In human orthotopic liver transplantation (LTX) intraoperative elevations of TNF-α (> 100 pg/ml) and IL-6 (>800 pg/ml) have been found to correlate with early post-operative rejections and infections respectively. In this study the possible mechanism responsible for the induction of these cytokines has been investigated during liver allografting in 38 recipients. Intraoperative elevations of TNF-α (> 100 pg/ml) were detected in the majority of pre-transplant endotoxin positive recipients , the patients turning endotoxin positive until the end of grafting (3/5), and in a subgroup (6/21 patients), apparently endotoxin negative for the whole operation. Therefore endotoxin (ET) seems to stimulate release of TNF-α in approximately 50% of the patients, whereas sensitized Kupffer graft cells or immediate allograft reactivity of the host are likely to account for the remaining TNF-α positive cases. Elevations of IL-6 > 800 pg/ml) were found in approximately 50% of the TNF-α positive cases, indicating partially independent regulatory pathways for IL-6 induction in the TNF-α negative patients. In agreement with a previous study, 11/13 (85%) of the intraoperative TNF-α positive recipients rejected their grafts within the first 10 days post-operatively. These data demonstrate that ET/infection associated as well as ET independent/reperfusion associated intraoperative TNF-α elevations, promote the initiation of allograft rejection in human liver transplantation. The transient and low endotoxaemia caused by the liver grafting procedure performed without veno-venous bypass seems to be of minor importance in the intraoperative induction of TNF-α.


A comparison has been made of the weight loss produced by tumour necrosis factor (TNF) (cachectin) with that produced by a restricted food and water intake (pair-fed controls), and by mitozolomide, a drug which in toxic doses induces weight loss with a similar decrease in nutrient and water intake. When administered as two separate injections over a 24 h period (acute administration) TNF produced a dose-related weight reduction that was accompanied by and directly proportional to a decrease in both food and water intake. When administered daily by i.v. injection over a 5-day period (chronic administration) the major weight loss was found to occur during the first 24 h after injection and thereafter the weight of treated mice increased toward that of controls. Acute administration of TNF produced hypoglycaemia that was more severe than observed with either mitozolomide or in pair-fed controls, a reduction in the circulatory level of free fatty acids (FFA) and an increase in plasma triglycerides, while mitozolomide and pair-feeding had no effect on the level of blood glucose or plasma triglycerides. Body composition analysis showed a loss of adipose tissue in TNF-injected and pair-fed animals after both acute and chronic treatment. Acute administration of TNF also induced a decrease in the total body water content of treated animals which was similar to pair-fed controls. It is concluded that the weight loss produced by TNF arises from a combination of semi-starvation and a reduced water intake, and that the effect only occurred with the first administration of TNF.


West Nile virus (WNV) causes viremia after invasion to the hosts by mosquito bite. Endothelial cells could play an important role in WNV spread from the blood stream into the central nervous system and peripheral tissues. Here, we analyzed the capacity of virus-like particles (VLPs) of the highly virulent NY99 6-LP strain (6-LP VLPs) and the low virulence Eg101 strain (Eg VLPs) to cross cultured human endothelial cells.6-LP VLPs were transported from the apical to basolateral side of endothelial cells, whereas Eg VLPs were hardly transported. The localization of tight junction marker ZO-1 and the integrity of tight junctions were not impaired during the transport of 6-LP VLPs. The transport of 6-LP VLPs was inhibited by treatment with filipin, which prevents the formation of cholesterol-dependent membrane rafts, suggesting the involvement of raft-associated membrane transport. To determine the amino acid residues responsible for the transport of VLPs, we produced mutant VLPs, in which residues of E protein were exchanged between the 6-LP and Eg strains. Double amino acid substitution of the residues 156 and 159 greatly impaired the transport of VLPs.Our results suggest that a transcellular pathway is associated with 6-LP VLPs transport. We also showed that the combination of the residues 156 and 159 plays an important role in the transport of VLPs across endothelial cells. West Nile virus (WNV), a mosquito-borne single-stranded RNA virus, had been known to cause endemic febrile disease in Africa, the Middle East, Europe and Asia -4. Sinceet al. [In addition to the neuronal disease, WNV-associated inflammation outside the CNS can occur in humans. Khouzam  reportedet al.  reportedet al. [et al. [Shirato et al.  suggeste [et al.  demonstr [et al. . It is sIn this study, we assessed the possibility that WNV has an ability to cross human endothelial cells. To eliminate the influence of viral replication in endothelial cells, we used virus-like particles (VLPs) which can infect susceptible cells without production of progeny virions. Our results suggest that VLPs of the NY99-6922 6-LP (6-LP) strain cross human umbilical vein endothelial cells (HUVEC) by a transcellular pathway. We also showed that the 6-LP VLPs were transported greater than VLPs of the low-virulence Eg strain, which depends on Ser 156 and Val 159 of E protein.2) was confirmed 3 days after seeding. Here we used VLPs previously reported by Scholle et al. [HUVEC were seeded on the membranes of transwells, which have 0.4 μm pores. The presence of the tight junction with an increase of transendothelial electrical resistance . The number of VLPs transferred to the lower chambers was determined by infectious unit (IFU) assay at 0, 8 and 24 h post infection (p.i.)  of 2  and Tick-borne encephalitis virus (TBEV) lack the amino acids 157-160 resulting in the absence of this structure. The α-het al.  showed tIn this study, we propose a transcellular mechanism by which WNV crosses endothelial cells and enters the target organs. We also suggest that higher transendothelial migration ability could be one of the determinants of the different virulence of the NY and Eg strains, and that this depends on Ser 156 and Val 159 of E protein.HUVEC were purchased from Lonza Group Ltd. and cultured in EGM-2 Endothelial Cell Growth Medium-2 supplemented with SingleQuots growth factors, cytokines and supplements (Lonza). The cells at passage 5 were used for experiments. Vero cells were cultured in Eagle's minimum essential medium  supplemented with 5% fetal bovine serum . Baby hamster kidney (BHK) cells were cultured in MEM supplemented with 10% FBS. HEK293T cells were cultured in Dulbecco's Modified Eagle Medium (Nissui).Xho I, Sal I and Not I. The resultant plasmids were designated pCXSN 6-LP CME and pCXSN Eg CME, respectively. For the construction of chimeric VLPs between 6-LP and Eg, a Sma I site was generated by substitution of t to c (in 6-LP) and a to g (in 6-LP and Eg) at nucleotide positions 460 and 463, respectively, of the prM gene by PCR. The sequence containing the prM gene (nucleotides 461-555) and E gene (nucleotides 1-1500) was digested by Sma I and Not I from pCXSN 6-LP CME or pCXSN Eg CME and inserted into pCXSN Eg CME or pCXSN 6-LP CME. The resultant plasmids were designated pCXSN Eg CM 6-LP E and pCXSN 6-LP CM Eg E, respectively. The constructs for single or double mutant VLPs were generated by PCR with pCXSN 6-LP CME or pCXSN Eg CME.The WNV 6-LP and Eg strains were provided by Dr. I. Takashima, Hokkaido University, Japan ,34. 6-LPXba I and purified with a PCR purification kit (QIAGEN Inc), followed by ethanol precipitation. WNV replicon RNA was produced with in vitro transcription with an mMESSAGE mMASHINE T7 kit (Applied Biosystems) according to the manufacture's instructions. BHK cells (5 × 106) were trypsinized, washed three times with phosphate-buffered saline (PBS) and resuspended in 450 μl of PBS. Then, 5 μg of replicon RNA was added to the cell suspension and introduced by using a GenePulser II elecroporation apparatus (Bio-Rad Laboratories) at 750 V, 25 μF with the resistance set to ∞. Cells were cultured in 10 cm dishes with MEM supplemented with 10% FBS for 24 h. The culture media were replaced with Opti-MEM (Invitrogen) and incubated at 37°C for 30 min. The cells were transfected with 12 μg of the plasmid encoding the sequence of WNV structural genes by Lipofectamine (Invitrogen). After 48 h, supernatants were collected and cell debris was removed by centrifugation at 1000 g for 5 min. The supernatants were concentrated with Centriplus (Millipore). For the IFU assay, Vero cells in 24 well plates were infected with serial 10-fold dilutions of VLP preparations. After a 1 h incubation at 37°C, the solutions were removed and replaced with the culture media. After 48 h p.i., the number of VLPs-infected cells was counted by eGFP signals and the IFU value was calculated.WNV replicon cDNA construct (pWNR NS1-5 EG2 AN), was generously provided by Dr. Peter W. Mason, University of Texas Medical Branch, USA . WNVR NS2) were used for experiments. For VLPs transport assay, HUVEC were exposed to 4 × 104 IFU/transwell of VLPs (2 m.o.i.). The media in the lower chambers were collected at the indicated time points and subjected to the IFU assay on Vero cells.HUVEC were seeded in transwell inserts for 24 well plates with polycarbonate membranes having 0.4 μm pores (Millipore). The media volumes were 200 μl for transwells and 700 μl for the lower chambers, respectively. The cells were cultured for 3 days and the integrity of tight junctions was evaluated by measuring TEER using a Millicell ERS (Millipore). The wells showing TEER elevation  in PBS for 10 min at room temperature. After washing with PBS three times, the cells were permeabilized with 0.1% Triton X-100 in PBS and blocked with 2% bovine serum albumin in PBS (blocking solution) for 15 min at room temperature. The primary antibody incubation was performed overnight at 4°C with rabbit antiserum to human ZO-1 (BD Transduction Laboratories) diluted at 1:1000 in blocking solution. Then the cells were washed with PBS three times, and Alexa 488 conjugated donkey anti-rabbit IgG antibodies (Invitrogen) were added at 1:1000 dilution in blocking solution for a 1 h incubation at room temperature. After a PBS wash, the membranes were cut from transwell, placed on cover glasses and observed by fluorescent microscopy.Fluorescein (FITC)-labeled 70k Dx (Invitrogen) was added into HUVEC with 6-LP VLPs, TNF-α (positive control) or media (negative control). After 24 h incubation at 37°C, 100 μl of medium was collected from each well and transferred into a 96-well plate. The FITC signal was read by a fluorescent plate reader, Mithras LB940 (Berthold). The relative transfer of 70k Dx was calculated by dividing the FITC signal of samples incubated with 6-LP VLPs or TNF-α by the mean of the signal of the negative control. The relative transfer of 70k Dx in the negative control was defined as 1.For stock solutions, chlorpromazine (Sigma) and filipin III (Sigma) were dissolved in dimethyl sulfoxide (DMSO) at 5 and 1 mg/ml, respectively. HUVEC in transwells were preincubated with the inhibitor at the indicated concentration for 30 min, and exposed to 6-LP VLPs for 24 h. For the control, DMSO was added in the media at concentration of 0.1%. The evaluation of the transported VLPs was performed as described above. The integrity of monolayer of HUVEC was confirmed by the 70k Dx transfer assay described above.Wild type or mutant VLPs were produced with 293T cells as described above. Supernatants from cell cultures were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis and Western blotting with a mouse monoclonal antibody to WNV E protein clone 3.91 D (Millipore) for the primary antibody and horseradish peroxidase (HRP)-conjugated goat antibodies to mouse immunoglobulin . The immunocomplex was visualized with Immobilon™ Western chemiluminescent HRP substrate (Millipore) and LAS-1000 mini .t test.Quantitative data are expressed as means ± standard deviation (SD) and were compared with Student's Conception and design: RH; Acquisition of data: RH, TS, SY; Analysis and Interpretation of data: RH, TS, YM, MI, AM, MH, HS, TK; Drafting the paper: RHAll authors read and approved the final manuscript.


We previously showed that HIV-1 subtype C viruses elicit potent but highly type-specific neutralizing antibodies (nAb) within the first year of infection. In order to determine the specificity and evolution of these autologous nAbs, we examined neutralization escape in four individuals whose responses against the earliest envelope differed in magnitude and potency. Neutralization escape occurred in all participants, with later viruses showing decreased sensitivity to contemporaneous sera, although they retained sensitivity to new nAb responses. Early nAb responses were very restricted, occurring sequentially and targeting only two regions of the envelope. In V1V2, limited amino acid changes often involving indels or glycans, mediated partial or complete escape, with nAbs targeting the V1V2 region directly in 2 cases. The alpha-2 helix of C3 was also a nAb target, with neutralization escape associated with changes to positively charged residues. In one individual, relatively high titers of anti-C3 nAbs were required to drive genetic escape, taking up to 7 weeks for the resistant variant to predominate. Thereafter titers waned but were still measurable. Development of this single anti-C3 nAb specificity was associated with a 7-fold drop in HIV-1 viral load and a 4-fold rebound as the escape mutation emerged. Overall, our data suggest the development of a very limited number of neutralizing antibody specificities during the early stages of HIV-1 subtype C infection, with temporal fluctuations in specificities as escape occurs. While the mechanism of neutralization escape appears to vary between individuals, the involvement of limited regions suggests there might be common vulnerabilities in the HIV-1 subtype C transmitted envelope. Most HIV-1 infected individuals develop neutralizing antibodies against their own virus, termed an autologous neutralizing response. It is known that this response exerts pressure on the envelope of HIV, the target of such antibodies, resulting in neutralization escape. Here we have identified the targets of these antibodies and the precise genetic basis of neutralization escape in 4 individuals infected with HIV-1 subtype C. We show that V1V2 is commonly involved in escape, and that the C3 region is also a target in some cases. The latter observation confirms this region is exposed in subtype C, unlike subtype B. We show that neutralization escape is conferred by a few amino acid mutations, some of which are outside the antibody target site. Moreover, escape from these limited specificities even within a single individual occurs via a variety of different pathways involving substitutions, indels and glycan shifts. The finding in 2 individuals that an anti-C3 response developed first, followed by an anti-V1V2 response, suggests there may be specific regions of envelope particularly vulnerable to antibody neutralization. Overall, we propose a mechanistic explanation for how HIV-1 epitopes drive sequential waves of neutralization escape in early subtype C infection. The nature and timing of the novel responses, or whether initial autologous nAbs are maintained or decay is not clear. It seems likely that early nAbs will wane as escape occurs, when the antigen responsible for elicitation of such responses is replaced by escape variants, which would presumably no longer stimulate existing antigen-specific B cells.Neutralizing antibody (nAb) responses which target the Env of HIV-1 and block viral entry develop in most HIV-1 infected individuals, reaching detectable levels within a few months of infection when measured against the autologous Env Escape from autologous nAbs may occur through amino acid substitutions resulting in mutational variation at epitopes The autologous nAb response in subtype C infection appears to differ somewhat from that in subtype B viruses and is less well-characterized. In subtype C, these antibodies develop to higher titer and are particularly type-specific with little or no cross-neutralizing activity within the first year of infection The role of V1V2 in shielding neutralization determinants is well-recognized In addition to the variable regions, the C3 region, located in the outer domain of gp120 slightly upstream of the V3 loop has been implicated in neutralization escape in subtype C viruses Here we investigated neutralization escape in 4 individuals from the CAPRISA 002 Acute Infection cohort, including one virus controller, 2 individuals classified as intermediate progressors, and one rapid progressor. Neutralization profiles against the infecting virus from three of the four individuals have been described previously and were shown to differ in timing and magnitude Previously we have shown using the CAPRISA 002 Acute Infection cohort that HIV-1 subtype C infection is characterized by the appearance in the first year of potent and highly type-specific neutralizing antibodies (nAbs) against the infecting virus CAP88, an intermediate progressor, first showed a neutralizing response at 15 weeks p.i. We have previously probed the specificities of antibodies in CAP88 using heterologous chimeras, where regions of interest in CAP88 were transferred into an unrelated envelope, CAP63 We were interested in the relationship between these 2 defined specificities and the neutralization escape occurring in CAP88. Comparison of the neutralization curves of representative clones from 1 month, 6 months and 12 months p.i. with the neutralization data obtained using the heterologous chimeras showed that the 1 month clone (in yellow) was sensitive to both the anti-C3 and anti-V1V2 antibodies . In contAnalysis of the C3 region of the 6 month amplicons showed that each contained 2 potential escape mutations in the α2-helix; I339N plus E343K or I339N plus E350K . Back mus then back-mutating the C3 region to make 88.12m.c2-V1V2s,N339I,K350E. Use of these chimeras in neutralization assays showed that 88.12m.c2-V1V2s became sensitive to the second peak comprising anti-V1V2 antibodies, but remained resistant to anti-C3 antibodies , 6 months and 12 months p.i. Use of the transmitted envelope, inferred from the consensus sequence at preseroconversion, 177.2wk.cA3, showed the development of autologous nAbs by 19 weeks p.i., peaking at 1∶5,500 at about 50 weeks p.i. . Like CA similar . The inc7.6m.c8B , one of s resulted in a shift leftwards of the neutralization curve, with the chimeric envelope becoming as sensitive to neutralization as the 6 month clone  . Neutrals showed a shift left in the neutralization curve, becoming as sensitive as the early preseroconversion envelope , and which we proposed to be a nAb target in CAP45 Making use of heterologous chimeras described previously Given that a single amino acid change (I339N) was associated with escape from the anti-C3 antibody in CAP88, this allowed us to measure the timing of the emergence of the escape mutation relative to the appearance of the antibody. We made use of quantitative allele-specific real-time PCR to investigate the development of the I339N change in the C3 over time. in vitro and through analyses of genetic escape impacted at least in the short-term on viral levels in vivo.Development of the anti-C3 response corresponded temporally with an 86% decrease in viral load from 93,400 RNA copies/ml at 11 weeks p.i. to 12,800 copies/ml by 15 weeks p.i. . At thisThis study aimed to identify the antibody specificities mediating autologous neutralization in HIV-1 subtype C infection during the first year of infection, and investigate the mechanisms of viral escape from these antibodies. We showed that neutralization escape occurred shortly after the appearance of nAbs, and was mediated by relatively few amino acid changes, including substitutions, indels, and glycan shifts, commonly in the V1V2 and C3 regions. A limited number of specificities were responsible for driving genetic escape and these antibodies appeared sequentially and waned as escape mutations emerged. A schematic representation of the targets of autologous nAbs as well as the regions or residues involved in neutralization escape are shown in pers comm) which resulted in genotypic changes in this region. Thus, nAb and CTL pressure directly accounted for 7 of the 14 mutations found in the CAP88 envelope, with the remaining 7 mutations playing no obvious role in immune escape. Thus, attributing bulk variation in envelope sequences largely to immune pressure may overstate the direct effect of early nAbs on envelope variation. Of course, it is likely that other mutations may indirectly affect neutralization sensitivity via e.g. changes in fitness or entry efficiency which could increase the overall neutralization resistance, but which should be differentiated from specific changes mediating neutralization escape from single antibody specificitiesThe investigation of neutralization escape in conjunction with data examining the specificity of the circulating nAbs is a strength of this study. We examined neutralization escape in four individuals, with varying disease status and viral genetic diversity. In CAP45 and CAP210, where genetic diversity at 1 year p.i. was low, use of chimeric and mutant envelopes indicated the development of only a single nAb specificity resulting in neutralization escape. The low levels of viremia in CAP45 who was classified as a controller , may havChanges within the V1V2 region were implicated in neutralization escape in all 4 individuals  althoughWe previously showed that the C3-V4 region is a major target of autologous nAbs in subtype C The sequential development of nAb specificities, sometimes requiring months of infection was intriguing considering that the targets of these antibodies may have been present in the infecting virus. This is most clearly exhibited in CAP88 where an initial anti-C3 response developed, waned and was subsequently replaced by an anti-V1V2 response. The V1V2 epitope that was the target of this secondary response was present in the earliest virus, cloned at 1 month p.i. Despite the ongoing presentation of this epitope, an anti-V1V2 response was only detectable at 26 weeks p.i., 11 weeks after the detection of the initial anti-C3 response, suggesting the possibility of an immunological hierarchy. Delayed development of selected responses would be in line with the hierarchical binding antibody responses which develop in the very early stages of infection et alOf interest was the observation that after escape occurred, although specific responses waned, they continued to be maintained at somewhat lower levels. This was difficult to discern when looking at overall neutralization levels as novel responses replaced waning responses. However, the use of heterologous viruses in CAP88 clearly showed that the anti-C3 response was maintained, albeit at lower levels . How this response was maintained is not clear as by 6 months p.i., 8/8 envelope clones contained escape mutations which presumably no longer stimulated the B cells responsible for producing anti-C3 antibodies. It is possible that even after escape has occurred, low levels of sensitive variants remain in the lymph nodes and stimulate maintenance of low levels of antibodies. The persistence of such sensitive variants in the face of potent nAbs as reported by Mahalanbis The identification of a single amino acid change associated with initial neutralization escape in CAP88 afforded us the opportunity to investigate the kinetics of the development of neutralization escape with respect to the timing of the autologous neutralization response. The relationship between percentage neutralization at a 1∶45 plasma dilution and development of the initial escape mutation, showed a lag of 7 weeks in the development of genetic escape. This suggested a threshold requirement, whereby relatively high titers of nAbs were needed before sufficient pressure was exerted on the overall population, forcing escape to occur. Maturation of the antibody response, in terms of affinity and avidity may also play a role in the duration of time required for escape to occur. The decrease in the viral load which occurred as the autologous neutralizing antibody response developed was intriguing, suggesting the possibility that autologous nAbs may in the short term impact on viral load, with this effect abrogated by the development of neutralization escape mutations.The observation of the sequential development of anti-C3 antibodies followed by anti-V1V2 antibodies suggests that both of these regions are exposed and immunogenic on the HIV-1 subtype C envelope, possibly due to unique structural features of this viral subtype. Further studies are needed to determine if this is a common pattern, and whether emergence of these autologous antibodies is associated with decreases in HIV-1 viral load as seen in one individual who developed an anti-C3 specific nAb. However, as shown here, escape variants emerged as a result of a few genetic changes, not unlike the scenario with anti-retroviral monotherapy. The ease with which escape occurred, and the multiple pathways used to escape autologous responses further supports the notion that these responses, while driving considerable variation in the envelope region, have no long-term role in containing viral replication. Nonetheless, neutralization escape is reflective of active and ongoing replication in the face of an evolving and initially very low titer response, considerably different to a possible future vaccine scenario with pre-existing antibodies. Overall, these data provide insight into how a focused antibody response targeting limited regions of envelope in early subtype C infection drives sequential waves of neutralization escape.The CAPRISA Acute Infection study was reviewed and approved by the research ethics committees of the University of KwaZulu-Natal (E013/04), the University of Cape Town (025/2004), and the University of the Witwatersrand (MM040202). All participants provided written informed consent for study participation.Participants were from the CAPRISA 002 Acute Infection study, a cohort of 245 high risk HIV negative women which was established in 2004 in Durban, South Africa for follow-up and subsequent identification of HIV seroconversion The JC53bl-13 cell line, engineered by J. Kappes and X. Wu, was obtained from the NIH AIDS Research and Reference Reagent Program. 293T cells were obtained from Dr George Shaw . Both cell lines were cultured in D-MEM (Gibco BRL Life Technologies) containing 10% heat-inactivated fetal bovine serum (FBS) and 50 ug/ml gentamicin (Sigma). Cell monolayers were disrupted at confluency by treatment with 0.25% trypsin in 1 mM EDTA.env genes were amplified from single cDNA copies env sequences were assembled and edited using Sequencher v.4.0 software . The number of potential N-linked glycosylation sites (PNGs) was determined using N-glycosite (http:/www.hiv.lanl.gov/content/hiv-db/GLYCOSITE/glycosite.html). Multiple sequence alignments were performed using Clustal X (ver. 1.83) and edited with BioEdit (ver. 5.0.9). Pairwise DNA distances were computed using Mega 4 HIV-1 RNA was purified from plasma using the Qiagen Viral RNA kit, and reverse transcribed to cDNA using Superscript III Reverse Transcriptase . The Selected amplicons were cloned into the expression vector pCDNA 3.1  (Invitrogen) by re-amplification of SGA first-round products using Phusion enzyme (Finn Enzymes) with the EnvM primer Chimeric Env were created using an overlapping PCR strategy with the inserts and flanking regions amplified in separate reactions. After linkage, the 3 Kb chimeric PCR fragments, generated using EnvAdir and EnvM primers 50) causing 50% reduction of relative light units (RLU).Neutralization was measured as described previously CAT TAC TAA AGA CAG ATG Gtt) for detection of the 339I, 88AS-PCR-A-for (CAT TAC TAA AGA CAG ATG Gta) for the detection of 339N. Control primers were 88AS-PCR-control (GAG ATA TAA GAC AAG CAC ATT G) and 88AS-PCR-A/T-rev (CTA TGT GTT GTA ACT TCT AGG). The reaction was performed using ABI PowerSYBR Green PCR master mix, in the ABI 7500 Real Time PCR System. Primer concentrations were 300 nM, final volume 25 ul. Cycling was performed as follows: 95°C for 10 minutes followed by 45 cycles of 95°C for 15 seconds, 60°C for 15 seconds, and 72° for 1 minute, for a total of 45 cycles. Relative quantification of mutation frequency was determined by calculating the number of copies of wild type and mutant populations relative to an internal control.Real-time PCR was performed on RNA extracted from sequential plasma samples of CAP88 using the QIAamp Viral RNA Mini Kit (Qiagen). HIV-1 RNA was reverse transcribed to cDNA using the Superscript III Reverse Transcriptase System (Invitrogen) using the primer OFM19 as described Figure S1Clinical profiles of CAP45, CAP88, CAP177 and CAP210. Viral load (copies/ml) in red and CD4 count (cells/µl) in blue. Clinical status for each individual is indicated in parentheses. Arrows indicate time points at which SGA amplicons were derived.(0.19 MB TIF)Click here for additional data file.Figure S2Clinical profiles of CAP45, CAP88, CAP177 and CAP210. Viral load (copies/ml) in red and CD4 count (cells/µl) in blue. Clinical status for each individual is indicated in parentheses. Arrows indicate time points at which SGA amplicons were derived.(0.47 MB TIF)Click here for additional data file.Figure S3Amino acid alignment of the V1V2 regions of single genome amplicons of CAP210. Amplicons were derived from 1 month p.i. (yellow bar), 1 month p.i. (orange bar), 6 months p.i. (red bar) and 12 month p.i. (blue bar). Amplicons highlighted in bold text were cloned for neutralization assays. Potential N-linked glycosylation sites are highlighted in gray, dashes indicate deletions.(0.24 MB TIF)Click here for additional data file.Figure S4Amino acid alignment of the mutation observed in V1 (green), V2 (cyan) and V5 (pink) regions of single genome amplicons of CAP45. Amplicons were derived from 2 weeks p.i. (yellow bar), 1 month (orange), 6 months (red bar) and 12 months p.i. (blue bar). Amplicons highlighted in bold text were cloned for neutralization assays. Potential N-linked glycosylation sites are highlighted in gray, dashes indicate deletions.(0.23 MB TIF)Click here for additional data file.


Tumour necrosis factor (TNF) inhibits the accumulation of acetyl CoA carboxylase (ACC) mRNA by decreasing the rate of ACC gene transcription. The ACC mRNA species found in 30A5 cells are generated from promoter II and TNF inhibits the accumulation of class 2 type mRNAs. By using 5' deletion mutants of promoter II fused to the bacterial chloramphenicol acetyltransferase (CAT) gene, the DNA mobility shift assay and the DNase I footprinting assay, the authors have identified the 30 bp from −389 to −359 as the TNF responsive element in promoter II. TNF treatment causes a decrease in the binding activity of nuclear protein(s) specific to the TNF responsive element. When the fragment containing the TNF responsive element was incorporated into the thymidine kinase promoter, the chimeric gene exhibited TNF induced inhibition of expression.


Here we show that Doxil® has minimal antitumour activity in the isolated limb perfusion (ILP) setting and its activity was not enhanced by the addition of tumour necrosis factor (TNF). Doxil® accumulation in tumour tissue was low and also not augmented by TNF. In contrast, activity of free conventional doxorubicin was enhanced by TNF. We conclude that application of Doxil® in a TNF-based ILP is not a useful alternative to free conventional doxorubicin or melphalan. Isolated limb perfusion (ILP) provides an excellent tool in the treatment of locally advanced tumours. During ILP, high local drug concentrations are possible due to minimal leakage into the systemic circulation, and the effect on vital organs is limited, allowing high dosages to be used. We and others have demonstrated that addition of tumour necrosis factor (TNF) to an ILP with melphalan increased the tumour response dramatically as compared to melphalan alone  prolongs circulation time, decreases toxicity and augments localisation in tumour tissue . Pegylated liposomal doxorubicin  was kindly provided by Dr Working . Doxorubicin hydrochloride (adriblastina) was purchased from Pharmacia .Human recombinant TNF-A2B) (where B represents the largest diameter and A the diameter perpendicular to B). All animal studies were done in accordance with protocols approved by the Animal Care Committee of the Erasmus University Rotterdam, the Netherlands  and WAG/RIJ rats  were obtained from Harlan-CPB . Small fragments (3 mm) of tumour were implanted subcutaneously in the right hindleg, as previously described  or a complete remission .μg), Doxil® or doxorubicin (400 μg BN175 and 200 μg ROS-1) were added as boluses to the oxygenation reservoir. Control rats were perfused with Haemaccel or placebo liposomes alone. The concentration of TNF was adapted from previous animal studies, and doxorubicin concentrations that yielded no local toxicity were used. All animal studies were approved as stated above  .Perfusion with Doxil®, TNF or buffer alone resulted in progressive disease in all soft-tissue sarcoma-bearing rats . Isolated limb perfusion with Doxil® only, induced slight tumour growth delay comparable to free conventional doxorubicin. Strikingly, ILP with Doxil® plus TNF diminished the tumour response, and none of the rats showed a tumour response.Isolated limb perfusion in osteosarcoma-bearing rats with buffer or conventional doxorubicin alone had no significant effect on tumour growth . IsolateWe observed that addition of TNF did not significantly augment the accumulation of Doxil® in soft-tissue sarcoma or osteosarcoma when compared to ILP with Doxil® alone (data not shown). Levels of doxorubicin were significantly increased when TNF was added to ILP with free doxorubicin , which results in a long circulation time and extravasation through the leaky vasculature of tumours (


Streptococcus pneumoniae is a human pathogenic bacteria and a major cause of severe invasive diseases, including pneumonia, bacteremia, and meningitis. Infections with S. pneumoniae evoke a strong inflammatory response, which plays a major role in the pathogenesis of pneumococcal disease.S. pneumoniae affects expression of the inflammatory cytokine tumor necrosis factor (TNF) α, and the molecular mechanisms involved. Secretion of TNF-α was strongly induced by S. pneumoniae, which was able to stabilize TNF-α mRNA through a mechanism dependent on the viability of the bacteria as well as the adenylate uridylate-rich elements in the 3'untranslated region of TNF-α mRNA. The ability of S. pneumoniae to stabilize TNF-α mRNA was dependent on the mitogen-activated protein kinase (MAPK) p38 whereas inhibition of Toll-like receptor signaling via MyD88 did not affect S. pneumoniae-induced mRNA stabilization. P38 was activated through a pathway involving the upstream kinase transforming growth factor-activated kinase 1 and MAPK kinase 3.In this study, we have examined how S. pneumoniae stabilizes TNF-α mRNA through a pathway dependent on p38 but independent of Toll-like receptors. Production of TNF-α may contribute significantly to the inflammatory response raised during pneumococcal infection.Thus,  Streptococcus pneumoniae is an important cause of severe invasive infections, including pneumonia, bacteremia, and meningitis [S. pneumoniae is common among children, but in most cases bacterial invasion into the lungs or bloodstream is prevented by local host defenses in the upper airways [ningitis ,2. Nasop airways . However airways , which a airways . Pneumoc airways ,5, a key airways .S. pneumoniae [The cytokine tumor necrosis factor (TNF)-α is produced by macrophages and dendritic cells as a primary response to infections and tissue damage, and is constitutively expressed in several autoimmune diseases . TNF-α peumoniae -9. Howeveumoniae .Production of TNF-α is regulated both at the level of transcription, mRNA stability, and translation -13. The S. pneumoniae is the nucleotide-binding oligomerization domain (NOD) proteins, which are intracellular PRRs [S. pneumoniae [The inflammatory response to infection is triggered by pattern recognition receptors (PRR)s, which recognize evolutionarily conserved pathogen-associated molecular patterns (PAMP)s and activate intracellular signaling, thereby up-regulating expression of genes with inflammatory activities, including TNF-α . The Tollar PRRs . The NODeumoniae .S. pneunomiae, including the signaling mechanisms involved. Here we report that live S. pneunomiae strongly stabilizes TNF-α mRNA by a mechanism dependent on the AREs in the 3'-UTR of the mRNA. Importantly, increased TNF-α mRNA stability induced by S. pneunomiae was not mediated by TLRs but was dependent on the p38 MAPK, which was activated through a pathway involving transforming growth factor-activated kinase (TAK) 1 and MAPK kinase (MKK) 3.In this study, we have investigated the role of mRNA stabilization in TNF-α production induced by S. pneumoniae. In a first set of experiments, we measured expression of TNF-α in murine macrophages after treatment with S. pneumoniae, N. meningitidis or pure ligands for TLR2 (Pam3Csk4), TLR4 (LPS), and TLR9 (ODN1826). As expected, cells responded to addition of bacteria or TLR ligands by secreting high amounts of TNF-α . LPS and N. meningitidis also stabilized the TNF-α messenger but not to the same extent as S. pneumoniae. To examine whether the AREs of the TNF-α mRNA were required for the observed effect, we turned to a cell system derived from RAW264.7 cells, consisting of two cell lines stably expressing a reporter gene , transcribed from a constitutive promoter. In one of the cell lines (RAW TNF-α 3'-UTR AU+) the 3'-UTR of the mRNA encoding the reporter gene is derived from the wild-type TNF-α mRNA, and in the other cell line (RAW TNF-α 3'-UTR AU÷) the AREs of the TNF-α 3'-UTR are mutated. When the RAW TNF-α 3'-UTR AU+ cell line was incubated in the presence of S. pneumoniae, a very strong increase in CAT levels was observed  to about 65% . Thus, stabilization of TNF-α mRNA by S. pneumoniae is dependent on the viability of the bacteria.We next examined the pneumococcal requirement for mediating TNF-α mRNA stability. To this end, we compared the ability of live nes Fig.  and 2B. S. pneumoniae SK1013 strain used in this study has previously been demonstrated to be recognized by TLR2 and 9 [S. pneumoniae [S. pneumoniae. The agonists for TLR2, 4, and 9 all enhanced CAT expression but to a rather moderate extent compared to what was observed in cells receiving live S. pneumoniae , the presence of the TLR9 antagonist had no effect on CAT expression induced by S. pneumoniae  2 [S. pneumoniae-activated PRR NOD2 [The signaling pathways responsible for mediating mRNA stability have recently been studied extensively, and it appears that P38 MAPK plays a central role in this process . To exam (RIP) 2 , which pPRR NOD2 . TherefoPRR NOD2 , on induS. pneumoniae mediated stabilization of TNF-α mRNA. Therefore, we hypothesized that live versus heat-killed S. pneumoniae may differentially activate p38. RAW264.7 cells were stimulated with live or heat-killed S. pneumoniae for the indicated time intervals, whole-cell lysates were harvested and the levels of phosphorylated p38 were measured. Indeed, the results showed that live bacteria potently stimulated phosphorylation of p38, heat-killed bacteria were not able to elicit such a response .P38-mediated mRNA stabilization can occur through several mechanisms, including involvement of members of the MAPK-activated protein kinase family, in particular MK2 -30. To eS. pneumoniae, we first examined the role of TAK1, which has been ascribed an important role in this process by activating a number of different pathways [Z)-7-oxozeaenol 15 min prior to stimulation with S. pneumoniae or anisomycin. Lysates were prepared 30 min post-stimulation, and levels of phospho-p38 were measured. As shown in Fig. S. pneumoniae and anisomycin potently induced phosphorylation of p38. Whereas the TAK1 inhibitor did not affect activation of p38 in response to anisomycin, the ability of S. pneumoniae to induce p38 phosphorylation was abolished in the presence of the TAK1 inhibitor.In order to gain more insight into the mechanism of p38 activation during infection with pathways -33. RAW2S. pneumoniae-induced p38 activation pathway, we compared the ability of spleen cells from C57BL/6 and MKK3-/- mice to activate p38 in response to S. pneumoniae treatment. Anisomycin was included as a control, and was found to trigger p38 activation independently of MKK3 , professor Mathias Gaestel , professor Simon Arthur , and professor Richard A Flavell , respectively, and bred in the animal facility of The Faculty of Health Sciences, University of Aarhus, under pathogen-free conditions. Peritoneal macrophages were harvested by lavage of the peritoneal cavity with PBS supplemented with 5% LPS-free heat-inactivated fetal calf serum (FCS)  and 400 μl heparin  per 100 ml. RAW264.7 macrophage-like cells and the derived cell lines RAW TNF-α 3' untranslated region (UTR) AU+ and RAW TNF-α 3'UTR AU÷ -40 were S. pneumoniae strain SK1013 serotype 4 (TIGR4) and the N. meningitidis strain NGO93 serogroup B, serotype 15:P1.2, MLEE cluster I1, ET76. The bacteria were grown overnight in Brain Heart Infusion broth with 10% Levinthal broth  reaching a concentration of 18.0 ± 2.2 × 108 bacteria per ml as determined in a Thoma counting chamber. For stimulation, 300 μl and 10 μl from this stock was added to the cell cultures in 6- and 96-well plates, respectively, reaching final volumes of 3 ml and 100 μl, respectively. The bacteria were heat-inactivated by incubation of the cultures for 30 min at 65°C. To UV-inactivate the bacteria, the cultures were exposed to UV light for 10 min, and for killing of bacteria with penicillin, the cultures were incubated for 2 h with 1.0 μg/ml of the antibiotics.The bacteria used were the Z)-7-oxozeaenol was purchased from AnalytiCon Discovery GmbH. The cytokines TNF-α, and interferon (IFN)-γ were from R&D Systems . The Mnk inhibitor CGP57380 was kindly provided by Hermann Gram (Novatis).The TLR agonists Pam3Csk4, LPS, and ODN1826 as well as the TLR9 antagonist ODN2088 were obtained from InvivoGen . The MyD88 Homodimerization Inhibitory Peptide was purchased from IMGENEX . Actinomycin D, anisomycin, SB202190, and PP2 were from Calbiochem . The TAK1 inhibitor  according to the recommendations of the manufacturer. Briefly, cells were lysed in TRIzol, and chloroform was added, followed by phase separation by centrifugation. RNA was precipitated with isopropanol and pelleted by centrifugation. Pellets were washed with 80% ethanol and re-dissolved in RNase-free water. For cDNA generation, 1 μg of RNA was subjected to reverse transcription (RT) with oligo(dT) as primer and Expand Reverse Transcriptase (both from Roche). Prior to RT-PCR, RNA was treated with DNase I  to remove any contaminating DNA, the absence of which was confirmed in control experiments where the reverse transcriptase enzyme was omitted (data not shown). To measure the relative amount of TNF-α mRNAs, amplification of sample cDNA was monitored with the fluorescent DNA binding dye SYBR (QIAGEN). The PCR primers used in this study were: TNF-forward, TGGGAGTAGACAAGGTACAACCC; TNF-reverse, AGAGGGAAATCGTGCGTGAC; β-actin-forward, GCTCCCCGGGCTGTATTCC; β-actin-reverse, CTCTCTTGCTCTGGGCCTCGT). The data on TNF-α were normalized to β-actin, and presented as normalized ratio.The cells were seeded and treated as described for the appropriate amount of time. For cell lysis and measurement of CAT levels the CAT ELISA kit from Roche  was used.To assay for levels of total and phosphorylated p38, cells were seeded in 6-well plates as described above and stimulated with bacteria as specified in the text. At different time points post-stimulation, cells were lysed using the Bio-Plex Cell Lysis Kit  according to the recommendations of the manufacturer. Briefly, the cells were washed with 3 ml Cell Wash Buffer per well and treated with 1 ml Lysing Solution supplemented with PMSF followed by incubation for 20 min at 4°C. The suspension was centrifuged at 4500 × g for 20 min at 4°C and supernatants were harvested as whole-cell extracts.The levels of total and phosphorylated p38 were measured using the Luminex Technology™ and kits purchased from Bio-Rad. Briefly, the filter plate was washed with assay buffer and freshly vortexed antibody-conjugated beads were added to each well. The plate was washed with assay buffer and samples (45 μg of protein in 50 μl lysis buffer) were added. After a brief shake (30 sec at 1.100 rpm), the plate was incubated with shaking (300 rpm) overnight at 4°C. After a wash-step, detection antibody was added to each well, and the plate was shaken and incubated shaking (300 rpm) at room-temperature in the dark for 45 min to 2 h. Subsequently, the plate was washed and incubated for 10 min with 50 μl of a streptavidine-PE solution with shaking . Finally the plate was washed and 125 μl of assay buffer was added to each well and the plate was shaken for 10 sec at 1100 rpm and read immediately on the Bio-Plex reader.N-(1-naphthyl)-ethylenediamine dihydrochloride and 1% p-aminobenzene sulphanilamide diluted in 2.5% phosphoric acid) in a 96-well microtitre plate . After 10 min incubation at room temperature the absorbance at a wavelength of 540 nm was measured in a microplate reader . A range of 2-fold dilutions of sodium nitrite (0.05 to100 μM) in RPMI medium was run in each assay to generate a standard curve. In most experiments, control cultures not infected or stimulated gave small nitrite values in the order of 0–1 μM. These figures were subtracted from the experimental values in the data presentation.Nitrite is generated by the rapid oxidation of NO. It is stable and its accumulation in the culture medium reflects the amount of NO produced. To assay nitrite we used the Griess reaction. Aliquots of 100 μl culture supernatants were mixed with equal volumes of Griess reagent (equal volumes of 0.1% The work presented in this paper did not include research on humans. Animals, used for isolation of cells for in vitro experiments were sacrificed by cervical dislocation without receiving any prior experimental treatment. Therefore, to perform the experiments described in this article, no need for approval from ethics committees was required according to Danish law.ARE: adenylate uridylate rich elements; AU: adenylate uridylate; CAT: chloramphenicol acetyl transferase; FCS: fetal calf serum; MAPK: mitogen-activated protein kinase; MKK: mitogen-activated protein kinase kinase; NF: nuclear factor; NOD: nucleotide-binding oligomerization domain; PAMP: pathogen-associated molecular pattern; PRR: pattern recognition receptor; RIP: receptor-interacting protein; TAK: transforming growth factor-activated kinase; TLR: Toll-like receptor; TNF: tumor necrosis factor; UTR: untranslated region.The authors declare that they have no competing interests.THM and SRP designed experiments. THM and RSB performed experiments. THM, RSB, and SRP interpreted data. All authors helped preparing the manuscript and approved the final version.


Several different cytokines trigger the development of determined cell subsets            in BALT of growing Wistar rats. Early appearance (4 days post partum) of γδT cells in            BALT has been shown, as well as its role in up-regulating TNF-α production. In the            present report, we studied in the BALT: (1) the profile of the cytokines, TNF-α, INF-γ            and IL-10 and (2) in TCR γδ+ cells, the existence of a colocalization with TNF-α as well            as with INF-γ. All the cytokines studied were observed at an early stage of BALT            development by immunohistochemistry and in bronchoalveolar cells (BAL cells) by            flow cytometry and western blot. (1) The principal cytokine found at 4 days of age in            BALT cells was TNF-α that increases along BALT development. The same behavior            was found for cells containing IL-10 and INF-γ. (2) TCR γδ+ cells colocalize mainly with            TNF-α as it has been shown by immunohistochemistry in BALT and by flow cytometry             when we studied BAL.        The early appearance of TNF-α concomitant with TCR γδ+ cell suggests             an important role for this cytokine along BALT development. Moreover, mutual             regulation between them exists taking             part in the immune surveillance and repair of damaged epithelia.


It showed that LPS in vivo generates factors other than TNF, such as platelet activating factor (PAF), that are responsible for the increased capillary permeability.The literature presented illustrates that lipopolysaccharide (LPS), from bacterial cell walls, induces tumour necrosis factor (TNF) synthesis in macrophages. TNF affects a number of cell types, amongst which are endothelial cells, within a few hours. Its injection has been shown to produce all symptoms of the toxic syndrome. In the present communication the vulnerability of endothelial cells will be stressed. These cells require carnitine not only for fatty acid oxidation but also for membrane protection and repair. As endothelial cells lose carnitine during hypoperfusion, it is speculated that the supply of carnitine during the early phase of LPS toxicity in rats might delay or avoid loss of endothelial functions. Earlier it was observed that hearts from rats, injected 3 h previously with LPS, showed strongly increased interstitial fluid production compared to hearts from control rats, even when TNF was present during a 3 h


For a group of scientists or institution, nI is defined as the number of authors who appear in at least nI papers that bear the affiliation of the group or institution. 1I depends on the number of papers authored pN. The power exponent R of the relationship between 1I and pN categorizes scientists as solitary (R>2.5), nuclear (R = 2.25–2.5), networked (R = 2–2.25), extensively networked (R = 1.75–2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. nI similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define  Appraisal of the scientific impact of researchers, teams and institutions using their publication record and citation metrics h index h citations each. The original paper describing hh nor other similar indices provide information about the co-authorship pattern of a scientist. Two scientists may have the same h, but one may have no or only few co-authors in all her papers while the other may be a participant of one or several large collaborations and may have co-authored all her papers with dozens of others.While it is often difficult to see what an author has truly done in a specific paper, it may be easier and more informative to examine one's overall co-authorship behaviour across one's whole publication record. Current systems of measuring productivity and citation impact for individuals or groups count all papers and all citations the same, regardless of what each author has contributed. Such exercises have acquired strong supporters and have also raised major objections h. Defining the size of a team or institution with administrative data is difficult. Quotas for size would differ enormously depending on whether tenured faculty, tenure-track faculty, associates, post-graduates, pre-graduates, supporting staff, and close collaborators (some not even in the same location) are counted or not.Similar difficulties appear in appraising teams and institutions Here, I propose simple indices that measure the networking intensity, the effective size of a network, for scientists or groups of scientists who co-author papers. These indices are empirically demonstrated with data on authors from the medical sciences and comparatively on authors from physical scientists, where “mega-authorship” papers with hundreds of authors are already commonplace. I also demonstrate the use of these indices for institutions.1I as the number of authors who appear in at least 1I papers of that scientist. 1I increases with increasing number of publications pN. With more publications, opportunities arise for having more co-authors and for more papers written in common with each co-author. This relationship can be expressed with a power law pN = 1)R/log10(I1)log. R reflects the co-authorship pattern. With fewer co-authors per paper, for the same pN the 1I is smaller and R larger. For the same 1I, R increases, when a scientist writes more papers (larger pN) with new or sporadic co-authors who don't contribute to 1I; or keeps co-authoring only with a small core of his most common co-authors.For a single scientist, I define R may be imprecise when the two measures that enter into its calculation, pN and 1I, are small, because then small changes may result in considerable changes in R. I recommend to view R very cautiously if pN<30 or 1I<4.1I values are shown in pN for highly-cited scientists in Clinical Medicine and Physics according to ISI (ISI highlycited.com. Available at: http://isihighlycited.com Last accessed 2007 December 30). In particular for Physics, the diversity is extreme with 1I values ranging from 6 to 235. The range of 1I for Clinical Medicine highly-cited scientists is 9 to 25. About a third of the examined highly-cited scientists in Physics have 1I above 130. They are all physicists who participate routinely in extremely multi-authored collaborations, mostly in high energy and particle physics. They have written few, if any, papers as first authors, but based on plain citation counts they are among the 250 most influential people in their science. The values of R also range widely from 1.07 to 2.81.R, to categorize the co-authorship networking of scientists:I propose the following classification, based on R>2.5)solitary (R = 2.25–2.5)nuclear (R = 2–2.25)networked (R = 1.75–2)extensively networked (R<1.75)collaborator , but 1I may not increase similarly. This will lead to a spuriously high R. For example, for Smith F, we get pN = 809, 1I = 9, R = 3.05.For authors with common names, it is unlikely that same-name authors would share also co-authors. Therefore, if one inadvertently measures indices for a common name, h index for co-authorship networking. I propose an adjustment that would standardize the h index to what its value would have been for a typical “average” networking R = 2.00 (at the border between networked and extensively networked). To do this, in general one may multiply h by k(R/2). Unadjusted analyses have k = 0. With increasing k values, the citation impact of solitary-profile scientists is heightened, while the citation impact for collaborator-profile scientists decreases.One may also wish to adjust the h is multiplied by R/2 to get R = 2h. This standardization decreases the h index of the collaborator physicists to a median R = 2h of 29 (range 23 to 38) from the original unadjusted median h = 53 (range 44 to 63). For the other highly-cited physicists in the sample, the median R = 2h increases to 71 (range 35 to 128) from the original unadjusted median h = 61 (range 37 to 116). For the sample of highly-cited scientists in medicine, median R = 2h is 86 (range 60 to 167) vs. the original unadjusted median h = 83 (range 59 to 123). Upward or downward changes for individual scientists are considerable.For example, with k = 1, R should not be confused with the total number of co-authors of a scientist during his career. Scientists who typically co-author articles with very large established networks of investigators will have low R values because the same co-authors appear again and again in their publications. Conversely, some other scientists may also count cumulatively many co-authors, but these co-authors may be different each time in each paper. The R index will classify such scientists as solitary or nuclear. Paul Erdős, a legend for the number of people he co-authored papers with, is a classic example. In ISI, Erdős has pN = 671, h = 38 and his 1I is only 11, precisely because during his life he kept moving and working with new people each time. For Erdős, one gets R = 2.71, a most solitary R value. His biographers stress exactly his solitary path where he never really settled to be part of an established network. Per Wikipedia: “He would typically show up at a colleague's doorstep and announce “my brain is open”, staying long enough to collaborate on a few papers before moving on a few days later. In many cases, he would ask the current collaborator about whom he (Erdős) should visit next.”R, i.e. the same networking profile, throughout their career  had R = 2.50 in 1987 (at the border of nuclear and solitary), and this became R = 2.06 (networked) in 1997 and R = 1.94 (extensively networked) in 2007 as he grew larger teams of co-authors in superconductor research.Many scientists have relatively stable r career . A solitnI as the number of authors who appear in at least nI papers that bear an affiliation of that specific institution. nI values for various institutions for the papers published in a single year (2003) carrying their affiliation. nI offers a simple measure to approximate the effective networking size of an institution for a given year. nI increases with increasing number of papers authored with the affiliation of interest.For a group of scientists or institution , I define nI is susceptible to clustering of extremely multi-authored papers in an institution. The institution-affiliated collaborator authors inflate the top ranks of authors that contribute to nI. Occasionally they may also carry with them some of their collaborators from other universities, further inflating nI. This phenomenon is practically limited to high-energy and particle physics. Excluding such physics papers from calculations considerably reduces nI for some institutions  as Harvard University. The same problem may arise with any Japanese institution and possibly other national institutions where many names are redundant. Close inspection of the lists of most-prolific scientists, shows this is not an issue for American or European institutions which may also have some Japanese scientists: it is not common to have two same-name prolific scientists in the same foreign institution.Another artefact can be introduced, if different scientists with the same name in the same institution cluster as the same person and inflate R also for groups and institutions as R = 10(Np)/log10(In)log, but extra caution is needed. Most institutions take R values around 3. The extremes in nI = 8, but very different number of published papers in the year 2003 (244 versus 844).One may similarly define nI rather than R. Institutions represent a mix of authors with variable types of networking behaviour. Also a single year offers only a snapshot of the career of each author. Overall, R would increase, when there are more authors affiliated with the institution who don't publish enough papers to contribute to nI. The difference in R between NHGRI and Rio de Janeiro is attributed to a much longer tail in Rio de Janeiro of authors publishing <8 papers each but who nevertheless cumulatively publish many papers. This long tail may reflect low productivity of many affiliated authors, or a different mix of scientific fields. For example, NHGRI conducts genetics research (a high-output discipline), while a university includes diverse scientific disciplines, several of which publish few papers per author per year. Disciplines with inherently low productivity don't contribute to nI, i.e. they don't increase the estimated networking size of an institution. This is appropriate, because these disciplines usually also get few citations even for excellent work, since fewer papers are published in their fields. Inactive authors also don't contribute to nI; this is also appropriate, since nI reflects the effective networking size.For large institutions, adjustment of citation impact should be performed with 1/h over nI, Q = nh/I, may be used as a measure of citation impact adjusting for the effective networking size. For example, the papers published with a University of Texas affiliation in 2003 received in 2003–2007 six times more citations than the papers published with a Tufts University affiliation, but both have Q = 5.0, suggesting that both institutions produce on average research of similar citation impact. Q values in Q = 2.3  and University of Panama has Q = 1.5 .The ratio of institutional Q>6 is outstanding, 4.5–6 very good, 3–4.5 good and <3 fair, using a time window of 5-year citation impact . However, one should be cautious with simplifications. Q may depend on the mix of disciplines involved in each institution, e.g. Harvard is excellent in Mathematics, but similar analysis on papers carrying Harvard Univ and Dept Math in the same affiliation yields Q = 3.0.For institutions that focus on common mainstream biomedical and/or physical science disciplines, one may say that Q indices. The five major medical centers affiliated with Harvard Medical School  and Harvard University Medical School (Q = 7.0). Similarity of Q values occurs despite considerable differences in the size of each medical center .One may examine also whether smaller teams or sub-institutions with a similar research orientation have similar or dissimilar l School  have Q iQ values, but discipline-related differences remain .The appropriate time window for institutional citation impact can be debated and there is no perfect choice The proposed indices provide a simple overall impression of co-authoring behaviour. This allows examining whether a scientist has been mostly a participant in large established collaborations vs. a nuclear or solitary investigator. Nuclear or solitary investigators would either work with a core of few colleagues or keep changing collaborators rather than settling within a single large collaborative network. The indices may also convey a sense of how large is the effective networking size of a group or institution. This information may complement and adjust productivity and citation metrics.Adjustment for co-authorship may correct some of the major limitations of traditional bibliometric indices h indices, as performed automatically by the Publish or Perish software  (www.harzing.com). However, sometimes this may be a very stringent adjustment. For example, the 2001 Nature paper on the initial sequencing and analysis of the human genome received 5968 citations by the end of 2007, but included 244 authors, thus each author of this truly landmark paper would get credit for only 5968/244≈24 citations. Similarly, mega-authored physics papers would typically give credit for <1 citation to each author; collaborator-profile most-cited physicists may then be re-classified as being among the least-cited physicists. Another option is to adjust citations in a paper differently depending on the position of each author, e.g. the first author may get credit for the full number of citations, while the second and the last author may get credit for half, the third may get credit for a third of the citations and so forth. However, it is difficult to reach consensus on what adjustment would be appropriate across different papers and disciplines. Many multi-authored papers simply list authors alphabetically without any connotation of relative contribution in the presented order. Moreover, such complex adjustments would be computationally cumbersome. Conversely, an advantage for the indices that I propose is their easy computation. ISI Web of Science allows the routine automated listing of all authors in a set of papers according to diminishing number of papers to which they have participated. The set of papers can be defined based on the name of the author or institution of interest. Many authors or institutions may be appraised rapidly.Alternative quantitative approaches for adjusting for co-authorship may also be considered With mounting pressure to publish-or-perish, more authors are squeezed in the same manuscript Q). Adoption of metrics that measure and adjust for co-authorship may offer a disincentive against poor authorship practices. Of course, a “collaborator” profile should not be taken to mean gift authorship. However, authors may be more accountable about who will co-author a manuscript, if they know that inclusion of more authors will decrease their own estimated scientific performance.Increasing number of authors over time does not reflect only increased work that needs to be done per paper. An evaluation focusing on studies with similar design has witnessed a significant increase over time in the number of authors required to run a similar study Conversely to gift authorship, the opposite trend, ghost authorship, typically occurs when corporate authors write manuscripts for academics and the real authors don't appear on the manuscript 1I, therefore R decreases and the impact of one's work becomes even more prominent when adjusted by R. Therefore, the proposed approach would give more credit to scientists who can create and be involved in new cross-field collaborations.The proposed metrics should not discourage true collaboration that serves the needs of science rather than gift authorship. As discussed above, the proposed metrics may downgrade the citation impact of collaborator-profile scientists only modestly, while other methods such as adjustment of citations per number of authors almost totally eliminate their citation impact. Besides established networks producing routinely high numbers of papers, new cross-field collaborations at the margin of disciplines and in newly developing fields are particularly helpful. Such collaborations increase mostly the number of new co-authors in one's CV. This does not affect I,normh in contrast to the typical “collaborator” whose impact is almost annihilated in the I,normh metric.The networking profile of a scientist may also be examined as it evolves over time. Large-scale evaluations may examine whether indeed most scientists have the same profile throughout their career. A few scientists may also exhibit a mixed networking behavior, e.g. they may have their own solitary methodological work, but they may also be involved as participants in established large collaborations. If their involvement in large collaborations exceeds a certain level, they may get the label of “collaborator”, even though they may have also a strong track record in solitary and nuclear work. Such scientists would also have a high h, 1 and InI that are roughly proportional on logarithm of counts pN is small. Finally, comparisons of scientists and institutions can be misleading, when they work on fields with different citation densities Some additional limitations should be discussed. The number of indexed papers and citations depend on the database used Automated indices should not replace critical scientific thinking and careful multifaceted evaluation of excellence. However, even with the best intentions, peer assessment may be subjective and occasionally even clearly partial. Moreover, the proposed metrics should not offer an alibi towards lack of transparency about author contributions. We should encourage the complete, transparent, and just communication of contributions for each scientist participating in any project that results in a written manuscript. Nevertheless, automated measures of performance have already made a sweeping presence across scientific fields and they are probably here to stay, so we need to find ways to improve them. Absent a perfect, transparent world on who has done what, at a minimum the proposed co-authorship and networking indices can offer some clues about how each author is networking in publishing scientific work.1I is defined as the number of authors who appear in at least 1I papers of that scientist. For a group of scientists or institution , nI is defined as the number of authors who appear in at least nI papers that bear an affiliation of that specific institution.For a single scientist, 1I requires ranking co-authors in order of decreasing number of papers that they have co-authored with the specific scientist. Calculation of nI requires ranking authors in order of decreasing number of papers they have authored where the affiliation of the specific institution is involved. The decreasing-count ranking is conceptually similar to the process used to calculate the Hirsch h index for citations Calculation of ISI Web of Knowledge includes a list of most-cited scientists in each scientific field based on the number of ISI citations they have received in the period 1981–1999. Approximately 250–300 scientists are included per scientific field. For this analysis, I ordered the scientists in the fields of Clinical Medicine and Physics alphabetically and selected every tenth name for further analysis. Evaluation of publication records and citations was performed in ISI Web of Science for the entire career of each scientist until December 2007. Filters were used to exclude from all analyses meeting abstracts, corrections, and art items since they would increase the count of papers and co-authors without increasing citations perceptibly. Subject category filters were used, when needed, for disambiguation of same-name scientists. Four Japanese scientists and 4 non-Japanese scientists with very common names were not analyzed as it might not be possible to disambiguate with sufficient accuracy which papers were theirs and which belonged to synonymous scientists working in the same scientific field.1I and R indices for the earlier phases of each scientist's career censored the publications of each analyzed scientist at the end of 1987 and 1997, respectively. If a previously solitary scientist starts publishing many papers with many co-authors and the same co-authors are involved in many papers, R may gradually decrease. R may increase if the opposite scenario occurs (networked scientist becoming solitary). However, if a scientist has already been a common collaborator in many extremely multi-authored papers, R will not increase a lot, if he switches to publishing in solitary mode: 1I is already very high and the career-wide 1I can never decrease. This solitary switch would be better captured if the specific period, rather than the whole career is considered.Analyses of h index by the number of authors in the h top-cited papers h index, 1I and nI has the advantage of being robust to the influence of sporadic papers with extreme counts. Moreover, there is no automated rapid approach currently to record and analyze the number of authors in a set of papers. For large collections of articles the time and effort would be prohibitive.Previous adjustments of scientific citation impact for co-authorship have considered adjusting the The analyzed institutions have been selected for evaluation based on the numbers of citations that papers with each institution address have received in the last decade according to Thompson Web of Knowledge Essential Science Indicators (ESI) module (available with subscription from Thomson Scientific Web of Knowledge). Data were collected for the 6 most cited institutions, for the most-cited Canadian, Japanese, and European universities , as well as for systematically sampled institutions that have the ranks 51, 101, 151, 201, 251, 301, 351,401, 451, 501, 551, 601, 651, and 701 for number of citations in the same database. Also data were collected for the 5 major academic medical centers affiliated with Harvard Medical School  and for the Department of Mathematics (Dept Math Harvard Univ) and Harvard Medical School. For the main analysis, published articles in the year 2003 were considered and their citation impact traced for the 5-year window start 2003-end 2007.h, pN, 1I, and nI.It is expected that some scientist names and institutional affiliations  may have been miscoded in the ISI databases, and this would slightly underestimate h index by (pN)0.4 characterizes the scientific work quality of an institution. The adjustment by 1/nI that I propose follows the same principle, but there are also some differences. When scientific disciplines have inherently low productivity per author and receive few citations, adjustment by 1/nI will not penalize institutions that foster such disciplines, while the cumulative number of papers may increase considerably. Conversely, adjustment by 1/nI does not penalize an institution as much as 1/(pN)0.4 when there are many low-productivity scientists in the institution publishing few papers each and the cumulative number of their papers is substantial.For institutional impact, Kinney has recently proposed


The objective of the present study was to investigate the role of the stromal cell-derived factor 1 (SDF-1)/CXCR4 axis in TNF-induced mobilization of osteoclast precursors (OCPs) from bone marrow.+/Gr-1-/lo OCPs was assessed by fluorescence-activated cell sorting. OCP migration to the SDF-1 gradient and the osteoclast forming potency were assessed in chemotaxis/osteoclastogenic assays. SDF-1 expression was assessed by real-time RT-PCR, ELISA and immunostaining in primary bone marrow stromal cells, in the ST2 bone marrow stromal cell line, and in bones from TNF-injected mice.OCPs were generated from bone marrow cells of TNF-transgenic mice or wild-type mice treated with TNF or PBS. The percentage of CD11bin vitro from wild-type mice migrated to SDF-1 gradients and subsequently gave rise to osteoclasts in response to RANKL and macrophage colony-stimulating factor. TNF reduced SDF-1 expression by ST2 cells. Bone marrow stromal cells from TNF-transgenic mice produced low levels of SDF-1. TNF treatment of wild-type mice decreased the SDF-1 concentration in bone marrow extracts and decreased the SDF-1 immunostaining of bone marrow stromal cells, and it also increased the circulating OCP numbers. The percentage of bone marrow CXCR4+ OCPs was similar in TNF-transgenic mice and wild-type littermates and in TNF-treated and PBS-treated wild-type mice.OCPs generated Systemically elevated TNF levels inhibit bone marrow stromal cell production of SDF-1 and increase the release of bone marrow OCPs to the peripheral blood. Disruption of the SDF-1/CXCR4 axis by TNF may play an important role in mediating OCP mobilization from the bone marrow cavity in chronic inflammatory arthritis. TNF is a clinically validated etiological factor in inflammatory-erosive arthritis and is known to synergize with RANKL and macrophage colony-stimulating factor (M-CSF) to enhance the differentiation of osteoclast precursors (OCPs) into bone-resorbing osteoclasts in inflamed joints ,2. Patiein vitro, and SDF-1 treatment of OCPs increases osteoclastogenesis and subsequent osteoclast bone-resorbing capacity [Stromal cell-derived factor 1 (SDF-1), a member of the C-X-C chemokine family also known as CXCL12, acts through its receptor CXCR4, and is the master chemokine that modulates trafficking of hematopoietic stem cells and progenitors ,7. Studicapacity .in vivo to control OCP mobilization, however, has not been studied.SDF-1 is primarily produced by bone marrow stromal cells, such as osteoblasts and endothelial cells . ExpressWe used TNF-transgenic (TNF-Tg) mice as a model of chronic TNF overexpression and also injected WT mice with TNF as an acute model to investigate the involvement of TNF in the SDF-1/CXCR4 axis control of OCP mobilization. We found that TNF directly inhibits SDF-1 production by bone marrow stromal cells and that it has little effect on CXCR4 expression by OCPs. A mechanism whereby TNF accelerates OCP mobilization in inflammatory erosive arthritis may therefore be to reduce bone marrow SDF-1 concentrations.Recombinant murine SDF-1, TNFα, and RANKL were from R&D Systems . Allophycocyanin–anti-murine CD11b (M1/70) was from eBiosciences . FITC–anti-murine Gr-1 (RB6-8c5), biotin–anti-CXCR4 (2B11/CXCR4) and streptavidin–PE-Texas Red conjugate were from BD PharMingen . Mouse SDF-1/CXCL12 DuoSet Development system was from R&D Systems.Cxcr4 floxed and CD11b+/Cre mice were obtained from Dr YR Zou [TNF-Tg mice in a CBA × C57BL/6 background (3647 TNF-Tg line) were obtained originally from Dr G. Kollias and were characterized by our group previously [r YR Zou  and Dr Jr YR Zou , respectTNF was given by subcutaneous injection, as described previously . The Uni6 cells) cell suspension were loaded into the upper chamber of a transwell insert. The transwell inserts were immediately moved to wells of a 24-well tissue culture dish containing different doses of SDF-1α . After 3 hours of incubation, the migrated cells in the bottom wells were collected, centrifuged and solubilized . The calcein label was read in a 96-well FluoroNunc plate  and quantified in a Gemini XS microplate spectrofluorometer  at 485 nm/530 nm.Freshly isolated bone marrow cells were cultured with M-CSF in α-modified essential medium  supplemented with 10% fetal bovine serum (Invitrogen) for 3 days, and adherent cells were used as OCPs. Assays were performed using transwell chemotaxis inserts with 5-μm-pore polycarbonate filters . OCPs were labeled with Calcein AM  at a final concentration of 2 μg/ml, and 100 μl  × 100%. The cells in the upper and lower chambers of the transwell were collected and cultured with M-CSF and RANKL to determine whether they could differentiate into osteoclasts, as described previously . These tBone marrow cells or peripheral blood were freshly isolated, stained with various fluorescence-labeled antibodies, and subjected to fluorescence-activated cell sorting (FACS) analysis, as described previously ,20.Total RNA was extracted using TRIzol reagent  and cDNA was synthesized by the RNA PCR Core Kit . Quantitative PCR amplification was performed with gene-specific primers using an iCycler iQ Multiple-Color Real-Time PCR Detection System , as described previously .SDF-1, forward 5'-GCTCTGCATCAGTGACGG TA-3' and reverse 5'-TAATTACGGGTCAATGCACA-3' ; CXCR4, forward 5'-CTTTGTCATCACACTCC-CCTT-3' and reverse 5'-GCCCACATAGACTGCCT-TTTC-3' ; TGF-β, forward 5'-TCACTGGAGTTGTACGGCAG-3' and reverse 5'-TCTCTGTGGAGCTGAAGCAA-3' ; G-CSF, forward 5'-GCTGCTGCTGT-GGCAAAGT-3' and reverse 5'-AGCCTGACAGTGACCAGG-3' ; and actin, forward 5'-ACCCAGATCATGTTTGAGAC-3' and reverse 5'-GTCAGGATCTTCATGA-GGTAGT-3'.The primer sequences are as follows: A relative standard curve method was used to calculate the amplification efficiency. The standard curve was made from six points corresponding to 10-fold cDNA dilution series. For each sample, the relative amount was calculated from its respective standard curve. Standards and samples were run in triplicate.3 and 5% sucrose in PBS. Culture supernatants were diluted in reagent diluent  and incubated for 2 hours at room temperature. The detection antibody was diluted in reagent diluent and incubated for 2 hours at room temperature. Antibody binding was detected with streptavidin-conjugated horseradish peroxidase and developed with a substrate solution (1:1 mixture of H2O2 and tetramethylbenzidine).Culture supernatants were collected from primary stromal cells and from the ST2 stromal cells. ELISA was performed with the Mouse SDF-1/CXCL12 DuoSet Development system. Ninety-six-well EIA/RIA plates  were coated with a capturing monoclonal antibody to SDF-1 and were then blocked with a mixture of 1% bovine serum albumin, 0.05% NaNA standard curve was generated for each set of samples assayed and was made from seven points of a twofold dilution series. Each standard or sample was assayed in duplicate.Long bones from mice treated with TNF or PBS were fixed in 10% phosphate-buffered formalin, decalcified in 10% ethylenediamine tetraacetic acid and embedded in paraffin wax. Deparaffinized sections were quenched with 3% hydrogen peroxide and were treated for antigen retrieval for 30 minutes. Sections were then stained with a rabbit anti-SDF-1 antibody  and immunostaining was performed.Cxcr4 floxed female mice were bred with CD11b+/Cre male mice to generate the Cxcr4+/f/CD11b+/Cre F1 generation. Cxcr4+/f/CD11b+/Cre male mice were then crossed with Cxcr4f/f female mice to produce Cxcr4f/f/CD11b+/Cre conditional knockout mice (CXCR4 CKO). Each litter comprised five to eight pups, indicating that deletion of CXCR4 in CD11b+ cells does not cause embryonic death. CXCR4 CKO mice were identified by PCR genotyping. The efficiency of CXCR4 deletion in the bone marrow CD11b+ cells was assessed by FACS analysis using FITC–anti-CD11b and allophycocyanin–anti-CXCR4 antibodies.t test for unpaired data. P < 0.05 was considered to represent statistical significance.All results are presented as the mean ± standard error of the mean. Comparisons were made by analysis of variance and Student's in vitro and were used as the source of OCPs. To confirm that these cells are enriched for OCPs, we compared their surface expression of CD11b and Gr-1 proteins, cell surface markers for OCPs [We and other workers have demonstrated that patients or mice with chronic inflammatory arthritis have an increased frequency of OCPs in peripheral blood and spleens, and that TNF promotes the release of bone marrow OCPs into the bloodstream -5. To infor OCPs , with pr+/Gr-1-/lo. After 3 days of culture with M-CSF, more than 90% of adherent bone marrow cells become CD11b+/Gr-1-/lo – cells indicating enrichment of OCPs  for 9 days on bone slices. SDF-1 did not affect osteoclast numbers, but slightly increased osteoclast resorptive activity Figure . SDF-1 hSince an SDF-1 gradient determines the direction of mobilization of hematopoietic stem cells and progenitors , we examTo examine whether TNF directly affects SDF-1 production, we treated ST2 cells – a bone marrow-derived cell line – with TNF, and found that SDF-1 expression decreased within 8 hours and with a relatively low dose of TNF (0.1 ng/ml) Figure . TNF-redTo determine whether the reduction in bone marrow expression of SDF-1 induced by TNF leads to OCP mobilization, we treated wild-type mice with TNF using a subcutaneous injection protocol shown previously to increase the OCP frequency in the blood ,20. As e+ cells is altered in TNF-Tg mice, the percentage of bone marrow CXCR4+/CD11b+/Gr-1-/lo OCPs was examined by FACS analysis. No difference was observed in the percentage of CXCR4+/CD11b+/Gr-1-/lo cells between TNF-Tg mice and wild-type littermates (data not shown). TNF pretreatment of wild-type OCPs in vitro had no effect on CXCR4 expression on the cell surface  mice. FACS analysis of bone marrow CD11b+cells from adult CXCR4 CKO mice indicate that more CD11b+ cells from CXCR4 CKO mice are CXCR4-negative (49% in CXCR4 CKO mice versus 22% in control mice; Figure Cxcr4f/f/CD11b-/Cre control mice, and assessed the blood OCP frequency by FACS analysis. No clear difference in the percentage of CD11b+/Gr-1-/lo OCPs between TNF-treated CXCR4 CKO mice and control littermates was observed (Figure To determine whether specific deletion of CXCR4 protein in the OCPs affects TNF-induced OCP mobilization, we generated d Figure .Increased numbers of OCPs have been reported in the peripheral blood of mice in several animal models of arthritis ,5 and inSDF-1-regulated cell mobilization is determined by local SDF-1 gradients and/or CXCR4 expression on target cells. Although alternation of either of these could lead to impaired cell mobilization and homing, external factor regulation of SDF-1 expression levels appears to be the major mechanism. For example, hypoxia , DNA damOur findings that TNF significantly decreases SDF-1 levels but has little effect on OCP CXCR4 expression suggest that, like most hematopoietic cell mobilizers, TNF also promotes OCP mobilization through regulation of SDF-1 rather than through CXCR4 expression. TNF-mediated OCP mobilization, however, is different from stem cell and precursor mobilization induced by SDF-1, G-CSF or other agents because TNF also has a strong stimulatory effect on OCP generation. This represents a unique pathologic situation in chronic inflammatory arthritis, in that the entire process of generation of OCPs and their egress from the bone marrow is accelerated in response to TNF. This situation leads to increased numbers of OCPs in both bone marrow and blood, whereas SDF-1 or G-CSF administration triggers a rapid release of cells from the bone marrow – and the total bone marrow cell number is consequently reduced.We do not currently know the molecular mechanisms by which TNF inhibits SDF-1 production. SDF-1 is regulated at both transcriptional and post-translational levels ,21. We fin vivo. G-CSF is another cytokine that downregulates SDF-1 mRNA expression in osteoblasts [in vitro is not mediated by G-CSF. Furthermore, the SDF-1 promoter does not contain binding sites typically present in the other CXC chemokine promoters, especially for NF-κB, interferon regulatory factor recognition elements or NF-IL6, which are associated with transcriptional activation in response to proinflammatory extracellular signals, such as TNF, IL-6 or interferons [TGFβ at concentrations as low as 0.01 ng/ml decreases SDF-1 mRNA expression in stromal cells , implyineoblasts . TNF diderferons . These din vivo. We have attempted to answer this question using mice with CXCR4 specifically deleted in OCPs by generating CXCR4 CKO mice via crossing CXCR4 floxed mice [+ cells have no CXCR4 surface expression in these CXCR4 CKO mice (Figure cxcr4 in bone marrow CD11b-positive cells.The present study did not provide a direct association between TNF-reduced SDF-1 production and OCP mobilization xed mice  with CD1xed mice . We injee Figure , suggeste Figure . Our resin vivo needs to be further confirmed using a model where SDF-1 concentration in the bone marrow is maintained in the presence of TNF. Since rheumatoid arthritis and other forms of inflammatory bone disorders are chronic diseases, however, multiple factors may contribute to promote OCP release from the bone marrow. For example, we have demonstrated that TNF-stimulated OCP formation could increase the OCP pool in bone marrow and push cell egression [in vitro. They speculated that this could increase the ability of OCPs to enter the bloodstream [The importance of TNF-mediated reduction in SDF-1 production in increased OCP mobilization gression . Kindle odstream . It has odstream . TNF stiodstream , and thiOur findings demonstrate that TNF directly inhibits bone marrow stromal cells to produce SDF-1, which is associated with increased release of OCPs from the bone marrow. The SDF1/CXCR4 axis therefore may not only control hematopoietic cell homing, but may also contribute to the accelerated OCP mobilization in inflammatory arthritis where systemic TNF levels are elevated.CKO = conditional knockout; ELISA = enzyme-linked immunosorbent assay; FACS = fluorescence-activated cell sorting; FITC = fluorescein isothiocyanate; G-CSF = granulocyte colony-stimulating factor; IL = interleukin; M-CSF = macrophage colony-stimulating factor; NF = nuclear factor; OCPs = osteoclast precursors; PBS = phosphate-buffered saline PCR = polymerase chain reaction; RANKL = receptor activator of nuclear factor-B ligand; RT = reverse transcriptase; SDF-1 = stromal cell-derived factor 1; Tg = transgenic; TGFβ = transforming growth factor beta; TNF = tumor necrosis factor.The authors declare that they have no competing interests.LX had full access to all data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study design was by LX, QZ, EMS, and BFB. LX, QZ, and RG were responsible for acquisition of data. Analysis and interpretation of data were performed by LX, QZ, RG, EMS, and BFB. LX, EMS, BFB, and QZ prepared the manuscript. Statistical analysis was performed by QZ and RG.


In vitro, TNF-α is reported to activate human polymorphonuclear neutrophils (PMN), inducing responses such as phagocytic activity, degranulation and oxidative metabolism. Biological responses to TNF-α are initiated by its binding to specific cell surface receptors, and various studies have shown that the major TNF receptor species on PMN is the 75 kDa receptor. To verify the suggestion that the receptor binding domain includes the region close to the N-terminus of the TNF-α molecule, four TNF-α derivatives termed muteins were constructed, using a synthetic cDNA fragment substituting the N-terminal 3–7 selected hydrophilic or hydrophobic amino acids in the original TNF-α genomic DNA. Binding of muteins to PMN was assessed using monoclonal antibodies recognizing either the 55 kDa (p55) or the 75 kDa (p75) TNF receptor subtypes. Blocking by muteins of anti-p75 antibody binding to PMN was as expected from their N-terminal amino acid composition and hydrophilic properties. Hydrophilic muteins competed well with anti-TNF receptor antibodies for binding to the p75 receptor. In contrast, hydrophobic muteins were unable to block anti-p75 binding. Similarly, degranulation, chemiluminescence or enhancement of the PMN response to specific stimuli by the muteins correlated with the hydrophilic properties of the muteins. The significance of these observations in relation to the molecular structure of TNF-α is discussed.Tumour necrosis factor-α (TNF-α) has been implicated as an important inflammatory mediator.


Administration of DMXAA to mice with established transplantable tumours elicits rapid vascular collapse selectively in the tumour, followed by extensive haemorrhagic necrosis mediated primarily through the production of TNF-α. In this report we have investigated the synthesis of TNF-α mRNA in hepatic, splenic and tumour tissue. Co-administration of thalidomide with DMXAA increased anti-tumour activity and increased intra-tumoural TNF-α production approximately tenfold over that obtained with DMXAA alone. Thalidomide increased splenic TNF-α production slightly but significantly decreased serum and hepatic levels of TNF-α induced with DMXAA. Lipopolysaccharide (LPS) induced 300-fold higher serum TNF-α than did DMXAA at the maximum tolerated dose, but induced similar amounts of TNF-α in spleen, liver and tumour. Splenic TNF-α activity induced with LPS was slightly increased with thalidomide, but serum and liver TNF-α levels were suppressed. Thalidomide did not increase intra-tumoural TNF-α production induced with LPS, in sharp contrast to that obtained with DMXAA. While thalidomide improved the anti-tumour response to DMXAA, it had no effect on the anti-tumour action of LPS that did not induce a significant growth delay or cures against the Colon 38 tumour. The increase in the anti-tumour action by thalidomide in combination with DMXAA corresponded to an increase in intra-tumoural TNF-α production. Co-administration of thalidomide may represent a novel approach to improving selective intra-tumoural TNF-α production and anti-tumour efficacy of DMXAA. © 1999 Cancer Research Campaign


Nine patients received a 24 h continuous intravenous infusion ranging from 1.0 × 105 U/m2 to 3.0 × 105 U/m2; 14 patients received a 5 day continuous intravenous infusion ranging from 0.5 × 105 U/m2/day to 3.0 105 U/m2/day. Twenty one of 23 patients responded with marked increases in serum PLA2 activity that were detectable 3 h after the beginning of the rh-TNF infusion and reached maximum levels at 18 h with a mean increase of 16.2-fold. In patients receiving a 5 day rh-TNF infusion, the highest levels of PLA2 were observed after the first day of infusion. Serum PLA2 activity declined continuously to 2.9-fold above baseline at the end of the infusion. A significant correlation was noted between the dose of infused rh-TNF and the maximum increase in PLA2 activity. To our knowledge, this is the first time that an association between intravenous TNF administration and induction of circulating PLA2 in man has been established.We have examined the effects of intravenous infusion of recombinant human tumour necrosis factor (rh-TNF) on serum activity of phospholipase A


Heme oxygenase-1 (HO-1) is a stress response enzyme, which catalyses the breakdown of heme into biliverdin-IX alpha, carbon monoxide and ferrous iron. Under situations of oxidative stress, heat stress, ischemia/reperfusion injury or endotoxemia, HO-1 has been shown to be induced and to elicit a protective effect. The mechanism of how this protective effect is executed is unknown.HO-1 induction with cobalt protoporphorin (Co-PP) dose-dependently protected against apoptotic cell death as well as neutrophil-mediated oncosis in the galactosamine/endotoxin  shock model. Induction of HO-1 with Co-PP dose-dependently protected against neutrophil-mediated oncosis as indicated by attenuated ALT release and TNF-mediated apoptotic cell death as indicated by reduced caspase-3 activation. HO-1 induction did not attenuate Gal/ET-induced TNF-alpha formation. Furthermore, a similar protective effect with the high dose of Co-PP was observed when animals were treated with Gal/TNF-alpha.HO-1 induction attenuates apoptosis and neutrophil-mediated oncosis in the Gal/ET shock model. However, the protective effect is not due to the reduction of TNF-alpha release or the attenuation of neutrophil accumulation in the liver sinusoids. Heme oxygenase (HO) catalyzes the oxidative cleavage of Fe-protoporphyrin-IX yielding equimolar amounts of biliverdin-IX alpha, free divalent iron, and carbon monoxide (CO) . Among tSalmonella abortus equi endotoxin  or 20 micrograms/kg murine TNF-alpha . Some animals were pretreated with 5 or 15 mg/kg of cobalt-protoporphyrin  18 h before Gal/ET. The following parameters were measured as previously described: caspase-3 activity [Male C3Heb/FeJ mice  were treated i.p. with 700 mg/kg D-galactosamine  in combination with 100 micrograms/kg activity , neutropWestern blot and immunohistochemical analysis indicated that cobalt protoporphyrin (Co-PP) dose-dependently induced HO-1 expression in hepatocytes and nonparenchymal cells, especially Kupffer cells. To investigate if increased HO-1 expression affected apoptotic or oncotic cell death, animals were treated with galactosamine/endotoxin . It was previously shown that Gal/ET treatment induces TNF-alpha formation, which activates and recruits neutrophils into the liver vasculature  and causTo investigate if the beneficial effect was due to HO-1 induction, animals were additionally treated with the HO-1 inhibitor tin-protoporphyrin (Sn-PP). Treatment with Sn-PP alone did not affect liver injury after Gal/ET (Table Although the TNF response after Gal/ET could not explain the protective effect of Co-PP, the potential protection of HO-1 induction against Gal/TNF-induced liver injury was investigated. Gal/TNF caused massive caspase-3 activation (Table Unexpectedly, the massive HO-1 induction with increased formation of antioxidants in Kupffer cells did not attenuate TNF formation. In contrast, high doses of the antioxidant dimethyl sulfoxide eliminated TNF formation  and glutInduction of HO-1 in non-parenchymal cells and in hepatocytes with Co-PP dose-dependently protected against TNF-mediated apoptotic cell death and subsequent neutrophil-induced injury to hepatocytes. The protection is not due to inhibition of TNF-alpha formation or attenuation of neutrophil activation. HO-1 induction increases the resistance to both forms of cell death in hepatocytes.


The expression of tumour necrosis factor alpha  and its two distinct receptors, TNF-R p55 and TNF-R p75, was assessed by immunocytochemistry in 28 primary breast cancer and three reduction mammoplasty specimens . Expression of TNF-alpha or TNF-R p75 was not detectable in normal breast tissue or in non-malignant breast tissue adjacent to the tumours. By contrast, TNF-R p55 was expressed by occasional stromal cells in normal tissue. TNF-alpha was expressed focally in 50% of the tumours studied, being largely localised to macrophage-like cells in the stroma. TNF-R p55 was expressed by a population of stromal cells in all the tumours examined, and a varying proportion of neoplastic cells in 75% of these tissues. TNF-R p75 was detected in about 70% of the tumours, immunoreactivity being confined mainly to cells in the stroma. In this preliminary study there was no association between the above cytokine parameters and such measures of tumour biology as lymph node status, tumour grade, proliferative activity or degree of angiogenesis. However, there was a correlation between the expression of TNF-R p55 by blood vessels and the number of leucocytes present.