The performance of interferon-gamma release assays in tuberculosis patients with type II diabetes

The sensitivity of Interferon-γ release assays for detection of Mycobacterium tuberculosis (MTB) infection or disease is affected by conditions that depress host immunity (such as HIV). It is critical to determine whether these assays are affected by diabetes and related conditions (i.e. hyperglycemia, chronic hyperglycemia, or being overweight/obese) given that immune impairment is thought to underline susceptibility to tuberculosis (TB) in people with diabetes. This is important for tuberculosis control due to the millions of type 2 diabetes patients at risk for tuberculosis worldwide.^ The objective of this study was to identify host characteristics, including diabetes, that may affect the sensitivity of two commercially available Interferon-γ (IFN-γ) release assays (IGRA), the QuantiFERON®-TB Gold (QFT-G) and the T-SPOT®.TB in active TB patients. We further explored whether IFN-γ secretion in response to MTB antigens (ESAT-6 and CFP-10) is associated with diabetes and its defining characteristics (high blood glucose, high HbA1c, high BMI). To achieve these objectives, the sensitivity of QFT-G and T-SPOT. TB assays were evaluated in newly diagnosed, tuberculosis confirmed (by positive smear for acid fast bacilli and/or positive culture for MTB) adults enrolled at Texas and Mexico study sites between March 2006 and April 2009. Univariate and multivariate models were constructed to identify host characteristics associated with IGRA result and level of IFN-γ secretion.^ QFT-G was positive in 68% of tuberculosis patients. Those with diabetes, chronic hyperglycemia or obesity were more likely to have a positive QFT-G result, and to secrete higher levels of IFN-γ in response to the mycobacterial antigens (p<0.05). Previous history of BCG vaccination was the only other host characteristic associated with QFT-G result, whereby a higher proportion of non-BCG vaccinated persons were QFT-G positive, in comparison to vaccinated persons. In a separate group of patients, the T-SPOT.TB was 94% sensitive, with similar performance in all tuberculosis patients, regardless of host characteristics.^ In summary, we have demonstrated the validity of QFT-G and T-SPOT. TB to support the diagnosis of TB in patients with a range of host characteristics, but most notably in patients with diabetes. We also confirmed that TB patients with diabetes and associated characteristics (chronic hyperglycemia or BMI) secreted higher titers of IFN-γ when stimulated with MTB specific antigens, in comparison to patients without these characteristics. Together, these findings suggest that the mechanism by which diabetes increases risk to TB may not be explained by the inability to secrete IFN-γ, a key cytokine for TB control.^

Interferon-gamma release assays for latent tuberculosis infection in child and young adult candidates or recipients of tumor necrosis factor inhibitor therapy

Background. Inhibition of tumor necrosis factor (TNF) is associated with progression of latent tuberculosis infection (LTBI) to active disease. LTBI screening prior to starting TNF inhibitor therapy is recommended. Blood tests, collectively known as interferon-gamma release assays (IGRAs), offer a means other than the tuberculin skin test (TST) of screening for LTBI. However, in the setting of immune compromise, anergy may limit the clinical utility of IGRAs. ^ Methods. A cross-sectional study was conducted in children and young adults ≤ 21 years of age who were cared for at Texas Children's Hospital in Houston, TX, during 2011 and who were candidates for, or were receiving, tumor necrosis factor (TNF)-inhibitor therapy. All subjects answered a risk factor questionnaire and were tested for LTBI by two commercially available IGRAs (QuantiFERON-Gold In-Tube assay and the T-SPOT.TB assay), along with the TST. T-cell phenotypes were evaluated through flow cytometry, both at baseline and after antigen stimulation. ^ Results. Twenty-eight subjects were enrolled. All were TST negative and none were IGRA positive. Results were negative for the 27 subjects who were tested with QuantiFERON-Gold In-Tube. However, 26% of subjects demonstrated anergy in the T-SPOT.T. Patients with T-SPOT. TB anergy had lower quantitative IFN-γ responses to mitogen in the QFT assay—the mean IFN-γ level to mitogen in patients without T-SPOT.TB anergy was 9.84 IU/ml compared to 6.91 IU/ml in patients with T-SPOT.TB anergy (P = 0.046). Age and use of TNF inhibitors, corticosteroids, or methotrexate use were not significantly associated with T-SPOT.TB anergy. Antigen stimulation revealed depressed expression of intracellular IFN-γ in subjects with T-SPOT. TB anergy. ^ Conclusions. The frequency of anergy in this population is higher than would be expected from studies in adults. There appears to be inappropriate IFN-γ responses to antigen in subjects with T-SPOT. TB anergy. This immune defect was detected by the T-SPOT. TB assay but not by the QuantiFERON-Gold In-Tube assay. Further data are needed to clarify the utility of IGRAs in this population.^

Variability of the IFN-γ ELISpot assay in the context of proficiency testing and bridging studies.

Assays that assess cellular mediated immune responses performed under Good Clinical Laboratory Practice (GCLP) guidelines are required to provide specific and reproducible results. Defined validation procedures are required to establish the Standard Operating Procedure (SOP), include pass and fail criteria, as well as implement positivity criteria. However, little to no guidance is provided on how to perform longitudinal assessment of the key reagents utilized in the assay. Through the External Quality Assurance Program Oversight Laboratory (EQAPOL), an Interferon-gamma (IFN-γ) Enzyme-linked immunosorbent spot (ELISpot) assay proficiency testing program is administered. A limit of acceptable within site variability was estimated after six rounds of proficiency testing (PT). Previously, a PT send-out specific within site variability limit was calculated based on the dispersion (variance/mean) of the nine replicate wells of data. Now an overall 'dispersion limit' for the ELISpot PT program within site variability has been calculated as a dispersion of 3.3. The utility of this metric was assessed using a control sample to calculate the within (precision) and between (accuracy) experiment variability to determine if the dispersion limit could be applied to bridging studies (studies that assess lot-to-lot variations of key reagents) for comparing the accuracy of results with new lots to results with old lots. Finally, simulations were conducted to explore how this dispersion limit could provide guidance in the number of replicate wells needed for within and between experiment variability and the appropriate donor reactivity (number of antigen-specific cells) to be used for the evaluation of new reagents. Our bridging study simulations indicate using a minimum of six replicate wells of a control donor sample with reactivity of at least 150 spot forming cells per well is optimal. To determine significant lot-to-lot variations use the 3.3 dispersion limit for between and within experiment variability.

Evaluation of piezoelectric PVDF polymers for use in space environments. III. Comparison of the effects of vacuum UV and gamma radiation

Films of piezoelectric PVDF and P(VDF-TrFE) were exposed to vacuum UV (115-300 nm VUV) and -radiation to investigate how these two forms of radiation affect the chemical, morphological, and piezoelectric properties of the polymers. The extent of crosslinking was almost identical in both polymers after -irradiation, but surprisingly, was significantly higher for the TrFE copolymer after VUV-irradiation. Changes in the melting behavior were also more significant in the TrFE copolymer after VUV-irradiation due to both surface and bulk crosslinking, compared with only surface crosslinking for the PVDF films. The piezoelectric properties (measured using d33 piezoelectric coefficients and D-E hysteresis loops) were unchanged in the PVDF homopolymer, while the TrFE copolymer exhibited more narrow D-E loops after exposure to either - or VUV-radiation. The more severe damage to the TrFE copolymer in comparison with the PVDF homopolymer after VUV-irradiation is explained by different energy deposition characteristics. The short wavelength, highly energetic photons are undoubtedly absorbed in the surface layers of both polymers, and we propose that while the longer wavelength components of the VUV-radiation are absorbed by the bulk of the TrFE copolymer causing crosslinking, they are transmitted harmlessly in the PVDF homopolymer.

Gamma-tocotrienol as an effective agent in targeting prostate cancer stem cell-like population

Emerging evidence supports that prostate cancer originates from a rare sub-population of cells, namely prostate cancer stem cells (CSCs). Conventional therapies for prostate cancer are believed to mainly target the majority of differentiated tumor cells but spare CSCs, which may account for the subsequent disease relapse after treatment. Therefore, successful elimination of CSCs may be an effective strategy to achieve complete remission from this disease. Gamma-tocotrienols (-T3) is one of the vitamin-E constituents which have been shown to have anticancer effects against a wide-range of human cancers. Recently, we have reported that -T3 treatment not only inhibits prostate cancer cell invasion but also sensitizes the cells to docetaxel-induced apoptosis, suggesting that -T3 may be an effective therapeutic agent against advanced stage prostate cancer. Here, we demonstrate for the first time that -T3 can down-regulate the expression of prostate CSC markers (CD133/CD44) in androgen independent (AI) prostate cancer cell lines (PC-3 & DU145), as evident from western blotting analysis. Meanwhile, the spheroid formation ability of the prostate cancer cells was significantly hampered by -T3 treatment. In addition, pre-treatment of PC-3 cells with -T3 was found to suppress tumor initiation ability of the cells. More importantly, while CD133-enriched PC-3 cells were highly resistant to docetaxel treatment, these cells were as sensitive to -T3 treatment as the CD133-depleted population. Our data suggest that -T3 may be an effective agent in targeting prostate CSCs, which may account for its anticancer and chemosensitizing effects reported in previous studies.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros