Monospecific but not polyreactive human hybridoma rheumatoid factors exhibit preferential binding specificities for IgG3 and IgG4

Summary Among 38 human hybridoma-derived monoclonal rheumatoid factors (RFs) generated from patients with either rheumatoid arthritis (RA) or systemic lupus erythematosus (SLE), two groups of RFs can be identified. Monospecific RFs were derived primarily from patients with RA and are characterized by a binding specificity for IgG3 and/or IgG4. Polyreactive RFs were derived largely from patients with SLE and show a broader pattern of reactivity to all four isotypes of IgG. Neither population of RFs was exclusive to either disease. The binding specificities identified appear to be different from the RFs isolated from patients with mixed cryoglobulinemia and may reflect a different antigen selection mechanism.     

Effect of ultraviolet irradiation on selected host cell proteins including Ro/SS-A and Epstein-Barr virus in cultured lymphoblastoid cell lines.

Although systemic lupus erythematosus (SLE) and Sj?gren's syndrome (SS) are distinct collagen vascular illnesses, they share certain features. Both have clinical manifestations involving skin and mucous membranes and characteristically have high titers of circulating autoantibodies to the cellular components Ro/SS-A, calreticulin/Ro, 52 kDa Ro and La/SS-B. Viruses have been postulated to be involved in the pathogenesis of both diseases. Sensitivity to sun is a cardinal feature of SLE, and UV light may be involved in its pathogenesis. Using human B-lymphoblastoid cell lines, the effect of the resident Epstein-Barr virus on the expression of the above cellular components was investigated by flow cytometry. Sublethal irradiation with ultraviolet B light appeared to diminish EBV antigen expression (gp350/220) during the first 48 to 72 hours in culture, whereas there was no change in the expression of MHC class I or immunoglobulin host cell proteins, and an apparent increase in the expression of host cell autoantigens. The virus appeared to be more sensitive to UVB-induced damage yet did appear to be able to undergo repair. No direct correlation could be made between the presence of the virus and the increase in autoantigen expression. La/SS-B and/or 52 kDa Ro antigen(s) were found to be present in the cytoplasm of the B lymphoblastoid cells at a higher base level in EBV-infected cell lines than in the EBV-negative cell lines.     

Correlative studies of rheumatoid factors and anti-viral antibodies in patients with rheumatoid arthritis.

An analysis of the relationship between the immune response to ubiquitous herpes family viruses, namely Epstein-Barr virus (EBV), cytomegalovirus (CMV), and varicella-zoster virus (VZV) and the presence of rheumatoid factors (RF), which are autoantibodies characteristic of patients with rheumatoid arthritis (RA), was conducted. Antibody profiles (RF, anti-viral antibodies) were monitored in the serum of the RA patients, and in normal individuals. No patient was found to have circulating RF in the absence of anti-viral antibodies. When the patients and normal controls were subdivided according to the presence of serum RF, it was found that when RF were present, the frequency of anti-CMV antibodies, but not anti-EBV or anti-VZV antibodies, was significantly higher (P = 0.02) when compared with RF-negative individuals. The titres of anti-CMV but not anti-VZV antibodies were found to increase in the RA patients with disease duration. To see if these viruses could stimulate RF production in vitro, peripheral blood mononuclear cells (PBMC) isolated from the patients and normal controls were stimulated with viral antigens. PBMC from normal controls, but not from RA patients, appeared to be responsive to viral antigen stimulation and produced RF. These data suggest that the immune response to CMV, to a greater extent than to EBV or VZV, correlates with the presence of RF.     

Bioterrorism risk perceptions and educational needs of public health professionals before and after September 11, 2001: a national needs assessment survey.

The study objectives were to compare local public health professionals' bioterrorism risk perceptions, the extent of bioterrorism preparedness training, and to describe preferred methods for delivery of preparedness education in the United States. National needs assessments were conducted via a mailed survey to 3,074 local public health departments in October 2000 and November 2001. Compared to a survey conducted in October 2000, the perceived risk of a bioterrorism attack in the United States increased dramatically after September 11 (p < 0.0001); however, 57% of respondents believed one was unlikely to occur within their own community. Public health professionals perceive their own communities to be at low risk for a bioterrorism event. Ongoing, updated, standardized bioterrorism preparedness education is needed.     

Assessing the predictive ability of the Suicide Crisis Inventory for near‐term suicidal behavior using machine learning approaches

ObjectiveThis study explores the prediction of near‐term suicidal behavior using machine learning (ML) analyses of the Suicide Crisis Inventory (SCI), which measures the Suicide Crisis Syndrome, a presuicidal mental state.MethodsSCI data were collected from high‐risk psychiatric inpatients (N = 591) grouped based on their short‐term suicidal behavior, that is, those who attempted suicide between intake and 1‐month follow‐up dates (N = 20) and those who did not (N = 571). Data were analyzed using three predictive algorithms (logistic regression, random forest, and gradient boosting) and three sampling approaches (split sample, Synthetic minority oversampling technique, and enhanced bootstrap).ResultsThe enhanced bootstrap approach considerably outperformed the other sampling approaches, with random forest (98.0% precision; 33.9% recall; 71.0% Area under the precision‐recall curve [AUPRC]; and 87.8% Area under the receiver operating characteristic [AUROC]) and gradient boosting (94.0% precision; 48.9% recall; 70.5% AUPRC; and 89.4% AUROC) algorithms performing best in predicting positive cases of near‐term suicidal behavior using this dataset.ConclusionsML can be useful in analyzing data from psychometric scales, such as the SCI, and for predicting near‐term suicidal behavior. However, in cases such as the current analysis where the data are highly imbalanced, the optimal method of measuring performance must be carefully considered and selected.