Background. Premature infants are commonly subject to intestinal inflammation. Since the human small intestine does not reach maturity until term gestation, premature infants have a unique challenge, as either acute or chronic inflammation may alter the normal development of the intestinal tract. Tumor necrosis factor (TNF) has been shown to acutely alter goblet cell numbers and villus length in adult mice. In this study we tested the effects of TNF on villus architecture and epithelial cells at different stages of development of the immature small intestine. Methods. To examine the effects of TNF-induced inflammation, we injected acute, brief, or chronic exposures of TNF in neonatal and juvenile mice. Results. TNF induced significant villus blunting through a TNF receptor-1 (TNFR1) mediated mechanism, leading to loss of villus area. This response to TNFR1 signaling was altered during intestinal development, despite constant TNFR1 protein expression. Acute TNF-mediated signaling also significantly decreased Paneth cells. Conclusions. Taken together, the morphologic changes caused by TNF provide insight as to the effects of inflammation on the developing intestinal tract. Additionally, they suggest a mechanism which, coupled with an immature immune system, may help to explain the unique susceptibility of the immature intestine to inflammatory diseases such as NEC. Intestinal inflammation is a common occurrence for premature infants. After a relatively protective intrauterine environment, the newborn is abruptly exposed to nonmaternal antigens and abnormal bacterial flora in the intensive care setting . Even no Salmonella infection of the intestinal tract [NEC is predominantly a disease of premature infants, primarily affecting infants born at the shortest gestations , 5. The al tract  and can al tract . HoweverConsidering that (1) susceptibility to NEC appears to be developmentally-dependent, (2) premature infants have frequent exposure to intestinal inflammation, and (3) TNF induced inflammation can have developmental dependent effects on the intestinal epithelium, we tested whether TNF induces other developmentally dependent changes in the small intestine. To better understand how different exposures of inflammation would affect the developing intestinal tract, we examined components of intestinal architecture following several different types of exposure to TNF. In the following studies, we show that both acute and chronic exposure to TNF have developmental-stage dependent effects on the developing small intestine.−/−, TNFR2−/−, and TNFR1−/−2−/− mice were purchased from The Jackson Laboratory. CD-1 mice were purchased from Charles River Laboratories. All genetically modified mice were maintained on a C57BL/6J background and C57BL/6J was used as wild type comparisons. For acute TNF experiments, C57BL/6J or CD-1 mice were injected intraperitoneally at the indicated ages with 0.5 μg/gbw TNF (PeproTech) and maintained for 8 hours separated from mothers and without feeds at 33°C in a humidified incubator (Petiatric.com). The distal 1/3 of the small intestine was harvested and isolated for ileal samples. Tissues were fixed by snap freezing or Carnoy solution; tissues prepared for immunohistochemistry were paraffin-embedded and sectioned at 5 μm. For chronic TNF experiments, CD-1 mice were given weekly intraperitoneal injections with 0.5 μg/gbw TNF. Injections began at age P7 and ended one week prior to euthanasia. During injections, mice were housed under normal conditions at the animal care facility at the University of Iowa. On the final day of experimentation, tissue was harvested as described above. All animal experiments were performed according to protocols approved by the Institutional Animal Care and Use Committee at The University of Iowa.C57BL/6J, TNFR1Ileal sections were stained with H&E (Sigma-Aldrich). In an attempt to minimize sectioning variability, all sections were obtained from the center of the intestinal sample and only areas with full villi were included. In each sample used for measurement, at least 3 areas were counted to minimize sectioning variances. Measurements were obtained at each timepoint from at least five separate animals. A total of at least 20 consecutive villi from 3 separate areas per animal were analyzed in each experimental group. Villus length and surface area measurements were taken with a 10x objective  from the tip of the villus to the entrance of the crypt opening. Villus length was measured by drawing a bisecting line through the center of the villi. Surface area was measured by drawing a line around the exterior of each structure. Villus epithelial cells were counted with a 60x objective  from the entrance of the crypt opening to the beginning of the curve at the villus tip. Intestinal sections from at least five animals for a total of at least 70 villi per animal were analyzed for each experimental group. To detect Paneth cells, slides were stained with Alcian Blue/Periodic Acid Schiff stain (Sigma-Aldrich). Cells were quantified with a 60x objective  by a single blinded investigator. Intestinal sections from at least five animals were analyzed for each experimental group and at least 100 crypts were counted per animal. All data were obtained using a Nikon NiU microscope using Nikon Elements software (Nikon).β-actin in each sample. The 2ΔΔ-CT method was used to compare gene expression levels between samples.Ileal samples were homogenized using a TissueLyser LT (Qiagen), then cleared, and boiled as previously described . ProteinRates of apoptosis on histological specimens were determined by in situ oligo ligation DNA fragmentation assay , as we have previously reported .All data are representative of at least three independent experiments. Statistical significance of differences was assessed with one-way analysis of variance (ANOVA). Post-test comparisons between groups were made using Holm-Sidak's multiple comparisons test. All statistics were performed using Prism software (Graph Pad). Minimum level of significance was set at <0.05 and error bars designate standard error of the mean.We have previously shown that goblet cell numbers in the murine ileum increase in a developmental-dependent manner during the first four weeks of life . To deteWe have previously shown that TNF has an age-dependent effect on intestinal mucus production and secretion ; howeverP < 0.0001)  .P = 0.03)  to detect DNA fragmentation and compared to controls. Mice exposed to acute TNF had significantly more apoptosis than age-matched controls ( = 0.03) .−/−, TNFR2−/−, and TNFR1−/−2−/− mice were given intraperitoneal injections of TNF and their ileal villus measurements were compared to knockout controls. TNF induced villus blunting in wild type and TNFR2−/− mice, but not mice lacking TNFR1. This demonstrates a requirement for TNFR1, and no role for TNFR2. Similarly, TNF treatment induced loss of villus area only in wild type and TNFR2−/− mice, again demonstrating a requirement for the presence of TNFR1. However, only wild type mice showed a significant loss in epithelial cell number  signaling , 16. To l number .Our findings indicate that the degree of TNF-induced villus blunting varies depending on the stage of development. To test whether these effects were due to differences in ileal maturity, rather than ontogenic differences in TNFR1 expression, ileal tissue was harvested from wild type mice at various ages and examined by Western blot analysis for expression of TNFR1. No significant differences in TNFR1 expression were detected during development . This fiSince our data demonstrate a developmentally dependent effect of acute TNF on the architecture of the ileum, we investigated the effects of chronic exposure. To accomplish this, mice were treated with TNF once a week beginning on P7 until one week prior to euthanasia. In this fashion, we developed three groups of mice: control mice, mice exposed to a single dose of TNF one week prior to examination , and mice exposed to weekly TNF treatments beginning on P7, and ending with the last dose occurring one week prior to euthanasia . Using this methodology, we examined the ilea of mice from each group for villus length. Similar to the acute exposure, mice exposed to chronic TNF showed a significant loss in villus length. Mice treated with brief exposure (B-TNF) had significantly shorter villi than controls, and mice treated with chronic exposure (C-TNF) had significantly shorter villi than those with brief exposure . To deteP < 0.0001).As chronic TNF (C-TNF) caused developmentally dependent villus blunting, we next investigated its effects on villus surface area and epithelial cell counts. While acute TNF treatment induced decreases in villus area and epithelial counts at P14 and 21 , brief  (P < 0.0P = 0.002). However, there was no difference in Paneth cell numbers in mice treated with brief or chronic treatments (−/− mice demonstrating a requirement for TNFR1 (P = 0.035).Our lab and others have described a key protective role for Paneth cells in the immature intestinal tract , 18–20. eatments . To deteor TNFR1  (P = 0.0Premature infants are routinely subject to intestinal inflammation, both as a result of normal exposure to new environmental factors and through pathologic situations such as intestinal perforations and necrotizing enterocolitis. However, the ramifications of inflammation during development of the intestinal tract are not fully understood. In this study, we describe the normal growth patterns of intestinal villi. We next provide evidence that acute TNF exposure can blunt normal villus height during development. We also demonstrate that chronic TNF exposure can blunt height even more significantly. This blunting occurred through a TNFR1-mediated mechanism. Since TNFR1 expression remains constant through development of the small intestine, TNF-induced villus blunting may be dependent on downstream TNF signaling targets that are differentially expressed during development. Lastly, we show that acute TNFR1-mediated signaling also induces a significant decrease in the number of granule containing Paneth cells. Taken together, these morphologic changes caused by TNF exposure may help to explain why this cytokine plays a prominent role in the development of NEC in the immature intestine.Our data demonstrate that both acute and chronic TNF exposures induce significant changes in the immature ileum. TNF mediates distinct physiological effects through two separate transmembrane receptors, TNFR1, and TNFR2 , 26. PhyThe embryogenesis of the gastrointestinal tract is nearly identical in all mammals; however, the stage of development when birth occurs can vary dramatically between species . While hIn our experiments to study the effects of chronic inflammation on the intestine, we modeled two types of chronic TNF treatments. Brief dosing examined mice one week following a single TNF treatment, and chronic dosing examined mice one week following the last of multiple weekly TNF treatments. Our data show that both types of chronic exposure to TNF induced villus blunting at P14, P21, and P28. However, it was interesting to note that while chronic exposure to TNF induced loss of villus height at all ages, P14 and P21 mice had significantly increased villus area and epithelial cell counts with this exposure. This suggests a conformation change from thin long villi to shorter, wider villi in the face of chronic inflammation. This may be a compensation mechanism to place the villus epithelial layer closer in proximity to the lamina propria where the majority of adaptive immune cells reside. Interestingly, this trend was not seen in P28 mice, again demonstrating developmental stage-dependent effects of TNF on the small intestinal architecture.We and others have recently reported a loss of Paneth cells in infants who developed NEC , 31, andIn summary, we have shown that chronic exposure of the immature ileum to TNF induces not only functional changes but architectural changes as well. These findings may have important implications for elucidating the pathophysiology of NEC. Our recently proposed “bottom up” model of NEC hypothesizes that bacteria invade the intestinal tissue principally through the crypts, rather than through the villus tips as previously thought . In this


It represents the most frequent genetic cause of end-stage renal disease in the first three decades of life. NPH is characterized by the dysfunction of sensory cilia which explains the complexity of the NPH phenotype. It can be associated with retinitis pigmentosa (Senior-Løken syndrome), mental retardation and ataxia (Joubert syndrome), skeletal anomalies (Jeune syndrome), or To date, recessive mutations causing NPH have been identified in more than eighteen different genes (NPHP1-NPHP18). Their gene products localize at the primary cilia-centrosome complex, along the cilium as intraflagellar transport proteins and are important in signaling pathways downstream of cilia including Wnt signaling, Shh signaling and the DNA damaged response pathway.TRAF3IP1 in patients presenting with NPH, retinitis pigmentosa, skeletal defects of the pelvis, hexadactyly and hepatic fibrosis. TRAF3IP1 encodes IFT54 which is involved in the anterograde transport along the primary cilia.Using whole and targeted exome sequencing, we identified novel protein altering mutations in TRAF3IP1 knock-down cells confirmed the observed defects in microtubule organization. Furthermore, sphere formation assays as well as the pronephros of elipsa zebrafish embryos showed defects in epithelialization.Besides its known function in cilia we demonstrate that TRAF3IP1 act as a key regulator of cytoplasmic microtubule organization. Mass spectrometry analyses as well as pull-down experiments demonstrated that mutations in TRAF3IP1 lead to an altered binding to actin and microtubule associated proteins. Immunofluorescence stainings using patient fibroblasts as wells as mIMCD3 TRAF3IP1 affect both ciliary and non-ciliary functions of TRAF3IP1 which can provide an explanation for kidney tubules morphogenesis defects as well as the other disease phenotypes e.g. retinal, skeletal and hepatic defects.Altogether our findings demonstrate that NPH causing mutations of


Theoretical Domain Framework (TDF) provides an integrative conceptual model for assessing barriers to change. The TDF questionnaire has been applied by healthcare researchers in several countries for assessing barriers to performance improvement implying its possible usefulness in behavior modification.The purpose of this study is to review published literature on barriers to change using specific tools created without adhering to TDF theoretical framework and to investigate whether these tools incorporate domains and constructs of the TDF questionnaire.Selection criteria We included all papers that investigated barriers to change in health-related behavior or changing practice in health-related workplaces regardless of study design. Only papers published in English were included. We included in our review manuscripts that included the questionnaires either as attachment or in the content of the article. Duplicate studies were eliminated from the review by comparing authors’ names, type and location of study.We conducted a systematic literature review. We searched for papers in MEDLINE OVIDSP, PubMed, CINAHL, PsycINFO (that includes full text from PsycARTICLES), EBSCO Databases: Academic Search Complete and Google Scholar from beginning until April 2014. Data abstraction Study review and data abstraction were conducted by two reviewers working independently. Disagreements were resolved by discussion and referring unresolved issues to a third person.Of 552 papers initially identified, 50 papers were selected for final review. The average number of items in the questionnaires assessing barriers was 19.2. In total the 50 questionnaires included 961 items, out of which 96.8% (930 out of 961) were covered by TDF. The “Environmental Context and Resources”, “Beliefs about consequences” and “Social Influence” were the domains of TDF that most frequently studied in the selected papers: 30.2%, 12.4% and 10.3%, respectively.This study confirms the validity of TDF framework to assess barriers to change: only 2.2% of 961 items identified were not covered by the TDF questionnaire. However, unclear boundaries between domains and the difficulty in identifying the appropriate construct were two issues identified that may be worth considering to improve the framework.


The 4 dengue serotypes (DENV) are mosquito-borne pathogens that are associated with severe hemorrhagic disease. DENV particles have a lipid bilayer envelope that anchors two membrane glycoproteins prM and E. Two E-protein monomers form head-to-tail homodimers and three E-dimers align to form “rafts” that cover the viral surface. Some human antibodies that strongly neutralize DENV bind to quaternary structure epitopes displayed on E protein dimers or higher order structures forming the infectious virus. Expression of prM and E in cell culture leads to the formation of DENV virus-like particles (VLPs) which are smaller than wildtype virus particles and replication defective due to the absence of a viral genome. There is no data available that describes the antigenic landscape on the surface of flavivirus VLPs in comparison to the better studied infectious virion.A large panel of well characterized antibodies that recognize epitope of ranging complexity were used in biochemical analytics to obtain a comparative antigenic surface view of VLPs in respect to virus particles. DENV patient serum depletions were performed the show the potential of VLPs in serological diagnostics.VLPs were confirmed to be heterogeneous in size morphology and maturation state. Yet, we show that many highly conformational and quaternary structure-dependent antibody epitopes found on virus particles are efficiently displayed on DENV1–4 VLP surfaces as well. Additionally, DENV VLPs can efficiently be used as antigens to deplete DENV patient sera from serotype specific antibody populations.This study aids in further understanding epitopic landscape of DENV VLPs and presents a comparative antigenic surface view of VLPs in respect to virus particles. We propose the use VLPs as a safe and practical alternative to infectious virus as a vaccine and diagnostic antigen.The online version of this article (10.1186/s12985-018-0970-2) contains supplementary material, which is available to authorized users. T = 1 icosahedral lattice [Dengue viruses (DENV) are mosquito-borne flaviviruses responsible for dengue fever and dengue hemorrhagic fever , 2. DENV lattice . It is u lattice .In this study we describe in detail the properties of epitopes present on DENV VLPs of all 4 serotypes using a large panel of well-defined human mAbs and immune sera from dengue patients. We directly compare the antigenic features of DENV VLPs to whole virions and explore their use as tools in serologic assays. Our results show the equivalence between viruses and VLPs in a setting that is particularly relevant for flavivirus vaccine development, diagnostics and understanding the difference between virus and VLPs.Vero-81 cells were maintained at 37 °C as a monolayer in Dulbecco’s modified Eagle’s medium  supplemented with 5% fetal bovine serum (FBS), 1% non-essential amino acids, 100 U/ml penicillin and 100 μg/ml streptomycin. Culture supernatants of DENV1 WestPac-74, DENV2 S-16803, DENV3 CH53489 and DENV4 TVP-376 virus strains were used to determine antibody binding and neutralizing activity of depleted and undepleted serum. Purified DENV virus preparations were obtained according to previously described protocols  .The DENV virus-like particles (VLPs) were produced and kindly provided by The Native Antigen Company, Kidlington, UK. In short: recombinant dengue virus-like particles consisting of DENV prM and E proteins were transiently expressed in suspension culture adapted HEK293 cells. Three days post transfection culture supernatant was cleared by centrifugation and concentrated by tangential flow filtration. In a first step VLPs were purified by a 2-step discontinuous sucrose gradient with 20% and 40% sucrose densities. After a 6 h spin at 25,000 rpm in a SW28 rotor at 10 °C the 20%–40% interphase was harvested by needle-stick. As a second purification step ion exchange chromatography  was used in negative mode once. VLPs were further purified by size exclusion chromatography (Toyopearl HW-65F) which also provided exchange of buffers to storage buffer. Purified DENV1–3 VLPs were stored in 10 mM sodium phosphate, 20 mM sodium citrate, 154 mM sodium chloride, pH 7.4. DENV4 VLPs were stored in Dulbecco’s phosphate buffered saline (DPBS) pH 7.4 containing 30% sucrose. VLP samples were stored at − 80 °C.Purified VLP samples were subjected to sodium dodecyl sulphate polyacrylamide electrophoresis (SDS-PAGE) and analyzed by western blot (WB) and Coomassie Brilliant Blue (CBB) staining. 500 ng of DENV VLP or purified DENV virus  were loa100 ng/well of 1M7 or 4G2 mAb was coated onto High-binding Microlon plates (Greiner) in 0.1 M bicarbonate buffer pH 9.6 overnight at 4 °C. Plates were washed 3 times with PBS + 0.1% Tween-20 and blocked with PBS + 3% skim milk + 0.05% Tween-20 for 1 h at 37 °C. Next, plates were washed and incubated with serially diluted purified virus or VLPs (of 2 separate preparations) in blocking buffer for 1 h at 37 °C. After washing, the 1 M7 coated plates were incubated with the indicated serially diluted mouse derived mAbs and the 4G2 coated plates were incubated with indicated serially diluted human mAbs  were coated with 100 ng/well of 4G2 mAb in 0.1 M bicarbonate buffer pH 9.6 overnight at 4 °C. The plates were blocked with PBS + 3% skim milk + 0.05% Tween-20 for 1 h at 37 °C. Next, the plates were washed 3 times with PBS + 1% Tween-20 and incubated with 1:10 diluted virus culture supernatant in blocking buffer for 1 h at 37 °C. After washing, the plates were incubated with depleted or undepleted DT000 or DT168 serum  for 1 h at 37 °C. Next, the plates were washed and incubated with 1:2500 anti-human IgG-AP conjugated (Sigma) for 45 mins at 37 °C. The plates were washed and developed with AP-substrate (Sigma) and the absorbance was measured at 405 nm.50 values  calculated using GraphPad Prism software.The neutralizing capacity of depleted and undepleted DT000 serum was determined by flow based neutralization assay as previously described , 20. In Discharged copper 400 mesh formvar carbon coated grids  were loaded with 15 μl of purified DENV VLPs for 5 mins at room temperature. The grids were washed in MilliQ water and stained for 30 s with 2% uranyl acetate. Excess uranyl acetate was removed by filter paper. The grids were finally air-dried at RT and observed with a LEO 910 transmission electron microscope (Zeiss).DENV1–4 prM-E sequences were expressed in mammalian HEK 293 suspension cultures and purified by sucrose gradient and ion-exchange chromatography. Purified VLP fractions were subjected to SDS-PAGE and analyzed by Coomassie stain CBB; Fig. and WestNegative staining followed by transmission electron microscopy (TEM) revealed that the DENV VLPs are fairly monodispersed, but heterogeneous in morphology and size Fig. . The VLPTo compare antibody epitopes displayed by DENV VLPs and infectious virions, we analyzed the binding of a large panel of well-characterized human and mouse derived mAbs Table  to seriaDue to the experimental setup, binding signals of the same mAb to virus or VLP cannot be quantifiably compared. However, it is possible to get a relative insight into the differences in epitope exposure and abundance between virus and VLP. For this, we normalized the binding of each mAb to a well-characterized TS, quaternary epitope mAb of each of the 4 serotypes. By comparing the relative binding of each mAb between virus and VLP, one can demonstrate that certain epitopes are better represented on virus particles or VLPs. Future studies are needed for conclusive evidence, it does however give an indication on the relative epitope exposure.Binding of each mAb was normalized to 1F4 (DENV1), 2D22 (DENV2), 5 J7 (DENV3) and 5H2 (DENV4)  with DENV VLPs of each serotype individually. DT000 has been infected with multiple DENV serotypes > 20 years ago and has been shown to efficiently neutralize all 4 serotypes . DENV VLThe immunogenic properties of DENV VLPs have been analyzed in animal models by several groups. However, little is known about E-protein organization on the surface of VLPs , 11. VLPT = 1 icosahedral lattice, different from the 90 E-dimers found on mature virus particles organized in a T = 3 symmetry [DENV1–4 VLPs produced in mammalian cells efficiently display epitopes that have mapped on virus particles. TS and CR monoclonal antibodies isolated from different DENV patients with varying infection history bound to the VLPs indicating that native epitopes are present on the VLPs. In the low resolution cryo-EM structural data available on flavivirus virus-like particles or subviral particles, 30 E-dimers are assembled in a symmetry . Our anaThe DENV VLPs were found to have a similar size distribution as the TBEV subviral particles. With particle diameters of ~ 29–34 nm, the VLPs are considerably smaller in size than natural virus particles (~ 50 nm) , 22. TheHuman mAb 1F4 is DENV1 specific and although it only binds the virus and not the E-monomer, its footprint has been mapped within one E-monomer and not across neighboring E-proteins within the homodimer . DespiteWe used 1F4, 2D22, 5 J7 and 5H2 to normalize the binding of all the other mAbs to both virus and VLP, allowing for a relative comparison between epitope availability on virus vs VLPs. Relative to these mAbs we see that the EDIII binding mAbs 12C1.5 and 3H5 bind better to VLPs, indicating that the EDIII might be more exposed on VLPs. The quaternary CR EDE epitopes are relatively better presented on DENV2–3 virus particles. In particular EDE1-C10 binding has a strong preference for virus particles, due to the absence of binding to VLPs of all serotypes. It remains unclear why C10 does not bind VLPs, while the other EDE mAbs, that share a very similar footprint, bind efficiently.The maturity of virus particles and VLPs affects epitope display as exemplified by the fusion loop binding CR mAb 4G2. During virus replication, the pr peptide associates with the fusion loop in E, shielding it from premature low-pH induced fusion with host cell membranes . Our anaThe footprints of many mAbs have been mapped on dimers generated from soluble monomeric E proteins. Soluble E monomers crystallize into dimers and do not contain prM. Even though it is assumed that the crystallized dimers are structurally similar to E-dimers found on virus particles, they might differ when part of complex multiprotein complexes on VLP envelopes. Future studies should focus on DENV VLP protein structures to answer these questions.The VLPs and virus particles were captured by mAbs 4G2 and 1 M7, suggesting a bias for fusion loop exposed particles. However, using other capturing mAbs, the bias would be skewed towards particles displaying that specific epitope. Using other well-characterized mAbs, we have shown that DENV VLPs display an epitope landscape very similar to that found on virus particles. Depletion studies using VLPs as a depletion antigen translate this finding to polyclonal sera of DENV infected patients. Secondary infected serum was efficiently depleted from all TS and CR (non)-neutralizing antibodies. Serum depletions are usually performed using infectious purified virus antigen conjugated to microbeads. However the use of VLPs has practical benefits over the use of purified antigen. Issues of infectious virus production and purification and virus leaching into the serum during handling are not present when using VLPs. Additionally, VLPs are more easily genetically adapted and are therefore valuable tools in flavivirus pAb and mAb mapping and serology.Flavivirus VLP based vaccines are amongst the leading candidates in ongoing vaccine studies. Understanding the structure of VLPs is essential for interpreting the antibody response in vaccinees. VLPs also have potential value as diagnostic reagents. Besides, VLPs can be produced as a byproduct of natural infection. Therefore, the structure of VLPs also becomes important from the standpoint of virus assembly. By exploiting antibodies and insights high resolution structure of dengue virions, this study aids in further understanding the antigenic landscape of DENV VLPs and presents a comparative antigenic surface view of VLPs in respect to virus particles.Additional file 1:Normalized antibody binding to DENV virus particles and VLPs. The binding of each mAb to virus (black bars) or VLPs (grey bars) within every DENV serotype was normalized to 1F4 (DENV1), 2D22 (DENV2), 5 J7 (DENV3) and 5H2 (DENV4). (PDF 220 kb)


The ability of human immunodeficiency virus (HIV) to avoid recognition by humoral and cellular immunity  is well-documented, but the strength of the immune response needed to cause such a viral escape remains poorly quantified. Several previous studies observed a more rapid escape of HIV from CD8 T cell responses in the acute phase of infection compared to chronic infection. The rate of HIV escape was estimated with the help of simple mathematical models, and results were interpreted to suggest that CD8 T cell responses causing escape in acute HIV infection may be more efficient at killing virus-infected cells than responses that cause escape in chronic infection, or alternatively, that early escapes occur in epitopes mutations in which there is minimal fitness cost to the virus. However, these conclusions were challenged on several grounds, including linkage and interference of multiple escape mutations due to a low population size and because of potential issues associated with modifying the data to estimate escape rates. Here we use a sampling method which does not require data modification to show that previous results on the decline of the viral escape rate with time since infection remain unchanged. However, using this method we also show that estimates of the escape rate are highly sensitive to the time interval between measurements, with longer intervals biasing estimates of the escape rate downwards. Our results thus suggest that data modifications for early and late escapes were not the primary reason for the observed decline in the escape rate with time since infection. However, longer sampling periods for escapes in chronic infection strongly influence estimates of the escape rate. More frequent sampling of viral sequences in chronic infection may improve our understanding of factors influencing the rate of HIV escape from CD8 T cell responses. Due to the absence of a proof-reading capability, human immunodeficiency virus (HIV)-1 (HIV hereafter) has a relatively high average mutation rate of 2–4on cycle ,4,5; howon cycle . Given a–2 days, ) and lared cells ), HIV ised cells ,12,13. Oed cells ,15.While HIV clearly escapes from both cellular and humoral immune responses, frequent sampling of the escape dynamics suggested that escape from virus-specific CD8 T cell responses occurs earlier than from antibody-mediated responses ,17,18,19pe rates ,25. It rpe rates . More repe rates ,30. HereData. Experimental data used in this paper are from previous publications [ications ,25. In sications . We re-aModel. We used a previously suggested mathematical model of viral escape from a single CTL response [response ,22,23,25response ).Statistics. When fitting mathematical models to experimental data, it is important to estimate confidence intervals for the model parameters. One widely-used approach is bootstrap, in which either experimental data or residuals (difference between model prediction and the data) are sampled with replacement [m mutant and w wild-type sequences. A beta distribution is a continuous approximation of the binomial distribution, and the beta distribution has been used to calculate confidence intervals for proportions [lacement . Two typbest fit . In our portions .Programming. Model fits of the data were done in Mathematica 11 using a routine FindMinimum. All codes are available from the author upon request. An example of a Mathematica notebook illustrating the strategy of the sampling method to estimate escape rates is available as a supplement to this paper.t, respectively, and Several previous studies have shown that the kinetics of viral escape from a single CD8 T cell response can be described by the logistic equationape rate ,22,23,25ape rate . Becausef(t)=f0f0ls [10−5 .n time points. Note that we ignored constant terms for the binomial distribution since these do not matter during likelihood maximization. Parameters of the model including the escape rate Data on viral escape are generally given as the percent of escape variant in the viral population at different time points with a number of viral sequences obtained. For example, at time 10 days post symptoms, 15 viral sequences were obtained, and 3 of these contained mutated epitopes, making the frequency of the escape variant approach  in whichkelihood . As disckelihood .n time points, resulting in a bootstrap sample. In our analyses, we used the routine Random in Mathematica. Due to randomness, the resulting bootstrapped sample will have both wild-type and escape variants present at multiple time points. The model can then be fitted to these bootstrapped data using the likelihood approach according to Equation  to the ,wi+1/2) . This prWhile the sampling method was specifically designed to estimate escape rates from the data which cannot be fit by simple mathematical models  anOur results so far suggest that data modifications were not likely responsible for the observed decline in the estimated escape rate with time since infection. Therefore, it is important to understand whether other features in the data could be responsible for this declining trend. Previous studies have highlighted that the frequency of sampling in experimental data have changed over time, starting from weekly sampling and changing to monthly/bi-monthly sampling . Such a Several lines of evidence suggest that CD8 T cell responses play an important role in control of HIV replication ,35,36. EWe have proposed a new method of sampling sequence data to estimate escape rates in situations when direct fitting of simple deterministic mathematical models to the data fails. An alternative approach to estimating escape rates from sparsely sampled data would be to use more mechanistic stochastic models of HIV dynamics and evolution; for example, models that take into account virus effective population size, as well as the rate of HIV mutation and recombination . HoweverUsing the sampling method, we have shown that the observed phenomenon of a decline of the rate of HIV escape with time since infection is not the result of modification of data to accommodate fits of simple models of viral escape. However, the method suffers from a great sensitivity to the time frequency of sampling in the data, since increasing the time intervals between measurements naturally decreases the estimated escape rate. Furthermore, the inclusion of more data at later time points in which wild-type virus is nearly lost will also bias average estimates found by sampling downwards, which further limits the applicability of this method for the estimation of escape rates. Specifically, if for the first escape in ntervals . While fntervals . Finallyntervals .Overall, our results so far suggest that the current state of data on HIV escape does not allow us to make solid inferences on the escape rate without making strong assumptions either about the data or about the underlying dynamics of the virus. It appears that the way forward is to generate novel data in which patient sampling occurs at regular intervals over the course of a few months of infection, perhaps with the use of novel techniques such as deep sequencing. Consistent temporal sampling rather than deep sampling is likely to be more beneficial for determining if the rate of HIV escape from T cell responses declines with time since infection .


In this study, therefore, annual categories of field- and time-normalized citation scores  are used to study the citation histories of papers. As our dataset, we used all articles published in 2000 and their annual citation scores until 2015. We generated annual sequences of citation scores (e.g.,  Bibliometrics is the backbone of scientometrics; most of the studies in scientometrics are based on publication and citation data Vinkler . BibliomHowever, there is a gap in the literature with respect to studies analyzing citation distributions in more detail. In this study, therefore, annual categories of normalized citation scores  are used to study the citation histories of papers . Most of these studies have dealt with specific distributions of citations. Good examples are sleeping beauties. These are papers which generate little or no citation impact over a long time period (e.g. 10 years), before they start to generate considerable impact. According to Mir and Ausloos , the phePhysical Review archive, covering 120 years of physics. They found the following three types of citation curve: “(1) Marathoners: publications which start fast or slow, reach a moderate peak and keep improving the ratio of received citations, or at least keep being relevant over prolonged amounts of time by manifesting a slow decline or a plateau. Marathoners in effect tend to age slowly, or not at all, and are also more numerous and varied than sprinters. (2) Sprinters: publications with fast, even extremely fast and high peak, and equally rapid ageing. These publications are immediately relevant for their community, and rapidly forgotten thereafter, and are fewer in number in the APS dataset. (3) Middle-of-the-roads: publications with a citation history close to the global average citation history, that is, a fast but moderately peaking curve with a gradual decay over time” (p. 1043).Recently, the citation histories of papers have been investigated in more detail by two studies. Baumgartner and Leydesdorff  exploredi = 1, 2,… are publications, j = 1, 2,… are citing years, and f = 1, 2,… are fields. Here, field delineations based on disciplinary OECD minor codes are used. The OECD field definitions can be found at http://www.oecd.org/science/inno/38235147.pdf. We selected the 2 digit level scheme.This study uses standard impact scores in bibliometrics, namely field- and time-normalized citation impact scores  Vinkler . These dCij denotes citations received by publication i in year j, and Efj denotes mean (received) citations of all publications in field f and year j . Nfj is the number of cited publications in field f and year j (Nfj is based on non-zero citations), and f = f(i) means a certain field of a given publication. The indicator follows the standard approach in bibliometrics with both field- and time-normalized citations  publication years. If DNICij < 1, the impact is lower than the average.If n papers. The observed citations Xi received by paper i are ranked in descending order, X1* and Xn* denote the citations of the most and least frequently cited papers, respectively. Set the initial values β0 = 0 and v0 = n, where n is the number of papers. β1 is defined as the mean citations; v1 is defined by the comparison Glänzel and Schubert  introducβ0 ≤ β1 ≤ … and v0 ≥ v1 ≥ …. The kth class is defined by the pair of threshold values ; the number of papers belonging to this class amounts to vk−1 − vk.Thus, we obtain series The CSS method can be used to classify the papers within certain fields into four impact classes: “poorly cited”, “fairly cited”, “remarkably cited”, and “outstandingly cited”. Then, for example, the share of outstandingly cited papers can be determined for a set which includes papers from different fields . However, the method can not only be used to classify single papers, but also to certain aggregates of papers. For example, Bornmann and Glänzel  propose ij. Thus, we do not use the citation counts of single papers, but the annual field- and time-normalized scores for the classification. Consider the set n papers published in various disciplines. We used the OECD major codes to compare the results of six broad disciplines: natural sciences, engineering and technology, medical and health sciences, agricultural sciences, social sciences, and the humanities. The broad disciplines are aggregates of OECD minor codes.In this study, we use the CSS method for classifying the papers into four citation impact classes based on DNICij scores (of paper i in a given year j) are ranked in descending order . In other words, we have a sequence of 16 scores for every publication with values between 0 = poorly cited and 4 = outstandingly cited. Two examples of sequences are shown in Fig. In a yearly time series The statistical analyses of the data in the current study are based on the strategy proposed by Brzinsky-Fay et al.  for the The bibliometric data used in this study is from an in-house database developed and maintained by the Max Planck Digital Library  and derived from the Science Citation Index Expanded (SCI-E), Social Sciences Citation Index (SSCI), and Arts and Humanities Citation Index (AHCI) prepared by Clarivate Analytics, formerly the IP & Science business of Thomson Reuters. The study is based on 790,698 articles published in 2000 and the corresponding citations across 16 citing years (with 2000 as the first citing year). Since many papers have been assigned to more than one OECD minor code, 161,302 papers appear between two and six times in the dataset . We decided to let the papers appear multiple times in the dataset, since the papers might have different citation distributions in the disciplines.Table The sequence analyses which we describe in the “Table The CSS method was initially proposed by Glänzel and Schubert . Since tTable Similar field-specific differences in distributions of CSS scores are also reported by Glänzel  and AlbaTable In accordance with the prevalence of skewed citation distributions in the sciences and the dominance of non-cited and little cited papers, the list of sequences in Table Figure With regard to the differences between the disciplines, Table In order to obtain a better overview of the sequences in the dataset, two further analyses have been done. The analyses condense the sequences still further. The first condensation which is shown in Table entclass1pt{minimaiods 46.8%. This gn = 909) are constantly on the outstandingly cited level over a period of 16 years. Most of these papers have been published in the natural sciences (n = 417) and medical and health sciences (n = 383). There is only one such paper in the humanities and 6 such papers in agricultural sciences. Constant performers on the level of fairly cited (1) or remarkably cited (2) are very rare in the dataset. In total, only 37 papers are constantly fairly cited and 3 papers constantly remarkably cited.The results in Table The second condensation which is shown in Table In Table In recent years, a development has become apparent in bibliometrics for citation impact no longer to be reduced to the times cited information, but analyzed more specifically. For example, the citation context is considered in the bibliometric analyses to have more specific information on the impact of publications and how cited publications are perceived  are constantly on the outstandingly cited level. These might be the few papers which significantly drive scientific progress . Based on annually normalized citation scores, we generated annual sequences of CSS scores (e.g. y et al. . This stThis study was a first attempt to use sequence analyses with bibliometric data. We think that this statistical approach can lead to interesting insights in citation histories. The application of this approach can be further extended beyond the analyses in our study. For example, a focus of future research could be on the comparison of sequences and the measurement of differences between two sequences. According to Brzinsky-Fay et al. , the so-


Thoracic ossification of the ligamentum flavum (TOLF) is characterized by ectopic bone formation in the ligamentum flavum and is considered to be a leading cause of thoracic spinal canal stenosis and myelopathy. However, the underlying etiology is not well understood. An iTRAQ proteomics was used to reveal the involvement of inflammation factors in TOLF. TNF-α is a pro-inflammatory cytokine implicated in the pathogenesis of many human diseases. Protein profiling analysis showed that the protein level of TNF-α increased in the ossified ligamentum flavum of TOLF, which was confirmed by western blot. The effects of TNF-α on primary ligamentum flavum cells was examined. Cell proliferation assay demonstrated that primary cells from the ossified ligamentum flavum of TOLF grew faster than the control. Flow cytometry assay indicated that the proportions of cells in S phase of cell cycle of primary cells increased after TNF-α stimulation. To address the effect of TNF-α on gene expression, primary cells were derived from ligamentum flavum of TOLF patients. Culture cells were stimulated by TNF-α. RNA was isolated and analyzed by quantitative RT-PCR. G1/S-specific proteins cyclin D1 and c-Myc were upregulated after TNF-α stimulation. On the other hand, osteoblast differentiation related genes such as Bmp2 and Osterix (Osx) were upregulated in the presence of TNF-α. TNF-α activated Osx expression in a dose-dependent manner. Interestingly, a specific mitogen-activated protein kinase ERK inhibitor U0126, but not JNK kinase inhibitor SP600125, abrogated TNF-α activation of Osx expression. This suggests that TNF-α activates Osx expression through the mitogen-activated protein kinase ERK pathway. Taken together, we provide the evidence to support that TNF-α involves in TOLF probably through regulating cell proliferation via cyclin D1 and c-Myc, and promoting osteoblast differentiation via Osx. Ossification of ligamentum flavum (OLF) of the spine is characterized by ectopic bone formation in the ligamentum flavum, and it is more likely to affect Asian population, including the Chinese, Japanese and Korean –5. It haDue to the differences in patient population of TOLF, some researches tend to define TOLF as a disease with a genetic susceptibility component. For example, among the Han Chinese population, two novel variants in the BMP-2 gene has been identified in TOLF patients . In a caAn association between levels of basic metabolic elements and TOLF has been studies ,14. The Effect of inflammatory processes on new bone formation has drawn more and more attention recent years. A tightly controlled inflammatory phase has been observed after fracture, which triggers repair cascade and is critical for bone remodeling ,24. InteIn order to acquire a comprehensive and quantitative protein profile, the isobaric tags for relative and absolute quantitation (iTRAQ) has been developed to become an approach appropriate for investigating proteomic changes during various developmental stages .The aim of the current study was to utilize iTRAQ-based quantitative proteomics to explore the causes of TOLF. We sought to assess the involvement and possible mechanism of the pro-inflammatory cytokine TNF-α in thoracic ossification of the ligamentum flavum.Patients were recruited in the Department of Orthopedics, Peking University Third Hospital. This study was approved by the Ethics Committee of Peking University Third Hospital, and complied with the Declaration of Helsinki . Written informed consent was obtained from each participating patient. As for the TOLF patients, normal ligamentum flavum in adjacent levels from the same patient served as the self-control group for proteomic study. TOLF and control ligaments were aseptically collected from patients during the operation. The proteins of ossified and normal ligamentum flavum were extracted.After protein extraction, the protein concentration was determined by following the manufacture’s protocol with Braford method . Each sample 200 μg was added into 4 μl Recuding Reagent, then mixed with 2 μl Cysteine-Blocking Reagent. 100 μl Dissolution Buffer in iTRAQ kit was added. The solution in the bottom was discarded. After three times repetition of this step, a new collection tube was used to mix 4 μg trypsin with the acquired solution. The 50 μl Dissolution Buffer5 was combined with the above solutions, reaching 100 μl digested sample. The samples were labeled with iTRAQ reagents by adding the contents of the iTRAQ Reagent-8Plex Multiplex Kit, and the samples were then labeled with iTRAQ following the manufacture’s protocol (Applied Biosystem). As a result, proteins with iTRAQ ratios ≥ 1.5 were considered to be up-regulated, and proteins with iTRAQ ratios ≤ 0. 67 were considered to be down-regulated.3 pieces, washed twice with PBS, and then digested with 0.25% trypsin  for 1 h at 37°C followed by 200 U/ml type I collagenase  for 4 h at 37°C. The sections were cultured in DMEM  containing 10% FBS, 100 U/ml penicillin, and 100 μg/ml streptomycin (Gibco) at 37°C and 5% CO2. Explant-derived cells were passaged by 0.25% trypsin digestion. Passage 2 cells were used for the stimulation experiments. Photos of cells were taken by Olympus CKX41.The primary cells of ligamentum flavum were obtained by the tissue explant method as previously described . BrieflyProtein was purified by acetone precipitation from the cell lysates as previously described . Briefly4 cells/well overnight. Cell proliferation was determined using the Cell Counting Kit-8 (CCK8) kit  according to the manufacturer’s instructions. At each time point, the cells were stained with 10μl CCK8 dye in 90μl culture medium for 2 h at 37°C. Then microplate reader  was used to measure the absorbance at 450 nm. All experiments were performed in triplicates.The primary ligamentum flavum cells from the control normal site or the ossified site of TOLF patients were seeded in 96-well culture plates at initial density of 1×105–106 ligamentum flavum cells were collected, washed three times with ice-cold PBS, and fixed with 70% ice-cold ethanol overnight. Before analysis, the cells were stained with 7-aminoactinomycin D (7-AAD) (20 μg/ml−1) (BD) in the presence of RNase (100 μg/ml−1). After no more than 30 min, the cells were collected and filtered by 300 meshes, followed by analysis on a FACSAria II flow cytometer . Modfit LT 3.2 software  was used to calculate the percentage of phases of cell cycle.The cell cycle phases of cultured cells were determined using flow cytometry. A total of 10ΔΔCt method and were normalized to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) levels.Primary ligamentum flavum cells was stimulated by TNF-α  for 24 hr before harvest. Total RNA was extracted from cultured cells using TRIzol reagent  as previously described . The purAll qPCR experiments were repeated for at least three times. The data was reported as the mean ± standard deviation (S.D.). Comparisons were made between groups by Student’s t test, and p<0.05 was considered to be significant.iTRAQ-based quantitative proteomics was utilized to investigate protein profile of ligamentum flavum in patients with TOLF. These were evaluated by the fold change cutoff ratio ≥1.5 for up-regulation and ≤0.67 for down-regulation. There were totally 282 proteins identified to be differentially expressed. Among these proteins, ten inflammation-related factors were identified, including Tumor necrosis factor, Insulin-like growth factor II, Insulin-like growth factor-binding protein 5, Prostaglandin reductase 1, Latent-transforming growth factor beta-binding protein 3, Transforming growth factor beta-1, Neutrophil elastase, Serum amyloid A-4 protein, Protein S100-A9, and Prostaglandin-H2 D-isomerase. Several reasons led us to focus on the effect of TNF-α on TOLF in the current study. First of all, our preliminary data showed that the serum TNF-α of patients with TOLF was significantly higher compared with the control (data not shown); Secondly, our preliminary results of gene Microarray indicated that the gene expression level of TNF-α also increased in the ossified ligamentum flavum in TOLF (data not shown), supporting our proteomic observation in this study; Thirdly, previously reports have suggested an important role of TNF-α in fracture healing in transgenic animal model  or a proTo examine primary cell growth, the primary cells of ligamentum flavum from TOLF patients were obtained by the tissue explant method as described in Method Section. Cells were cultured for seven days, and cell growth of primary cells from the control normal site and the ossified site in TOLF were compared. The primary cells in two sites were long and spindle-shaped. We found that the level of TNF-α protein increased in the ossified ligamentum flavum, and that primary cells of the ossified ligamentum flavum grew faster. Since the proliferation of cells is mainly regulated by the cell cycle, next we asked what was the effect of TNF-α on cell cycle, especially on S phase. Primary cells of the ossified ligamentum flavum were cultured in the absence or presence of TNF-α. Flow cytometry assay were used to examine the cell cycle. As indicated in Next we determined the effect of TNF-α on G1/S-specific protein cyclin D1 and c-Myc. Primary ligamentum flavum cells derived from TOLF patients were cultured and treated as indicated with recombinant human TNF-α  for 24 hr. Total RNA was isolated and measured by real time RT-PCR. As shown in The level of TNF-α protein increased in TOLF , and it Furthermore, we asked which pathway was involved in TNF-α induced Osx gene expression. To explore molecular mechanisms of TNF-α effect on Osx expression in primary ligamentum flavum cells, we used a loss-of-function approach to examine possible pathways involved. The following selective inhibitors were used: U0126 is a specific ERK inhibitor in mitogen-activated protein kinase pathway, and SP600125 is a specific inhibitor for JNK kinase pathway. Primary ligamentum flavum cells were treated with 100 ng/ml of TNF-α. Different inhibitors were added in the culture medium as indicated. As shown in TOLF is characterized by pathological ectopic ossification in ligamentum flavum that generally consists of fibrous tissues. It has been considered to be a leading cause of thoracic spinal stenosis and can occur in multiple segments . AlthougiTRAQ analysis uncovered 282 proteins which were identified to be differentially expressed in TOLF, including ten inflammation-related factors such as Tumor necrosis factor, Insulin-like growth factor II, Insulin-like growth factor-binding protein 5, Prostaglandin reductase 1, Latent-transforming growth factor beta-binding protein 3, Transforming growth factor beta-1, Neutrophil elastase, Serum amyloid A-4 protein, Protein S100-A9, and Prostaglandin-H2 D-isomerase. We focused on the effect of TNF-α on TOLF in this study.TNF-α is a pro-inflammatory cytokine implicated in the pathogenesis of many human diseases. TNF-α interacts with its receptor to function through several pathways including the activation of nuclear factor kappa-B (NF-kB) involved in inflammation . It is kOsx-null mice lacked bone completely [in vitro. TNF-α induced the expressions of Bmp2 and Osx in primary ligamentum flavum cells from TOLF Click here for additional data file.


The role of TIPE2 in type 2 diabetes mellitus (T2DM) remains unknown, although TIPE2 plays key roles in preserving inflammatory homeostasis.  Tumor necrosis factor-α (TNF-α), high-sensitivity C-reactive protein (hsCRP), interleukin 6 (IL-6), and other related biometabolic parameters were detected using a nephelometer or by ELISA. Differentiated THP-1 cells were exposed to siTIPE2 and TIPE2 adenovirus.  TIPE2 expression was measured by Western blotting and real-time polymerase chain reaction (RT-PCR) in peripheral blood mononuclear cells (PBMCs) isolated from T2DM patients and healthy controls, and tumor necrosis factor-α, IL-6, and hsCRP concentrations but positively correlated with HbA1c and LDL-C in T2DM patients. High glucose treatment (50 mmol/L) can upregulate the expression of TIPE2 and cytokine secretion in differentiated THP-1 cells. siTIPE2 infection exacerbated the increased TNF-α and IL-6 concentrations in differentiated THP-1 cells under high glucose conditions (50 mmol/L), while infection with TIPE2 adenovirus reversed the increased TNF-α concentration.  TIPE2 was significantly increased in PBMCs from T2DM patients compared with those from healthy controls and was negatively correlated with serum TNF-α production. The present study indicates that TIPE2 may participate in T2DM by regulating TNF- Intensiglycemia , and it iabetics , 5. Insuα, high-sensitivity C-reactive protein (hsCRP), IL-1β, and IL-6 are increased in the tissues and serum of T2DM patients [α takes part in obesity-related systemic insulin resistance by suppressing insulin receptor tyrosine kinase activity in the adipose tissue and skeletal muscle [α prevents the insulin-dependent tyrosine phosphorylation of insulin receptor substrate 1 (IRS-1) and the insulin receptor in adipocytes and myeloid 32D cells [α diminished glucose transporter 4 (GLUT4) expression and protein kinase B (Akt) activity [α is a key arbitrator of insulin resistance in obesity, and it could be a target in obesity-induced insulin resistance in individuals with T2DM. The tumor necrosis factor-α-induced protein 8 (TNFAIP8) family was distinguished not long ago; they are generated after TNF-α stimulation and NF-κB actuation [α-mediated signaling and diabetes.Inflammatory markers such as TNF-patients –10. TNF-l muscle . Some ev2D cells . Furtheractivity . Every octuation , 8, and α-induced protein 8-like 2 (TIPE2), an innovative gene belonging to the TNFAIP8 family, suppresses the liberation of proinflammatory cytokines, such as TNF-α, IL-4, IL-12, and IFN-γ, to maintain immune homeostasis [κB and activating protein 1 activation and that TIPE2-deficient cells are hyper-reactive to Toll-like receptor (TLR) and T cell receptor (TCR) actuation [TIPE2 production and that of TNF-α and IL-6 to illuminate the precise roles of TIPE2 in T2DM.Tumor necrosis factor-eostasis . TIPE2 ictuation –16. Morectuation –21. The We enrolled 46 T2DM patients who attended Zibo Central Hospital  and fulfilled the 1999 criteria of the World Health Organization for T2DM. The study excluded patients with type 1 diabetes, gestational diabetes, secondary diabetes, or severe liver and kidney disease. In addition, 30 age- and sex-matched blood donors who did not have any chronic or metabolic diseases were randomly recruited as a control group. All the patients signed an informed consent form prior to study participation. The characteristics of all the subjects are summarized in 2 at 37°C. Macrophage-like cells were differentiated from parental THP-1 cells by induction with phorbol-12-myristate-13-acetate  for 24 h and were then infected with TIPE2 adenovirus and siTIPE2 or treated with culture medium containing glucose  for 24 h.THP-1 cells  were cultured in RPMI1640 medium containing 10% fetal bovine serum in a humidified atmosphere of 5% COα and IL-6 levels in cell culture supernatants were measured.TIPE2-specific siRNA and a nonspecific negative control were purchased from Life Technologies . The TIPE2-expressing adenoviruses (Ad-TIPE2) were enlarged, titrated in 293 cells, and cleansed by cesium chloride techniques as detailed prior . TransfeThe following biometabolic parameters were analyzed in T2DM patients: fasting glucose, HbA1c, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, and hsCRP. The serum was separated and prepared according to standard protocols. The serum levels of fasting glucose, LDL-C, HDL-C, total cholesterol, and triglycerides were detected using standard commercially available, colorimetric-based enzymatic kits . HbA1c was estimated using an HPLC method . Concentrations of hsCRP were measured using a nephelometer .α and IL-6 concentrations in serum from T2DM patients or in culture supernatants of differentiated THP-1 cells were determined by ELISA  based on the manufacturer's directions. Serum samples were placed in a 96-well ELISA microplate that was prepared with captured antibody. The captured antibody-bound cytokines were determined with biotin-conjugated anti-TNF-α and anti-IL-6 antibodies and horseradish peroxidase- (HRP-) conjugated avidin. The reaction plates were read within 30 min at 450 nm using a microplate reader . TNF-α and IL-6 concentrations were determined based on a standard curve according to the manufacturer's instructions. Each sample was assayed in triplicate wells.TNF-6) using Trizol , and the samples were treated with RNase-free DNase  to remove genomic DNA contamination according to the manufacturer's instructions.Peripheral blood from healthy controls was placed in sodium citrate-containing cell preparation tubes. PBMCs were isolated by gradient centrifugation over Lymphoprep  and washed twice with phosphate-buffered saline (PBS). Total RNA was then extracted from PBMCs (5 × 10μg) was reverse transcribed to cDNA with oligo (dT) primers with the RT system based on the manufacturer's directions. PCR was performed in a 25 μl volume with 2.5 μl of cDNA, 5 mM of MgCl2, 0.2 mM of dNTPs, 0.2 mM of each primer, 1.25 U of AmpliTaq DNA polymerase, and 1 μl of 800 X SYBR Green I with the Mx3000 Multiple Quantitative PCR System . RNA quality was ascertained by gel electrophoresis, and negative controls without RT were incorporated.Total RNA  technique. The Ct value of the housekeeping gene (18S rRNA) was removed from the Ct value of the target gene to gain the ΔCt. The normalized fold change in the target mRNA expression was shown as 2μg proteins from each sample was loaded onto SDS-PAGE gel. Proteins were transferred to nitrocellulose membranes. The membranes were incubated with 5% BSA in Tris-buffered saline containing Tween-20 for 1 h at room temperature, followed by incubation with anti-TIPE2 antibodies  overnight at 4°C. Specific reaction was detected using IRDye-conjugated second antibody for 1 h incubation and visualized using the Odyssey infrared imaging system . Quantification of image density in pixel was performed by using the NIH ImageJ software .The TIPE2 protein expression was detected by Western blotting. PBMCs and THP-1 were quickly harvested, rinsed thoroughly with PBS, and then homogenized on ice in lysis buffer. After centrifugation for 10 min at 4°C, the supernatant was used for Western blot analysis. Protein concentration was measured by a bicinchoninic acid protein assay kit . A total of about 60 TIPE2 mRNA expression level and the protein expression of TNF-α, IL-6, or other parameters in T2DM patients. All the statistical analyses were performed using GraphPad Prism 5.0 . Two-tailed P < 0.05 was considered significant.The significance of differences between groups was determined by a two-tailed nonparametric test. Pearson's correlation analysis was performed to determine the strength of the linear relationship between TIPE2 mRNA expression was higher in PBMCs from 46 T2DM patients compared to those from 30 healthy controls. There was a substantial escalation in the mean TIPE2 mRNA expression in T2DM individuals in contrast to the controls , suggesting that elevated TIPE2 expression could be initiated by escalated levels of inflammatory elements  and IL-6 , suggesting that TIPE2 may inhibit TNF-α and IL-6 production  for 24 h. However, the concentrations of TNF-α and IL-6 were obviously increased in the culture supernatants of differentiated THP-1 cells exposed to 50 mmol/L glucose  and TIPE2-specific siRNA (siTIPE2) to change the expression of TIPE2. Under high glucose conditions (50 mmol/L), siTIPE2 infection exacerbated the increased TNF- Figures , and Ad-ntration , while Antration . These rTIPE2 mRNA and metabolic parameters in T2DM patients. And then, a positive correlation was found between TIPE2 mRNA expression and HbA1c  and LDL-C  . These outcomes imply that TIPE2 could play a protective part in the occurrence of T2DM.We analyzed the association between  Figures , which a+ and CD8+ T cell-mediated immune reactions were supplemented in the TIPE2−/−mice in contrast to the control mice, indicating the critical part of TIPE2 in T cell-mediated immunity [TIPE2 is an innovative, necessary negative regulator of natural and adaptive immunity that is needed to preserve immune homeostasis and inhibit deleterious inflammatory reactions , 23. TIPimmunity .TIPE2 mRNA expression was substantially declined in individuals with SLE in contrast to healthy individuals and was negatively correlated with the SLE disease activity index (SLEDAI) and myxoma resistance protein 1 (MX1) mRNA expression levels in SLE participants [TIPE2 mRNA expression was substantially diminished in PBMCs from individuals with chronic hepatitis B in contrast to healthy people, and TIPE2 expression was negatively correlated with blood levels of ALT, AST, and total bilirubin (Tbil) and with HBV load in these patients [TIPE2 mRNA expression in PBMCs from pediatric patients with asthma in contrast to healthy individuals was negatively linked to serum IL-4 and IgE levels and to eosinophil count [The dysregulation of TIPE2 has been discovered to resolve heterogeneous human immunological and inflammatory diseases. It has been stated that icipants . Researcicipants . Xi et apatients . A studyil count .TIPE2 mRNA expression was markedly increased in T2DM patients compared with controls, indicating that TIPE2 participates in T2DM.However, Jia et al. showed that TIPE2 expression was highly upregulated in PBMCs from the chronic rejection group than in those from the healthy control group . In addiβ-cells and severely impair their insulin secretion [TIPE2 mRNA expression is negatively linked with the levels of hsCRP, an inflammatory factor, suggesting that increased TIPE2 expression may be caused by inflammatory elements in the early stage of T2DM, which would account for the increased TIPE2 mRNA expression in T2DM patients in contrast to healthy individuals.In T2DM patients, some danger signals, such as systemic free fatty acid (FFA) flux, hyperglycemia, microhypoxia, ER stress, and higher mitochondrial ROS, can activate macrophages and other immune cells to make greater amounts of proinflammatory cytokines and various chemokines, which recruit additional macrophages , 25. In ecretion . As an iα, IL-4, IL-12, and IFN-γ [β and TNF-α, are escalated in the serum and tissues of diabetics [α is a vital regulatory molecules of insulin resistance in T2DM; the neutralization of TNF-α might represent a strategy for combating obesity-induced insulin resistance in individuals with T2DM. In accordance with previous research, our study showed that the mRNA level of TIPE2 was negatively linked with TNF-α and IL-6 in T2DM. In vitro experiments showed that siTIPE2 infection exacerbated the increased TNF-α and IL-6 concentrations, while Ad-TIPE2 infection reversed the increased TNF-α concentration in differentiated THP-1 cells under high glucose conditions (50 mmol/L). TIPE2 may be induced by the proinflammatory cytokines TNF-α and IL-6 and then inhibit the subsequent release of cytokines, especially TNF-α, in a negative feedback loop. We speculate that TIPE2 may participate in the pathogenesis of T2DM by modulating TNF-α production. Our study also identified a positive relationship between TIPE2 mRNA expression and HbA1c and LDL-C levels. HbA1c is an indirect marker of dyslipidemia that points to long-term glycemic control; it has been connected to cardiovascular issues in T2DM patients [TIPE2, which belongs to the TNFAIP8 family, suppresses the liberation of proinflammatory cytokines, such as TNF-nd IFN-γ . Inflammiabetics , and TNFpatients –30. TherTIPE2 mRNA and protein expression levels in PBMCs from T2DM patients and healthy individuals and scrutinized the connections between TIPE2 mRNA expression and the levels of inflammatory factors and metabolic parameters in vivo and in vitro. TIPE2 mRNA and protein expression was upregulated in T2DM individuals and was negatively correlated with hsCRP, IL-6, and TNF-α, but positively correlated with HbA1c and LDL-C in T2DM patients. In vitro, high glucose treatment (50 mmol/L) can upregulate the expression of TIPE2 and cytokine secretion in differentiated THP-1 cells. siTIPE2 infection exacerbated the increased TNF-α and IL-6 concentrations, while Ad-TIPE2 infection reversed the increased TNF-α concentration in differentiated THP-1 cells under high glucose conditions (50 mmol/L). These outcomes imply that TIPE2 may take part in T2DM by regulating TNF-α production.Thus, in the current evaluation, we contrasted


Haemophilus influenzae and Streptococcus pneumoniae which are major bacterial pathogens in acute exacerbations of COPD. In addition, we found that a PAFr antagonist decreased the adhesion of both respiratory bacterial pathogens to non-cigarette exposure control levels. This highlights the possibility that epithelial receptors, that are upregulated in response to cigarette smoke, could be targeted to specifically block chronic bacterial infections of the lower respiratory tract. In this commentary, we explore the question of whether adhesion to a temporally-upregulated host receptor is a common event in chronic bacterial disease, and as such, could represent a putative therapeutic target for blocking infection by respiratory and other pathogens.Expression of the platelet-activating factor receptor is upregulated in the respiratory epithelium of smokers and chronic obstructive pulmonary disease patients. We have recently determined that increased expression of PAFr correlates with higher levels of adhesion to human bronchial epithelial cells by non-typable  Lung disease remains a major cause of death globally after heart disease and stroke . BacteriHaemophilus influenzae (NTHi) and Streptococcus pneumoniae are the main bacterial species involved in triggering AECOPD [Non-typable g AECOPD , 3. The g AECOPD , 5. Exprg AECOPD , 7.S. pneumoniae to bronchial epithelial cells is enhanced by exposure to cigarette smoke extract [S. pneumoniae utilise a receptor which is temporally-upregulated in response to a specific external stimulus, in this case, tobacco smoke. We also determined that a PAFr antagonist, WEB-2086 (Apafant), reduced the adhesion of both respiratory bacterial pathogens down to non-cigarette exposure control levels [S. pneumoniae.In a new publication, we report that attachment of both NTHi and  extract . We iden extract . PAFr is extract . While hPAFr, when bound to its natural ligand, platelet activating factor (PAF), has been implicated in the pathophysiology of anaphylaxis, bronchial hyper-responsiveness, endotoxin shock, respiratory bacterial infections, skin diseases, and disorders of the central nervous system . In addiS. pneumoniae?Use of a non-constitutively expressed surface receptor for colonisation appears to be opportunistic. The question therefore arises: Is this phenomenon unique to PAFr and respiratory pathogens NTHi and Pseudomonas aeruginosa, a major bacterial pathogen in cystic fibrosis, also express ChoP [P. aeruginosa results in upregulation of PAFr expression which is inhibited in the presence of PAFr antagonist WEB-2086 [Escherichia coli of its own ileal epithelial cell receptor, carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) [Some strains of ess ChoP . InfectiWEB-2086 . InstancWEB-2086 , 20. ICACEACAM6) .Streptococcus pyogenes [Streptococci by enhancing receptor presentation.It is also evident that infection by one pathogen can increase the level of a receptor available for another pathogen. For example, it was reported recently that influenza A viral (IAV) infection of human lung epithelial cells results in heightened expression of cellular adhesins which in turn promotes streptococcal infection . A previpyogenes . Thus, iS. pneumoniae [S. pneumoniae was blocked in the presence of anti-PAFr antibodies [S. pneumoniae [S. aureus, S. pneumoniae, and H. influenzae [In a similar manner, respiratory syncytial virus (RSV) infection of respiratory epithelial cells has been shown to elevate the expression of ICAM-1, PAFr and CEACAM1, which correlated with increased adhesion of NTHi and eumoniae . NTHi bitibodies . An addieumoniae . Rhinovifluenzae . The uprfluenzae . It has fluenzae . Furtherfluenzae , viral iS. pneumoniae. PAFr antagonists including WEB-2086 are well tolerated [Our recent findings  should bolerated –30 and tIn conclusion, blocking adhesion to temporally upregulated host cell receptors may offer a basis for developing drugs that prevent infection by respiratory and other pathogens following exposure to insults such as viral infection or cigarette smoking.


Proinflammatory cytokines have been known to be elevated in patients with Chronic Heart Failure (CHF). Given the importance of proinflammatory cytokines in the context of the failing heart, the prevalence of Tumor Necrosis Factor-α (TNF-α), Interleukin (IL)-6 polymorphisms in patients with CHF was studied due to ischemic heart disease.Forty three patients with ischemic heart failure were enrolled in this study and compared with 140 healthy individuals. The allele and genotype frequency of four Single Nucleotide Polymorphisms (SNPs) within the IL-6  and TNF-α  genes were determined, using Polymerase Chain Reaction with Sequence-Specific Primers (PCR-SSP) assay.The frequency of the TNF-α (-238) A/A genotype was significantly higher in patients comparing to controls (p=0.043), while TNF-α G/A genotype at the same position decreased significantly, in comparison with controls (p=0.018). The most frequent haplotype for TNF-α was A/A in the patient group in comparison with controls (p=0.003). There was no significant difference in allele and genotype frequencies of IL-6 at positions -174 and nt565, and TNF-α at position -308.Certain alleles, genotypes, and haplotypes in TNF-α, but not IL-6, gene were overrepresented in patients with ischemic heart failure, which may, in turn, predispose individuals to this disease. Given the increasing incidence of the disease, identifying groups of patients who may be genetically more susceptible to developing CHF would be essential. Thus initiating therapy at an early stage of the disease could be considered.Chronic Heart Failure (CHF) is among the leading causes of mortality worldwide, with an incidence rate of 10 per 1000 population after the age of 656. Meanwhile, their roles in the development and progression of the underlying Ischemic Heart Disease (IHD) are also well established8. Genetic polymorphisms within the coding and promoter regions of proinflammatory cytokine genes have been described to regulate gene expression, ultimately altering cytokine production11. The association between some cytokine gene polymorphisms and a number of diseases has been previously studied17. Indeed association of TNF-α with the susceptibility to and severity of CHF has also been examined. The promoter region of TNF-α gene contains several SNPs which influence gene expression or cytokine secretion. In addition to genetic variations, environmental stimuli of inflammatory processes, such as smoking and obesity, were shown to influence TNF-α protein concentrations, further contributing to individualized differences in TNF-α level19. The overall contribution of genetic variation to the development of CHF is not well established. TNF-α -308G/A polymorphism is one of the widely studied polymorphisms in CHF; however, despite their association with other inflammatory diseases, a comprehensive review of the literatures fails to show any relationship between TNF-α polymorphism and the presence of CHF or the elevation of circulating TNF-α20. However, the role of polymorphisms in other proinflammatory cytokine genes in CHF has not been fully investigated.Increased levels of proinflammatory cytokines, including Tumor Necrosis Factor-α (TNF-α) and Interleukin (IL)-6, have been previously reported in patients with CHFThe objective of this research was to study proinflammatory cytokine gene polymorphisms in Iranian patients with CHF due to IHD.cm) on echocardiography. All patients underwent transthoracic echocardiography and cardiac catheterization. Subjects with chronic lung disease, malignancies, recent myocardial infarction, and acute decompensated heart failure within 3 months before recruitment were excluded. Eligible patients were in stable clinical condition and received conventional medical therapy for at least 3 months.In the present study, a total of 43 consecutive Iranian patients with chronic ischemic heart failure  with angiographically significant Coronary Artery Disease (CAD), defined as ≥50% diameter stenosis in at least one of the major coronary arteries, were enrolled. The diagnosis of CHF was based on impaired left ventricular systolic function (left ventricular ejection fraction ≤40%) and left ventricular dilation . The presence or absence of PCR products was visualized by 2% agarose gel electrophoresis. All individuals were genotyped for polymorphic sites of the following cytokine genes: IL-6, -174 G/C and nt565 G/A; TNF-α, -308 G/A and -238 G/A.Genomic DNA was isolated from peripheral blood leukocytes, using saltingout method. Cytokine typing was performed by polymerase chain reaction with sequence-specific primers (PCR-SSP) assay , as previously described in detailsStatistical analyses were performed with EPI info software. Allele, genotype, and haplotype frequencies for all cytokine gene polymorphisms were calculated by direct counting. Frequencies of alleles, genotypes, and haplotypes were compared between the patient and control groups using the Fisher’s exact test. The odds ratio with 95% confidence intervals was calculated.21, results of three controls were not conclusive for TNF-α, while no result was detected for IL-6 of a control.Allelic and genotype frequencies in patients with ischemic heart failure and healthy controls are presented in vs. 0.7%, p=0.043), while TNF-α G/A genotype at the same position decreased significantly in patients compared to controls .A significant positive association with the A/A genotype was found for TNF-α at position -238 in our patients compared to controls .Haplotype frequencies in patients with ischemic heart failure and healthy control subjects are shown in et al reported increased frequency of TNF-α -238/A allele in patients suffering from dilated cardiomyopathy on left ventricular assisted device compared to patients on medical therapy22. However, no such association was reported in patients with ischemic heart failure22. In the present study, the TNF-α (-238) A/A genotype frequency in patients with ischemic heart failure was significantly higher, while the G/A genotype at the same position was significantly lower than controls. Moreover, the frequency of TNF-α  A/A haplotype was higher in patients compared to controls. To the best of our knowledge, this is the first report describing an association between TNF-α (-238) A/A genotype and TNF-α  A/A haplotype with ischemic heart failure. The number of patients with this haplotype was low; however, it should be emphasized that a very rare haplotype was found that was more common among patients with ischemic heart failure than healthy controls. Although this might be a chance finding, the results need to be replicated in other, preferably larger, population with greater haplotype diversity. Moreover, given the small number of patients in this study, any conclusions can only be interpreted with caution.There is a paucity of data in the literature on the association of TNF-α -238G/A polymorphism with CHF. Bruggink 23, whilst other investigators reported no significant association between TNF-α -238G/A polymorphism and the cytokine expression level25. A single SNP, together with other SNPs, may only be able to modify the disease phenotype in an appropriate environmental context. Therefore, circulating TNF-α levels might reflect combined effects of multiple SNPs, in addition to environmental factors. This might in part explain the conflicting reports regarding the influence of TNF-α -238G/A polymorphism on the expression level of TNF-α.There are conflicting reports on the influence of TNF-α -238G/A polymorphism on the expression level of TNF-α. The TNF-α -238/A allele has been reported to be associated with both increased and decreased TNF-α expression26. However, to the best of our knowledge, the association between IL-6 gene polymorphisms and risk of ischemic heart failure has not been reported previously. In the present study, no association between -174G/C and +565A/G polymorphisms in the IL-6 gene and ischemic heart failure was found.Increased levels of IL-6 have been described repeatedly in patients with CHF with a positive correlation with disease severity. Previous studies have also reported the association between the polymorphisms in the promoter region of the IL-6 gene and altered cytokine productionet al reported no significant association between five SNPs in the TNF-α promoter region  and risk of Myocardial Infarction (MI)27. Similarly, allele frequencies, and genotype and haplotype distributions of the TNF-α promoter polymorphisms -863C/A and -308G/A were not related to the risk of CAD and MI28. In another study, none of the four TNF-α SNPs  investigated reached statistical significance in the total sample of patients; however, a significant interaction between 238G/A polymorphism and risk of CHD was reported among nonsmokers in Chinese Han population29. Regarding the role of IL-6 gene polymorphisms in CHD, in a very recent meta-analysis, it was shown that the IL-6 -174G/C polymorphism is not significantly associated with increased risk of CHD; however, a significant association can be found between the -572- G/C polymorphism in the IL-6 gene and CHD risk, especially in Asian populations30.Relationship between polymorphisms in the TNF-α and IL-6 genes and IHD, as one of the most common causes of CHF, has been reported but remains controversial. Bennet While significant differences in some cytokine gene polymorphisms were found between the two groups of patients and controls, the small sample size can affect the robustness of the findings. Moreover, since the role of TNF-α and IL-6 SNPs in the pathogenesis of CHD has remained inconclusive, investigating patients with IHD and no heart failure might have given more conclusive results.In conclusion, this study demonstrates the association between certain allele, genotype, and haplotype frequencies in TNF-α gene with ischemic heart failure. Further investigation, using a larger sample size, to obtain more conclusive data regarding the role of TNF-α genotype in the pathogenesis of ischemic heart failure and influence on TNF-α level is warranted.


The protein-folding chaperone Hsp90 has been proposed to buffer the phenotypic effects of mutations. The potential for Hsp90 and other putative buffers to increase robustness to mutation has had major impact on disease models, quantitative genetics, and evolutionary theory. But Hsp90 sometimes contradicts expectations for a buffer by potentiating rapid phenotypic changes that would otherwise not occur. Here, we quantify Hsp90’s ability to buffer or potentiate  the effects of genetic variation on single-cell morphological features in budding yeast. We corroborate reports that Hsp90 tends to buffer the effects of standing genetic variation in natural populations. However, we demonstrate that Hsp90 tends to have the opposite effect on genetic variation that has experienced reduced selection pressure. Specifically, Hsp90 tends to enhance, rather than diminish, the effects of spontaneous mutations and recombinations. This result implies that Hsp90 does not make phenotypes more robust to the effects of genetic perturbation. Instead, natural selection preferentially allows buffered alleles to persist and thereby creates the false impression that Hsp90 confers greater robustness. Most biologists appreciate that natural selection filters new mutations , such that genetic variation in nature is biased. The idea that selection also skews the types of genetic interactions that exist in nature is less appreciated. For example, studies spanning diverse species have shown that the protein Hsp90, which helps other proteins to fold properly, tends to diminish the observable effects of genetic variation. This observation has led to the assumption that Hsp90 also buffers the effects of new mutations. This untested assumption has served as a rationale for cancer-treatment strategies and shaped our understanding of variation in complex traits. We measured the effects of new mutations on the shapes and sizes of individual yeast cells and found that Hsp90 does not tend to buffer these effects. Instead, Hsp90 interacts with new mutations in diverse ways, sometimes buffering, but more often enhancing mutational effects on cell shape and size. We conclude that selection preferentially allows buffered mutations to persist in natural populations. This result alters common perceptions about why cryptic  genetic variation exists and casts doubt on cancer-treatment strategies aiming to target presumed buffers of mutational effects. Previous work in diverse eukaryotes has demonstrated that inhibition of the protein-folding chaperone Hsp90 reveals previously hidden phenotypic effects of standing genetic variation  lines created previously [To study new mutations, we utilized 94 eviously . These yeviously . Becauseeviously , each lieviously ,29. The eviously .A previous study demonstrated that the MA lines contain mutations that affect the morphologies of individual cells . As in tWe used high-throughput microscopy and automated image analysis  to quantWe inhibited Hsp90 using geldanamycin (GdA), a small-molecule inhibitor that binds the ATP-binding site of Hsp90, rendering it unable to perform its cellular function . This dr6 cells/mL. Then cells were fixed in 4% paraformaldehyde and stained with dyes that label cell-wall components and nuclear DNA. Stained cells grown in control or inhibited conditions were mounted side by side, in duplicate, on 384-well microscopy plates. High-throughput microscopy and morphometric analysis [In each step  of each replicate experiment in this study, cells grown in Hsp90-inhibited (8.5 μM GdA) and control conditions were studied side by side . The effanalysis  typicallIn addition to variation between replicate experiments, there is another source of variation that must be considered when estimating phenotypic variance between yeast strains: cell-to-cell variation within each yeast strain. Hsp90 inhibition has been shown to increase nongenetic heterogeneity for some single-cell morphological features , so the Using the approach outlined above and in , we quanp < 0.001 . However, there might be other reasons that GdA treatment affects phenotypic variation, including reduction of growth. Although previous studies ,2,6 concr) is 0.95 (r = 0.76)  are hig is 0.95 . MA line = 0.76) ; S4 Fig. = 0.76) —neither  = 0.76) . FinallyAlthough GdA treatment impacts the phenotypes of individual MA lines more than it changes the overall amount of variance between lines , we can The idea that Hsp90 increases robustness against the effects of new mutations has persisted ,15,19–24Saccharomyces paradoxus, isolated from one soil environment in England [To test this selection hypothesis, we repeated all experiments on several additional collections of yeast strains isolated from natural environments . These f England ,45; and Unlike the mutations in the MA lines, which accumulated under artificially reduced selection pressure, the standing genetic variation among natural yeast isolates has survived natural selection. Patterns of genetic variation in the collections of natural isolates that have been sequenced  reveal evidence of selection ,46. ThesThe selection hypothesis predicts that the single-cell morphologies in yeast collections representing natural isolates will tend to become more divergent upon Hsp90 inhibition. Consistent with the selection hypothesis, Hsp90 inhibition tends to increase morphological diversity in all four such yeast collections . The quaThe distinction between the MA lines and natural isolates might support the hypothesis that natural selection acts as a filter of new mutations with epistatic interactions ,8, skewiPrevious studies of Rec lines have produced mixed results. A study in yeast found roughly equal frequencies of buffering and potentiation . In contSimilarly to the MA lines, we found that GdA treatment tends to decrease phenotypic diversity among the Rec lines . These dp < 0.01; orange shading in To further characterize how the relationship between Hsp90 and genetic variation differs in the MA and Rec lines versus the natural isolates, we partitioned genetic interactions into line spreading versus line crossing  reached the same conclusions about another candidate robustness-increasing factor, the histone variant H2A.Z. Together, the Hsp90 and H2A.Z results raise the question of whether any gene product increases robustness to mutation on a genome-wide scale .Additionally, our results highlight that natural selection transforms the types of epistasis that are present in nature, leaving the false impression of robustness. Although it is appreciated that selection filters out certain types of new mutations , the idea that natural selection also skews the types of epistasis that accumulate in genomes is much less appreciated. The false equality drawn between the genetic interactions common in nature and those that are common among new mutations has likely prevented a full and accurate understanding of natural variation in complex traits (including human disease traits).To be clear, our results do not contradict the prevalence or importance of cryptic genetic variation in nature . Our stuThe nature of Hsp90’s interaction with new mutations is of high practical importance, because Hsp90 inhibitors are considered promising anticancer drugs. One rationale for inhibiting Hsp90 has been that Hsp90 protects tumor cells from the deleterious effects of their elevated mutation rates by suppressing the effects of many mutations . Our worMore recent work  has focused on enhancing the efficacy of another anticancer drug by combining it with low-dose Hsp90 inhibition that does not activate the stress response . The rati automated microscope using a 40× objective. For each strain, typically between 500 and 1,000 cells were imaged per condition , and analysis generally followed that done previously for similar morphology datasets [All data analysis was performed using the open-source R statistical computing package , we reported a significant genotype-by-GdA interaction for that phenotype in that strain collection  Growth rates were measured as log-linear increases in optical density over time. Each point represents growth of a single strain performed in a separate well on a 96-well plate; boxplots summarize the distributions of growth rates across all strains tested in a given condition displaying the median (center line), interquartile range (IQR) (upper and lower hinges), and highest value within 1.5 × IQR (whiskers). Representative strains from each collection were grown in SC with different concentrations of DMSO (blue) or geldanamycin (GdA) + DMSO (red). In all experiments, GdA is solubilized in DMSO, we therefore added DMSO to GdA− experiments such that the only difference between GdA+ and GdA− conditions is the presence/absence of GdA−. Fitness decreases along the horizontal axis in both the control and Hsp90-inhbited conditions because both GdA and DMSO reduce cell growth. We performed most experiments in 8.5 μM GdA as this concentration had only minimal effects on exponential growth rate relative to GdA−. The parents of the Rec cross are included among the Diverse strains surveyed . (B) Bars represent the average proportion of cells in the unbudded stage of the cell cycle in our complete dataset. (C) Points represent the numbers of phenotyped cells that pass filtering for each strain in control and GdA-treated conditions. Boxplots represent the distributions of cell counts across all strains within a given collection and display the same summary statistics as panel A. (D) Bar heights represent the number of strains surveyed in a given collection.(PDF)Click here for additional data file.S2 FigThese plots are similar to those in (PDF)Click here for additional data file.S3 Figi.e. we calculated the distance between the end of the unit vector for each MA line and the end of the unit vector for the ancestor). This distance is plotted on the vertical axis. For the farthest points from the MA line ancestor, the name of the corresponding MA line is written on the plot.For each MA line and cell cycle phase, we measured the length of a single vector starting from the mean phenotypes in the GdA− condition and ending at the mean phenotypes in the GdA+ condition. The horizontal axis is the length (magnitude) of each vector, minus the length of the vector for the MA line ancestor. Then we converted all vectors to unit vectors by dividing all GdA− and GdA+ phenotypic means by the magnitude of the corresponding vector for each MA line. We shifted all unit vectors to begin at the origin and calculated the distance between the normalized GdA+ phenotypes for each MA line and the normalized GdA+ phenotypes for the ancestor ((PDF)Click here for additional data file.S4 Figr) is displayed for GdA vs. Rad (left side), and GdA vs. less growth (right side). PCs related to unbudded cells are highlighted in blue, small-budded cells in green, or large-budded cells in purple.The structurally unrelated Hsp90 inhibitors GdA and Rad have similar effects on the morphologies of the MA lines, but the effect of modulating the length of exponential growth is not as similar. These plots are similar to those in (PDF)Click here for additional data file.S5 Fig(A) The dots depict, for each of 132 morphological traits, changes to variance that occur across a subsample of 22 MA lines upon perturbing the length of exponential growth phase or treating cells with 8.5 μM GdA. Phenotypic variance between strains is quantified as it was for the full dataset, using MCMCglmm. Shortening the duration of exponential growth tends to increase between-strain variation in 132 morphological traits, while GdA treatment has a smaller and opposite effect. Boxplots summarize the distribution of these changes across all 132 traits after a given perturbation . Boxplots display the median (center line), interquartile range (IQR) (upper and lower hinges), highest value within 1.5 × IQR (whiskers), and roughly a 95% confidence interval around the median calculated as 1.58 × IQR / √n (notches). (B) The effect of shortening exponential growth does not predict the effect of GdA treatment on between-strain variation. These points are the same as in panel A, but here, error bars represent the 95% posterior density interval surrounding the change in between strain variance for each of the 132 traits. Phenotypes are colored purple when, in the full dataset of MA lines, the difference in between-strain variance between GdA+ and GdA− conditions is significantly below zero. The phenotypes colored in purple are evenly spread along the horizontal axis suggesting the effect of GdA on morphological variation is not dependent on any concomitant effect of growth, at least not one that was captured by our particular growth manipulation. (C) Similar to (PDF)Click here for additional data file.S6 FigEach point represents a compromise PC and each boxplot summarizes the distribution across 51 compromise PCs for a single strain collection. Boxplots display the median (center line), interquartile range (IQR) (upper and lower hinges), highest value within 1.5 × IQR (whiskers), and roughly a 95% confidence interval around the median calculated as 1.58 × IQR / √n (notches). The vertical axis displays the amount of variance present between strains in the GdA− condition. For each PC, overall variance is scaled to 1 before variance is partitioned into within-strain, between-strain, GdA+, and GdA− components.(PDF)Click here for additional data file.S1 TablePCs are highlighted in orange corresponding to whether they are influenced by a GdA-by-genotype interaction at p < 0.01.(XLSX)Click here for additional data file.S2 TableMA lines are highlighted in blue, green, or red corresponding to the color of that MA line in (XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.