The high-quality sequences with ≥97% similarity were classified as the same operational taxonomic unit (OTU) and annotated by the Silva database and Unite database to classify the soil microbial communities into phenotypes. Soil microbial community diversity and richness information were analyzed by QIIME (v1.8.0).Leymus chinensis were collected randomly from each plot, rinsed with Milli-Q water carefully, and then disinfected with 2% Hg2Cl2. The root exudates were collected by the L. chinensis root system dipped in a dark conical flask containing 200 ml sterile Milli-Q water every 2 h. After multiple collections, the collected root secretion solution was combined until 1,000 ml of root exudate at each degradation level was obtained. The samples were filtered through a 0.45-μm filter, 40 ml of the samples was freeze-dried and extracted with 1,000 μl of extract , and 10 μl of adonitol (0.5 mg mL−1) was added as an internal standard. The mixture was centrifuged at 12,000 rpm for 15 min at 4°C, and the supernatant was derivatized with methoxyamine hydrochloride (20 mg mL−1 in pyridine), BSTFA  and FAMEs (in chloroform) for further analysis. Root exudates were ultimately separated by a DB-5MS capillary column  and analyzed with gas chromatography time-of-flight mass spectrometry (GC-TOFMS). The metabolic markers were identified by the LECO-Fiehn Rtx5 database after filtering and normalizing the resulting data. The quality control samples for root exudate analysis were prepared by mixing aliquots of all samples.n = 6), and the remaining experiments were performed in triplicate (n = 3). Data are presented as the mean ± standard errors and were analyzed by one-way analysis of variance (ANOVA). SPSS 19.0 and Origin Pro 9.0 software were used to analyze the significance of differences between groups, and p < 0.05 was considered statistically significant. Statistical tests were performed on the α diversity of the microbial data for each group, and differences between the groups were assessed. The R vegan package (version 3.3.2) was used to draw Venn diagrams showing the number of OTUs shared between samples, visually illustrating the overlap of OTUs between each sample. The top 10 phyla and genera with high abundance were filtered from the OTUs of bacteria and fungi, and the abundance composition heatmap of the top 10 phyla and genera in different treatments was plotted using R version 3.3.2. Principal coordinate analysis (PCoA) with a paired Bray–Curtis similarity matrix was performed by the OTU count statistics of 97% similarity between different samples. Linear discriminant analysis-effect size (LEfSe) analysis was used to determine the effect size of linear discriminant analysis (LDA), and the Wilcoxon rank sum test (α = 0.05) was used to identify species with abundance that differed significantly between categories. A cut-off of LDA values>3 was used to estimate the influence of species that differed significantly. The different root exudate metabolites were screened by variable importance in projection (VIP) scores and Student’s t test and identified using biochemical pathways with the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Correlations between bacteria, fungi and root exudate composition were calculated by Pearson correlation analysis. The R vegan package (version 3.3.2) was used to plot the correlation heatmap between bacteria, fungi and root exudate composition .Root exudate analysis was performed with six biological replicates . LR attracted Sphingomonas and dispersed H116, and MR dispersed Nitrospira and Haliangium , and PC2 explained 14.3% of the variance . The samonadetes , and theliangium . The funliangium . The rhint phyla . Root exgazzinia .Lgnavibacteria and Lgnavibacteriales were significantly enriched. LN had 4 significant biomarkers , and Spartobacteria and Chthoniobacterales were significantly enriched. Five significant biomarkers  were identified in MR, which was significantly enriched in Micromonosporaceae and Micromonosporales. The most prominent order, 43F-1404R, was a significant biomarker in MN. Four significant biomarkers  were identified in HR, and Thermomicrobia was significantly enriched. The OM1 clade was the only significant biomarker in HN  were identified in LR, and er in HN .Rhizophydiales and Rhizophydiomycetes. LN was enriched in Torulaceae, which emerged as a significant biomarker. For the M treatment, 4 significant biomarkers (1 order and 3 families) were exclusively identified in MR, which was significantly enriched in Didymosphaeriaceae and Bolbltoaceae. Five (2 orders and 3 families) and 1 family biomarkers were significantly enriched in HR and HN, respectively. Tubeufiaceae, Tubeufiales and Cucurbitariaceae were significantly enriched in HR, and Mrakiaceae was enriched in HN  were identified in LR, which was significantly enriched in ed in HN . The aboL. chinensis. OPLS-DA was applied to compare the changes in root exudates at different soil degradation levels (p ≤ 0.05) and VIP score (VIP > 1). These metabolites mainly involve organic acids, fatty acids, amino acids and other metabolites. The main metabolic changes were concentrated in nonpolar metabolites, including saturated and unsaturated long-chain fatty acids, such as palmitic acid, stearic acid, arachidic acid, and lauric acid. Some compounds with anti-abiotic stress properties were also altered by adaptation to degraded soil environments.A total of 473 metabolites were detected in the GC-TOFMS chromatogram of root exudates of n levels . The OPLL. chinensis and rhizosphere microorganisms, Spearman correlation analysis was performed between rhizosphere microorganisms with the top 20 relative abundances at the genus level and 43 differential root exudates  has shown that the main source of SOC content is root-derived C inputs  to promote plant growth and improve soil nutrients , the Heilongjiang Provincial Natural Science Foundation of China (LH2020C021), the National Key R&D Program of China (2016YFC0500607), the Heilongjiang Postdoctoral Fund to pursue scientific research (LBH-Z20003), and the Young Talents Project of Northeast Agricultural University (19QC21). Each of the funding bodies granted the funds based on a research proposal. The bodies had no influence on the experimental design, data analysis and interpretation, or writing of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.https://www.frontiersin.org/articles/10.3389/fmicb.2022.951838/full#supplementary-materialThe Supplementary material for this article can be found online at: Click here for additional data file.Click here for additional data file.Click here for additional data file.Click here for additional data file.


To study the impact of hyperuricemia on clinical presentation, severity, and associated comorbidities of psoriatic arthritis (PsA).Retrospective bicentric case–control study performed in Strasbourg and Colmar, France, from 2009 to 2019. Patients with PsA (according to ICD-10 coding) and at least one available serum urate (SU) measurement were included. Demographic, comorbidities, clinical, and radiographic data were collected. Hyperuricemia was defined as SU level ≥ 360 µmol/L.p = 1.6 × 10−6) with higher body mass index  and more comorbidities . PsA started at an older age  was more polyarticular  than axial  and more destructive . PsA patients with joint destruction more frequently had hyperuricemia than did others . Multivariable analysis confirmed the association of hyperuricemic PsA with peripheral joint involvement  and less good response to treatment .We included 242 patients: 73 (30.2%) had hyperuricemia and 15 (6.2%) met 2015 ACR/EULAR criteria for gout. On univariate analysis, as compared with normo-uricemic patients, hyperuricemic patients were more frequently male (72.6% vs 39.1%, Patients with hyperuricemic PsA show poorer response to PsA treatment and have more peripheral and destructive joint damage than normo-uricemic patients. Gout and psoriatic arthritis (PsA) are 2 common diseases that can co-exist in the same patient. These 2 diseases seem strongly linked, but the pathophysiological mechanisms of this link have not yet been defined. Nonetheless, monosodium urate (MSU) crystals play a pathogenic role in psoriasis with a mechanism we could extend to PsA . We hypoPsA and gout also share comorbidities, both associated with type 2 diabetes, high blood pressure, and increased risk of major adverse cardiovascular events (MACEs) . MetabolDespite examples suggesting that hyperuricemia worsens and maintains skin psoriasis , 8, it hThis study aimed to compare PsA patients with normo-uricemia and hyperuricemia. Our main objective was to assess the impact of hyperuricemia on PsA in its clinical presentation, its severity, and associated comorbidities.This was a retrospective case–control, bicentric cohort study. Patients from Strasbourg University Hospital and Colmar Civilian Hospital, France, were included from January 1, 2009, to December 20, 2019.We included patients with a history of PsA according to their rheumatologists and codes of International Classification of Diseases, 10th edition (ICD-10) and the presence of at least one serum urate (SU) measurement in the medical file. In case of diagnostic doubt with rheumatoid arthritis  during the medical file review, patients were excluded if they met the 2010 ACR/EULAR classification criteria for rheumatoid arthritis.We excluded patients who expressed their opposition to participate to the study or with a diagnosis other than PsA after the medical file review.Patients with normo-uricemia and hyperuricemia were compared according to a hyperuricemia threshold ≥ 360 µmol/L, whether they were women or men, based on the median SU level for each patient. To minimize the impact of one isolated hyperuricemia event  and to promote the inclusion in the hyperuricemic group with persistent and lasting hyperuricemia, we used the median value for each patient to determine whether they were above this cutoff or not. The median was used to lower sensitivity to extreme values and because of the distribution of these values. This 360-µmol/L cutoff was chosen for several reasons. In vitro, MSU crystals crystallize at 35 °C above the threshold of 360 µmol/L, at which the risk of gout attack is increased in both women and men , 14. TheDemographic, clinical, biological, and radiological available data were collected. Data collected for PsA included disease duration, age at PsA onset, HLA-B27 status, characteristics of clinical manifestations, and therapeutic history . PsA was defined for each patient according to the five Moll and Wright subtypes: oligoarticular, polyarticular, axial, distal, and mutilant . CoexistFor each patient, every SU measurement available was collected, as was the number of tests reported, in order to calculate the median SU level for each patient. A history of gout attack or evidence of MSU crystals within a joint was collected. Each patient was tested for 2015 American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) gout criteria. Data on hypo-uricemic and gout attack treatment were collected.Radiologic characteristics of PSA and gout from standard X-rays, ultrasonography, tomodensitometry, and MRI were collected. PsA was defined as destructive with any erosion related to PsA regardless of the technique . In addition to comparing hyperuricemic and normo-uricemic patients, we compared patients with destructive and non-destructive PSA.We collected data on cardiovascular comorbidities, metabolic syndrome , MACEs,t test for quantitative data. The Shapiro test associated with data visualization was used to assess normality. We did not calculate the sample size needed because we included all available patients. We used logistic regression to analyze the primary outcome with estimation of odds ratios (ORs) and 95% confidence intervals (CIs). Model included 7 “hyperuricemia” variables, which were selected according to expert knowledge from the literature, univariate analysis, and backward stepwise selection on the Akaike Information Criterion  years, and mean age at PsA onset was 44.4 (SD 14) years. Overall, 99 (42.1%) patients had radiographic destructive involvement related to PsA, and 158 (80.3%) showed good response to the last ongoing treatment. As expected, most patients had peripheral articular involvement and 45 (19%) had isolated axial involvement. The mean SU level was 309.2 (SD 88.04) µmol/L. Three (1.2%) patients had a history of MSU crystals in synovial fluid, 15 (6.2%) had a history of gout attack, and 15 (6.2%) met the 2015 ACR/EULAR criteria for gout.The main characteristics of the cohort are in Table n = 73) and normo-uricemia (n = 169) is in Table p = 0.020) and more frequently men . They had higher mean BMI . The 2 groups did not differ in HLA-B27 positivity. The mean age at PsA onset was significantly higher in the hyperuricemic than normo-uricemic group: 47.5 (SD 13.71) vs 43 (SD 14) years (p = 0.016), but the groups did not differ in median duration of PsA. At the end of follow-up, as compared with normo-uricemic patients, hyperuricemic patients had a more peripheral PsA involvement  and more polyarticular disease . They had significantly less isolated axial involvement of PsA . Overall, 38 (52.8%) had radiographic destructive PsA as compared with 63 (38.7%) of normo-uricemic patients (p = 0.047). Erosion seen on standard X-rays was more frequent for hyperuricemic than for normo-uricemic patients . Good response to ongoing PsA treatment was lower for hyperuricemic than normo-uricemic patients , with no difference between the groups in distribution of last ongoing treatments.The comparison between patients with hyperuricemia (p = 0.005). Significantly more hyperuricemic than normo-uricemic patients had metabolic syndrome , high blood pressure , MACEs , ischemic stroke , acute coronary syndrome , moderate or chronic renal failure , and type 2 diabetes .The study of the main comorbidities is in Table p = 0.024) and the median SU level was significantly higher . Destructive disease was associated with SU level ≥ 300 µmol/L  and ≥ 360 µmol/L .Uricemia was measured more frequently in patients with destructive than non-destructive PsA . The probability of a good response to ongoing treatment was reduced for patients with PsA and hyperuricemia . Radiographical destructive PsA was associated but not significantly with hyperuricemia .On multivariable analysis based on the “hyperuricemia” variable Table , variablAs compared with normo-uricemic patients, hyperuricemic patients were more frequently male, with a more polyarticular and less axial PsA presentation, a more destructive radiographic involvement, more cardiovascular and renal comorbidities, and poorer response to PsA treatment. In addition, median SU level was higher with destructive than non-destructive PSA. Moreover, SU level was measured more frequently in patients with destructive than non-destructive PSA. These latter data may be explained by more frequent PsA flares with destructive than non-destructive PSA and more frequent measurement of SU level in this case to search for a differential diagnosis such as gout.Our cohort of patients with PsA is mainly comparable to the known epidemiology of PsA , 21–23. The prevalence of gout in the French general population is 0.9%  and was The prevalence of hyperuricemia in Europe reaches up to 25% . In our Little is known about the stability of the measurement in the same person over time, and some studies are limited because they measured SU level at a single time point . HoweverOur study has some limitations. The retrospective data limit its power. Our inclusion criteria could have overestimated the severity of PsA because the use of ICD-10 coding allowed us to include only hospitalized patients, thus implying Berkson’s bias . In the The main strength of our study is that it is the first to specifically evaluate PsA in terms of SU level. A large number of patients were included, for which we also had little missing data because of deep reading of medical files.The present study allows for distinguishing 2 distinct PsA profiles according to their association with hyperuricemia Fig. .Fig. 1DOur results support a potential worsening impact of MSU crystals on PsA, previously named psout . The exiHere, we propose recommendations for the diagnosis of psout and management of PsA with or without hyperuricemia Fig. .Fig. 2RTo confirm this viewpoint, new studies, especially prospective and interventional ones, could help better understand the role of hyperuricemia in PsA.Patients with hyperuricemic PsA show poorer response to PsA treatment and more peripheral and destructive joint damage than do normo-uricemic patients.


Decreased baroreflex sensitivity (BRS) has been shown to be a marker of cardiovascular (CV) risk. In the present study, the difference in CV risk biomarkers in type 2 diabetes (T2D) patients receiving oral antidiabetic drugs (OAD) with and without hypertension has been assessed.Ninety-two T2D patients on OAD without hypertension (control group) and eighty-eight diabetic patients with hypertension on OAD and antihypertensive drugs (test group) matched for age, gender, body mass index, serum glucose, glycated haemoglobin, and duration of the disease were recruited for the study. Their blood pressure (BP) variability including BRS, heart rate variability (HRV), insulin, lipid profile, osteoprotegerin (OPG), and tumor necrosis factor-α (TNF-α) were estimated. The association of various factors with BRS was assessed by Spearman correlation and multiple regression analysis.BRS was decreased (13.90 ± 5.27 vs 6.76 ± 4.58), HRV sympathetic indices , HOMA-IR, atherogenic index of plasma (AIP), OPG (223.08 ± 103.86 vs 287.60 ± 121.36) and TNF-α were increased, and parasympathetic indices  were decreased in the test group compared to control group. In control group, parasympathetic indices, AIP, OPG, and TNF-α had a significant correlation and OPG had an independent association  with BRS. In test group, BP, LF-HF ratio, parasympathetic indices, AIP, OPG, and TNF-α had significant correlation, and TNF-α alone  had an independent contribution to decreased BRS.Despite antidiabetic and antihypertensive treatments, T2D patients with hypertension had more cardiometabolic risks in comparison to normotensive T2D patients. Inflammation could be the inciting factor for rise in BP and decrease in BRS (CV risk) in hypertensive T2D patients. Hypertension in diabetes could attenuate the link of OPG to the reduction in BRS. Reduction in BRS could be a physiological marker of CV risk in T2D patients treated with OAD. Hypertension is present in more than 50% of diabetes mellitus (DM) patients contributing significantly to microvascular and macrovascular complications , 2. IndeFor long, the first line of drugs of choice for the management of type 2 diabetes mellitus (T2D) is sulfonylurea and biguanides, either as monotherapy or in combination . At the Baroreflex sensitivity (BRS) and heart rate variability (HRV) have recently been reported as sensitive markers of CV risks in various clinical disorders –19. We hAlthough alteration in HRV and BRS has been reported in DM , the magThis was a cross-sectional analytical study conducted in Biochemistry, Physiology, and Medicine departments at Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India. This study was first reviewed and approved by an institutional review board (JSAC), followed by Institutional Ethics Committee (Human studies: JIP/IEC/2018/305) before the study was conducted. Written informed consent was obtained from all participants at the time of recruitment.n = 92) consisting of T2D patients on treatment with oral antidiabetic drugs (OAD), and the test group consisting of T2D patients (n = 88) on treatment with antidiabetic and antihypertensive drugs . We screened around 2200 diabetic patients between November 2018 and January 2020 and recruited 201 T2D patients following exclusion and inclusion criteria. Twenty-one patients with uncontrolled diabetes/hypertension were excluded from the study. Thus, the final sample size for the present study was 180. Among them, 92 patients had no hypertension and 88 patients had hypertension. Accordingly, they were divided into two groups: the control group  between two independent means of BRS (17.23 vs 9.07) based on the previous report  and a siThe study protocol was explained to the patients in their local language before obtaining written informed consent. All the participants were asked to avoid intake of coffee, nicotine, and alcohol 24 hours before the recordings. They were instructed to report next morning to the autonomic function test (AFT) lab between 8:30 am and 9:30 am in overnight fasting state. Fasting blood samples were collected the next day morning, and basal recordings were obtained 2 h after a light breakfast meal.Basal demographic and anthropometric data were collected using a wall-mounted stadiometer to measure height, and a digital weight balance was used to measure the weight of individuals with light clothing. Body mass index was (BMI) derived using Quetelet’s formula. Basal demographic and anthropometric parameters of all the participants were recorded, and the personal history was noted using a structured data sheet.t 8.30 am. Their age, body weight, height, and BMI were recorded. Omron (SEM 1 Model), the automatic BP monitor apparatus , was used to measure their BP. The cuff size of the equipment used was 121 mm (width) × 446 mm (length), and the cuff tube length was 600 mm. The patients sat upright with backs straight on a wooden armed chair. After placing one forearm comfortably on the table, the middle of the arm of the subjects was coincided with the heart level. The BP cuff was tied on the arm roughly 2 cm above the cubital fossa, which was neither too tight nor loose. For each participant, heart rate (HR), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were recorded at an interval of 5 minutes in each arm twice, and the mean of the four recordings was considered for each parameter.Patients reported in the autonomic function laboratory of Physiology Department at abouThe CV parameters and BRS were measured using the continuous BPV method . Finapres is a non-invasive continuous hemodynamic CV monitor that uses the principle of finger plethysmography as described in detail in our earlier reports , 21. TheFor the recording of short-term HRV, the HRV measurement and analysis procedures described earlier were followed , 23. ECGFollowing overnight fasting, five ml of venous blood was collected under aseptic precautions in clot activator tubes. Blood samples were centrifuged for 15 min after coagulation at 2500 RPM. Serum separated was processed for fasting glucose and lipid profile. Fasting serum glucose (FSG) was estimated by the Hexokinase method and lipid profile was measured by an automated AU5800 chemistry analyzer using commercial kits . LDL-C was analyzed by direct estimation. Total cholesterol, HDL-C, and triglyceride were analyzed by cholesterol oxidase, direct immunosuppression method, and Lipase/Glycerol phosphate oxidase method, respectively.TNF-α , insulin , and OPG  were estimated by an enzyme-linked immunosorbent assay (ELISA). In the method of ELISA for OPG, the polyclonal goat anti-human OPG antibody binds to human endogenous OPG. Thus, the monomeric and dimeric OPG form a complex with the antibody. The washing step removes the nonspecific bound materials, while a second antibody complexed with streptavidin-HRP detects this complex, which follows the principle of sandwich ELISA. The concentration of OPG is directly determined by the standard dose-response curve. HOMA-IR was calculated using formula. HOMA-IR = Glucose X Insulin / 405 . The intP value < 0.05 was considered significant.All the clinical characteristics and variables were expressed in frequencies and percentages for categorical variables. Continuous variables were expressed as Mean ± SD. The normality of data was checked by the Shapiro-Wilk test. Chi-square test was used for comparison between two groups for all the nominal data. For comparison between continuous parameters, Student’s unpaired t-test and Mann–Whitney-U test was used for normally distributed variables and non-normally distributed variables, respectively. The relationship between the variables in each group was evaluated by Spearman’s rank correlation analysis. For assessing the independent contribution of variables to BRS, multiple regression analysis was used. This was followed by stepwise regression analysis to elucidate the most important variable contributing to alteration in BRS. All statistical tests were performed using SPSS version 20.0. A total of 180 diabetes mellitus patients were recruited from October 2018 to January 2020. The distribution of age, gender, and other histories are shown in Table A significant increase was observed in the HR, SBP, DBP, MAP, and RPP in T2D patients with hypertension Table .Among the BPV parameters, SV, LVET, CO, and TPR were significantly increased, while BRS was decreased in the test group Table .Among the HRV indices TP, SDNN, RMSSD, NN50, and pNN50 were significantly less in T2D patients with hypertension Table . LFnu waThe serum concentration of glycemic parameters, lipid profile, and atherogenic indices among study participants are presented in Table p = 0.009) and RPP  in the test group  and LF/HF  and TNF-α  in test group (Table p = 0.000) and for T2D patients without hypertension (Table p = 0.004) in the test group.Decreased BRS was significantly associated with rise in HR  compared to the control group  Table . BRS wasr = − 0.595, P = 0.000) compared to the control group   and we found that OPG  had more significant association with decrease in BRS compared to TNF-α   in the entire study population (7) Table . This inDiabetes and hypertension share several pathophysiologic mechanisms such as inappropriate activation of the renin-angiotensin-aldosterone system (RAAS), oxidative stress, impaired insulin-mediated vascular function, inflammation, increased sympathetic activation, dysfunctional immune responses, and abnormal renal handling of sodium , 51. PerThe glycemic status (levels of serum glucose and glycated hemoglobin) is known to influence HRV . TherefoThough the major limitation of the present study is that we did not take a pure nondiabetic control group to compare cardiometabolic risks of diabetic patients with nondiabetic subjects, based on our previous data of control subjects , 21 we cDespite antidiabetic and antihypertensive treatment, patients with hypertension and diabetes had more cardiometabolic risks compared to normotensive patients with diabetes. Inflammation could be the inciting factor for rise in BP and decreased BRS in hypertensive diabetics. Decreased BRS could be the marker of CV risk in T2D patients.


Quinolones are popular antibiotics that are known for their potency, broad coverage, and reasonable safety. Concerns have been raised about a possible association between quinolones and retinal detachment (RD).We conducted a nested case–control study using electronic health records (EHR) from the Health Facts® Database. The initial cohort included all patients who were admitted between 2000 and 2016, with no history of eye disease, and had a minimum medical history of one year. Eligible cases comprised inpatients who were first admitted with a primary diagnosis of RD between 2010 and 2015. Each eligible case was matched without replacement to five unique controls by sex, race, age, and period-at-risk. We used conditional logistic regression to calculate RD risk, adjusting for exposure to other medications, and major risk factors.We identified 772 cases and 3860 controls. Whereas our primary analysis of all subjects revealed no quinolone-associated RD risk, elevated but non-significant risks were noted in African Americans (ciprofloxacin and levofloxacin), those aged 56–70 years old (moxifloxacin), and women (ciprofloxacin).Our study did not identify an elevated RD risk within 30 days following systemic administration of quinolone antibiotics. Suggestions of increased risk observed in some population subgroups warrant further investigation.The online version contains supplementary material available at 10.1007/s00228-021-03260-4. Quinolones are a popular class of antibiotics that are heavily prescribed worldwide due to their potency, broad coverage, and reasonable safety –12. KnowRetinal detachment (RD) is a serious medical condition with an annual incidence of 5–14/100,000 as reported from population studies conducted in Sweden, Finland, Croatia, Japan, and USA –25. ThisMany epidemiologic studies have examined quinolone-associated RD risk, with conflicting results , 33–49. This study comprises one of a comprehensive, three-part examination of the association between systemic quinolones and risk of RD, which has been conducted in response to the heightened scientific and regulators’ safety concerns. The first part examines evidence from the FDA adverse drug event reporting system (FAERS)  to flag In this study, we analyzed inpatient EHR data from the Cerner Corporation’s Health Facts Data Warehouse® , Kansas City, Missouri, USA. This large database includes detailed EHR for almost 70 million deidentified patients , and all other medications combined (excluding antibiotics). Data on medication exposure was limited to prescriptions filled during inpatient care.We reported categorical variables as frequencies and percentages, and continuous variables as means with standard deviations. Categorical variables included sex, race , socioeconomic indicators including census region and division, hospital setting ; health insurance , and 30-day exposure to each of the three medication groups and individual quinolones (ever/never). Additional variables included diabetes mellitus  and alcohol abuse.Continuous variables included age at index encounter, comorbidity status, and the number of medications filled during the 30-day period preceding the index encounter. Age was stratified into 10-year intervals . Comorbidity was measured by the score generated via the Hude Quan version  of the EWe generated a series of conditional logistic regression models to identify the best estimate of quinolone-associated RD risk, while adjusting for other medication exposures and major confounders. For each medication group, we fitted a base model including only sex, race, age at index encounter as matching variables, and use (ever/never) of the medication group as the independent variable. We then fit a minimally adjusted model including all variables in the base model as well as all other medication groups (ever/ never). Finally, we fit a maximally adjusted model, extending the minimally adjusted model to include health insurance, census division, hospital setting/type, diabetes mellitus, and alcohol abuse, as potentially important demographic and socioeconomic covariates. To identify the individual quinolone(s) with the strongest possible association with RD risk, we repeated the same series of regression models using exposure to individual quinolones, rather than a class, as predictors of RD.To avoid possible confounding, we excluded a priori all patients with a history of eye diseases. We also adjusted for other major confounders, including health status, major risk factors , and socioeconomic status .To isolate the effect of notable differences in comorbidity and inpatient medication prescribing between cases and controls, we fitted a third series of regression models to different subgroups of our study population via stratifying by sex, race, comorbidity status (tertiles), and age at index encounter (tertiles).The entire Health Facts® Data Warehouse contained unique patients who were admitted at least once between 2000 and 2016 to any of the Health Facts® participating hospitals. By excluding inpatients with prior eye diseases, we identified 67,117,520 potentially eligible patients. By removing all patients with a medical history of less than 1 year, we were able to identify an initial study cohort of 3,361,592 individuals.Excluding those with missing or inconsistent data for any of the matching variables restricted this pool to 2,873,591 subjects, which included 845 RD cases and 2,872,746 potential controls. We then removed cases and potential controls with an index date between 2010 and 2015 to reach a final cohort consisting of 772 cases and 1,465,233 potential controls. Based on our matching algorithm, we were able to match a total of 3860 unique controls to the 772 cases  and included slightly more men 51%) than women. Incidence of RD ranged from 3 to 5% in the first four decades of life, and doubled twice to 9.3% and 21% in the fifth and sixth decades, respectively, before reaching a plateau afterward. Whereas there were more controls than cases with no comorbidities (34% compared to 15%), cases with comorbidities showed consistently higher comorbidities than controls, particularly within the CMI level 1–5 (55% compared to 43%). A higher prevalence of diabetes mellitus was identified in cases compared to controls at both levels of severity, uncomplicated (33% compared to 21%) and complicated (18% compared to 9%). Alcohol abuse showed no difference in prevalence between the two groups. Further details on the study population are shown in Table % than woThe average number of quinolone prescriptions per patient filled during the 30 days preceding the index date was comparable between cases (0.044 ± 0.28) and controls (0.037 ± 0.26). However, prescribing of other non-quinolone medications was higher in cases compared to controls . Each of ciprofloxacin, levofloxacin, and moxifloxacin were similarly prescribed among cases and controls during the 30 days preceding the index date, with moxifloxacin being prescribed only once for a single case and once for each of three controls .Our primary analysis of the entire study population showed that exposure to systemically administered quinolone antibiotics was not associated with an increased risk of RD [(aOR: 0.75 (95% CI: 0.43–1.32)], upon adjusting to exposure to non-quinolone antibiotics and other medications combined, as well as major risk factors for this outcome. Repeating the same analysis based on individual quinolones produced similar results to the multi-medication model including all quinolones simultaneously. The risk estimates reported in Table Upon stratifying the study population into tertiles  based on their comorbidity status (CMI score), neither quinolones nor other antibiotics showed any RD risk upon adjusting to major confounders. Quinolone antibiotics showed an almost twofold non-significant increase in RD risk in African Americans [aOR: 2.88 (95% CI: 0.43–19.33)]. This risk was driven by ciprofloxacin [aOR: 2.09 (95% CI: 0.11–41.09)] and levofloxacin [aOR: 1.85 (95% CI: 0.08–42.88)].Whereas quinolones showed no difference in RD risk between men and women, ciprofloxacin showed a marginal, non-significant increased risk in women [aOR: 1.34 (95% CI: 0.34–5.22)]. Upon stratifying the study population by age into tertiles , quinolones were not associated with an increased risk in any age group. However, moxifloxacin was associated with a more than fourfold, but highly uncertain, increase in RD risk in the (56–70) year-old group [aOR: 5.36 (95% CI: 0.30–97.21)].Our primary analysis of the entire study population showed an increased RD risk in association with complicated diabetes mellitus [aOR: 2.19 (95% CI: 1.68–2.86)]. Upon stratifying the study population, a similar pattern was identified in population subgroups, particularly in the healthiest comorbidity tier (CMI: 0–1): 14.08 (95% CI: 1.40–141.93)]. An increased risk was also noted in women [aOR: 2.69 (1.82–4.00)] more so than in men [aOR: 1.82 (95% CI: 1.26–2.63)], and in African Americans [aOR: 5.85 (95% CI: 2.70–12.65)] more so than in Caucasians [aOR: 1.69 (95% CI: 1.24–2.30)]. A fivefold risk was also noted in the youngest age tertile (0–55): [aOR: 6.18 (95% CI: 3.65–10.46)], which declined and became non-significant in the older age tertiles. In contrast to diabetes, alcohol abuse showed no elevated RD risk in either the entire study population or population subgroups.p-value for all regression analyses are provided in Supplementary Material V-VII.Results for the base and maximally adjusted models for the primary analysis examining the entire study population and the subgroup analysis based on comorbidity score are presented in this manuscript for all medication groups and for the individual quinolones in Tables Examining our entire study population revealed no evidence of a quinolone class-wide association with increased RD risk within 30 days of administering a systemic preparation of a quinolone antibiotic. However, a nearly twofold non-significant increase in RD risk in African Americans was attributable to ciprofloxacin and levofloxacin. Moxifloxacin showed more than fourfold non-significant increase in RD risk in those 56–70 years of age. Ciprofloxacin showed also a marginal and non-significant increase in RD risk in women. An overall low consumption of medications, particularly antibiotics, reflected a relatively healthy population with minimal to moderate comorbidity burden.Patients with complicated diabetes mellitus showed a consistently increased RD risk in all analyses. However, diagnosis of alcohol abuse showed an increased and non-significant RD risk only in Caucasians, women, and those ≥ 71 years of age. A complete listing of risk estimates for all analyses involving diabetes mellitus and alcohol abuse is provided in Supplementary Material VII.Similar to an earlier study that utilized Health Facts® data for a different outcome, the total number of RD cases was remarkably low except, between 2010 and 2015 . Prior tTo avoid possible confounding of the association between quinolones and RD risk, we excluded all inpatients with current or prior eye diseases, and adjusted for two major risk factors, complicated diabetes mellitus and alcohol abuse. Since the study subjects were inpatients, we used medication filling orders as proxy for medication administration with a high degree of confidence that the medications were consumed by patients while in the hospital.In our study, we selected a nested case–control rather than cohort design since the former offers similar benefits, but with greater computational efficiency than the cohort design –63. The To put our results in context with those of recent major epidemiologic studies that examined the association of quinolones with RD risk, we identified eight original studies , 33–39, A major strength for our study is its use of a major EHR database, which provided a great opportunity for studying large patient populations over a long period of time, thereby supporting meaningful investigation of a rare adverse drug reaction such as RD , 68. WitLimiting our pool of cases and possible controls to those with a medical history of 1 year at a minimum allowed for a better assessment of the health status of the examined study population. Finally, using prescriptions filled for our study population and delivered by nursing staff as proxy for medication administration provided more confidence in patients’ medication compliance compared to medications prescribed on an outpatient basis.Similar to other EHR databases, Health Facts® was primarily created for the purpose of supporting a seamless exchange of patients’ medical information among providers across the care continuum. However, despite all robust data cleaning techniques, EHR databases are subject to data integrity issues such as misclassification of demographics, comorbidities, medications, outcomes, or other clinical care details , 72. AddConsidering the fact that 50–80% of antibiotics are prescribed in physician offices rather than hospitals , 73, recOur study results provided no evidence of an increased class-wide association between quinolones and RD risk. Care should be exercised in interpreting the results of this study due to small number of filled quinolone prescriptions during the 30-day window prior to case ascertainment. Further attention should be directed at quinolone exposure within certain population subgroups such as women, those 56–70 years old, and African Americans. Further studies with additional information on outpatient medication use would be also complement the present findings.Supplementary file1 (PDF 140 KB)Below is the link to the electronic supplementary material.


Remarkably, correlations between gut content metabolic profiles and those of other organs are the most significant. Gut contents are also the only ones to show dynamic correlations during IIR. Additionally, according to targeted metabolomics analysis, several neurotransmitters are considerably altered in the gut during IIR, and displayed noteworthy correlations with remote organs. Likewise, metagenomics analysis (n = 35) confirm the effects of IIR on gut microbiota, and identify key species fundamental to the changes in gut metabolites, particularly neurotransmitters. Our multi-omics results establish key roles of gut contents in IIR induced remote injury and provide clues for future exploration.Intestinal ischemia–reperfusion (IIR) is a life-threatening clinical event with damaging signals whose origin and contents are unclear. Here we observe that IIR significantly affect the metabolic profiles of most organs by unbiased organ-wide metabolic analysis of gut contents, blood, and fifteen organs in rats  injury in rats. Their results provide further insight into how gut contents contribute to widespread injury in IIR patients. It is a result of both surgical and non-surgical approaches such as abdominal aortic aneurysm surgery5, cardiopulmonary bypass5, small bowel transplantation6, acute mesenteric ischemia7, neonatal necrotizing enterocolitis8, trauma6, and septic shock9. The primary clinical characteristic of these diseases is the interruption of blood supply, which causes ischemic impairment10. Paradoxically, restoring of blood flow does not alleviate the symptoms of the injury; on the contrary, it magnifies the damage drastically. Most astonishingly, IIR substantially impacts the integrity and function of remote organs (the non-ischemic organs), and if severe enough, it can clinically result in systemic inflammatory response syndrome and multiple organ dysfunction syndrome4, which account for 30–40% of in-hospital mortality11.Intestinal ischemia-reperfusion (IIR) is a life-threatening clinical event in many diseases that affect infants, children, and adults13, inflammatory cytokines release, oxygen-free radical formation14, complement activation, microvasculature damage, and neutrophil infiltration16. Several research groups have also investigated the roles of gut microbiota in IIR19. Per ref. 17 found that depleting gut commensal bacteria attenuates IIR-induced injury, while ref. 18 established the essential role of commensal bacteria in epithelial restitution after IIR. Collectively, many factors, including Toll-like receptors, oxidative stress and nitric oxide, have been reported to be associated with intestinal bacteria during IIR19. However, a few questions remain to be answered: (1) what are the primary source and contents of the damaging signal(s) to remote organs during and after IIR? (2) what route do these signals take to remote organs? (3) what roles do the signals play after they reach remote organs?In recent years, researchers have advanced several hypotheses on the origin and/or nature of the damaging signals to remote organs during IIR, including intestinal barrier dysfunctionTo answer these questions, we performed a systemic, time-resolved multi-omic analysis of gut contents, blood, bronchoalveolar lavage fluid (BALF) and fifteen organs during IIR using a rat model. Our results support a gut translocation model in which gut contents leaked into peripheral blood because of a compromised gut barrier during IIR and then to remote organs, causing inflammatory responses. Additionally, we found that several neurotransmitter-related gut metabolites changed significantly during IIR, which could influence remote organs through the enteric nervous system. We also profiled the gut microbiota during IIR, and identified a few key species that underly the changes in metabolites and neurotransmitters. In summary, we provide evidence that gut contents, as the major source of IIR, caused damage to remote organs and established their putative routes. Our results warrant further research on the impact of gut-derived metabolites, neurotransmitters, and microbes.n = 29) to understand the impact of IIR on gut contents and remote organs  to explore the taxonomic and functional characterization alteration of the gut microbiome during IIR.To explore the key roles gut contents play in IIR-induced injury, we carried out a series of multi-layer and multi-angle experiments. Our overall experimental design is shown in Fig. ans Fig. b, c. The13, we fed Fluorescein isothiocyanate (FITC)-dextran to rats through gavage and quantified its levels in serum and a few tissues during IIR. FITC-dextran is widely used as a marker of mucosal barrier dysfunction and paracellular transport20. We also quantified the concentrations of D-lactic acid, fatty acid-binding proteins (IFABPs), citrulline and endotoxins in blood during IIR. D-lactic acid is a fermentation product of various gut bacteria. It has been shown to enter the bloodstream when intestinal permeability increased21. IFABPs are small cytosolic water-soluble proteins present in mature enterocytes and reportedly reflect the physiological turnover rate of enterocytes, the increase of which is linked to intestinal epithelial cell damage22. Circulating citrulline, an amino acid not incorporated in proteins is mainly produced by enterocytes and is frequently suggested as a biomarker of remnant small bowel mass and function23. Endotoxins are constituents of the outer membrane of gram-negative bacteria24; systemic endotoxemia is also associated with increased intestinal permeability. These selected substances are representatives of the broad spectrum of gut contents and thus ideal markers for intestinal damage and gut translocation.To confirm previous findings that IIR increases gut permeability by compromising the intestinal barrierp values < 0.05, Wilcoxon test) of most of these substances in the blood and a few of them in several tissues  using Mahalanobis distances and reports p values for the null hypothesis at all internal branches; p values less than 0.05 indicated a statistically significant difference.To provide an unbiased view of body-wide metabolic changes during IIR, we performed global metabolomics profiling using both liquid chromatography-mass spectrometry (LC/TOF-MS) and gas chromatography-mass spectrometry (GC/MS) on blood, gut  contents, BALF and 15 organs including liver, kidney, adrenal glands, thymus, heart, jejunum, ileum, colon, rectum, brain, epididymal fat (EpiFat), lung, lymph, spleen and subcutaneous fat (SubFat) Fig. . To checP < 0.01) and were restored to normal at IR72h (72 h after reperfusion). Colon and brain also belonged to this pattern with a different mode  and identified their corresponding metabolites (see Methods). We identified 132 metabolites in total from the abovementioned nine organs, blood, and cecal contents, including 32 amino acids, peptides, and analogs; 5 benzenoids; 7 bile acids, alcohols, and derivatives; 5 Eicosanoids; 18 lipids and lipid-like molecules; 25 lysophosphatidylcholine or lysophosphatidylethanolamine or phosphatidylcholine or phosphatidylethanolamine; 5 nucleosides, nucleotides, and analogs; 25 organic compounds and others and 10 unsaturated fatty acid  in gut content, blood, and most organs   in most organs , UDP, UDP-N-acetylglucosamine, cytidine diphosphate, citrate, and isocitrate , and N-(omega)-Hydroxyarginine -Hydroxyarginine is an intermediate in the biosynthesis of nitric oxide from l-arginine37. They are both linked to nitric oxide, which is a signaling molecule in the nervous system38. 5-Aminopentanoic acid is a methylene homolog of gamma-aminobutyric acid, an inhibitory neurotransmitter in the human cerebral cortex39, and sphingosine is a sphingolipid metabolite that can exert vital neuron-specific functions, such as the regulation of neurotransmitter release40.The Unrecovered_Up subgroup comprised uric acid, allantoin, L-pipecolic acid, 5-aminopentanoic acid, 3-methylhistidine, histamine, acetylcholine, sphingosine, ine Fig. . Outstan41 and enteric nervous system45. As expected, these markers were drastically altered during IIR .To further explore the alteration of intestinal flora and their associations with gut metabolome, we submitted cecal samples to metagenomic next-generation sequencing, followed by taxonomic analysis using MetaPhlAn248.We identified a total of 111 species in all samples see Fig. . We founp < 0.05 with Kruskal–Wallis test, Supplementary Data Lactobacillus johnsonii and Lactobacillus sp ASF360, reduced significantly, with others, including Escherichia coli and Bacteroides vulgatus, and species in the Enterobacteriaceae and Enterococcaceae families increasing markedly  effect size (LEfSe) analysis to identify differential taxa between time points. Five differential taxa were identified at IR0h compared to Sham -Hydroxyarginine, which is related to nitric oxide, a signaling molecule in the nervous system. Remarkably, metabolomics analysis identified these neurotransmitter-related molecules to be significantly increased. Hence, we inferred that alterations in gut content metabolites could be the result of abnormal gut microbiota metabolism.As expected, the functional analysis of the sequencing data identified significantly more downregulated genes and pathways than upregulated ones at IR0h compared to Sham Fig. e, g. Fur49 56 analysis . The overall correlation pattern between microbial metabolites and gut pathways during reperfusion was distinctive from that during ischemia Fig. . We idenion Fig. . Furtherl-arginine. The corresponding urea cycle-related pathways like CITRULBIO-PWY: l-citrulline biosynthesis were also increased at IIR6h. Sphingosine belongs to lipids, and pathways related to lipids synthesis, like PWY-5138: unsaturated, even-numbered fatty acid and beta-oxidation, widely increased at IIR6h.To further explore the influence of intestinal microflora on metabolites at the biotransformation level, we created a global metabolic map connecting significantly altered metabolites at IIR6h  compared to the Sham and IIR0h groups. Outstandingly, most of these metabolites are neurotransmitters related Fig. , such asIn summary, we revealed that gut contents are critical to IIR-caused remote organ injuries. We performed an integrated multi-omics analysis of gut content during IIR in multi-layer and multi-angle, trying to explore how cecal metabolites and microbes could alter the metabolomes in remote organs. Here we established the routes of gut contents to remote organs, including translocation through compromised gut barrier and influencing the enteric nervous system by neurotransmitters. As IIR-induced remote organs injury is a complex physiological process associated with many factors, systematical and comprehensive explorations are still needed. Our results provide clues for future experiments aiming to illustrate the molecular mechanisms causing the damages. Given that experimental rats are small in size, future efforts are still needed to further explore and validate the study findings.All animal experiments were approved by the Animal Ethics Committee of Huazhong University of science and technology and were performed in accordance with their guidelines. Male Sprague–Dawley rats (220–260 g body weight) in specific pathogen-free status were purchased from Vital River Laboratory Animal Technology Co., Ltd., Beijing, China. Rats were randomly assigned to the Sham or IIR group, maintained under controlled conditions of temperature(21 ± 1 °C) and relative humidity (&55%) on a 12 h light/12 h dark cycle. Animals were fed ad libitum with food and water for 1 week before experiments and were fasted overnight before the day of the experiment.For the IIR group, rats were treated with anesthesia with 20% urethane. A midline laparotomy was performed to expose the superior mesenteric artery and occlusion of the superior mesenteric artery was applied with a noncrushing microvascular clamp. After the 120-minute period of ischemia, the micro clamp was removed, and the blood supply was restored. Sham animals were also subjected to laparotomy, but with no occlusion of the superior mesenteric artery. Samples, including Blood, tissues and cecal contents, were immediately collected for the Sham and IIR group at the ending of ischemia (IR0h) and in the period of reperfusion . On collection, samples were subsequently stored at −80 °C for further analysis.n = 7 in Sham, n = 6 in IIR0h, n = 9 in IIR6h, n = 7 in IIR72h) were sacrificed for global metabolite profiling, and then 35 rats  were used for metagenomic analysis and further validation.In total, 64 rats were used in our experiments and a two-stage approach was performed. First, 29 rats  were determined using a BioTek Epoch microplate spectrophotometer  and Chemray 240 automated biochemical analyzer . All assay plates were run according to the manufacturer’s protocol.The biochemical indexes  relative to a standard curve (range 12.5–2500 ug/ml).Four hours prior to operation, rats received a 20 ml/kg dose of 4 kDa fluorescein isothiocyanate (FITC)‐dextran  by oral gavage. Blood was collected at IIR 6 h by retro-orbital bleeding and stored in a dark and dry place to protect it from light. Samples were centrifuged at 3000×The collected tissues were first fixed and then dehydrated and embedded in melted paraffin wax. The obtained block was then mounted on a microtome and cut into thin slices. The slices were affixed to microscope slides with the wax removed. The tissue slices attached to the slides were rehydrated and then stained. The hematoxylin and eosin staining was performed by the first application of haematoxylin mixed with a metallic salt, then removing excess staining with a rinse in a weak acid solution, followed by building in mildly alkaline water, then counterstaining with eosin. Following the eosin stain, the slide was passed through several changes of alcohol to remove all traces of water, then rinsed in several baths of xylene, which clears the tissue and renders it completely transparent. A thin layer of polystyrene mountant was used, followed by a glass cover slip. Then microscopic image acquisition and analysis were performed.41 and enteric nervous system45. All procedures were performed according to the recommended protocols of Abclonal’s film method.The paraffin sections of the intestinal were immunostained with antibodies nitric oxide synthase Rabbit pAb (# A0312), C-Kit (#A0357), synaptophysin (#A6344), protein gene product 9.5 (#A19101), substance P (#A13550) , which were commonly used molecular markers for neuroendocrine system59. The irregular automated optical inspection function in the software was applied to score and rule out non-target staining. The measurement parameter was integrated optical density. All images obtained from IPP 6.0 were further verified by pathologists. Measurements for three cores per sample were averaged and the mean value of the integrated optical density was considered the final value.The immunostaining level was assessed and analysed using the Image-pro Plus 6.0 (IPP 6.0) softwareCoupling chromatography to mass spectrometry (MS) offers a combination of sensitivity and selectivity for complex mixture analyses and has evolved as a critical and indispensable platform in metabolomics. As each detecting method has its biases, a combination of gas chromatography (GC)-MS and liquid chromatography (LC)-MS data provides a more comprehensive and unbiased metabolite profiling.61.Serum/tissue extracts/cecal contents were first thawed at 4 °C and then mixed with acetonitrile to perform protein precipitation. The supernatant was obtained after two centrifugations  and was further divided into two aliquots. One was used for GCMS analysis after the complex derivatization process, i.e., alkylation and silylation, whereas the other was employed directly for UFLC-IT-TOF/MS (ion trap/time-of-flight hybrid mass spectrometry) analysis60. Mass spectrometry operation parameters were set as follows: positive and negative ion modes were both used. And interface voltage was set at 4.5 and −3.5 kV for each mode, respectively. The mass range was scanned from 100 to 1000 m/z using an accumulation time of 20 ms per spectrum. Nitrogen was used as the nebulizer and drying gas, set at a constant flow rate of 1.5 and 10 L/min, respectively. Metabolites were identified by comparing the formulae, mass-to-charge ratio (m/z), and the MS/MS fragmentation information with our labs’ self-built database and the online database, such as LIPID MAPS (http://www.lipidmaps.org), Human Metabolome Database , and Metlin database (http://metlin.scripps.edu). For further validation, gut content metabolome were reanalyzed using the Agilent 1290 Infinity LC system  coupled to the AB Triple TOF 5600/6600 system  with an Acquity UPLC BEH Amide column .For LC/MS analysis, the Phenomenex Kinetex C18 column was used to perform chromatographic separations. Gradient elution was applied with 0.1% formic acid and acetonitrile at a constant flow rate of 0.4 mL/min. The column temperature was kept at 40 °C and the injection volume was 5 μL. Electrospray ionization (ESI) source in both the positive and negative ion mode was used for mass analysis. The detailed MS instrumental parameters were set as previously describedFor GC/MS analysis, helium was used as the carrier gas and the flow rate was 1 mL/min. The oven temperature was programmed at 70 °C for 2 min and then increased at a rate of 10 °C/min to 320 °C, and held at 320 °C for 2 min. And the total run time was 29 min. The mass spectrometer was operated in electron impact mode (70 eV) at full scan mode from m/z 45 to 600 with a scan time of 0.2 s. The injector split ratio was set to 1:50. Metabolites in GC/MS were identified by comparison of mass spectra and retention time with those in the commercial compound libraries, National Institute of Standards and Technology (NIST). And they were further confirmed by comparison with the reference standards in our lab.Peak deconvolution and alignment for the LC/MS and GC/MS chromatograms were performed using Profiling Solution version 1.1  installed in the instrument. As a result, a matrix containing matched peaks with m/z value, retention time and corresponding intensities was generated and was then exported to an Excel table.Possible sources of instrumental or reagent contamination were excluded by randomly injecting solvent blanks and checking against the blank runs. The so-called 80% rule was used to retain metabolites detectable in at least 80% of subjects. And 30% rule was applied to remove features with higher relative standard deviation (RSD) in quality control (QC) samples. Furthermore, the missing values were filled with half of the minimum value in the dataset. Additionally, the total area normalization was performed and the relative abundances were obtained.LC–MS/MS analysis was performed on an Agilent 1290 Infinity UHPLC coupled to an AB Sciex Qtrap ® 5500 MS/MS using an Acquity UPLC™ BEH Amide column  and acetonitrile (B). The initial gradient condition was 90% B, which was decreased to 40% gradually over 18 min, to 90% after 18.1 min, and then maintained at 90% B from 18.1 to 23 min.The MS system was operated using electrospray ionization (ESI) in negative mode. The optimum conditions were source temperature, 450 °C; ion Source Gas1 (Gas1), 45; Ion Source Gas2 (Gas2), 45; Curtain gas (CUR), 30; ion sapary voltage floating (ISVF), 4500 V. The MRM transitions, retention times, and conditions are shown in Supplementary Data ® DNA Kit  according to the manufacturer’s protocols. The DNA concentration and purity was quantified with TBS-380 and NanoDrop2000, respectively. DNA quality was assessed with the 1% agarose gel electrophoresis system. After final precipitation, the DNA samples were resuspended in TE buffer and stored at −80 °C for further analysis.DNA was extracted from frozen fecal samples using E.Z.N.A.www.illumina.com).DNA was first fragmented to an average size of about 300 bp using Covaris M220 . And Paired-end library was constructed by using the TruSeqTM DNA Sample Prep Kit . Adapters containing the full complement of sequencing primer hybridization sites were ligated to the Blunt-end fragments. Whole-genome shotgun sequencing of fecal samples was carried out on the Illumina HiSeq4000 platform  with HiSeq 3000/4000PE Cluster Kit and HiSeq 3000/4000 SBS Kits  using bowtie2. And those mapped were considered unwanted human reads and were discarded. FastQC was then used for quality control prior to downstream analysis.46 was applied to quantitatively profile the taxonomic composition of the metagenome of all metagenomic samples, whereas HUMANn247 was conducted with the UniRef90 database for functional analysis. The HUMAnN2 algorithm generated pathway abundance, gene-family abundance and pathway coverage. Linear discriminant analysis (LDA) effect size (LEfSe), using a factorial Kruskal–Wallis and LDA test, was applied to identify significant differences in bacterial groups.To identify reads belonging to rats, we first downloaded the reference genome of rat from NCBI. And then, we align the obtained metagenomic sequence reads to the rat reference genome using Bowtie2 (version bowtie2-2.1.0). By doing this, we identified and deleted the reads belonging to rat. MetaPhlAn2Through extensive searching, exploring, and reading literature, we obtained the potential functional role of every bacteria identified. Detailed information about the functions/characteristics of the species searched from the literature is listed in Supplementary Data 62. Here, PCAtoTree28 was applied for improved quantitative analysis in score plots and for better visualization. Employing both nonparametric and parametric hypothesis testing, it can quantitatively describe significant differences between different groups through dendrograms and bootstrapping techniques.For metabolomics data with different metabolic states, it will be difficult to evaluate the similarity or difference between the respective data point clusters in PCA score plots25. Multiblock-PCA can be applied for visualizing the overall tendency of the fusing data. And multiblock-PLS (MBPLS), a kind of regression model, can be used for variable selection using the regression coefficients . These multiblock methods were performed using the ade4 R package.Metabolites detected in LC/MS and GC/MS are different and can complement each other. To get a comprehensive view of the metabolites, it is better to fuse LG/MS and GC/MS datasets of the same samples. Multiblock methods were used here to merge datasets from different platforms by extracting latent variables from each block, which was considered information carriersThe linear discriminant analysis (LDA) effect size (LEfSe) analysis was performed to compare the relative abundance of the different features between groups. LDA score threshold of >2.0 and a 0.05 alpha value for the factorial Kruskal–Wallis test was applied to select different bacteria.p value <0.05 and absolute Log2 fold change (Log2FC) >1. The volcano Plot was used to simultaneously display the statistical significance  versus the magnitude of change (Log2 fold change). We could get a quick visual identification of features with large fold changes that are also statistically significant, which may be the most biologically significant features.A series of strict filtering criteria were applied to select significant different features for gut metabolites, KO and pathway abundance data. The VIP (Variable Importance in Projection) value, representing the importance of selected metabolites in the discriminating OPLS-DA model, was first used to filter variables . Then the dataset was further screened using Wilcoxon test 49, which can combine three data dimensions . Using a so-called leave-one-out analysis, this method can identify species which contributed particularly to the observed linkage between clinical phenotype and metagenomic functional potential. And the identified species was considered a driver species, which may have a great influence on the functions of the microbiome. The detailed analysis framework has been reported as source R code at the accompanying Git repository Microbial driver species analysis was a pipeline referred to the methods explained in literature56, is used for metabolic model-based evaluation of paired microbiome-metabolome datasets to support mechanistic interpretation and hypothesis generation. MIMOSA2 first constructs community metabolic models, and then assesses whether metabolite measurements are consistent with estimated community metabolic potential, followed by identifying specific taxa and reactions that can explain metabolite variation. The MIMOSA2 web application is available at http://elbo-spice.cs.tau.ac.il/shiny/MIMOSA2shiny/.A novel comprehensive framework, the Model-based Integration of Metabolite Observations and Species Abundances 2 (MIMOSA2)26 is an R package dedicated to integrate multivariate “omics biological data. By adopting a biology approach, the toolkit provides a wide range of methods focused on data exploration, dimension reduction and visualization. Among which, the toolkit can provide a supervised framework” analyses 27 to probe relationships between different tissues by identifying a multi-tissue signature composed of highly correlated features across different tissues and which can discriminate the outcome of interest. The packages can be obtained on the website http://mixomics.org.MixOmicshttp://www.r-project.org). Mann–Whitney U-test was used to select different features. P < 0.05 was considered statistically significant.All the data analysis and the drawing of the diagrams were implemented in the R package . For the metagenomic analysis of gut contents, 35 rats were used . And for detection of the bowel barrier damage-related biomarkers and immunohistochemical analysis, three biologically independent animals were used.For the global metabolite profiling, 29 rats were used (Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Supplementary Data 10Supplementary Data 11Supplementary Data 12Supplementary Data 13Supplementary Data 14Supplementary Data 15Supplementary Data 16Supplementary Data 17Supplementary Data 18Supplementary Data 19Supplementary Data 20Supplementary Data 21Supplementary Data 22Supplementary Data 23Supplementary Data 24Reporting Summary