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Bacteriological methods. Sputum samples were collected as described elsewhere [ 13 , 14 ]. Cultures for isolation of S. pneumoniae were performed by plating serial dilutions of the sputum samples onto blood agar plates. S. pneumoniae was identified by colony morphology and optochin sensitivity. No patient who was found to be colonized with S. pneumoniae within 2 months of enrollment in the study was included in the present article.

Serum samples. Blood samples collected during clinic visits were allowed to clot. Serum was obtained by centrifugation and were stored at −80°C. We chose to analyze the serum sample 2 or 4 months before a visit at which a new strain of S. pneumoniae was isolated (referred to as the 2 month or 4 month preacquisition serum), to reduce the possibility that a patient preacquisition sample may in fact represent a sample obtained after colonization had occurred but had not yet been detected. Patients followed up in the same study who did not have any S. pneumoniae isolated for >24 months were defined as control subjects, and their serum samples were used for comparison. In our study, each serum assay represents a unique patient.

Measurements of serum antipneumococcal antibody concentration. All antibody measurements were performed by ELISA. The concentration of serum IgG to capsular polysaccharides type 6B, 7F, 14, 19F, and 23F was determined by ELISA according to published methods, using both C polysaccharide (CPS) and 22F absorption to remove nonspecific, cross-reactive antibodies [ 16 ]. The standard used in these assays was serum G141A-3 (a gift from Dr. George Siber, Wyeth-Lederle Vaccine, Pearl River, NY), which was assigned values of 6.64, 20.1, 31.5, 16.4, and 11.4 µg/mL for concentrations of IgG against types 6B, 7F, 14, 19F, and 23F, respectively.

A whole-cell pneumococcal IgG ELISA was developed by modifying a previously established assay in mice [ 17 ]. The whole-cell ELISA used pneumococcal strain Rx1AL ⁻ , an unencapsulated derivative of a serotype 2 strain. Rx1AL ⁻ is also lytA deficient; this mutation allows growth to high density and impairs the release of pneumolysin, which is thus concentrated in the bacterial pellet. Rx1AL ⁻ was grown to the late logarithmic phase in Todd-Hewitt broth supplemented with 0.5% yeast extract, harvested by centrifugation, killed by the addition of 70% ethanol, washed repeatedly, and resuspended in PBS. This ethanol-inactivated whole-cell bacterial suspension was used to coat the wells of a microtiter plate (Immulon II; Thermo Labsystems)—100 µL of the suspension were used in each well, corresponding to ∼10 ⁷ cells/well. The plate was incubated overnight at 4°C. The next day, wells were washed with 0.05% Tween 20 in PBS (PBST), and unbound sites in the wells were blocked by the addition of 5% fetal calf serum in PBST for 1 h at room temperature. After wells were washed, 100 µL of 8 serial dilutions of serum in PBST were added to the wells, and the plate was incubated at 37°C for 2 h. After the wells were washed 3 times with PBST, 100 µL of dilution of peroxidase-labeled goat anti-human IgG or IgM (Sigma-Aldrich) in PBST were added to each well, and the plate was incubated at room temperature for 1 h. After another wash, 100 µL of Sureblue peroxidase substrate (Kirkegaard Perry Laboratories) were added to each well. After 15 min of color development in the dark, the reaction was stopped by the addition of 50 µL of 2 N sulfuric acid to each well, and the optical density at 450 nm was read. Controls included wells in which PBS was used instead of serum and wells in which PBS was used instead of the bacterial suspension. These controls consistently showed negligible color development. A standard was also used on all plates that consisted of serum from a healthy adult volunteer selected by virtue of a high concentration of anti-pneumococcal antibodies.

A high percentage of patients (25/30 patients – 83.3%) had at least one comorbidity associated with RA. The main morbid conditions found were arterial hypertension (22/30 – 73.3%), fibromyalgia (16/30 – 53.3%), dyslipidemia (10/30 – 33.3%), depression (8/30 – 26.6%), anxiety disorders (7/30 – 23.3%), hypothyroidism (11/30 – 36.6%) and osteoporosis (2/30 – 6.6%).

Fig. 1

Effects of anti-CCP and RF positivity on phagocytosis of non-opsonized yeast cells by neutrophils from RA patients. Data are expressed as medians, quartiles and extreme values. RA caused a rise in the phagocytosis of non-opsonized yeast ( < 0.0001; test with Welch’s correction) and anti-CCP-positive and RF-positive individuals displayed a higher phagocytic index. This increase was due to an increase in the percent of neutrophils engaged in phagocytosis, but no difference was observed in the number of yeast ingested between anti-CCP- or RF-negative or -positive individuals ( > 0.05).Top: neutrophil phagocytic index ( a , b , c ); Middle: average number of S. cerevisiae yeast cells ingested by phagocytosing neutrophil ( d , e , f ); Bottom: percent of neutrophils engaged in phagocytosis ( g , h , i ). The statistical differences are marked in the graphics and in text

Fig. 2

Effect of anti-CCP and RF positivity on the phagocytosis of non-opsonized yeast cells by monocytes from RA patients. Data are expressed as medians, quartiles and extreme values. RA caused a rise in the phagocytosis of non-opsonized yeasts ( < 0.0009; test with Welch’s correction), but no difference was observed between anti-CCP- or RF-negative or -positive individuals ( > 0.05).Top: monocyte phagocytic index ( a , b , c ); Middle: average number of S. cerevisiae yeast cells ingested by phagocytosing monocyte ( d , e , f ); Bottom: percent of monocytes engaged in phagocytosis ( g , h , i ). The statistical differences are marked in the graphics and in text

Fig. 3

Effect of anti-CCP and RF positivity on the phagocytosis of opsonized yeast cells by neutrophils from RA patients. Data are expressed as medians, quartiles and extreme values. RA caused a rise in the phagocytosis of opsonized yeast ( < 0.04; Mann–Whitney test), but no difference was observed between anti-CCP- or RF-negative or -positive individuals ( > 0.05).Top: neutrophil phagocytic index ( a , b , c ); Middle: number of S. cerevisiae yeast cells phagocytosed by neutrophil ( d , e , f ); Bottom: percent of neutrophils engaged in phagocytosis ( g , h , i ). The statistical differences are marked in the graphics and in text

Fig. 4

Effect of anti-CCP and RF positivity on the phagocytosis of opsonized yeast cells by monocytes from RA patients. Data are expressed as medians, quartiles and extreme values. RA caused an increase in the phagocytosis of opsonized yeast ( < 0.001; test with Welch’s correction), but no difference was observed between anti-CCP- or RF-negative or -positive individuals ( > 0.05).Top: monocyte phagocytic index ( a , b , c ); Middle: number of S. cerevisiae yeast cells phagocytosed by monocyte ( d , e , f ); Bottom: percent of monocytes engaged in phagocytosis ( g , h , i ). The statistical differences are marked in the graphics and in text

Fig. 5

Effect of anti-CCP and RF positivity on the production of superoxide anions by phagocytes from RA patients. Data are expressed as medians, quartiles and extreme values, and outlier values are indicated. Individuals with RA produced a significantly higher amount of superoxide anion than controls ( = 0.0026, Mann–Whitney test). Positivity for anti-CCP or RF was not statistically associated with increased superoxide anion production ( > 0.05). a : rheumatoid arthritis patients versus healthy control; b : anti-CCP negative versus positive RA patients; c : RF negative versus positive RA patients. The statistical differences are marked in the graphics and in text

Although radiographic erosions at initial evaluation were more frequent in anti-CCP-positive individuals (Table 1 ), no association between phagocytosis or superoxide anion production by peripheral neutrophils and monocytes and the clinical, radiological, and therapeutic variables analyzed in this study were observed. These variables included disease activity (DAS28), functional incapacity (HAQ), use of synthetic or biologic DMARDs (medication, dosage), lifestyle (physical activity, current or prior smoking), education, comorbidities and presence of radiographic erosions ( p > 0.05 for all, Mann–Whitney test).

I already responded to the first part so now I’ll respond to the second part, the part about random mutations messing up the design.

First of all, your imaginary designer-god must be a total klutz if it didn’t design things so that random mutations are prevented from messing up its designs. Maybe you could explain how a designer-god that allegedly designed and created the entire universe and all living things could be so inept? I suppose you could say that the designer-god isn’t inept but then you’d need to explain why the designer-god of the universe and living things would be so cruel as to deliberately design destructive/deadly mutations into living things and to deliberately design catastrophes that ‘mess up’ living things or the rest of its designs.

And by the way joe, you seem to have a problem making up your mind about whether mutations are or can be “random”. For instance, here you are posting as “ID guy”:

(don provan): I’m not objecting to the observation that bacteria have some control over their mutations. I’m just pointing out that, despite that, there is a random element to mutations.

All you have done, if anything, is show that some mutations are random- and that is because the researchers refuse to accept that organisms are designed.

Ya see peter, the only way to say that all mutations are random in any sense of the word is to demonstrate stochastic processes can produce living organisms- IOW just as I have been telling you the origins is essential to understanding any subsequent evolution.

ID claims that it occurred by design, ie via genetic algorithms directing mutations to achieve a pre-specified result.

Ya see saying it occurred via accumulations of random mutations is untestable and besides that there isn’t any evidence to support it.

(Zachriel): The Lederberg Experiment shows that the variations are random with respect to fitness.

(Zachriel): If you are referring to Quiet Bacteria and Antibiotic Resistance, it doesn’t impact the Lederberg Experiment.