Anoxic Iron Cycling Bacteria from an Iron Sulfide- and Nitrate-Rich Freshwater Environment

In this study, both culture-dependent and culture-independent methods were used to determine whether the iron sulfide mineral- and nitrate-rich freshwater nature reserve Het Zwart Water accommodates anoxic microbial iron cycling. Molecular analyses (16S rRNA gene clone library and fluorescence in situ hybridization, FISH) showed that sulfur-oxidizing denitrifiers dominated the microbial population. In addition, bacteria resembling the iron-oxidizing, nitrate-reducing Acidovorax strain BrG1 accounted for a major part of the microbial community in the groundwater of this ecosystem. Despite the apparent abundance of strain BrG1-like bacteria, iron-oxidizing nitrate reducers could not be isolated, likely due to the strictly autotrophic cultivation conditions adopted in our study. In contrast an iron-reducing Geobacter sp. was isolated from this environment while FISH and 16S rRNA gene clone library analyses did not reveal any Geobacter sp.-related sequences in the groundwater. Our findings indicate that iron-oxidizing nitrate reducers may be of importance to the redox cycling of iron in the groundwater of our study site and illustrate the necessity of employing both culture-dependent and independent methods in studies on microbial processes

Another Avenue for Anatomy of Income Comparisons : Evidence from Hypothetical Choice Experiments

September 2010, Revised December 2010, Secondly Revised November 2011, Thirdly Revised May 2012, Fourthly Revised March 2013

Perceived barriers for treatment of chronic heart failure in general practice; are they affecting performance?

BACKGROUND: The aim of this study is to determine to what extent barriers perceived by general practitioners (GPs) for prescribing angiotensin-converting enzyme inhibitors (ACE-I) in chronic heart failure (CHF) patients are related to underuse and underdosing of these drugs in actual practice. METHODS: Barriers were assessed with a semi-structured questionnaire. Prescribing data were extracted from GPs' computerised medical records for a random sample of their CHF patients. Relations between barriers and prescribing behaviour were assessed by means of Spearman rank correlation and multivariate regression modelling. RESULTS: GPs prescribed ACE-I to 45% of their patients and had previously initiated such treatment in an additional 3.5%, in an average standardised dose of 13.5 mg. They perceived a median of four barriers in prescribing ACE-I or optimising ACE-I dose. Many GPs found it difficult to change treatment initiated by a cardiologist. Furthermore, initiating ACE-I in patients already using a diuretic or stable on their current medication was perceived as barrier. Titrating the ACE-I dose was seen as difficult by more than half of the GPs. No significant relationships could be found between the barriers perceived and actual ACE-I prescribing. Regarding ACE-I dosing, the few GPs who did not agree that the ACE-I should be as high as possible prescribed higher ACE-I doses. CONCLUSION: Variation between GPs in prescribing ACE-I for CHF cannot be explained by differences in the barriers they perceive. Tailor-made interventions targeting only those doctors that perceive a specific barrier will therefore not be an efficient approach to improve quality of care

Methods to identify the target population: implications for prescribing quality indicators

Background: Information on prescribing quality is increasingly used by policy makers, insurance companies and health care providers. For reliable assessment of prescribing quality it is important to correctly identify the patients eligible for recommended treatment. Often either diagnostic codes or clinical measurements are used to identify such patients. We compared these two approaches regarding the outcome of the prescribing quality assessment and their ability to identify treated and undertreated patients. Methods: The approaches were compared using electronic health records for 3214 diabetes patients from 70 general practitioners. We selected three existing prescribing quality indicators (PQI) assessing different aspects of treatment in patients with hypertension or who were overweight. We compared population level prescribing quality scores and proportions of identified patients using definitions of hypertension or being overweight based on diagnostic codes, clinical measurements or both. Results: The prescribing quality score for prescribing any antihypertensive treatment was 93% (95% confidence interval 90-95%) using the diagnostic code-based approach, and 81% (78-83%) using the measurement-based approach. Patients receiving antihypertensive treatment had a better registration of their diagnosis compared to hypertensive patients in whom such treatment was not initiated. Scores on the other two PQI were similar for the different approaches, ranging from 64 to 66%. For all PQI, the clinical measurement -based approach identified higher proportions of both well treated and undertreated patients compared to the diagnostic code -based approach. Conclusions: The use of clinical measurements is recommended when PQI are used to identify undertreated patients. Using diagnostic codes or clinical measurement values has little impact on the outcomes of proportion-based PQI when both numerator and denominator are equally affected. In situations when a diagnosis is better registered for treated than untreated patients, as we observed for hypertension, the diagnostic code-based approach results in overestimation of provided treatment

What's New Is Old: Resolving the Identity of Leptothrix ochracea Using Single Cell Genomics, Pyrosequencing and FISH

Leptothrix ochracea is a common inhabitant of freshwater iron seeps and iron-rich wetlands. Its defining characteristic is copious production of extracellular sheaths encrusted with iron oxyhydroxides. Surprisingly, over 90% of these sheaths are empty, hence, what appears to be an abundant population of iron-oxidizing bacteria, consists of relatively few cells. Because L. ochracea has proven difficult to cultivate, its identification is based solely on habitat preference and morphology. We utilized cultivation-independent techniques to resolve this long-standing enigma. By selecting the actively growing edge of a Leptothrix-containing iron mat, a conventional SSU rRNA gene clone library was obtained that had 29 clones (42% of the total library) related to the Leptothrix/Sphaerotilus group (≤96% identical to cultured representatives). A pyrotagged library of the V4 hypervariable region constructed from the bulk mat showed that 7.2% of the total sequences also belonged to the Leptothrix/Sphaerotilus group. Sorting of individual L. ochracea sheaths, followed by whole genome amplification (WGA) and PCR identified a SSU rRNA sequence that clustered closely with the putative Leptothrix clones and pyrotags. Using these data, a fluorescence in-situ hybridization (FISH) probe, Lepto175, was designed that bound to ensheathed cells. Quantitative use of this probe demonstrated that up to 35% of microbial cells in an actively accreting iron mat were L. ochracea. The SSU rRNA gene of L. ochracea shares 96% homology with its closet cultivated relative, L. cholodnii, This establishes that L. ochracea is indeed related to this group of morphologically similar, filamentous, sheathed microorganisms

Determinants of the range of drugs prescribed in general practice: a cross-sectional analysis

Background: Current health policies assume that prescribing is more efficient and rational when general practitioners (GPs) work with a formulary or restricted drugs lists and thus with a limited range of drugs. Therefore we studied determinants of the range of drugs prescribed by general practitioners, distinguishing general GP-characteristics, characteristics of the practice setting, characteristics of the patient population and information sources used by GPs. Methods: Secondary analysis was carried out on data from the Second Dutch Survey in General Practice. Data were available for 138 GPs working in 93 practices. ATC-coded prescription data from electronic medical records, census data and data from GP/ practice questionnaires were analyzed with multilevel techniques. Results: The average GP writes prescriptions for 233 different drugs, i.e. 30% of the available drugs on the market within one year. There is considerable variation between ATC main groups and subgroups and between GPs. GPs with larger patient lists, GPs with higher prescribing volumes and GPs who frequently receive representatives from the pharmaceutical industry have a broader range when controlled for other variables. Conclusion: The range of drugs prescribed is a useful instrument for analysing GPs' prescribing behaviour. It shows both variation between GPs and between therapeutic groups. Statistically significant relationships found were in line with the hypotheses formulated, like the one concerning the influence of the industry. Further research should be done into the relationship between the range and quality of prescribing and the reasons why some GPs prescribe a greater number of different drugs than others.