Screeningof Indian Plants for BiologicalActivity-Part XI

Alcoholic extracts of two hundred and ninety two botanically identified plant species have been tested for a wide variety of biological activities including chemotherapeutic and pharmacological activities. Biological activities have been confirmed in fractions of 46 of these extracts. Follow-up studies have been carried out in some plants with confirmed activity. The active principles and results of these studies have also been reported.

Coping resources in a sample of chronic low back pain patients: Evaluation of the questionnaire for back pain

BACKGROUND The coping resources questionnaire for back pain (FBR) uses 12 items to measure the perceived helpfulness of different coping resources (CRs, social emotional support, practical help, knowledge, movement and relaxation, leisure and pleasure, spirituality and cognitive strategies). The aim of the study was to evaluate the instrument in a clinical patient sample assessed in a primary care setting. SAMPLE AND METHODS The study was a secondary evaluation of empirical data from a large cohort study in general practices. The 58 participating primary care practices recruited patients who reported chronic back pain in the consultation. Besides the FBR and a pain sketch, the patients completed scales measuring depression, anxiety, resilience, sociodemographic factors and pain characteristics. To allow computing of retested parameters the FBR was sent to some of the original participants again after 6 months (90% response rate). We calculated consistency and retest reliability coefficients as well as correlations between the FBR subscales and depression, anxiety and resilience scores to account for validity. By means of a cluster analysis groups with different resource profiles were formed. Results. RESULTS For the study 609 complete FBR baseline data sets could be used for statistical analysis. The internal consistency scores ranged fromα=0.58 to α=0.78 and retest reliability scores were between rTT=0.41 and rTT=0.63. Correlation with depression, fear and resilience ranged from r=-0.38 to r=0.42. The cluster analysis resulted in four groups with relatively homogenous intragroup profiles (high CRs, low spirituality, medium CRs, low CRs). The four groups differed significantly in fear and depression (the more inefficient the resources the higher the difference) as well as in resilience (the more inefficient the lower the difference). The group with low CRs also reported permanent pain with no relief. The groups did not otherwise differ. CONCLUSIONS The FBR is an economic instrument that is suitable for practical use e.g. in primary care practices to identify strengths and deficits in the CRs of chronic pain patients that can then be specified in face to face consultation. However, due to the rather low reliability, the use of subscales for profile differentiation and follow-up measurement in individual diagnoses is limited.

Assessing vegetation cover and biomass in restored erosion areas in Iceland using SPOT satellite data

Due to highly erodible volcanic soils and a harsh climate, livestock grazing in Iceland has led to serious soil erosion on about 40% of the country's surface. Over the last 100 years, various revegetation and restoration measures were taken on large areas distributed all over Iceland in an attempt to counteract this problem. The present research aimed to develop models for estimating percent vegetation cover (VC) and aboveground biomass (AGB) based on satellite data, as this would make it possible to assess and monitor the effectiveness of restoration measures over large areas at a fairly low cost. Models were developed based on 203 vegetation cover samples and 114 aboveground biomass samples distributed over five SPOT satellite datasets. All satellite datasets were atmospherically corrected, and digital numbers were converted into ground reflectance. Then a selection of vegetation indices (VIs) was calculated, followed by simple and multiple linear regression analysis of the relations between the field data and the calculated VIs. Best results were achieved using multiple linear regression models for both %VC and AGB. The model calibration and validation results showed that R2 and RMSE values for most VIs do not vary very much. For percent VC, R2 values range between 0.789 and 0.822, leading to RMSEs ranging between 15.89% and 16.72%. For AGB, R2 values for low-biomass areas (AGB < 800 g/m2) range between 0.607 and 0.650, leading to RMSEs ranging between 126.08 g/m2 and 136.38 g/m2. The AGB model developed for all areas, including those with high biomass coverage (AGB > 800 g/m2), achieved R2 values between 0.487 and 0.510, resulting in RMSEs ranging from 234 g/m2 to 259.20 g/m2. The models predicting percent VC generally overestimate observed low percent VC and slightly underestimate observed high percent VC. The estimation models for AGB behave in a similar way, but over- and underestimation are much more pronounced. These results show that it is possible to estimate percent VC with high accuracy based on various VIs derived from SPOT satellite data. AGB of restoration areas with low-biomass values of up to 800 g/m2 can likewise be estimated with high accuracy based on various VIs derived from SPOT satellite data, whereas in the case of high biomass coverage, estimation accuracy decreases with increasing biomass values. Accordingly, percent VC can be estimated with high accuracy anywhere in Iceland, whereas AGB is much more difficult to estimate, particularly for areas with high-AGB variability.

An unmatched case controlled study of clinicopathologic abnormalities in dogs with Bartonella infection

We compared clinicopathologic findings in dogs with Bartonella infection to Bartonella spp. negative dogs suspected of a vector-borne disease. Cases (n=47) and controls (n=93) were selected on the basis of positive or negative enrichment culture PCR results, respectively. Signalment, clinicopathologic findings and treatments were extracted from medical records. DNA sequencing identified Bartonella henselae (n=28, 59.6%), Bartonella vinsonii subsp. berkhoffii (n=20, 42.6%), Bartonella koehlerae (n=3, 6.4%), Bartonella volans-like (n=3, 6.4%) and Bartonella bovis (n=1, 2.1%). There were no significant differences in age, breed, size, sex or neuter status between cases and controls. Dogs infected with Bartonella sp. often had a history of weight loss [OR=2.82; 95% CI: 1.08-7.56] and were hypoglobulinemic [OR=4.26; 95% CI: 1.31-14.41]. With the exception of weight loss and hypoglobulinemia, clinicopathologic abnormalities in Bartonella-infected dogs in this study were similar to dogs suspected of other vector-borne infections.

Transcatheter aortic valve implantation: patient selection

Transcatheter aortic valve implantation (TAVI) is a disruptive technology as it satisfies a previously unmet need which is associated with a profound therapeutic benefit. In randomized clinical trials, TAVI has been shown to improve survival compared with medical treatment among patients considered not suitable candidates for surgical aortic valve replacement (SAVR), and to provide similar outcomes as SAVR in selected high-risk patients. Currently, TAVI is limited to selected elderly patients with symptomatic severe aortic stenosis. As this patient population frequently suffers from comorbid conditions, which may influence outcomes, the selection of patients to undergo TAVI underlies a complex decision process. Several clinical risk score algorithms are routinely used, although they fall short to fully appreciate the true risk among patients currently referred for TAVI. Beyond traditional risk scores, the clinical assessment by an interdisciplinary Heart Team as well as detailed imaging of the aortic valve, aortic root, descending and abdominal aorta as well as peripheral vasculature are important prerequisites to plan a successful procedure. This review will familiarize the reader with the concepts of the interdisciplinary Heart team, risk scores as well as the most important imaging algorithms suited to select appropriate TAVI patients.