Kazuo Ando

All Publications

• Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions NATURE MACHINE INTELLIGENCE Culos, A., Tsai, A. S., Stanley, N., Becker, M., Ghaemi, M. S., McIlwain, D. R., Fallahzadeh, R., Tanada, A., Nassar, H., Espinosa, C., Xenochristou, M., Ganio, E., Peterson, L., Han, X., Stelzer, I. A., Ando, K., Gaudilliere, D., Phongpreecha, T., Maric, I., Chang, A. L., Shaw, G. M., Stevenson, D. K., Bendall, S., Davis, K. L., Fantl, W., Nolan, G. P., Hastie, T., Tibshirani, R., Angst, M. S., Gaudilliere, B., Aghaeepour, N. 2020

  View details for DOI 10.1038/s42256-020-00232-8

  View details for Web of Science ID 000579336000001

• IMMUNE PROFILING TO PREDICT RECOVERY OUTCOMES AFTER SURGERY Tsai, E. S., Rumer, K., Wong, K., Warrington, B., Shelton, E., Ganio, E., Verdonk, F., Ando, K., Tingle, M., Folk-Tolbert, M., Shankar, K., Shelton, A., Morris, A., Kirilcuk, N., Gurland, B., Kebebew, E., Kin, C., Angst, M. S., Aghaeepour, N., Gaudilliere, B. LIPPINCOTT WILLIAMS & WILKINS. 2020: 66–67

  View details for Web of Science ID 000587668800152

• Multi-Omic, Longitudinal Profile of Third-Trimester Pregnancies Identifies a Molecular Switch That Predicts the Onset of Labor. Stelzer, I., Ghaemi, M., Han, X., Ando, K., Peterson, L., Contrepois, K., Ganio, E., Tsai, A., Tsai, E., Rumer, K., Stanley, N., Fallazadeh, R., Becker, M., Culos, A., Gaudilliere, D., Wong, R., Winn, V., Shaw, G., Stevenson, D., Snyder, M., Angst, M., Aghaeepour, N., Gaudilliere, B. SPRINGER HEIDELBERG. 2020: 89A

  View details for Web of Science ID 000525432600082

• Factors associated with persistent pain after childbirth: a narrative review. British journal of anaesthesia Komatsu, R., Ando, K., Flood, P. D. 2020

  Abstract

  A systematic literature search was performed to identify studies that reported risk factors for persistent pain after childbirth. Many studies have sought to identify risk factors for post-delivery pain in different populations, using different methodologies and different outcome variables. Studies of several different but interrelated post-partum pain syndromes have been conducted. Factors strongly and specifically associated with persistent incisional scar pain after Caesarean delivery include a coexisting persistent pain problem in another part of the body and severe acute postoperative pain. For persistent vaginal and perineal pain, operative vaginal delivery and the magnitude of perineal trauma have been consistently linked. History of pregnancy-related and pre-pregnancy back pain and heavier body weight are robust risk factors for persistent back pain after pregnancy. Unfortunately, limitations, particularly small samples and lack of a priori sample size calculation designed to detect specific effect sizes for risk of persistent pain outcomes, preclude definitive conclusions about many other predictors and the strength of outcome associations. In future studies, assessments of specific phenotypes using a rigorous analysis with appropriate predetermined sample sizes and validated instruments are needed to allow elucidation of stronger and reliable associations. Interventional studies targeting the most robustly associated, modifiable risk factors, such as acute post-partum pain, may lead to solutions for the prevention and treatment of these common problems that impact a large population.

  View details for DOI 10.1016/j.bja.2019.12.037

  View details for PubMedID 31955857

• Multiomic immune clockworks of pregnancy. Seminars in immunopathology Peterson, L. S., Stelzer, I. A., Tsai, A. S., Ghaemi, M. S., Han, X., Ando, K., Winn, V. D., Martinez, N. R., Contrepois, K., Moufarrej, M. N., Quake, S., Relman, D. A., Snyder, M. P., Shaw, G. M., Stevenson, D. K., Wong, R. J., Arck, P., Angst, M. S., Aghaeepour, N., Gaudilliere, B. 2020

  Abstract

  Preterm birth is the leading cause of mortality in children under the age of five worldwide. Despite major efforts, we still lack the ability to accurately predict and effectively prevent preterm birth. While multiple factors contribute to preterm labor, dysregulations of immunological adaptations required for the maintenance of a healthy pregnancy is at its pathophysiological core. Consequently, a precise understanding of these chronologically paced immune adaptations and of the biological pacemakers that synchronize the pregnancy "immune clock" is a critical first step towards identifying deviations that are hallmarks of peterm birth. Here, we will review key elements of the fetal, placental, and maternal pacemakers that program the immune clock of pregnancy. We will then emphasize multiomic studies that enable a more integrated view of pregnancy-related immune adaptations. Such multiomic assessments can strengthen the biological plausibility of immunological findings and increase the power of biological signatures predictive of preterm birth.

  View details for DOI 10.1007/s00281-019-00772-1

  View details for PubMedID 32020337

• Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries. JAMA network open Jehan, F., Sazawal, S., Baqui, A. H., Nisar, M. I., Dhingra, U., Khanam, R., Ilyas, M., Dutta, A., Mitra, D. K., Mehmood, U., Deb, S., Mahmud, A., Hotwani, A., Ali, S. M., Rahman, S., Nizar, A., Ame, S. M., Moin, M. I., Muhammad, S., Chauhan, A., Begum, N., Khan, W., Das, S., Ahmed, S., Hasan, T., Khalid, J., Rizvi, S. J., Juma, M. H., Chowdhury, N. H., Kabir, F., Aftab, F., Quaiyum, A., Manu, A., Yoshida, S., Bahl, R., Rahman, A., Pervin, J., Winston, J., Musonda, P., Stringer, J. S., Litch, J. A., Ghaemi, M. S., Moufarrej, M. N., Contrepois, K., Chen, S., Stelzer, I. A., Stanley, N., Chang, A. L., Hammad, G. B., Wong, R. J., Liu, C., Quaintance, C. C., Culos, A., Espinosa, C., Xenochristou, M., Becker, M., Fallahzadeh, R., Ganio, E., Tsai, A. S., Gaudilliere, D., Tsai, E. S., Han, X., Ando, K., Tingle, M., Maric, I., Wise, P. H., Winn, V. D., Druzin, M. L., Gibbs, R. S., Darmstadt, G. L., Murray, J. C., Shaw, G. M., Stevenson, D. K., Snyder, M. P., Quake, S. R., Angst, M. S., Gaudilliere, B., Aghaeepour, N. 2020; 3 (12): e2029655

  Abstract

  Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies.To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB.This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019.Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites.The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation.Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways.This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB.

  View details for DOI 10.1001/jamanetworkopen.2020.29655

  View details for PubMedID 33337494

• VoPo leverages cellular heterogeneity for predictive modeling of single-cell data. Nature communications Stanley, N., Stelzer, I. A., Tsai, A. S., Fallahzadeh, R., Ganio, E., Becker, M., Phongpreecha, T., Nassar, H., Ghaemi, S., Maric, I., Culos, A., Chang, A. L., Xenochristou, M., Han, X., Espinosa, C., Rumer, K., Peterson, L., Verdonk, F., Gaudilliere, D., Tsai, E., Feyaerts, D., Einhaus, J., Ando, K., Wong, R. J., Obermoser, G., Shaw, G. M., Stevenson, D. K., Angst, M. S., Gaudilliere, B., Aghaeepour, N. 2020; 11 (1): 3738

  Abstract

  High-throughput single-cell analysis technologies produce an abundance of data that is critical for profiling the heterogeneity of cellular systems. We introduce VoPo (https://github.com/stanleyn/VoPo), a machine learning algorithm for predictive modeling and comprehensive visualization of the heterogeneity captured in large single-cell datasets. In three mass cytometry datasets, with the largest measuring hundreds of millions of cells over hundreds of samples, VoPo defines phenotypically and functionally homogeneous cell populations. VoPo further outperforms state-of-the-art machine learning algorithms in classification tasks, and identified immune-correlates of clinically-relevant parameters.

  View details for DOI 10.1038/s41467-020-17569-8

  View details for PubMedID 32719375

• Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions. Nature machine intelligence Culos, A., Tsai, A. S., Stanley, N., Becker, M., Ghaemi, M. S., McIlwain, D. R., Fallahzadeh, R., Tanada, A., Nassar, H., Espinosa, C., Xenochristou, M., Ganio, E., Peterson, L., Han, X., Stelzer, I. A., Ando, K., Gaudilliere, D., Phongpreecha, T., Marić, I., Chang, A. L., Shaw, G. M., Stevenson, D. K., Bendall, S., Davis, K. L., Fantl, W., Nolan, G. P., Hastie, T., Tibshirani, R., Angst, M. S., Gaudilliere, B., Aghaeepour, N. 2020; 2 (10): 619–28

  Abstract

  The dense network of interconnected cellular signalling responses that are quantifiable in peripheral immune cells provides a wealth of actionable immunological insights. Although high-throughput single-cell profiling techniques, including polychromatic flow and mass cytometry, have matured to a point that enables detailed immune profiling of patients in numerous clinical settings, the limited cohort size and high dimensionality of data increase the possibility of false-positive discoveries and model overfitting. We introduce a generalizable machine learning platform, the immunological Elastic-Net (iEN), which incorporates immunological knowledge directly into the predictive models. Importantly, the algorithm maintains the exploratory nature of the high-dimensional dataset, allowing for the inclusion of immune features with strong predictive capabilities even if not consistent with prior knowledge. In three independent studies our method demonstrates improved predictions for clinically relevant outcomes from mass cytometry data generated from whole blood, as well as a large simulated dataset. The iEN is available under an open-source licence.

  View details for DOI 10.1038/s42256-020-00232-8

  View details for PubMedID 33294774

  View details for PubMedCentralID PMC7720904

• Society for Obstetric Anesthesia and Perinatology Consensus Statement: Monitoring Recommendations for Prevention and Detection of Respiratory Depression Associated With Administration of Neuraxial Morphine for Cesarean Delivery Analgesia ANESTHESIA AND ANALGESIA Bauchat, J. R., Weiniger, C. F., Sultan, P., Habib, A. S., Ando, K., Kowalczyk, J. J., Kato, R., George, R. B., Palmer, C. M., Carvalho, B. 2019; 129 (2): 458–74

  View details for DOI 10.1213/ANE.0000000000004195

  View details for Web of Science ID 000475951100036

• Determinants of women's dissatisfaction with anaesthesia care in labour and delivery. Anaesthesia Yurashevich, M., Carvalho, B., Butwick, A. J., Ando, K., Flood, P. D. 2019

  Abstract

  Patient-centred care and factors associated with patient satisfaction with anaesthesia have been widely studied. However, the most important considerations in the setting of obstetric anaesthesia are uncertain. Identification of, and addressing, factors that contribute to patient dissatisfaction may improve quality of care. We sought to identify factors associated with<100% satisfaction with obstetric anaesthesia care. At total of 4297 women treated by anaesthetists provided satisfaction data 24h after vaginal and 48h after caesarean delivery. As 78% of women were 100% satisfied, we studied factors associated with the dichotomous variable, 100% satisfied vs. < 100% satisfied. We evaluated patient characteristics and peripartum factors using multivariable sequential logistic regression. The following factors were strongly associated with maternal dissatisfaction after vaginal delivery: pain intensity during the first stage of labour; pain intensity during the second stage of labour; postpartum pain intensity; delay >15min in providing epidural analgesia and postpartum headache (all p<0.0001). Pruritus (p=0.005) also contributed to dissatisfaction after vaginal delivery, whereas non-Hispanic ethnicity was negatively associated with dissatisfaction (p=0.01). After caesarean delivery, the intensity of postpartum pain (p<0.0001), headache (p=0.001) and pruritus (p=0.001) were linked to dissatisfaction. Hispanic ethnicity also had a negative relationship with dissatisfaction after caesarean delivery (p=0.005). Thus, inadequate or delayed analgesia and treatment-related side-effects are associated with maternal dissatisfaction with obstetric anaesthesia care. Development of protocols to facilitate identification of ineffective analgesia and provide an appropriate balance between efficacy and side-effects, are important goals to optimise maternal satisfaction.

  View details for DOI 10.1111/anae.14756

  View details for PubMedID 31264207

• Postpartum chronic pelvic pain and pelvic girdle pain. Minerva anestesiologica Komatsu, R., Ando, K., Flood, P. D. 2019

  View details for DOI 10.23736/S0375-9393.19.13893-X

  View details for PubMedID 31238646

• Differential Dynamics of the Maternal Immune System in Healthy Pregnancy and Preeclampsia FRONTIERS IN IMMUNOLOGY Han, X., Ghaemi, M. S., Ando, K., Peterson, L. S., Ganio, E. A., Tsai, A. S., Gaudilliere, D. K., Stelzer, I. A., Einhaus, J., Bertrand, B., Stanley, N., Culos, A., Tanada, A., Hedou, J., Tsai, E. S., Fallahzadeh, R., Wong, R. J., Judy, A. E., Winn, V. D., Druzins, M. L., Blumenfeld, Y. J., Hlatky, M. A., Quaintance, C. C., Gibbs, R. S., Carvalho, B., Shaw, G. M., Stevenson, D. K., Angst, M. S., Aghaeepour, N., Gaudilliere, B. 2019; 10

  View details for DOI 10.3389/fimmu.2019.01305

  View details for Web of Science ID 000470999000001

• Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy. Bioinformatics (Oxford, England) Ghaemi, M. S., DiGiulio, D. B., Contrepois, K., Callahan, B., Ngo, T. T., Lee-McMullen, B., Lehallier, B., Robaczewska, A., Mcilwain, D., Rosenberg-Hasson, Y., Wong, R. J., Quaintance, C., Culos, A., Stanley, N., Tanada, A., Tsai, A., Gaudilliere, D., Ganio, E., Han, X., Ando, K., McNeil, L., Tingle, M., Wise, P., Maric, I., Sirota, M., Wyss-Coray, T., Winn, V. D., Druzin, M. L., Gibbs, R., Darmstadt, G. L., Lewis, D. B., Partovi Nia, V., Agard, B., Tibshirani, R., Nolan, G., Snyder, M. P., Relman, D. A., Quake, S. R., Shaw, G. M., Stevenson, D. K., Angst, M. S., Gaudilliere, B., Aghaeepour, N. 2019; 35 (1): 95–103

  Abstract

  Motivation: Multiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia.Results: We performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified.Availability and implementation: Datasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.Supplementary information: Supplementary data are available at Bioinformatics online.

  View details for PubMedID 30561547

• Systemic Immunologic Consequences of Chronic Periodontitis. Journal of dental research Gaudilliere, D. K., Culos, A., Djebali, K., Tsai, A. S., Ganio, E. A., Choi, W. M., Han, X., Maghaireh, A., Choisy, B., Baca, Q., Einhaus, J. F., Hedou, J. J., Bertrand, B., Ando, K., Fallahzadeh, R., Ghaemi, M. S., Okada, R., Stanley, N., Tanada, A., Tingle, M., Alpagot, T., Helms, J. A., Angst, M. S., Aghaeepour, N., Gaudilliere, B. 2019: 22034519857714

  Abstract

  Chronic periodontitis (ChP) is a prevalent inflammatory disease affecting 46% of the US population. ChP produces a profound local inflammatory response to dysbiotic oral microbiota that leads to destruction of alveolar bone and tooth loss. ChP is also associated with systemic illnesses, including cardiovascular diseases, malignancies, and adverse pregnancy outcomes. However, the mechanisms underlying these adverse health outcomes are poorly understood. In this prospective cohort study, we used a highly multiplex mass cytometry immunoassay to perform an in-depth analysis of the systemic consequences of ChP in patients before (n = 28) and after (n = 16) periodontal treatment. A high-dimensional analysis of intracellular signaling networks revealed immune system-wide dysfunctions differentiating patients with ChP from healthy controls. Notably, we observed exaggerated proinflammatory responses to Porphyromonas gingivalis-derived lipopolysaccharide in circulating neutrophils and monocytes from patients with ChP. Simultaneously, natural killer cell responses to inflammatory cytokines were attenuated. Importantly, the immune alterations associated with ChP were no longer detectable 3 wk after periodontal treatment. Our findings demarcate systemic and cell-specific immune dysfunctions in patients with ChP, which can be temporarily reversed by the local treatment of ChP. Future studies in larger cohorts are needed to test the boundaries of generalizability of our results.

  View details for DOI 10.1177/0022034519857714

  View details for PubMedID 31226001

• ASSESSMENT OF MATERNAL PERIPHERAL IMMUNE SYSTEM BY MASS CYTOMETRY TO PREDICT THE ONSET OF LABOR Ando, K., Han, X., Ghaemi, S., Angst, M., Carvalho, B., Aghaeepour, N., Gaudilliere, B. LIPPINCOTT WILLIAMS & WILKINS. 2018: 403

  View details for Web of Science ID 000460106500230

• Mass Cytometry and Proteomic Based Prediction of the Onset of Labor. Ando, K., Han, X., Ghaemi, S., Tsai, A., Ganio, E., Gaudilliere, D., Culos, T., Shaw, G., Wong, R., Stevenson, D., Carvalho, B., Tingle, M., Angst, M., Aghaeepor, N., Gaudilliere, B., Stanford March Dimes Prematurity SAGE PUBLICATIONS INC. 2018: 153A

  View details for Web of Science ID 000429928200292

• Centrally administered isoproterenol induces sympathetic outflow via brain prostaglandin E-2-mediated mechanisms in rats AUTONOMIC NEUROSCIENCE-BASIC & CLINICAL Ando, K., Kondo, F., Yamaguchi, N., Tachi, M., Fukayama, M., Yoshikawa, K., Gosho, M., Fujiwara, Y., Okada, S. 2015; 189: 1–7

  Abstract

  Brain β-adrenoceptor stimulation can induce elevations of plasma levels of noradrenaline. However, there have been no detailed studies related to signaling pathways downstream of β-adrenoceptors responsible for central sympathetic outflow. In the present study, we pharmacologically examined the possibility that centrally administered isoproterenol can induce elevations of plasma noradrenaline levels in a brain prostaglandin-dependent manner. In addition, we also examined whether or not intracerebroventricular administration of isoproterenol could release endogenously synthesized prostaglandin (PG) E2 in the hypothalamic paraventricular nucleus (PVN) by using the brain microdialysis technique combined with liquid chromatography-ion trap tandem mass spectrometry (LC-ITMS(n)). Under urethane anesthesia, a femoral venous line was inserted for infusion of saline and a femoral arterial line was inserted for collecting blood samples. Next, animals were placed in a stereotaxic apparatus for application of test agents. Catecholamines in the plasma were extracted by alumina absorption and were assayed by high-performance liquid chromatography with electrochemical detection. Quantification of PGE2 in rat PVN microdialysates was performed by the LC-ITMS(n) method. We demonstrated that centrally administered isoproterenol-induced elevations of plasma noradrenaline could be mediated via activation of β-adrenoceptors and the downstream phospholipase A2-cyclooxygenase pathway. Furthermore, PGE2 in the PVN and the PGE2 receptor EP3 subtype appear to play an important role in the process. Our results suggest that central isoproterenol-induced sympathetic outflow is mediated via brain PGE2 in a PGE2 receptor EP3 subtype-dependent manner.

  View details for PubMedID 25549851

• Particulate matter in bicarbonate Ringer’s solution Experimental and clinical cardiology. Ando, K., Akahori, T., Nakamura, E., Fujiwara, Y., Kinoshita, H. 2014: 139-142
• Right ventricular perforation due to a stabilizing bar installed for the Nuss procedure MINERVA ANESTESIOLOGICA Sakakibara, K., Kinoshita, H., Ando, K., Yasuda, Y., Mori, Y., Fujiwara, Y. 2013; 79 (7): 820–21

  View details for Web of Science ID 000330327500018

  View details for PubMedID 23419344

• Role of naofen in apoptosis of hepatocytes induced by lipopolysaccharide through mitochondrial signaling in rats HEPATOLOGY RESEARCH Fan, J., Feng, G., Huang, L., Tsunekawa, K., Honda, T., Katano, Y., Hirooka, Y., Goto, H., Kandatsu, N., Ando, K., Fujiwara, Y., Koide, T., Okada, S., Ishikawa, N. 2012; 42 (7): 696–705

  Abstract

    Lipopolysaccharide (LPS) causes apoptosis of hepatocytes, which is probably mediated by inflammatory substances released from Kupffer cells (KCs). Recently, we have reported that naofen, a newly found intracellular WD40-repeat protein, has a role in inducing the apoptosis in HEK293 cells. Hence, the present study was undertaken to investigate a role of naofen in the LPS-induced apoptosis of rat hepatocytes.  Rats were treated with i.v. injections of LPS, and livers were extirpated to evaluate expression of naofen and apoptosis. In in vitro experiments, hepatocytes and KCs were separately isolated from rat livers. The incubation medium for KCs treated with LPS (KC-CM) was used for hepatocyte culture.  Intravenous injections of LPS enhanced the expression of naofen in the livers. Livers showed terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL)-positive staining, and elevated caspase-3 activity. In isolated KCs or hepatocytes, LPS hardly affected naofen expression and caspase-3 activity, whereas incubation of hepatocytes with KC-CM enhanced both naofen expression and caspase-3 activation. Transfection of hepatocyte with naofen siRNA prevented such effects of KC-CM, and clearly eliminated KC-CM-induced reduction of Bcl-2 and Bcl-xL. In contrast, overexpression of naofen in hepatocytes downregulated Bcl-2 and Bcl-xL, released cytochrome c from mitochondria, and activated caspase-3.  These results indicate that LPS may induce the hepatic apoptosis in association with enhanced naofen expression, and that naofen may mediate the activation of caspase-3 through downregulating the Bcl-2 and Bcl-xL expression, and releasing cytochrome c from mitochondria to cytoplasm.

  View details for PubMedID 22409254