Female, 6–8-week-old BALB/c mice were purchased from the Biomedical Services Unit at the John Radcliffe Hospital, Oxford. All animal procedures and care were approved by a local Ethical Committee and strictly conformed to the UK Home Office Guidelines. Mice were immunized into their tibialis anterior muscle under general anesthesia and bled via a superficial vein. The blood was collected

into 200 μL of 5 mM EDTA/PBS solution, RBCs were removed by adding 1 mL of RBC Lysis Buffer (Sigma) at room temperature for 30 min. PBMCs were then spun at 4000 × g at 4°C for 2 min, washed and resuspended in R-10 medium (RPMI 1640 supplemented with 10% FCS, penicillin/streptomycin). On the day of sacrifice, spleens were collected and splenocytes were Sirolimus isolated by pressing spleens individually through a 70-μm cell strainer using a 5 mL syringe rubber plunger. Following the

removal of RBCs with RBC Lysis Buffer (Sigma), see more splenocytes were washed and resuspended in R-10 medium at concentration of 2 × 107 cells/mL. One million of cells were added to each well of a 96-well round-bottomed plate (Falcon) and pulsed with peptides or peptide pools and incubated at 37°C, 5% CO2 for 90 min, followed by addition of GolgiStop (BD bioscience). Note that CD107a/b-FITC was added together with peptide solution. After a further 5 h incubation, reaction was terminated, the cells were washed with FACS wash buffer (PBS, 1% FCS, 0.01% Azide), and blocked with anti-CD16/32 antibodies (eBioscience) at 4°C for 20 min. All subsequent Ab stains were performed using the same condition of incubation at 4°C for 20 min with fantofarone 1.25 μg/mL Ab. Cells were washed and stained with anti-CD8 (eBioscience) or anti-CD4 mAb (eBioscience), washed again, and permeablized using the Cytofix/Cytoperm kit (BD Biosciences). Perm/Wash buffer (BD Biosciences) was used to wash cells before staining with anti-TNF-α, anti-IFN-γ, and anti-IL-2 (eBioscience) mAb. The

cells were washed with Perm/Wash buffer and fixed with the Cell Fix (BD Biosciences) and stored at 4°C until analysis. Note that fluorescence dyes used in each experiment may be different, depending on the experimental design. Stained cells were acquired on a nine-color Cyan flow cytometry (Dako) and data were then analyzed using FlowJo Software (Three Star). Syngeneic splenocytes were incubated with irrelevant or AMQ peptide at concentration 2 μg/mL at 37°C, 5% CO2 for 90 min and thoroughly washed three times with PBS. Cells were then labeled with either 0.5 or 5 μM CFSE (Molecular Probes). Two differentially labeled cell populations were combined for intravenous adoptive transfer into naïve or vaccinated animals with each animal receiving approximately 2 × 106 cells of each population. Six hours later, splenocytes were isolated and analyzed on flow cytometer.

That is precisely what Sperling found, even for large arrays of items, as long as the subset to be reported was relatively small (e.g., three to five items). A recent study by Blaser and Kaldy (2010) reported a similar pattern of results in 6-month-old infants. They presented infants with an array CP-690550 in vivo of up to 10 items varying in shape and color for a brief 1-sec duration and then highlighted two of the items by removing them from the array for 1/2 sec. When these removed items reappeared, one of them had changed. The dependent measure was whether infants looked at the changed item. As

in Sperling (1960), if all of the items in the array were encoded into STM, then regardless of which subset was highlighted, infants should detect the changed item and look longer at it. However, if infants cannot encode all of the items in the array, there will be a set-size limit beyond which the novelty preference for the changed item will fail to exceed chance. This pattern of results was precisely

what Blaser and Kaldy found—at set sizes of 2, 4, and 6 infants looked longer at the changed item, but at set sizes of 8 and 10 they did not. These results suggest that 6-month-olds have a STM capacity of at least six items in a briefly presented array. Along with prior results on WM, these results also confirm that infants have more limited information-processing capacities than adults, although their capacities are still rather impressive given Selleck GW-572016 the absence of task instructions, motivation, and training. What then mitigates Problem 2—the Depsipeptide datasheet inability to keep track of all possible statistics? Over the past two decades, a variety of constraints have been proposed and verified experimentally to account for the naïve learner’s ability to overcome the computational explosion problem (i.e., attempting to keep track of everything).

These constraints include the following. Attentional biases—infants appear to “naturally” attend to object shape and to the whole object rather than its parts (Smith, 2003), to syllables rather than phonemes (Bertoncini & Mehler, 1981), to a variety of Gestalt principles (Bhatt & Quinn, 2011) such as proximity, synchrony, and stream segregation (within an octave), and to limit inferences to a single possibility (i.e., mutual exclusivity in object names; Markman, Wasow, & Hansen, 2003). Social cues—infants appear to be guided in their attention by the gaze, manual exploration, and pointing gestures of their caregivers (Baldwin, 1993). Environmental simplification—infants benefit from a variety of ways in which caregivers declutter or enhance stimuli in their proximal environment (Kuhl et al., 1997). Cross-situational statistical learning—infants can determine by a simplified “process of elimination” that names and objects are linked even when these linkages are inferred rather than overt (Smith & Yu, 2008).

A further consideration relates to variations in antibody

levels in a given individual’s serum samples, collected at different times. The most reactive serum is generally called the ‘peak serum’. This may have been collected Crenolanib several years earlier, with the ‘current serum’ showing quite different reactivity. As an example, the peak serum may show a clear positive CDC crossmatch result, but as the antibody levels have fallen in subsequent sera, so too may the degree of cell lysis in the assay. This may render the CDC crossmatch negative. Nevertheless, the antibodies found in the peak sera may still be of relevance, increasing the risk of early rejection as a result of this prior sensitization and the resulting immunological memory. For this reason, patients on transplant waiting lists have sera collected at frequent intervals; variations can be monitored

and newly appearing HLA antibodies can be detected. In interpreting crossmatches a basic understanding of HLA expression is required. The genes encoding Gefitinib HLA are found on chromosome 6 and are inherited en bloc; such that half of each individual’s HLA (an allele) will be from each parent.9 HLA is divided into class I and class II. Class I molecules are HLA A, B and C while class II molecules are HLA DR, DP and DQ. Class I molecules are expressed on all nucleated cells while class II molecule Sinomenine expression is restricted to cells such as antigen presenting cells, for example, dendritic cells, macrophages and B cells. Importantly for transplant rejection pathophysiology, both class I and II HLA

can be expressed by vascular endothelial cells.9 Most rejection responses are thought to be due to differences in HLA between donor and recipient, with the HLA mismatched antigens serving as the targets in antibody-mediated rejection. Non-HLA antigens may generate rejection responses but in general this is thought to be less common.1 There are important differences in HLA expression between T and B cells, which influence the interpretation of the crossmatch. T cells do not constitutively express HLA class II so the result of a T-cell crossmatch generally reflects antibodies to HLA class I only. B cells on the other hand express both HLA class I and II so a positive B-cell crossmatch may be due to antibodies directed against HLA class I or II or both. Hence, if the T- and B-cell crossmatches are positive the interpretation is that there may be either single or multiple HLA class I DSAb/s or a mixture of HLA class I and II DSAbs.

In the intestinal mucosae, the ratio of CD138+ cells/total area (7·4 ± 5·3% in wt versus 7·4 ± 5·9% in mutant animals) and the ratio of B220+ cells/total area (3·0 ± 2·3% in wt versus 4·0 ± 1·4% in mutant

animals) did not significantly differ between wt and mutant mice, suggesting that plasma cell differentiation might proceed at a similar efficiency in both mutant and wt mice (Fig. 5c). We wished to block the expression of mIgA during B-cell differentiation by deleting the exon that encodes the membrane-anchoring domain of IgA within the Cα immunoglobulin gene. As expected, early B-cell maturation was normal in homozygous mutant animals, with absolute numbers of B cells accumulating in all of the peripheral lymphoid organs of the homozygous mutant mice, including TGF-beta inhibitor PD0325901 spleen follicles, marginal zone, lymph nodes, Peyer’s patches and in the peritoneum B1 compartment. Lack of

mIgA expression in peripheral B cells strongly altered but did not abrogate the in vivo production of IgA antibodies, whereas the IgA serum level was cut by about 20-fold. Part of normal serum IgA might therefore come from recently switched and stimulated IgM+ naïve B cells simultaneously undergoing CSR to IgA and plasma cell differentiation, and hence bypassing the need for an IgA class BCR.18,23 Strikingly, the defect appeared much more severe when the IgA level was evaluated in digestive secretions, falling by about 500-fold. This more profound alteration of digestive rather than serum IgA levels indicates that in physiology, IgA production in the gut overwhelmingly relies on mIgA+ memory cells.23,24 Another likely feature of mIgA-driven B-cell differentiation in wt animals is to promote plasma cell differentiation in peripheral organs where mIgA+ cells are abundant, i.e. in the MALT. The propensity of mIgA+ B cells to undergo plasma cell differentiation

was recently shown in a model where B cells were forced to prematurely express mIgA instead of mIgM and IgD.22 By contrast, in the mutant homozygous mice described herein, the total amount of plasma cells in the MALT was grossly normal in the small intestine lamina propria, as estimated by tissue sections. Although IgA plasma cells were almost absent, they were replaced by plasma cells producing other immunoglobulin classes. Patients with IgA deficiency often show increased almost levels of IgM in mucosal secretions, compensating the lack of IgA, and a similar mechanism probably occurs in the IgA-deficient mice. This may lead to forced differentiation of B cells into IgM plasma cells under conditions that would normally favour the generation of IgA plasma cells. Hence, it appears likely that the abundance of plasma cells within the gut-associated lymphoid tissues rather reflects the local concentration of mediators stimulating plasma cell differentiation, instead of being specifically boosted by signalling peculiarities from the IgA-class BCR.

Aliquots were incubated for 15 min in the dark at room temperature with a mixture of optimally titrated MAbs within 24 h after sampling. The antibodies we used are CD3 fluoresceïne-isothiocyanate (FITC), CD5 FITC, CD38 FITC, CD4 phycoerythrin (PE), CD16 PE, CD20 PE, CD24 PE, CD56 PE, BAFF-R PE, CD8 peridinin chlorophyll

protein–cyanin (PerCP-Cy-5.5), CD19 PerCP-Cy5.5, CD45 PerCP-Cy5.5, CD10 allophycocyanin (APC), CD14 APC, CD21 APC, CD27 APC [all Becton Dickinson (BD), San Jose, California USA], SmIgκ FITC, SmIgD FITC, SmIgλ PE, SmIgM PE (Dakopatts, Glostrup, Denmark), CD235a FITC, CD71 PE find more (Sanquin, Amsterdam, The Netherlands) and TACI Biotin (Peprotech, Rocky Hill, USA)/streptavidine APC (BD). Before surface staining, erythrocytes were lysed with ammonium chloride (NH4Cl). Remaining cells were washed twice with phosphate buffered saline/bovine serum albumin

0.5%, and analysed with a FACSCalibur flowcytometer (BD) using CellQuestPro software. Calibration of the flowcytometer took place with CaliBRITE beads according to the manufacturer’s instructions (BD) en daily quality control with Cyto-Cal (microgenics Duke Scientific, Fremont CA, USA) following the guidelines of Kraan et al. [27]. The lymphogate was checked with a CD3/CD14 labelling and considered correct if less than 1% monocyte contamination was present. T-lymphocytes and NK-cells were used to check the ‘lymphosum’ (B+T+NK = 100 ± 5%). Leukocyte selleck screening library count and differential were determined with a routine haematology analyzer (XE 2100, 2-hydroxyphytanoyl-CoA lyase Sysmex, Kobe, Japan). In neonatal cord blood, the lymphogate was corrected for contamination with erythroid cells (normoblasts and unlysed erythrocytes) using the following formula: corrected % of lymphocyte subpopulation = % of lymphocyte subpopulation within the lymphogate × 100/[100 − (%CD71+ normoblasts + %CD235+CD71- unlysed erythrocytes within the lymphogate)]. The absolute size of each lymphocyte subpopulation was calculated by multiplying the relative size of the lymphocyte subpopulation and the absolute lymphocyte count. Statistics.  The number of subjects in the different age groups varied between 10

and 21 per tested subpopulation; numbers that are too low to determine robust percentile points at 5 and 95%. Confidence intervals may seem to offer an alternative, but deal with estimating the range of the population mean, and do not cover the distribution of the population values. The proper statistical procedure is to calculate the tolerance interval which enclosures a specific proportion of the population, estimated on the basis of the values sampled. The tolerance interval takes into account the sample size, the noise in the estimates of the mean and standard deviation, and the confidence about the tolerance interval [28]. We set the proportion to be included at 0.90 (two-sided, comparable to the percentile points p5 and p95), with a confidence level of 0.95. Tolerance intervals assume normally distributed populations.

It has been shown previously that both exogenous and endogenous oestradiol hamper CAIA [12], as well as CIA [30–32]. We have shown potent anti-arthritic effects of raloxifene previously in the CIA model [6,7], with protection against both erosivity and generalized osteoporosis even when treatment was started in established disease. The present study is the first to show that despite these anti-arthritic properties, raloxifene did not affect CAIA. The CAIA model does not involve the induction phase, but instead only the antibody-mediated

effector phase of arthritic disease. Our results suggest therefore that raloxifene does not exert its effects during the effector phase, in contrast to oestradiol, which has an effect at this stage of disease development [12]. It has also been shown that oestradiol treatment during the induction Ponatinib concentration phase of CIA delays the onset of the disease by approximately this website 10 days [33]. Therefore, in an additional study, mice were treated with raloxifene, oestradiol or vehicle during the induction phase, and were then evaluated continuously for arthritis. However, in this study treatment with oestradiol or raloxifene daily for 12 days, starting 2 days before immunization, did not influence the appearance of arthritis significantly. Recent studies have proposed that the anti-inflammatory

mechanisms may be different during raloxifene treatment compared to oestradiol treatment. Oestradiol down-regulated T lymphocyte-dependent and granulocyte-mediated inflammation, but raloxifene did not [19]. Raloxifene lowered PIK3C2G the levels of tumour necrosis factor (TNF)-α and receptor activator of nuclear factor kappa-B ligand (RANKL) mRNA in spleen from arthritic mice, whereas oestradiol did not affect these mediators of inflammation [6]. To elucidate further the differences between these two compounds, we investigated the activation of the ERE in spleen from ERE-Luc reporter mice immunized with CII and Freund’s

complete adjuvant. As expected, exposure to oestradiol resulted in increased luciferase activity in the spleen, whereas vehicle controls displayed a total lack of luciferase activity. Immunization with CII greatly enhanced the luciferase activity (indicating oestradiol-induced ERE activation). One previous in vitro study shows that raloxifene acts ERE-dependently in osteoblasts as an oestradiol agonist, and in breast cancer cells as an antagonist [34]. In addition, both oestradiol and raloxifene can act via the raloxifene response element [35] and at an AP1 enhancer element [36,37] (non-classical pathway), suggesting different pathways of activation in different cells. Interestingly, exposure to raloxifene increased the ERE-induced luciferase activity in spleen, but to a lesser degree than oestradiol.

The hypercalcemia is mediated

by extra-renal 1-alpha hydroxylation and is seen in other fungal infections in immunosuppressed patients. We suggest that PJP should be considered as a differential cause in unexplained PTH-independent hypercalcemia in renal transplant recipients even in the absence of respiratory symptoms. 288 INFECTIVE BURSITIS DUE TO MYCOPLASMA HOMINIS IN A SIMULTANEOUS PANCREAS KIDNEY TRANSPLANT RECIPIENT RS ELKHATIM1, CA MILTON1,3, DL GORDON2,3, JA BARBARA1,3, JY LI1,3 Department of 1Renal Medicine; 2Infectious Disease, Flinders Medical see more Centre and 3School of Medicine, Flinders University, Adelaide, South Australia, Australia Background: Mycoplasma hominis is a common inhabitant of the genitourinary tract and recognized as an opportunistic pathogen. We report a case buy VX-770 of infective bursitis due to M. hominis in a simultaneous pancreas kidney (SPK) transplant recipient. Case Report: A 39-year-old man with end stage renal failure secondary to diabetic nephropathy received SPK transplantation in November 2013. His post-transplant course was complicated by pancreatic graft loss due to arterial thrombosis.

Renal function has been stable (creatinine 76 μmol/L). Immunosuppressive therapy included tacrolimus, mycophenolate and prednisolone. Three weeks post-transplant, he developed a low grade fever, severe left hip pain and was unable to weight bear. The MRI showed an effusion in the trochanteric bursa with high T2 signal and oedema in the left gluteus and adductor muscles. The bursal fluid was aspirated and the culture grew M.

hominis. Muscle biopsy revealed no abnormality. He was treated with doxycycline which is planned for 6 months. He mobilized independently 4 weeks after treatment commenced. Conclusion: To the best of our knowledge, this is the first reported case of M. hominis causing bursitis in a transplant recipient. The combination of surgical manipulation of the urinary tract and immunosuppression places the renal transplant patient at high risk for Thymidine kinase M. hominis infection. M. hominis lacks a cell wall, is not visualized on Gram stain and slow to grow in culture. Therefore, there is often a significant delay in diagnosis. It is important for clinicians to have high index of suspicion for atypical organisms whilst working up the cause of infection in immunosuppressed patients. The first choice antibiotic for M hominis is a tetracycline but the duration of therapy is not well established. 289 UNEXPLAINED NEPHROTIC-RANGE PROTEINURIA IN A CONSANGUINEOUS 2-YEAR-OLD BOY K BLAZE, T FORBES, C QUINLAN, A WALKER Royal Children’s Hospital, Melbourne, Victoria, Australia Background: We report a case of a consanguineous 26-month-old boy with a chromosome 2q35 deletion.

Jianqin He, Shiping Ding and Jianguo Wang collected patient samples and clinical information; Jianqin He and Shiping Ding designed the case–control study; Jianqin He, Shiping Ding, Jianguo Wang and Dajiang Lei performed the molecular biology experiments and analysed the genetic data. The manuscript was written by Jianqin He and Shiping Ding with contributions from Jianguo Wang. The authors declare no conflict of interest. “
“T cell and T cell-related cytokine abnormalities are involved in the pathogenesis

of systemic lupus erythematosus (SLE). Our previous study showed that the interleukin (IL)-22+CD4+T cells and IL-22 play an important role in the see more pathogenesis of SLE. In this study, we aimed to investigate the effects of glucocorticoids (GCs) and immunodepressant agents on IL-22 and IL-22-producing T cell subsets in SLE

patients. The frequencies of peripheral blood T helper type 22 (Th22), IL-22+Th17, IL-22+Th1 and Th17 cells and the concentrations of serum IL-22, IL-17 and interferon (IFN)-γ in SLE patients receiving 4 weeks of treatment with cyclophosphamide (CYC), methylprednisolone and hydroxychloroquine learn more (HCQ) were characterized by flow cytometry analysis and enzyme-linked immunosorbent assay (ELISA). The frequencies of Th22, IL-22+ Th17 and Th17 cells and the concentrations of IL-22 and IL-17 were reduced in response to the drugs methylprednisolone, cyclophosphamide and hydroxychloroquine for 4 weeks in the majority Doxacurium chloride of SLE patients. However, the percentage of Th1 cells showed no change. No differences in the levels of IL-22 and IL-22+CD4+ T cells were found between non-responders and health controls either before or after therapy. IL-22 levels were correlated positively with Th22 cells in SLE patients after treatment. These results suggest that elevated IL-22 is correlated with IL-22+CD4+T cells, especially Th22 cells, and may have a co-operative or synergetic function in the immunopathogenesis of

SLE. GC, CYC and HCQ treatment may regulate the production of IL-22, possibly by correcting the IL-22+CD4+T cells polarizations in SLE, thus providing new insights into the mechanism of GC, CYC and HCQ in the treatment of SLE. “
“Efficient induction of antigen-specific immunity is achieved by delivering multiple doses of vaccine formulated with appropriate adjuvants that can harness the benefits of innate immune mediators. The synthetic glycolipid α-galactosylceramide (α-GalCer) is a potent activator of NKT cells, a major innate immune mediator cell type effective in inducing maturation of DCs for efficient presentation of co-administered antigens. However, systemic administration of α-GalCer results in NKT cell anergy in which the cells are unresponsive to subsequent doses of α-GalCer.

brasiliensis-derived antigens. Some CD4 T cells from DO11/4get

mice can still respond to other antigens because allelic exclusion at the TCR α-chain locus is leaky and endogenous TCR α-chains can be expressed in addition to the transgenic α-chain, which leads to development of T cells with two different functional TCRs.25–27 Finally, we used DO11/4get mice on a Rag-deficient background (DO11/4get/Rag−/− mice), which express the transgenic TCR but lack expression of endogenous TCR α-chains so that we could determine whether Th2 cells are induced by cytokine-mediated bystander activation. Very few Th2 cells could be detected in lymph nodes and lungs of naive 4get, DO11/4get and DO11/4get/Rag−/− mice (Fig. 3a). However, on day 9 after infection 4get mice contained about 35% Th2 cells in the lung and about 14% Th2 cells in mesenteric lymph nodes whereas these frequencies Ponatinib solubility dmso were reduced to 11% and 5%, respectively, in DO11/4get mice (Fig. 3a,b). The majority of Th2 cells in DO11/4get mice could not be stained with the clonotypic antibody KJ1-26, suggesting that most of these T cells expressed endogenous TCR α-chains, leading to preferential expression of a second TCR (Fig. 3a). The transgenic TCR in DO11/4get mice is composed of Vα5/Vβ8.1 chains. To determine whether endogenous

TCR α-chains are expressed on KJ1-26+ cells we stained peripheral blood samples from DO11/4get mice with antibodies against two different endogenous TCR α-chains. Among all KJ1-26hi cells, about 4·4% co-expressed Vα2 and 0·3% co-expressed Wnt antagonist Vα8.3 chains (Fig. 3c). This demonstrates that DO11/4get mice contain a small repertoire of CD4 T cells with TCR specificities that are not restricted to recognition of OVA and some of these cells can mount a Th2 response against N. brasiliensis. Importantly, Th2 cells were completely absent in N. brasiliensis-infected DO11/4get/Rag−/− mice, which demonstrates that the OVA-specific

TCR is not cross-reactive with N. brasiliensis-derived antigens and Th2 cells were not induced by unspecific bystander activation (Fig. 3a,b). To support these findings in another system, we repeated these experiments with Smarta/4get mice, which express a transgenic TCR specific Exoribonuclease for lymphocytic choriomeningitis virus (LCMV)GP61–80 peptide in I-Ab. In contrast to DO11/4get mice, N. brasiliensis infection of Smarta/4get mice did not induce Th2 cells (Fig. 4a). This was not because of differences in the genetic background because comparable frequencies of Th2 cells were observed in normal 4get mice on C57BL/6 or BALB/c background (compare Figs 3a and 4a). However, co-expression of three different endogenous TCR α-chains (Vα3.2, Vα8.3 and Vα11) together with the transgenic Vα2 chain was not observed in Smarta/4get mice (Fig. 4b). This might reflect a more efficient positive selection process in comparison to thymocyte maturation in DO11.

tuberculosis27–30. This analysis showed that while many genes for apoptosis-promoting proteins are upregulated in the cells of TB patients, so are some negative regulators, such as FLIPS and FLIPL (Fig. 5). It is possible that these negative regulators are able to reduce the degree of apoptosis induced – or push cell death towards necrosis instead, to the possible benefit of the pathogen 56–58. More striking, however, is the data on PBMC separated on the basis of CD14, which indicate that surface expression of the receptor responsible for initiating the extrinsic pathway of apoptosis is find more not equal in the different cell types. Figure 1 shows

that monocytic cells from TB patients – and only from TB patients – express a lower ratio of mRNA TNF-α receptors compared with the T-cell-containing fraction – and the increased shedding of TNF-α receptors into the plasma of TB patients (Fig. 2) may attenuate the effect of TNF-α even further 31. Similarly, the increase

in the pro-apoptotic molecule Caspase 8 seen in blood from TB patients (Fig. 4A) is not seen in monocytes (Fig. 4B) where if anything, expression is decreased compared with controls. If we compare the ratio of the markers analyzed in CD14+ and CD14− subsets (Table 1), it can be very clearly seen that the balance of expression of genes for the TNF-α receptors and Caspase 8 is strongly altered in TB patients, reflecting a significant shift away from expression in the monocyte-containing subset. We can therefore hypothesize that in active TB the increased apoptosis learn more we see in PBMC falls disproportionately on the non-monocytic cells – including the T-cell compartment. This hypothesis is compatible with the in vitro data already published showing inhibition of apoptosis in infected macrophages by virulent M. tuberculosis (but not avirulent mycobacteria) the 27, 28, 55, 59–63. It is also consistent with multiple reports suggesting that upregulation of Fas/FasL in vivo is specifically associated with T-cell death in TB 38, 64–67. A bias in cell death towards activated T cells in

TB patients might explain the anergy seen in advanced TB patients, which appears to be TNF-α related 68, 69. Finally, if TNF-α-driven apoptosis of T cells plays a role in M. tuberculosis pathogenesis, it would also provide an interesting explanation for why blocking TNF-α with Etanercept (soluble TNF receptor) in TB patients undergoing treatment, led to an increase in CD4T cell numbers 70. We have tested some aspects of this hypothesis by infecting human THP-1 cells with virulent M. tuberculosis or avirulent M. tuberculosis and BCG in vitro and measuring expression of the same genes as we have tested here. These experiments have confirmed both the overall anti-apoptotic effect of virulent M. tuberculosis infection of monocytes, at the same time as it drives activation of many of the genes we see upregulated in patients – including the TNF-α/TNFR axis (Abebe et al., submitted).