Improved detection of Candida albicans by PCR in blood of neutropenic mice with systemic candidiasis

A PCR using primers aimed at the multicopy gene coding for the small subunit rRNA and resulting in the synthesis of a 180-bp fragment was evaluated for its use in diagnosing invasive candidiasis in comparison with blood culture. With the use of a C. albicans-specific probe, +/- 10 to 15 C. albicans cells are detected in 100 microliters of whole blood by Southern analysis. A DNase pretreatment was critical in the purification process of yeast DNA from whole blood. Omission of the DNase pretreatment decreased assay sensitivity 10-fold. PCR analysis of blood specimens collected from mice with invasive candidiasis is more sensitive than blood culture (100 versus 67%, respectively) at 72 h after intravenous (i.v.) inoculation with C. albicans. Furthermore, the intensity of the hybridization signals increased with the progression of infection. In contrast, multiple blood samples from gastrointestinally colonized mice were all negative by PCR, indicating that the PCR assay is also specific and may, therefore, make a positive contribution to the detection and follow-up of invasive candidiasis

PCR monitoring of response to liposomal amphotericin B treatment of systemic candidiasis in neutropenic mice

When a diagnosis of invasive candidiasis has been made, treatment with toxic fungicidal agents is inevitable. The crucial decision of when to stop such treatment is difficult to make, because cultures are often negative despite ongoing invasive candidiasis and can therefore not be used as a reliable parameter of effective therapy. In the present study, the use of PCR in monitoring the therapeutic efficacy of antifungal treatment with liposomal amphotericin B was evaluated by using neutropenic mice with systemic candidiasis. Blood cultures of infected mice treated with different doses of liposomal amphotericin B were only positive at the early onset of the infection process and became sterile within 3 days; this was true even with mice treated with 1 mg of liposomal amphotericin B per kg of body weight that experienced a relapse of infection 14 days later. A significant correlation between presence of Candida albicans in the kidneys and PCR results obtained with blood was demonstrated. Thus, PCR results obtained with blood samples correlated well with the therapeutic efficacy of antifungal treatment

Onweerstaanbare sekslokstoffen komen uit het lab (interview met Frans Griepink et al)

Feromonen krijgen een steeds grotere rol in de gewasbeschermmg: om een specifiek insect te detecteren, massaal te vangen, te verwarren of te lokken voor chemische bestrijding. Pherobank (PRI) is wereldwijd dé specialist op het gebied van mottenseksferomonen. In het lab worden ze chemisch nagemaakt en 'verpakt' in de bekende rubber dopje

Longitudinaal Verplaatsingsonderzoek, meting 10, 1989 - LVO

Monitoring the effects of tariff raises in public transport within the framework of the general mobility developments. This description comprises the tenth wave of the longitudinal mobility survey ( longitudinaal verplaatsingsonderzoek ). Preceding waves are stored under different study numbers. The survey monitors ( changes in ) transportational behaviour, mobility and effects of raising tariffs for public transportation. Data were gathered by questionnaire. Diaries were used for describing all mobility during one week. Detailed data were gathered on: family composition, financial situation of family, working hours, commuting, travelling allowances, car, train, use of reduced fare cards for public transport. Moving to another home and factors influencing this. Use of train in preceding week, month, half year and year. Change in place of work last three years and factors influencing this. Parking facilities near place of work, use of public transportation in commuting, attitude regarding public transport and ownership and use of Pas 65 ( reduction card for the aged ). This wave proper consists of seven files, containing family-data( A=SPSS-file, D=raw data ), family member-data ( B=SPSS-file, E=raw data ), transfer-data ( C=raw data ), week-matrices ( F=raw data ), and commuting data ( G=raw data ) respectively. It contains two extra cumulative files. One contains the most relevant variables from all March-waves of all respondents ever participating ( P1015H ). The second ( P1045J ) uses cars owned by panel-members as units of analysis and contains car-related variables and costs analysis. Moreover this wave contains two general SPSS-setup files, to be used for analyzing the week- matrices and commuting-data files of all waves ( P1045K and P1045L ). General hard-copy documentation relevant to all preceding waves is also stored under this number. Background variables: basic characteristics/ residence/ household characteristics/ occupation/employment/ income/capital assets/ education/ consumption of durable

Longitudinaal Verplaatsingsonderzoek, meting 9, 1988 - LVO

Monitoring the effects of tariff raises in public transport within the framework of the general mobility developments. This description comprises the ninth wave of the longitudinal mobility survey ( longitudinaal verplaatsingsonderzoek ). Subsequent waves will be stored under different study numbers. The survey monitors ( changes in ) transportational behaviour, mobility and effects of raising tariffs for public transportation. Data were gathered by questionnaire. Diaries were used for describing all mobility during one week. Detailed data were gathered on: family composition, financial situation of family, working hours, commuting, travelling allowances, car, train, use of reduced fare cards for public transport. Moving to another home and factors influencing this. Use of train in preceding week, month, half year and year. Change in place of work last three years and factors influencing this. This wave consists of seven files, containing family-data( A=SPSS-file, D=raw data ), family member-data ( B=SPSS-file, E=raw data ), transfer-data ( C=raw data ), week-matrices ( F=raw data ), and commuting data ( G=raw data ) respectively. Background variables: basic characteristics/ residence/ household characteristics/ occupation/employment/ income/capital assets/ education/ consumption of durable