Multi-cohort analysis of host immune response identifies conserved protective and detrimental modules associated with severity across viruses.

Viral infections induce a conserved host response distinct from bacterial infections. We hypothesized that the conserved response is associated with disease severity and is distinct between patients with different outcomes. To test this, we integrated 4,780 blood transcriptome profiles from patients aged 0 to 90 years infected with one of 16 viruses, including SARS-CoV-2, Ebola, chikungunya, and influenza, across 34 cohorts from 18 countries, and single-cell RNA sequencing profiles of 702,970 immune cells from 289 samples across three cohorts. Severe viral infection was associated with increased hematopoiesis, myelopoiesis, and myeloid-derived suppressor cells. We identified protective and detrimental gene modules that defined distinct trajectories associated with mild versus severe outcomes. The interferon response was decoupled from the protective host response in patients with severe outcomes. These findings were consistent, irrespective of age and virus, and provide insights to accelerate the development of diagnostics and host-directed therapies to improve global pandemic preparedness.

Small and Micro-Water Quality Monitoring Based on the Integration of a Full-Space Real 3D Model and IoT.

In order to address the challenges of small and micro-water pollution in parks and the low level of 3D visualization of water quality monitoring systems, this research paper proposes a novel wireless remote water quality monitoring system that combines the Internet of Things (IoT) and a 3D model of reality. To begin with, the construction of a comprehensive 3D model relies on various technologies, including unmanned aerial vehicle (UAV) tilt photography, 3D laser scanning, unmanned ship measurement, and close-range photogrammetry. These techniques are utilized to capture the park's geographical terrain, natural resources, and ecological environment, which are then integrated into the three-dimensional model. Secondly, GNSS positioning, multi-source water quality sensors, NB-IoT wireless communication, and video surveillance are combined with IoT technologies to enable wireless remote real-time monitoring of small and micro-water bodies. Finally, a high-precision underwater, indoor, and outdoor full-space real-scene three-dimensional visual water quality monitoring system integrated with IoT is constructed. The integrated system significantly reduces water pollution in small and micro-water bodies and optimizes the water quality monitoring system.

Validation of Inflammopathic, Adaptive, and Coagulopathic Sepsis Endotypes in Coronavirus Disease 2019.

OBJECTIVES: Complex critical syndromes like sepsis and coronavirus disease 2019 may be composed of underling "endotypes," which may respond differently to treatment. The aim of this study was to test whether a previously defined bacterial sepsis endotypes classifier recapitulates the same clinical and immunological endotypes in coronavirus disease 2019. DESIGN: Prospective single-center observational cohort study. SETTING: Patients were enrolled in Athens, Greece, and blood was shipped to Inflammatix (Burlingame, CA) for analysis. PATIENTS: Adult patients within 24 hours of hospital admission with coronavirus disease 2019 confirmed by polymerase chain reaction and chest radiography. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We studied 97 patients with coronavirus disease 2019, of which 50 went on to severe respiratory failure (SRF) and 16 died. We applied a previously defined 33-messenger RNA classifier to assign endotype (Inflammopathic, Adaptive, or Coagulopathic) to each patient. We tested endotype status against other clinical parameters including laboratory values, severity scores, and outcomes. Patients were assigned as Inflammopathic (29%), Adaptive (44%), or Coagulopathic (27%), similar to our prior study in bacterial sepsis. Adaptive patients had lower rates of SRF and no deaths. Coagulopathic and Inflammopathic endotypes had 42% and 18% mortality rates, respectively. The Coagulopathic group showed highest d-dimers, and the Inflammopathic group showed highest C-reactive protein and interleukin-6 levels. CONCLUSIONS: Our predefined 33-messenger RNA endotypes classifier recapitulated immune phenotypes in viral sepsis (coronavirus disease 2019) despite its prior training and validation only in bacterial sepsis. Further work should focus on continued validation of the endotypes and their interaction with immunomodulatory therapy.

Cascaded Fabry-Perot interferometer-regenerated fiber Bragg grating structure for temperature-strain measurement under extreme temperature conditions.

We demonstrated an optical fiber sensor based on a cascaded fiber Fabry-Perot interferometer (FPI)-regenerated fiber Bragg grating (RFBG) for simultaneous measurement of temperature and strain under high temperature environments. The FPI is manufactured from a ∼74 µm long hollow core silica tube (HCST) sandwiched between two single mode fibers (SMFs). The RFBG is inscribed in one of the SMF arms which is embedded inside an alundum tube, making it insensitive to the applied strain on the entire fiber sensor, just in case the temperature and strain recovery process are described using the strain-free RFBG instead of a characteristic due-parameter matrix. This feature is intended for thermal compensation for the FPI structure that is sensitive to both temperature and strain. In the characterization tests, the proposed device has exhibited a temperature sensitivity ∼ 18.01 pm/°C in the range of 100 °C - 1000 °C and excellent linear response to strain in the range of 300 °C - 1000 °C. The measured strain sensitivity is as high as ∼ 2.17 pm/µÉ› for a detection range from 0 µÉ› to 450 µÉ› at 800 °C, which is ∼ 1.5 times that of a FPI-RFBG without the alundum tube.

Nonclinical cardiovascular safety evaluation of romosozumab, an inhibitor of sclerostin for the treatment of osteoporosis in postmenopausal women at high risk of fracture.

Romosozumab (EVENITY™ [romosozumab-aqqg in the US]) is a humanized monoclonal antibody that inhibits sclerostin and has been approved in several countries for the treatment of osteoporosis in postmenopausal women at high risk of fracture. Sclerostin is expressed in bone and aortic vascular smooth muscle (AVSM). Its function in AVSM is unclear but it has been proposed to inhibit vascular calcification, atheroprogression, and inflammation. An increased incidence of positively adjudicated serious cardiovascular adverse events driven by an increase in myocardial infarction and stroke was observed in romosozumab-treated subjects in a clinical trial comparing alendronate with romosozumab (ARCH; NCT01631214) but not in a placebo-controlled trial (FRAME; NCT01575834). To investigate the effects of sclerostin inhibition with sclerostin antibody on the cardiovascular system, a comprehensive nonclinical toxicology package with additional cardiovascular studies was conducted. Although pharmacodynamic effects were observed in the bone, there were no functional, morphological, or transcriptional effects on the cardiovascular system in animal models in the presence or absence of atherosclerosis. These nonclinical studies did not identify evidence that proves the association between sclerostin inhibition and adverse cardiovascular function, increased cardiovascular calcification, and atheroprogression.

Dose-related differences in the pharmacodynamic and toxicologic response to a novel hyperglycosylated analog of recombinant human erythropoietin in Sprague-Dawley rats with similarly high hematocrit.

We recently reported results that erythropoiesis-stimulating agent (ESA)-related thrombotic toxicities in preclinical species were not solely dependent on a high hematocrit (HCT) but also associated with increased ESA dose level, dose frequency, and dosing duration. In this article, we conclude that sequelae of an increased magnitude of ESA-stimulated erythropoiesis potentially contributed to thrombosis in the highest ESA dose groups. The results were obtained from two investigative studies we conducted in Sprague-Dawley rats administered a low (no thrombotic toxicities) or high (with thrombotic toxicities) dose level of a hyperglycosylated analog of recombinant human erythropoietin (AMG 114), 3 times weekly for up to 9 days or for 1 month. Despite similarly increased HCT at both dose levels, animals in the high-dose group had an increased magnitude of erythropoiesis measured by spleen weights, splenic erythropoiesis, and circulating reticulocytes. Resulting prothrombotic risk factors identified predominantly or uniquely in the high-dose group were higher numbers of immature reticulocytes and nucleated red blood cells in circulation, severe functional iron deficiency, and increased intravascular destruction of iron-deficient reticulocyte/red blood cells. No thrombotic events were detected in rats dosed up to 9 days suggesting a sustained high HCT is a requisite cofactor for development of ESA-related thrombotic toxicities.

Cytokines associated with increased erythropoiesis in Sprague-Dawley rats administered a novel hyperglycosylated analog of recombinant human erythropoietin.

We previously reported an increased incidence of thrombotic toxicities in Sprague-Dawley rats administered the highest dose level of a hyperglycosylated analog of recombinant human erythropoietin (AMG 114) for 1 month as not solely dependent on high hematocrit (HCT). Thereafter, we identified increased erythropoiesis as a prothrombotic risk factor increased in the AMG 114 high-dose group with thrombotic toxicities, compared to a low-dose group with no toxicities but similar HCT. Here, we identified pleiotropic cytokines as prothrombotic factors associated with AMG 114 dose level. Before a high HCT was achieved, rats in the AMG 114 high, but not the low-dose group, had imbalanced hemostasis (increased von Willebrand factor and prothrombin time, decreased antithrombin III) coexistent with cytokines implicated in thrombosis: monocyte chemotactic protein 1 (MCP-1), MCP-3, tissue inhibitor of metalloproteinases 1, macrophage inhibitory protein-2, oncostatin M, T-cell-specific protein, stem cell factor, vascular endothelial growth factor, and interleukin-11. While no unique pathway to erythropoiesis stimulating agent-related thrombosis was identified, cytokines associated with increased erythropoiesis contributed to a prothrombotic intravascular environment in the AMG 114 high-dose group, but not in lower dose groups with a similar high HCT.

Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

Common inflammatome gene signatures as well as disease-specific signatures were identified by analyzing 12 expression profiling data sets derived from 9 different tissues isolated from 11 rodent inflammatory disease models. The inflammatome signature significantly overlaps with known drug targets and co-expressed gene modules linked to metabolic disorders and cancer. A large proportion of genes in this signature are tightly connected in tissue-specific Bayesian networks (BNs) built from multiple independent mouse and human cohorts. Both the inflammatome signature and the corresponding consensus BNs are highly enriched for immune response-related genes supported as causal for adiposity, adipokine, diabetes, aortic lesion, bone, muscle, and cholesterol traits, suggesting the causal nature of the inflammatome for a variety of diseases. Integration of this inflammatome signature with the BNs uncovered 151 key drivers that appeared to be more biologically important than the non-drivers in terms of their impact on disease phenotypes. The identification of this inflammatome signature, its network architecture, and key drivers not only highlights the shared etiology but also pinpoints potential targets for intervention of various common diseases.

A machine learning classifier using 33 host immune response mRNAs accurately distinguishes viral and non-viral acute respiratory illnesses in nasal swab samples.

BACKGROUND: Viral acute respiratory illnesses (viral ARIs) contribute significantly to human morbidity and mortality worldwide, but their successful treatment requires timely diagnosis of viral etiology, which is complicated by overlap in clinical presentation with the non-viral ARIs. Multiple pandemics in the twenty-first century to date have further highlighted the unmet need for effective monitoring of clinically relevant emerging viruses. Recent studies have identified conserved host response to viral infections in the blood. METHODS: We hypothesize that a similarly conserved host response in nasal samples can be utilized for diagnosis and to rule out viral infection in symptomatic patients when current diagnostic tests are negative. Using a multi-cohort analysis framework, we analyzed 1555 nasal samples across 10 independent cohorts dividing them into training and validation. RESULTS: Using six of the datasets for training, we identified 119 genes that are consistently differentially expressed in viral ARI patients (N = 236) compared to healthy controls (N = 146) and further down-selected 33 genes for classifier development. The resulting locked logistic regression-based classifier using the 33-mRNAs had AUC of 0.94 and 0.89 in the six training and four validation datasets, respectively. Furthermore, we found that although trained on healthy controls only, in the four validation datasets, the 33-mRNA classifier distinguished viral ARI from both healthy or non-viral ARI samples with > 80% specificity and sensitivity, irrespective of age, viral type, and viral load. Single-cell RNA-sequencing data showed that the 33-mRNA signature is dominated by macrophages and neutrophils in nasal samples. CONCLUSION: This proof-of-concept signature has potential to be adapted as a clinical point-of-care test ('RespVerity') to improve the diagnosis of viral ARIs.

A robust gene expression signature for NASH in liver expression data.

Non-Alcoholic Fatty Liver Disease (NAFLD) is a progressive liver disease that affects up to 30% of worldwide population, of which up to 25% progress to Non-Alcoholic SteatoHepatitis (NASH), a severe form of the disease that involves inflammation and predisposes the patient to liver cirrhosis. Despite its epidemic proportions, there is no reliable diagnostics that generalizes to global patient population for distinguishing NASH from NAFLD. We performed a comprehensive multicohort analysis of publicly available transcriptome data of liver biopsies from Healthy Controls (HC), NAFLD and NASH patients. Altogether we analyzed 812 samples from 12 different datasets across 7 countries, encompassing real world patient heterogeneity. We used 7 datasets for discovery and 5 datasets were held-out for independent validation. Altogether we identified 130 genes significantly differentially expressed in NASH versus a mixed group of NAFLD and HC. We show that our signature is not driven by one particular group (NAFLD or HC) and reflects true biological signal. Using a forward search we were able to downselect to a parsimonious set of 19 mRNA signature with mean AUROC of 0.98 in discovery and 0.79 in independent validation. Methods for consistent diagnosis of NASH relative to NAFLD are urgently needed. We showed that gene expression data combined with advanced statistical methodology holds the potential to serve basis for development of such diagnostic tests for the unmet clinical need.

Analyzing Influencing Factors of Transfer Passenger Flow of Urban Rail Transit: A New Approach Based on Nested Logit Model Considering Transfer Choices.

With the continuous improvement of the operation line network of urban rail transit, analyzing influencing factors of transfer passenger flow of urban rail transit is critical to improve the transfer demand analysis of urban rail transit. Using data collected from questionnaires, transfer passenger flow surveys and smart cards, this study proposes an approach base on nested logit passenger flow assignment model considering transfer choice behaviours of passengers. The transfer passenger flow at seven transfer stations in Nanjing is obtained. Subsequently, this study investigates the potential influencing factors of transfer passenger flow, including the node degree, geographic location (located in the city center, urban fringe, suburbs or suburban fringe), economic location (distance from the city center) and transportation locations (if it is close to a transportation hub or in combination with the hub) of rail transit transfer stations. The results indicate that a positive correlation between the transfer passenger flow and the node degrees of transfer stations. However, the relationship between transfer passenger flow and the economic, geographic, and transportation locations of transfer stations is not clear. The finding have reference value for the network design of rail transit transfer stations and transfer facilities, and provide reference for the analysis of passenger flow under network operation.

A Multi-mRNA Prognostic Signature for Anti-TNFα Therapy Response in Patients with Inflammatory Bowel Disease.

BACKGROUND: Anti-TNF-alpha (anti-TNFα) therapies have transformed the care and management of inflammatory bowel disease (IBD). However, they are expensive and ineffective in greater than 50% of patients, and they increase the risk of infections, liver issues, arthritis, and lymphoma. With 1.6 million Americans suffering from IBD and global prevalence on the rise, there is a critical unmet need in the use of anti-TNFα therapies: a test for the likelihood of therapy response. Here, as a proof-of-concept, we present a multi-mRNA signature for predicting response to anti-TNFα treatment to improve the efficacy and cost-to-benefit ratio of these biologics. METHODS: We surveyed public data repositories and curated four transcriptomic datasets (n = 136) from colonic and ileal mucosal biopsies of IBD patients (pretreatment) who were subjected to anti-TNFα therapy and subsequently adjudicated for response. We applied a multicohort analysis with a leave-one-study-out (LOSO) approach, MetaIntegrator, to identify significant differentially expressed (DE) genes between responders and non-responders and then used a greedy forward search to identify a parsimonious gene signature. We then calculated an anti-TNFα response (ATR) score based on this parsimonious gene signature to predict responder status and assessed discriminatory performance via an area-under-receiver operating-characteristic curve (AUROC). RESULTS: We identified 324 significant DE genes between responders and non-responders. The greedy forward search yielded seven genes that robustly distinguish anti-TNFα responders from non-responders, with an AUROC of 0.88 (95% CI: 0.70-1). The Youden index yielded a mean sensitivity of 91%, mean specificity of 76%, and mean accuracy of 86%. CONCLUSIONS: Our findings suggest that there is a robust transcriptomic signature for predicting anti-TNFα response in mucosal biopsies from IBD patients prior to treatment initiation. This seven-gene signature should be further investigated for its potential to be translated into a predictive test for clinical use.

The Optimization and Biological Significance of a 29-Host-Immune-mRNA Panel for the Diagnosis of Acute Infections and Sepsis.

In response to the unmet need for timely accurate diagnosis and prognosis of acute infections and sepsis, host-immune-response-based tests are being developed to help clinicians make more informed decisions including prescribing antimicrobials, ordering additional diagnostics, and assigning level of care. One such test (InSep™, Inflammatix, Inc.) uses a 29-mRNA panel to determine the likelihood of bacterial infection, the separate likelihood of viral infection, and the risk of physiologic decompensation (severity of illness). The test, being implemented in a rapid point-of-care platform with a turnaround time of 30 min, enables accurate and rapid diagnostic use at the point of impact. In this report, we provide details on how the 29-biomarker signature was chosen and optimized, together with its molecular, immunological, and medical significance to better understand the pathophysiological relevance of altered gene expression in disease. We synthesize key results obtained from gene-level functional annotations, geneset-level enrichment analysis, pathway-level analysis, and gene-network-level upstream regulator analysis. Emerging findings are summarized as hallmarks on immune cell interaction, inflammatory mediators, cellular metabolism and homeostasis, immune receptors, intracellular signaling and antiviral response; and converging themes on neutrophil degranulation and activation involved in immune response, interferon, and other signaling pathways.

Transcriptomic similarities and differences in host response between SARS-CoV-2 and other viral infections.

The pandemic 2019 novel coronavirus disease (COVID-19) shares certain clinical characteristics with other acute viral infections. We studied the whole-blood transcriptomic host response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using RNAseq from 24 healthy controls and 62 prospectively enrolled patients with COVID-19. We then compared these data to non-COVID-19 viral infections, curated from 23 independent studies profiling 1,855 blood samples covering six viruses (influenza, respiratory syncytial virus (RSV), human rhinovirus (HRV), severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1), Ebola, dengue). We show gene expression changes in COVID-19 versus non-COVID-19 viral infections are highly correlated (r = 0.74, p < 0.001). However, we also found 416 genes specific to COVID-19. Inspection of top genes revealed dynamic immune evasion and counter host responses specific to COVID-19. Statistical deconvolution of cell proportions maps many cell type proportions concordantly shifting. Discordantly increased in COVID-19 were CD56bright natural killer cells and M2 macrophages. The concordant and discordant responses mapped out here provide a window to explore the pathophysiology of the host response to SARS-CoV-2.

Universal Toxicity Gene Signatures for Early Identification of Drug-Induced Tissue Injuries in Rats.

A new safety testing paradigm that relies on gene expression biomarker panels was developed to easily and quickly identify drug-induced injuries across tissues in rats prior to drug candidate selection. Here, we describe the development, qualification, and implementation of gene expression signatures that diagnose tissue degeneration/necrosis for use in early rat safety studies. Approximately 400 differentially expressed genes were first identified that were consistently regulated across 4 prioritized tissues (liver, kidney, heart, and skeletal muscle), following injuries induced by known toxicants. Hundred of these "universal" genes were chosen for quantitative PCR, and the most consistent and robustly responding transcripts selected, resulting in a final 22-gene set from which unique sets of 12 genes were chosen as optimal for each tissue. The approach was extended across 4 additional tissues (pancreas, gastrointestinal tract, bladder, and testes) where toxicities are less common. Mathematical algorithms were generated to convert each tissue's 12-gene expression values to a single metric, scaled between 0 and 1, and a positive threshold set. For liver, kidney, heart, and skeletal muscle, this was established using a training set of 22 compounds and performance determined by testing a set of approximately 100 additional compounds, resulting in 74%-94% sensitivity and 94%-100% specificity for liver, kidney, and skeletal muscle, and 54%-62% sensitivity and 95%-98% specificity for heart. Similar performance was observed across a set of 15 studies for pancreas, gastrointestinal tract, bladder, and testes. Bundled together, we have incorporated these tissue signatures into a 4-day rat study, providing a rapid assessment of commonly seen compound liabilities to guide selection of lead candidates without the necessity to perform time-consuming histopathologic analyses.

A compound attributes-based predictive model for drug induced liver injury in humans.

Drug induced liver injury (DILI) is one of the key safety concerns in drug development. To assess the likelihood of drug candidates with potential adverse reactions of liver, we propose a compound attributes-based approach to predicting hepatobiliary disorders that are routinely reported to US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Specifically, we developed a support vector machine (SVM) model with recursive feature extraction, based on physicochemical and structural properties of compounds as model input. Cross validation demonstrates that the predictive model has a robust performance with averaged 70% of both sensitivity and specificity over 500 trials. An independent validation was performed on public benchmark drugs and the results suggest potential utility of our model for identifying safety alerts. This in silico approach, upon further validation, would ultimately be implemented, together with other in vitro safety assays, for screening compounds early in drug development.

The Effect of Commuting Time on Job Stress in Obese Men With Different Exercise Frequency in China.

Previous studies have mainly focused on the independent impact of commuting time, exercise, and stress on people. There are few studies regarding the impact of the combined effect of multiple factors on special populations such as obese people. As obesity has become increasingly widespread in China, we studied the impact of commuting time on work stress on Chinese obese men (who exercise regularly vs. who exercise irregularly). We performed a secondary retrospective analysis of the cross-sectional data from the 2014 China Labor Force Dynamics Survey. We found that long commute times and less exercise have a positive effect on the increase in stress, but the effect is less evident for people who exercise regularly. Commuters traveling on foot are more stressed than those traveling by car. This study also found that commuting time had a significant impact on the perceived work stress of obese men who exercised irregularly. But the relationship between commuting time and work stress was different among groups with different commuting styles. For obese men who commuted on foot or motorcycle, commuting time had a significant impact on their job stress. However, for obese men who commuted by bicycle, bus, or car, commuting time had no significant effect on job stress. Additionally, active and passive commuting have different effects on stress. Active commuters tend to be more stressed, while passive commuters do not show a significant impact.

Biomarkers of genome instability in normal mammalian genomes following drug-induced replication stress.

Genome instability is a hallmark of most human cancers and is exacerbated following replication stress. However, the effects that drugs/xenobiotics have in promoting genome instability including chromosomal structural rearrangements in normal cells are not currently assessed in the genetic toxicology battery. Here, we show that drug-induced replication stress leads to increased genome instability in vitro using proliferating primary human cells as well as in vivo in rat bone marrow (BM) and duodenum (DD). p53-binding protein 1 (53BP1, biomarker of DNA damage repair) nuclear bodies were increased in a dose-dependent manner in normal proliferating human mammary epithelial fibroblasts following treatment with compounds traditionally classified as either genotoxic (hydralazine) and nongenotoxic (low-dose aphidicolin, duvelisib, idelalisib, and amiodarone). Comparatively, no increases in 53BP1 nuclear bodies were observed in nonproliferating cells. Negative control compounds (mannitol, alosteron, diclofenac, and zonisamide) not associated with cancer risk did not induce 53BP1 nuclear bodies in any cell type. Finally, we studied the in vivo genomic consequences of drug-induced replication stress in rats treated with 10 mg/kg of cyclophosphamide for up to 14 days followed by polymerase chain reaction-free whole genome sequencing (30X coverage) of BM and DD cells. Cyclophosphamide induced chromosomal structural rearrangements at an average of 90 genes, including 40 interchromosomal/intrachromosomal translocations, within 2 days of treatment. Collectively, these data demonstrate that this drug-induced genome instability test (DiGIT) can reveal potential adverse effects of drugs not otherwise informed by standard genetic toxicology testing batteries. These efforts are aligned with the food and drug administration's (FDA's) predictive toxicology roadmap initiative.

Exploring the Relationship between Walking and Emotional Health in China.

Walking has a positive impact on people's emotional health. However, in the case of serious air pollution, it is controversial whether walking exercise can still improve individuals' emotional health. Using data from the 2014 wave of the China Labor-Force Dynamics Survey, this study explored the relationship between walking and emotional health with different levels of environmental pollution. The results indicated that respondents who took regular walks had better emotional health than those who did not walk regularly. For those whose main mode of physical exercise was walking, the average number of walks per week was significantly and positively correlated with their emotional health; however, the average duration of the walk had no significant impact on their emotional health. Moreover, for those whose main mode of physical exercise was walking and who lived in neighborhoods with a polluted environment, regular walking still had a positive impact on their emotional health. This suggests that even if environmental pollution is serious, walking still plays an important role in regulating individuals' mental health. We propose that in order to promote the emotional health of residents, it is necessary to create more public spaces for outdoor activities and simultaneously increase efforts to control environmental pollution.

Tissue distribution of naringin and derived metabolites in rats after a single oral administration.

Naringin has been documented to possess multiple pharmacological activities. Reported pharmacokinetic studies revealed that oral bioavailability of naringin was low, in contrast to its significant pharmacological effects. The in vivo distribution of naringin and derived metabolites might partly explain this discrepancy. In this study, an ultra-fast liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry system (UFLC-Q-TOF-MS/MS) was used for profiling the distribution of naringin and its metabolites in rat plasma and fourteen tissues after oral administration. Naringin was widely distributed and its concentrations in certain tissues were much higher than that in plasma, especially in trachea and lung. Moreover, a total of 23 flavonoid metabolites and 15 phenolic catabolites were screened. Naringenin glucuronides were principal metabolites in plasma, while free naringenin and naringenin-7-O-sulfate were the major molecular forms in most tissues. Meanwhile, phenolic catabolites derived from naringin were found to be abundant in liver and kidney. These pharmacokinetic results would be useful to explain the pharmacodynamics of naringin.