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Sero-surveillance can monitor and project disease burden and risk. However, SARS-CoV-2 antibody test results can produce false positive results, limiting their efficacy as a sero-surveillance tool. False positive SARS-CoV-2 antibody results are associated with malaria exposure, and understanding this association is essential to interpret sero-surveillance results from malaria-endemic countries. Here, pre-pandemic samples from eight malaria endemic and non-endemic countries and four continents were tested by ELISA to measure SARS-CoV-2 Spike S1 subunit reactivity. Individuals with acute malaria infection generated substantial SARS-CoV-2 reactivity. Cross-reactivity was not associated with reactivity to other human coronaviruses or other SARS-CoV-2 proteins, as measured by peptide and protein arrays. ELISAs with deglycosylated and desialated Spike S1 subunits revealed that cross-reactive antibodies target sialic acid on N-linked glycans of the Spike protein. The functional activity of cross-reactive antibodies measured by neutralization assays showed that cross-reactive antibodies did not neutralize SARS-CoV-2 in vitro. Since routine use of glycosylated or sialated assays could result in false positive SARS-CoV-2 antibody results in malaria endemic regions, which could overestimate exposure and population-level immunity, we explored methods to increase specificity by reducing cross-reactivity. Overestimating population-level exposure to SARS-CoV-2 could lead to underestimates of risk of continued COVID-19 transmission in sub-Saharan Africa.

RationaleThere are few treatment options for severe COVID-19 pneumonia. Opaganib is an oral treatment under investigation.ObjectiveEvaluate opaganib treatment in hospitalized patients with severe COVID-19 pneumonia.MethodsA randomized, placebo-controlled, double-blind phase 2/3 trial was conducted in 60 sites worldwide from August 2020 to July 2021.Patients received either opaganib (n=230; 500mg twice daily) or matching placebo (n=233) for 14 days.Main Outcome MeasurementsPrimary outcome was the proportion of patients no longer requiring supplemental oxygen by day 14. Secondary outcomes included changes in the World Health Organization Ordinal Scale for Clinical Improvement, viral clearance, intubation, and mortality at 28- and 42-days.Main ResultsPre-specified primary and secondary outcome analyses did not demonstrate statistically significant benefit (except for time to viral clearance). Post-hoc analysis revealed the fraction of inspired oxygen (FiO2) at baseline was prognostic for opaganib treatment responsiveness and corresponded to disease severity markers. Patients with FiO2levels at or below the median value (≤60%) had better outcomes after opaganib treatment (n=117) compared to placebo (n=134). The proportion of patients with ≤60% FIO2 at baseline that no longer required supplemental oxygen (≥24 hours) by day 14 of opaganib treatment increased (76.9% vs 63.4%: p-value =0.033). There was a 62.6% reduction in intubation/mechanical ventilation (6.84% vs 17.91%; p-value=0.012) and a clinically meaningful 62% reduction in mortality (5.98% vs 16.7%; p-value=0.019) by day 42. No new safety concerns observed.ConclusionsPost-hoc analysis supports opaganib benefit in COVID-19 severe pneumonia patients that require lower supplemental oxygen (≤60% FiO2). Further studies are warranted.Trial registration numberNCT04467840

Multiple myeloma (MM) remains an incurable disease and there is an unmet medical need for novel therapeutic drugs that do not share similar mechanisms of action with currently available agents. Sphingosine kinase 2 (SK2) is an innovative molecular target for anticancer therapy. We previously reported that treatment with SK2 inhibitor opaganib inhibited myeloma tumor growth in vitro and in vivo in a mouse xenograft model. In the current study, we performed a phase I study of opaganib in patients with relapsed/refractory multiple myeloma (RRMM). Thirteen patients with RRMM previously treated with immunomodulatory agents and proteasome inhibitors were enrolled and treated with single-agent opaganib at three oral dosing regimens (250 mg BID, 500 mg BID, or 750 mg BID, 28 days as a cycle). Safety and maximal tolerated dose (MTD) were determined. Pharmacokinetics, pharmacodynamics, and correlative studies were also performed. Opaganib was well tolerated up to a dose of 750 mg BID. The most common possibly related adverse event (AE) was decreased neutrophil counts. There were no serious AEs considered to be related to opaganib. MTD was determined as at least 750 mg BID. On an intent-to-treat basis, one patient (7.7%) in the 500 mg BID dose cohort showed a very good partial response, and one other patient (7.7%) achieved stable disease for 3 months. SK2 is an innovative molecular target for antimyeloma therapy. The first-in-class SK2 inhibitor opaganib is generally safe for administration to RRMM patients, and has potential therapeutic activity in these patients. Clinicaltrials.gov: NCT02757326.

Background Opaganib, an oral sphingosine kinase-2 inhibitor with antiviral and anti-inflammatory properties, was shown to inhibit severe acute respiratory syndrome coronavirus 2 replication in vitro. We thus considered that opaganib could be beneficial for moderate to severe coronavirus disease 2019 (COVID-19) pneumonia. The objective of the study was to evaluate the safety of opaganib and its effect on supplemental oxygen requirements and time to hospital discharge in COVID-19 pneumonia hospitalized patients requiring supplemental oxygen. Methods This Phase 2a, randomized, double-blind, placebo-controlled study was conducted between July and December 2020 in 8 sites in the United States. Forty-two enrolled patients received opaganib (n = 23) or placebo (n = 19) added to standard of care for up to 14 days and were followed up for 28 days after their last dose of opaganib/placebo. Results There were no safety concerns arising in this study. The incidence of ≥Grade 3 treatment-emergent adverse events was 17.4% and 33.3% in the opaganib and placebo groups, respectively. Three deaths occurred in each group. A numerical advantage for opaganib over placebo was observed in in this nonpowered study reflected by total supplemental oxygen requirement from baseline to Day 14, the requirement for supplemental oxygen for at least 24 hours by Day 14, and hospital discharge. Conclusions In this proof-of-concept study, hypoxic, hospitalized patients receiving oral opaganib had a similar safety profile to placebo-treated patients, with preliminary evidence of benefit for opaganib as measured by supplementary oxygen requirement and earlier hospital discharge. These findings support further evaluation of opaganib in this population.

The Covid-19 pandemic driven by the SARS-CoV-2 virus continues to exert extensive humanitarian and economic stress across the world. Although antivirals active against mild disease have been identified recently, new drugs to treat moderate and severe Covid-19 patients are needed. Sphingolipids regulate key pathologic processes, including viral proliferation and pathologic host inflammation. Opaganib (aka ABC294640) is a first-in-class clinical drug targeting sphingolipid metabolism for the treatment of cancer and inflammatory diseases. Recent work demonstrates that opaganib also has antiviral activity against several viruses including SARS-CoV-2. A recently completed multinational Phase 2/3 clinical trial of opaganib in patients hospitalized with Covid-19 demonstrated that opaganib can be safely administered to these patients, and more importantly, resulted in a 62% decrease in mortality in a large subpopulation of patients with moderately severe Covid-19. Furthermore, acceleration of the clearance of the virus was observed in opaganib-treated patients. Understanding the biochemical mechanism for the anti-SARS-CoV-2 activity of opaganib is essential for optimizing Covid-19 treatment protocols. Opaganib inhibits three key enzymes in sphingolipid metabolism: sphingosine kinase-2 (SK2); dihydroceramide desaturase (DES1); and glucosylceramide synthase (GCS). Herein, we describe a tripartite model by which opaganib suppresses infection and replication of SARS-CoV-2 by inhibiting SK2, DES1 and GCS. The potential impact of modulation of sphingolipid signaling on multi-organ dysfunction in Covid-19 patients is also discussed.

Poster created by students of The Island School semester research class of Spring 2010

Supplemental material, sj-docx-1-chi-10.1177_17423953221101606 for Cytokine network analysis in a community-based pediatric sample of patients with myalgic encephalomyelitis/chronic fatigue syndrome by Leonard A. Jason, Caroline L. Gaglio, Jacob Furst, Mohammed Islam, Matthew Sorenson, Karl E. Conroy and Ben Z. Katz in Chronic Illness

BackgroundOpaganib, an oral sphingosine kinase-2 inhibitor with antiviral and anti-inflammatory properties, was shown to inhibit SARS-CoV-2 replication in vitro. We thus considered that opaganib could be beneficial for moderate to severe COVID-19 pneumonia. The objective of the study was to evaluate the effect of opaganib on supplemental oxygen requirements, time to hospital discharge and its safety in COVID-19 pneumonia hospitalized patients requiring supplemental oxygen.MethodsThis Phase 2a, randomized, double-blind, placebo-controlled study was conducted between July and December 2020 in eight sites in the USA. Forty-two enrolled patients received opaganib (n=23) or placebo (n=19) added to standard of care for up to 14 days and were followed up for 28 days after their last dose of opaganib/placebo.ResultsThe relative decrease in total supplemental oxygen requirement from baseline to Day 14 was 61.6% in the opaganib versus 46.7% in the placebo arms. By Day 14, 50.0% of patients in the opaganib and 22.2% in the placebo group no longer required supplemental oxygen for at least 24 hours, while 86.4% and 55.6%, respectively, were discharged from hospital. The incidence of ≥ Grade 3 treatment-emergent adverse events was 17.4% and 33.3% in the opaganib and placebo groups, respectively. Three deaths occurred in each group.ConclusionsIn this proof-of-concept study, hypoxic, hospitalized patients receiving oral opaganib required less supplementary oxygen and had earlier hospital discharge, with no safety concerns arising. These findings support further evaluation of opaganib in this population.SummaryUpon receiving opaganib, patients with COVID-19 pneumonia who were hospitalized and required supplemental oxygen showed symptomatic clinical improvement compared to placebo, with less supplemental oxygen requirement, resulting in earlier hospital discharge, and no safety concerns arising.

Supplemental material, sj-docx-1-tah-10.1177_20406207211035272 for Daratumumab in combination with proteasome inhibitors, rapidly decreases polyclonal immunoglobulins and increases infection risk among relapsed multiple myeloma patients: a single center retrospective study by Roy Vitkon, Dan Netanely, Shai Levi, Tomer Ziv-Baran, Ronit Ben-Yzak, Ben-Zion Katz, Noam Benyamini, Svetlana Trestman, Moshe Mittelman, Yael Cohen and Irit Avivi in Therapeutic Advances in Hematology

Additional file 1 Supplementary Table 1A. Matching Rules and Algorithms for Identifying Participants across Study Datasets. Supplementary Table 1B. Breakdown of Participants by Matching Conditions. Supplementary Table 2. Distribution of Elixhauser Comorbidity Groups within Study Population (n = 1208). Individuals could have multiple comorbidities. Supplementary Fig. 1. TB infection screening workflow in Middle Tennessee. Supplementary Fig. 2. Association between days from US arrival to initial screening appointment and TBI treatment completion. Days to screening appointment is modeled as a continuous variable using restricted cubic splines with 3 knots. In the final logistic model, covariates are adjusted using the following levels: sex (female), Elixhauser comorbidity index (score

Background: Upamostat is an orally available small molecule serine protease inhibitor that is a highly potent inhibitor of trypsin 1, trypsin 2 and trypsin 3 (PRSS1/2/3) as well as urokinase-type plasminogen activator (uPA) which are expressed in many cancers and mediate cell migration, invasion and tissue remodeling. Opaganib (ABC294640), a novel, orally available small molecule is a specific inhibitor of sphingosine kinase 2 (SPHK2), which phosphorylates sphingosine to sphingosine-1-phosphate (S-1-P). While proliferation induced by S-1-P is regulated by both sphingosine kinase 1 (SPHK1) and SPHK2, SPHK2 appears to be more involved in cancer. We aimed to investigate the potential antitumor effect of upamostat and opaganib, individually and in combination, on cholangiocarcinoma (CCA) patient derived xenografts (PDX) in nude mice. Methods: PAX165, a PDX from a surgically resected CCA, expresses substantial levels of SPHK2, PRSS1, PRSS2 and PRSS3. 4 groups of 18 mice were treated with either drug or both. Mouse weights and tumor volumes were measured. In addition, experiments were conducted using the chorioallantoic membrane (CAM) of chicken embryos. Results: Table 1 shows the average tumor size for the control, upamostat, opaganib, and upamostat+opaganib groups at the study end point (Day 42). Tumor volumes in the upamostat, opaganib, and upamostat+opagnib groups were significantly decreased compared to the control group. The CAM experiments are ongoing and will be presented at the AACR Annual Meeting. Change in tumor volumes (mean) of CCA PDX after opaganib, upamostat or combination treatmentControlOpaganibUpamostatOpaganib+UpamostatPre-treatment129.9128.7118.8126.8Day 42198.6102.093.3186.09Percent change Day 0-42+53%-21%-21%-32%P value vs. control0.00020.00100.0008 Conclusion: This preclinical study demonstrated that upamostat and opaganib resulted in tumor regression in mice. Body weights of the mice showed no significant inter- or intra- group differences. The combination of upamostat and opaganib treatment showed greater regression compared to either upamostat or opaganib alone. Studies are underway to identify the molecular mechanisms of their interaction. Citation Format: Faizal Z. Asumda, Mohamed A. Hassan, Yo Han Kim, Nellie A. Campbell, Xin Luo, Daniel R. O'Brien, Sarah A. Buhrow, Joel M. Reid, Michael J. Moore, Vered Katz Ben-Yair, Reza Fathi, Mark L. Levitt, Fabrice Lucien-Matteoni, Jennifer L. Leiting, Mark J. Truty, Lewis R. Roberts. Effects of upamostat and opaganib on cholangiocarcinoma patient derived xenografts [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3078.

Over the past few years, we constructed a number of biological network models representing comprehensive connectivity maps of fundamental molecular mechanisms regulating cell proliferation, cellular stress, and cell fate in the healthy and inflamed lung and cardiovascular system [1, 2, 3, 4]. These network models are based on causal and correlative biological relationships expressed in Biological Expression Language (BEL). We further developed a method that quantifies network response as a whole in an interpretable manner by integrating these causal networks with systems biology data (e.g. transcriptomics) and could show that quantitative network perturbation was in agreement with experimental endpoint data for many of the mechanistic effects of interest [5]. Recently, we extended our efforts in an attempt to build a comprehensive set of computational models reflecting the biology of cancer hallmarks as described by Hanahan and Weinberg [6] with specific attention to mechanisms occurring in the early stages of non-small cell lung cancer (NSCLC) development and progression. Using a dual approach of curating relevant literature and supplementing this information with experimental data sets from a variety of NSCLC microarray studies, we thus far completed the construction of a “Sustaining Proliferative Signaling/Evading Growth Suppressors” hallmark model that describes multiple autocrine and paracrine signaling pathways responsible for driving continuous growth of tumor cells (e.g. growth factor/growth factor receptor, MAPK, JAK/STAT signaling etc.) and deregulating cell cycle check points, as well as a “Resisting Cell Death” hallmark model combining biological mechanisms indicative of intrinsic and extrinsic apoptosis pathways, necroptosis and autophagy that ensure (lung) tumor maintenance and survival. Processes related to VEGF- and other growth factor-driven angiogenesis, vascular sprouting and tubulogenesis, HIF1A signaling and endothelial cell activation were included in an “Inducing Angiogenesis” hallmark model. The latter is closely connected to the hallmark model “Activating Invasion and Metastasis” which also considers the mechanisms associated with the acquisition of invasive capabilities by e.g. epithelial-mesenchymal transition, the degradation of extracellular matrix, and epithelial and endothelial permeability permitting tumor cell dissemination. We further built a “Deregulating Cellular Energetics” hallmark model reflecting the metabolic switch in tumor cells to aerobic glycolysis including various aspects of hypoxia and autophagy. Our focus at the current time is to address the features associated with tumor immune surveillance as exemplified by the complex interplay between tumor cells and tumor-infiltrating lymphocytes, macrophages, dendritic cells and natural killer cells which could be reflected in an “Avoiding Immune Destruction” hallmark model. As a next step we wish to integrate specific mechanisms that contribute to persistent pro-inflammatory signaling into a “Tumor-promoting Inflammation” hallmark network model. This will be followed by a comprehensive review of the newly constructed models and, if necessary, further augmentation by literature and validation with molecular data. Ultimately, we will employ our previously developed network quantification approach together with a number of publicly available lung cancer data sets to objectively evaluate the predictability of disease mechanisms in silico using transcriptomics data, and we hope that, if successful in this endeavor, various applications from drug development to environmental impact analysis could benefit from employing this portfolio of network models in unraveling disease-specific mechanisms and identifying new therapeutic targets. [1] Westra JW, Schlage WK, Frushour BP et al. (2011). Construction of a computable cell proliferation network focused on non-diseased lung cells. BMC Syst Biol. 5, 105. [2] Gebel S, Lichtner RB, Frushour B et al. (2013). Construction of a computable network model for DNA damage, autophagy, cell death, and senescence. Bioinform Biol Insights 7, 97-117. [3] Westra JW, Schlage WK, Hengstermann A et al. (2013). A modular cell-type focused inflammatory process network model for non-diseased pulmonary tissue. Bioinform Biol Insights 7, 167-192. [4] De León H, Boué S, Schlage WK et al. (2014). A vascular biology network model focused on inflammatory processes to investigate atherogenesis and plaque instability. J Transl Med. 12, 185. [5] Thomson TM, Sewer A, Martin F et al. (2013). Quantitative assessment of biological impact using transcriptomic data and mechanistic network models. Toxicol Appl Pharmacol. 272(3), 863-878. [6] Hanahan D & Weinberg RA (2011). Hallmarks of Cancer: The Next Generation. Cell 144(5), 646–674. Citation Format: Karsta Luettich, Marja Talikka, Anita Iskandar, Justyna Szostak, Ulrike Kogel, Walter Schlage, Yang Xiang, Vered Katz Ben-Yair, Shay Rotkopf, Brett Fields, Jennifer Park, Julia Hoeng, Manuel Peitsch. Computable cancer hallmarks - The construction of novel computable biological network models reflecting causal mechanisms of cancer hallmarks. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-19.

Site-to-site variability in samples from healthy control subjects. Hotellingâ s T squared residual distance separating samples collected in all 3 groups of healthy control subjects from a principal component analysis (PCA) model describing the co-expression patterns linking 16 cytokines. Middle-aged and adolescent groups were statistically comparable (pâ =â 0.839) despite samples being collected at separate sites. (PDF 37 kb)

Summary of 2-way ANOVA. Significance of time, group and time x group effects of conventional metabolic profiling in blood across 6, 12 and 24 months following diagnosis with IM. False discovery rates (FDR) were based on Storey [36] using the bootstrap (boot) and the polynomial (poly) fit methods to estimate lambda, as well as on by Benjamini and Hochberg [37] (BH). Table S2b. Summary of 2-way ANOVA. Significance of time, group and time x group effects for complete blood count (CBC) profiling in blood across 6, 12 and 24 months following diagnosis with IM. False discovery rates (FDR) were based on Storey [36] using the bootstrap (boot) and the polynomial (poly) fit methods to estimate lambda, as well as on by Benjamini and Hochberg [37] (BH). Table S2c. Summary of 2-way ANOVA. Significance of time, group and time x group effects for conventional differential blood count profiling in blood across 6, 12 and 24 months following diagnosis with IM. False discovery rates (FDR) were based on Storey [36] using the bootstrap (boot) and the polynomial (poly) fit methods to estimate lambda, as well as on by Benjamini and Hochberg [37] (BH). Basophil count was not considered due to a large proportion of missing values. Table S2d. Summary of 2-way ANOVA. Significance of time, group and time x group effects for standard endocrine profiling in blood with urine specific gravity and pH across 6, 12 and 24 months following diagnosis with IM False discovery rates (FDR) were based on Storey [36] using the bootstrap (boot) and the polynomial (poly) fit methods to estimate lambda, as well as on by Benjamini and Hochberg [37] (BH). (DOC 150 kb)

Summary of 2-way ANOVA. Significance of time, group and time x group effects of conventional metabolic profiling in blood across 6, 12 and 24 months following diagnosis with IM. False discovery rates (FDR) were based on Storey [36] using the bootstrap (boot) and the polynomial (poly) fit methods to estimate lambda, as well as on by Benjamini and Hochberg [37] (BH). Table S2b. Summary of 2-way ANOVA. Significance of time, group and time x group effects for complete blood count (CBC) profiling in blood across 6, 12 and 24 months following diagnosis with IM. False discovery rates (FDR) were based on Storey [36] using the bootstrap (boot) and the polynomial (poly) fit methods to estimate lambda, as well as on by Benjamini and Hochberg [37] (BH). Table S2c. Summary of 2-way ANOVA. Significance of time, group and time x group effects for conventional differential blood count profiling in blood across 6, 12 and 24 months following diagnosis with IM. False discovery rates (FDR) were based on Storey [36] using the bootstrap (boot) and the polynomial (poly) fit methods to estimate lambda, as well as on by Benjamini and Hochberg [37] (BH). Basophil count was not considered due to a large proportion of missing values. Table S2d. Summary of 2-way ANOVA. Significance of time, group and time x group effects for standard endocrine profiling in blood with urine specific gravity and pH across 6, 12 and 24 months following diagnosis with IM False discovery rates (FDR) were based on Storey [36] using the bootstrap (boot) and the polynomial (poly) fit methods to estimate lambda, as well as on by Benjamini and Hochberg [37] (BH). (DOC 150 kb)

Site-to-site variability in samples from healthy control subjects. Hotellingâ s T squared residual distance separating samples collected in all 3 groups of healthy control subjects from a principal component analysis (PCA) model describing the co-expression patterns linking 16 cytokines. Middle-aged and adolescent groups were statistically comparable (pâ =â 0.839) despite samples being collected at separate sites. (PDF 37 kb)

Structure of a simple prototype classification model for ME/CFS. A diagrammatic representation of the step-by-step use of an initial linear model for the classification of ME/CFS versus age and BMI-matched healthy control subjects adjusted for duration of illness. (PDF 128 kb)

Two studies examined the contribution of the new concept of "family climate for road safety" and several aspects of the social environment to the driving behavior of young drivers. Study 1 (n=120) investigated the effect of the seven dimensions of the family climate for road safety - Modeling, Feedback, Communication, Monitoring, Noncommitment, Messages, and Limits - as well as a general tendency to conform to authority, and peer pressure. Study 2 (n=154) examined the dimensions of family climate for road safety and perceived popularity of reckless driving among peers. The findings indicate associations both between the familial and the social aspects, and between these variables and driving styles, willingness to take risks while driving, reckless driving habits, and personal commitment to safe driving. Positive aspects of the parent-child relationship and high levels of conformity to authority were related to greater endorsement of the careful driving style, whereas family's noncommitment to safety, higher peer pressure, and lower conformity to authority were associated with greater endorsement of the reckless driving style. In addition, positive aspects of the family climate for road safety and lower perceived popularity of reckless driving among friends were associated with more personal commitment to safe driving and a lower tendency for risky driving. The discussion stresses the need to look at the complex set of antecedents of reckless driving among young drivers and addresses the practical implications of the findings for road safety.

This research adapted the workplace concept of safety climate to the domain of safe driving, defining a new construct of "family climate for road safety". Four studies were conducted in Israel with the aim of developing and validating a multidimensional instrument to assess this construct among young drivers. Study 1 (n=632) focused on developing the Family Climate for Road Safety Scale (FCRSS), a self-report scale assessing the family climate by means of seven aspects of the parent-child relationship: Modeling, Feedback, Communication, Monitoring, Noncommitment, Messages, and Limits. Significant differences were found between young men and women on all factors. In addition, significant associations were found between the FCRSS factors on the one hand, and the reported frequency of risky driving and personal commitment to safety on the other. Studies 2-4 confirmed the factorial structure of the FCRSS and the reliability of its factors, adding to its criterion and convergent validity. Study 2 (n=178) yielded significant associations between the scale and young drivers' perception of their parents as involved, encouraging autonomy, and providing warmth; Study 3 (n=117) revealed significant associations between the scale and youngsters' reported proneness to take risks while driving, as well as significant associations between the factors and various dimensions of family functioning; and Study 4 (n=156) found associations between the FCRSS factors and both driving styles (risky, angry, anxious, careful) and family cohesion and adaptability. The discussion deals with the validity and utility of the concept of family climate for road safety and its measurement, addressing the practical implications for road safety.

Two studies explored the interplay between death awareness, attachment style, and maternal separation anxiety among first-time mothers of infants aged 3–12 months. In Study 1 (N = 60), a higher accessibility of death-related thoughts was found following induction of thoughts about separation from the infant. In Study 2 (N = 100), a mortality salience induction led to higher maternal separation anxiety. Contrary to expectations, these findings were not moderated by mother's attachment style. The results are explained in terms of Terror Management Theory, and demonstrate its applicability to maternal emotions and cognitions.

The chemokine stromal cell-derived factor-1 (SDF-1) and its receptor, CXCR4, participate in the retention of AML cells within the bone marrow microenvironment and their release into the circulation. We previously showed that the expression of cell surface elastase in AML cells is dependent on the SDF-1/CXCR4 axis, giving a first evidence for the association between the SDF-1 and elastase pathways. In the present study, we hypothesized that inhibition of the SDF-1/CXCR4 axis or elastase may regulate similar pathways and genes in AML cells. In order to test our hypothesis, we compared gene expression profiles of U937 AML cells that express high level of membrane CXCR4, treated with neutralizing CXCR4 mAb or elastase inhibitor (EI), with non-treated cells, by employing gene-array technology. Unsupervised hierarchical clustering analysis demonstrated similar gene expression profiles of anti-CXCR4 antibody or EI treated cells, as compared to control. Analysis of the 364 genes that were differentially expressed in both anti CXCR4 mAb or EI treated cells under both treatment agents identified genes that correspond to the transcriptional profiles of differentiated myeloid cells in a significantly high prevalence. Quantitative Real-time RT-PCR for 4 selected genes C/EBPe, FLT3, HOXA9 and G-CSFR, demonstrated gene expression profiles identical to the microarray expression profiles. Given thus, we further analyzed the effect of CXCR4 inhibition on AML cell growth and differentiation using the antagonist AMD3100. AMD3100 arrested proliferation in five AML cell lines as was suggested by proliferation assay, cell cycle and caspase 3 activity analyses. Moreover, cell differentiation was demonstrated by: Modifications in cell morphology, Increased expression of myeloid differentiation antigens Acquisition of the ability to produce oxidative bursts An increase in DNA ploidy in megakaryoblasts. Our study defines a new role for the SDF-1/CXCR4 axis in the regulation of leukemic cell survival and differentiation.

Summary descriptive statistics of clinical assays. Mean and standard deviation () of the conventional complete metabolic profiling in blood at 6, 12 and 24 months following diagnosis with IM. Table S1b. Summary descriptive statistics of clinical assays. Mean and standard deviation () of the conventional complete blood count (CBC) profiling in blood at 6, 12 and 24 months following diagnosis with IM. Table S1c. Summary descriptive statistics of clinical assays. Mean and standard deviation () of the conventional differential blood count profiling in blood at 6, 12 and 24 months following diagnosis with IM. Basophil count was not considered due to a large proportion of missing values. Table S1d. Summary descriptive statistics of clinical assays. Mean and standard deviation () of the conventional endocrine profiling in blood with urine specific gravity and pH at 6, 12 and 24 months following diagnosis with IM. (DOC 149 kb)

Summary descriptive statistics of clinical assays. Mean and standard deviation () of the conventional complete metabolic profiling in blood at 6, 12 and 24 months following diagnosis with IM. Table S1b. Summary descriptive statistics of clinical assays. Mean and standard deviation () of the conventional complete blood count (CBC) profiling in blood at 6, 12 and 24 months following diagnosis with IM. Table S1c. Summary descriptive statistics of clinical assays. Mean and standard deviation () of the conventional differential blood count profiling in blood at 6, 12 and 24 months following diagnosis with IM. Basophil count was not considered due to a large proportion of missing values. Table S1d. Summary descriptive statistics of clinical assays. Mean and standard deviation () of the conventional endocrine profiling in blood with urine specific gravity and pH at 6, 12 and 24 months following diagnosis with IM. (DOC 149 kb)