T lymphocytes are often induced naturally in melanoma patients and infiltrate tumors. Given that γδ T cells mediate antigen-specific killing of tumor cells, we studied the representation and the in vitro cytokine production and cytotoxic activity of tumor infiltrating γδ T cells from 74 patients with primary melanoma. We found that γδ T cells represent the major lymphocyte population infiltrating melanoma, and both Vδ1+ and Vδ2+ cells are involved. The majority of melanoma-infiltrating γδ cells showed effector memory and terminally-differentiated phenotypes and, accordingly, polyclonal γδ T cell lines obtained from tumor-infiltrating immune cells produced IFN-γ and TNF-α and were capable of killing melanoma cell lines in vitro. The cytotoxic capability of Vδ2 cell lines was further improved by pre-treatment of tumor target cells with zoledronate. Moreover, higher rate of γδ T cells isolation and percentages of Vδ2 cells correlate with early stage of development of melanoma and absence of metastasis. Altogether, our results suggest that a natural immune response mediated by γδ T lymphocytes may contribute to the immunosurveillance of melanoma.

Hospital readmission rates are increasingly used as signals of hospital performance and a basis for hospital reimbursement. However, their interpretation may be complicated by differential patient survival rates. If patient characteristics are not perfectly observable and hospitals differ in their mortality rates, then hospitals with low mortality rates are likely to have a larger share of un-observably sicker patients at risk of a readmission. Their performance on readmissions will then be underestimated. We examine hospitals' performance relaxing the assumption of independence between mortality and readmissions implicitly adopted in many empirical applications. We use data from the Hospital Episode Statistics on emergency admissions for fractured hip in 290,000 patients aged 65 and over from 2003 to 2008 in England. We find evidence of sample selection bias that affects inference from traditional models. We use a bivariate sample selection model to allow for the selection process and the dichotomous nature of the outcome variables.

We used the Luminex Bead Array Multiplex Immunoassay to measure cytokines, chemokines and growth factors responses to the same antigens used for RD1-based Interferon γ Release Assay (IGRA) test. Seventy-nine individuals, 27 active TB, 32 latent infection subsets, 20 individuals derivative purified protein (PPD) negative (subjects that do not have any indurative cutaneous reaction after 72 hrs of intradermal injection of PPD) and with other pulmonary disease were retrospectively studied. Forty-eight analytes were evaluated by Luminex Assay in plasma obtained from whole blood stimulated cells. The diagnostic accuracies of the markers detected were evaluated by ROC curve analysis and by the combination of multiple biomarkers to improve the potential to discriminate between infection/disease and non infection. Among 48 cytokines, 13 analytes, namely IL-3, IL-12-p40, LIF, IFNα2, IL-2ra, IL-13, b-NGF, SCF, TNF-β, TRAIL, IL-2, IFN-γ, IP-10, and MIG, were significantly higher in the active TB and LTBI groups, compared to NON-TB patients, while MIF was significantly lower in active TB patients compared to NON-TB and LTBI groups. The diagnostic accuracies of the markers detected in the culture supernatants evaluated by ROC curve analysis revealed that 11 analytes (IL2, IP10, IFN-γ, IL13, MIG, SCF, b-NGF, IL12-p40, TRAIL, IL2 Ra, LIF) discriminated between NON-TB and LTBI groups, with AUC for all analytes ≥0.73, while 14 analytes (IL2, IP10, IFN-γ, MIG, SCF, b-NGF, IL12-p40, TRAIL, IL2Ra, MIF, TNF-β, IL3, IFN-α2, LIF) discriminated between NON-TB and active TB groups, with AUC ≥0.78, that is a moderate, value in terms of accuracy of a diagnostic test. Finally, the combinations of seven biomarkers resulted in the accurate prediction of 88.89% of active TB patients, 82.35% of subjects with latent infection and 90% of non-TB patients, respectively. Taken together, our data suggest that combinations of whole blood Mycobacterium tuberculosis (Mtb) antigen dependent cytokines production could be useful as biomarkers to determine tuberculosis disease states when compared to non TB cohort.

The empirical analysis of inequality of opportunity centres on disparities between social types, defined by the exposure to circumstances beyond individual control. Despite this, its main theoretical foundation-the Roemer model-does not indicate how to carry out, in practice, the required partition of the population into such types. This paper operationalises this definition of social types using a latent classes approach. Our specification is embedded in a probabilistic extension of the canonical Roemer model, which assumes that the relevant population consists of a finite number of latent types, from which each individual can be treated as a random draw. This makes possible the use of the full set of circumstances in the data, allows for unobserved individual heterogeneity and does not require an ex-ante specification of the number of types by the researcher. Our approach is illustrated by an empirical application featuring a large UK cohort study that was used in earlier literature to examine inequalities of opportunity in a wide array of social outcomes.

Perception of inequality is important for the analysis of individuals' motivations and decisions and for policy assessment. Despite the broad range of analytic gains that it grants, our knowledge about measurement and determinants of perception of inequality is still limited, since it is intrinsically unobservable, multidimensional, and essentially contested. Using a novel econometric approach, we study how observable individual characteristics affect the joint distribution of a set of indicators of perceived inequality in specific domains. Using data from the International Social Survey Programme, we shed light on the associations among these indicators and how they are affected by covariates. The approach also gives insights on some results in the literature on inequality. The role of many subjective indicators for the perception of inequality is re‐examined and examples of policy applications are reviewed. The importance of our empirical approach to the measurement of perceived inequality is, in so doing, reinforced.