За кадры. 1985. № 76 (2569)

22 декабря - День энергетикаМинистр - выпускник ТПИПредлагают геологи / Г. БровченкоТранспортникам нужна помощь / В. МакаренкоИстория партии и народа / Н. ШевченкоГоловоломка и другие задачи / Р. АкимоваНиже возможностей / Л. КалугинаОдин за всех / Н. Емельянович, Н. БогомоловаПервокурсники перед сессией / А. ГромаковКирпич будет прочнее / В. И. ВерещагинК новым рубежам / В. ЕреминСвет и тепло города / Н. Попов, Г. БекманНаступление на болезни / [беседа с] Т. И. ТеркинаВсегда в поиске / М. АркадьевОмскому литобъединению / Г. БородянскийВстреча с классикой / И. МороцкаяГости из Томск

Cardiovascular risk algorithms in primary care: Results from the DETECT study

Abstract Guidelines for prevention of cardiovascular diseases use risk scores to guide the intensity of treatment. A comparison of these scores in a German population has not been performed. We have evaluated the correlation, discrimination and calibration of ten commonly used risk equations in primary care in 4044 participants of the DETECT (Diabetes and Cardiovascular Risk Evaluation: Targets and Essential Data for Commitment of Treatment) study. The risk equations correlate well with each other. All risk equations have a similar discriminatory power. Absolute risks differ widely, in part due to the components of clinical endpoints predicted: The risk equations produced median risks between 8.4% and 2.0%. With three out of 10 risk scores calculated and observed risks well coincided. At a risk threshold of 10 percent in 10 years, the ACC/AHA atherosclerotic cardiovascular disease (ASCVD) equation has a sensitivity to identify future CVD events of approximately 80%, with the highest specificity (69%) and positive predictive value (17%) among all the equations. Due to the most precise calibration over a wide range of risks, the large age range covered and the combined endpoint including non-fatal and fatal events, the ASCVD equation provides valid risk prediction for primary prevention in Germany

Biomarker-Based Risk Model to Predict Cardiovascular Mortality in Patients With Stable Coronary Disease

Currently, there is no generally accepted model to predict outcomes in stable coronary heart disease (CHD). This study evaluated and compared the prognostic value of biomarkers and clinical variables to develop a biomarker-based prediction model in patients with stable CHD. In a prospective, randomized trial cohort of 13,164 patients with stable CHD, we analyzed several candidate biomarkers and clinical variables and used multivariable Cox regression to develop a clinical prediction model based on the most important markers. The primary outcome was cardiovascular (CV) death, but model performance was also explored for other key outcomes. It was internally bootstrap validated, and externally validated in 1,547 patients in another study. During a median follow-up of 3.7 years, there were 591 cases of CV death. The 3 most important biomarkers were N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and low-density lipoprotein cholesterol, where NT-proBNP and hs-cTnT had greater prognostic value than any other biomarker or clinical variable. The final prediction model included age (A), biomarkers (B) (NT-proBNP, hs-cTnT, and low-density lipoprotein cholesterol), and clinical variables (C) (smoking, diabetes mellitus, and peripheral arterial disease). This "ABC-CHD" model had high discriminatory ability for CV death (c-index 0.81 in derivation cohort, 0.78 in validation cohort), with adequate calibration in both cohorts. This model provided a robust tool for the prediction of CV death in patients with stable CHD. As it is based on a small number of readily available biomarkers and clinical factors, it can be widely employed to complement clinical assessment and guide management based on CV risk. (The Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy Trial [STABILITY]; NCT00799903

Naive CD8 T-cells initiate spontaneous autoimmunity to a sequestered model antigen of the central nervous system

In multiple sclerosis, CD8 T-cells are thought play a key pathogenetic role, but mechanistic evidence from rodent models is limited. Here, we have tested the encephalitogenic potential of CD8 T-cells specific for the model antigen ovalbumin (OVA) sequestered in oligodendrocytes as a cytosolic molecule. We show that in these ‘ODC-OVA’ mice, the neo-self antigen remains invisible to CD4 cells expressing the OVA-specific OT-II receptor. In contrast, OVA is accessible to naïve CD8 T-cells expressing the OT-I T-cell receptor, during the first 10 days of life, resulting in antigen release into the periphery. Introduction of OT-I as a second transgene leads to fulminant demyelinating experimental autoimmune encephalomyelitis with multiple sclerosis-like lesions, affecting cerebellum, brainstem, optic nerve and spinal cord. OVA-transgenic oligodendrocytes activate naïve OT-I cells in vitro, and both major histocompatibility complex class I expression and the OT-I response are further up-regulated by interferon-γ (IFN-γ). Release of IFN-γ into the circulation of ODC-OVA/OT-I double transgenic mice precedes disease manifestation, and pathogenicity of OT-I cells transferred into ODC-OVA mice is largely IFN-γ dependent. In conclusion, naïve CD8 T-cells gaining access to an ‘immune-privileged’ organ can initiate autoimmunity via an IFN-γ-assisted amplification loop even if the self-antigen in question is not spontaneously released for presentation by professional antigen presenting cells.Shin-Young Na, Yi Cao, Catherine Toben, Lars Nitschke, Christine Stadelmann, Ralf Gold, Anneliese Schimpl, and Thomas Hüni