Recombinant gamma interferon provokes resistance of human breast cancer cells to spontaneous and IL-2 activated non-MHC restricted cytotoxicity.

Natural and lymphokine activated killer cells (NK and LAK) are believed to play an important role in the control of tumour progression and metastasis. Their specific receptors on tumours cells are still unknown. Several studies suggest that these cells recognise and eliminate abnormal cells with deleted or reduced expression of MHC class I molecules. Previous reports suggest that interferons (IFN), by increasing MHC class I expression on target cells, induce resistance to killing by NK cells. We investigated the role of MHC molecule expression by two human breast cancer cell lines T47D and ZR75-1 in their susceptibility to NK and LAK cells. These two cell lines spontaneously express low levels of HLA class I antigens but no HLA class II molecules. After IFN-gamma treatment they both overexpressed MHC class I and de novo expressed class II molecules as detected by flow cytometry, quantified by a radioimmunoassay and analysed by two-dimensional gel electrophoresis. Opposed to untreated cells these IFN-gamma treated cells were resistant to NK and LAK lysis. Furthermore, preincubation of IFN-gamma treated breast cancer cells with F(ab')2 fragments of monoclonal antibodies to HLA class I and HLA class II molecules was unable to restore lysis. In contrast, several complete monoclonal antibodies including anti-HLA class I and HLA class II induced the lysis of target cells whether or not they had been treated by IFN-gamma. The therapeutic use of monoclonal antibodies directed against antigens expressed on tumour cells (ADCC) in conjunction with interferon therapy should be discussed in lymphokine-based strategies for treatment of cancer patients

Applying a genetic risk score model to enhance prediction of future multiple sclerosis diagnosis at first presentation with optic neuritis

Optic neuritis (ON) is associated with numerous immune-mediated inflammatory diseases, but 50% patients are ultimately diagnosed with multiple sclerosis (MS). Differentiating MS-ON from non-MS-ON acutely is challenging but important; non-MS ON often requires urgent immunosuppression to preserve vision. Using data from the United Kingdom Biobank we showed that combining an MS-genetic risk score (GRS) with demographic risk factors (age, sex) significantly improved MS prediction in undifferentiated ON; one standard deviation of MS-GRS increased the Hazard of MS 1.3-fold (95% confidence interval 1.07–1.55, P < 0.01). Participants stratified into quartiles of predicted risk developed incident MS at rates varying from 4% (95%CI 0.5–7%, lowest risk quartile) to 41% (95%CI 33–49%, highest risk quartile). The model replicated across two cohorts (Geisinger, USA, and FinnGen, Finland). This study indicates that a combined model might enhance individual MS risk stratification, paving the way for precision-based ON treatment and earlier MS disease-modifying therapy

Histological validation of a type 1 diabetes clinical diagnostic model for classification of diabetes

This is the final version. Available on open access from Wiley via the DOI in this recordAims: Misclassification of diabetes is common due to an overlap in the clinical features of type 1 and type 2 diabetes. Combined diagnostic models incorporating clinical and biomarker information have recently been developed that can aid classification, but they have not been validated using pancreatic pathology. We evaluated a clinical diagnostic model against histologically defined type 1 diabetes. Methods: We classified cases from the Network for Pancreatic Organ donors with Diabetes (nPOD) biobank as type 1 (n = 111) or non-type 1 (n = 42) diabetes using histopathology. Type 1 diabetes was defined by lobular loss of insulin-containing islets along with multiple insulin-deficient islets. We assessed the discriminative performance of previously described type 1 diabetes diagnostic models, based on clinical features (age at diagnosis, BMI) and biomarker data [autoantibodies, type 1 diabetes genetic risk score (T1D-GRS)], and singular features for identifying type 1 diabetes by the area under the curve of the receiver operator characteristic (AUC-ROC). Results: Diagnostic models validated well against histologically defined type 1 diabetes. The model combining clinical features, islet autoantibodies and T1D-GRS was strongly discriminative of type 1 diabetes, and performed better than clinical features alone (AUC-ROC 0.97 vs. 0.95; P = 0.03). Histological classification of type 1 diabetes was concordant with serum C-peptide [median < 17 pmol/l (limit of detection) vs. 1037 pmol/l in non-type 1 diabetes; P < 0.0001]. Conclusions: Our study provides robust histological evidence that a clinical diagnostic model, combining clinical features and biomarkers, could improve diabetes classification. Our study also provides reassurance that a C-peptide-based definition of type 1 diabetes is an appropriate surrogate outcome that can be used in large clinical studies where histological definition is impossible. Parts of this study were presented in abstract form at the Network for Pancreatic Organ Donors Conference, Florida, USA, 19–22 February 2019 and Diabetes UK Professional Conference, Liverpool, UK, 6–8 March 2019.Diabetes UKNational Institutes of Health (NIH)National Institute for Health Research (NIHR)JDRFHelmsley Charitable Trus

A combined risk score enhances prediction of type 1 diabetes among susceptible children

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordType 1 diabetes (T1D)-an autoimmune disease that destroys the pancreatic islets, resulting in insulin deficiency-often begins early in life when islet autoantibody appearance signals high risk1. However, clinical diabetes can follow in weeks or only after decades, and is very difficult to predict. Ketoacidosis at onset remains common2,3 and is most severe in the very young4,5, in whom it can be life threatening and difficult to treat6-9. Autoantibody surveillance programs effectively prevent most ketoacidosis10-12 but require frequent evaluations whose expense limits public health adoption13. Prevention therapies applied before onset, when greater islet mass remains, have rarely been feasible14 because individuals at greatest risk of impending T1D are difficult to identify. To remedy this, we sought accurate, cost-effective estimation of future T1D risk by developing a combined risk score incorporating both fixed and variable factors (genetic, clinical and immunological) in 7,798 high-risk children followed closely from birth for 9.3 years. Compared with autoantibodies alone, the combined model dramatically improves T1D prediction at ≥2 years of age over horizons up to 8 years of age (area under the receiver operating characteristic curve ≥ 0.9), doubles the estimated efficiency of population-based newborn screening to prevent ketoacidosis, and enables individualized risk estimates for better prevention trial selection.National Institutes of Health/National Center for Advancing Translational Sciences Clinical and Translational ScienceDiabetes Research CenterDiabetes UKWellcome TrustJDR

Experimental ovine toxoplasmosis: influence of the gestational stage on the clinical course, lesion development and parasite distribution

P. 1-14The relation between gestational age and foetal death risk in ovine toxoplasmosis is already known, but the mechanisms involved are not yet clear. In order to study how the stage of gestation influences these mechanisms, pregnant sheep of the same age and genetic background were orally dosed with 50 oocysts of Toxoplasma gondii (M4 isolate) at days 40 (G1), 90 (G2) and 120 (G3) of gestation. In each group, four animals were culled on the second, third and fourth week post infection (pi) in order to evaluate parasite load and distribution, and lesions in target organs. Ewes from G1 showed a longer period of hyperthermia than the other groups. Abortions occurred in all groups. While in G2 they were more frequent during the acute phase of the disease, in G3 they mainly occurred after day 20 pi. After challenge, parasite and lesions in the placentas and foetuses were detected from day 19 pi in G3 while in G2 or G1 they were only detected at day 26 pi. However, after initial detection at day 19 pi, parasite burden, measured through RT-PCR, in placenta or foetus of G3 did not increase significantly and, at in the third week pi it was lower than that measured in foetal liver or placenta from G1 to G3 respectively. These results show that the period of gestation clearly influences the parasite multiplication and development of lesions in the placenta and foetus and, as a consequence, the clinical course in ovine toxoplasmosis.S

Descriptors of Posidonia oceanica meadows: Use and application

The conservation of the coastal marine environment requires the possession of information that enables the global quality of the environment to be evaluated reliably and relatively quickly. The use of biological indicators is often an appropriate method. Seagrasses in general, and Posidonia oceanica meadows in particular, are considered to be appropriate for biomonitoring because of their wide distribution, reasonable size, sedentary habit, easy collection and abundance and sensitivity to modifications of littoral zone. Reasoned management, on the scale of the whole Mediterranean basin, requires standardized methods of study, to be applied by both researchers and administrators, enabling comparable results to be obtained. This paper synthesises the existing methods applied to monitor P. oceanica meadows, identifies the most suitable techniques and suggests future research directions. From the results of a questionnaire, distributed to all the identified laboratories working on this topic, a list of the most commonly used descriptors was drawn up, together with the related research techniques (e.g. standardization, interest and limits, valuation of the results). It seems that the techniques used to study meadows are rather similar, but rarely identical, even though the various teams often refer to previously published works. This paper shows the interest of a practical guide that describes, in a standardized way, the most useful techniques enabling P. oceanica meadows to be used as an environmental descriptor. Indeed, it constitutes the first stage in the process. (c) 2005 Elsevier Ltd. All rights reserved.Peer reviewe

Mineral phosphorus drives glacier algal blooms on the Greenland Ice Sheet

Melting of the Greenland Ice Sheet is a leading cause of land-ice mass loss and cryosphere-attributed sea level rise. Blooms of pigmented glacier ice algae lower ice albedo and accelerate surface melting in the ice sheet’s southwest sector. Although glacier ice algae cause up to 13% of the surface melting in this region, the controls on bloom development remain poorly understood. Here we show a direct link between mineral phosphorus in surface ice and glacier ice algae biomass through the quantification of solid and fluid phase phosphorus reservoirs in surface habitats across the southwest ablation zone of the ice sheet. We demonstrate that nutrients from mineral dust likely drive glacier ice algal growth, and thereby identify mineral dust as a secondary control on ice sheet melting.SCOPUS: ar.jinfo:eu-repo/semantics/publishe