Measurement of the main and critical parameters for optimal laser treatment of heart disease

Abstract: Laser light is frequently used in the diagnosis and treatment of patients. As in traditional treatments such as medication, bypass surgery, and minimally invasive ways, laser treatment can also fail and present serious side effects. The true reason for laser treatment failure or the side effects thereof, remains unknown. From the literature review conducted, and experimental results generated we conclude that an optimal laser treatment for coronary artery disease (named heart disease) can be obtained if certain critical parameters are correctly measured and understood. These parameters include the laser power, the laser beam profile, the fluence rate, the treatment time, as well as the absorption and scattering coefficients of the target treatment tissue. Therefore, this paper proposes different, accurate methods for the measurement of these critical parameters to determine the optimal laser treatment of heart disease with a minimal risk of side effects. The results from the measurement of absorption and scattering properties can be used in a computer simulation package to predict the fluence rate. The computing technique is a program based on the random number (Monte Carlo) process and probability statistics to track the propagation of photons through a biological tissue

The Distances of the Magellanic Clouds

The present status of our knowledge of the distances to the Magellanic Clouds is evaluated from a post-Hipparcos perspective. After a brief summary of the effects of structure, reddening, age and metallicity, the primary distance indicators for the Large Magellanic Cloud are reviewed: The SN 1987A ring, Cepheids, RR Lyraes, Mira variables, and Eclipsing Binaries. Distances derived via these methods are weighted and combined to produce final "best" estimates for the Magellanic Clouds distance moduli.Comment: Invited review article to appear in ``Post Hipparcos Cosmic Candles'', F. Caputo & A. Heck (Eds.), Kluwer Academic Publ., Dordrecht, in pres

Does long-term care use within primary health care reduce hospital use among older people in Norway? A national five-year population-based observational study

<p>Abstract</p> <p>Background</p> <p>Population ageing may threaten the sustainability of future health care systems. Strengthening primary health care, including long-term care, is one of several measures being taken to handle future health care needs and budgets. There is limited and inconsistent evidence on the effect of long-term care on hospital use. We explored the relationship between the total use of long-term care within public primary health care in Norway and the use of hospital beds when adjusting for various effect modifiers and confounders.</p> <p>Methods</p> <p>This national population-based observational study consists of all Norwegians (59% women) older than 66 years (N = 605676) (13.2% of total population) in 2002-2006. The unit of analysis was defined by municipality, age and sex. The association between total number of recipients of long-term care per 1000 inhabitants (LTC-rate) and hospital days per 1000 inhabitants (HD-rate) was analysed in a linear regression model. Modifying and confounding effects of socioeconomic, demographic and geographic variables were included in the final model. We defined a difference in hospitalization rates of more than 1000 days per 1000 inhabitants as clinically important.</p> <p>Results</p> <p>Thirty-one percent of women and eighteen percent of men were long-term care users. Men had higher HD-rates than women. The crude association between LTC-rate and HD-rate was weakly negative. We identified two effect modifiers (age and sex) and two strong confounders (travel time to hospital and mortality). Age and sex stratification and adjustments for confounders revealed a positive statistically significant but not clinically important relationship between LTC-rates and hospitalization for women aged 67-79 years and all men. For women 80 years and over there was a weak but negative relationship which was neither statistically significant nor clinically important.</p> <p>Conclusions</p> <p>We found a weak positive adjusted association between LTC-rates and HD-rates. Opposite to common belief, we found that increased volume of LTC by itself did not reduce pressure on hospitals. There still is a need to study integrated care models for the elderly in the Norwegian setting and to explore further why municipalities far away from hospital achieve lower use of hospital beds.</p

Design and Synthesis of a Quintessential Self-Transmissible IncX1 Plasmid, pX1.0

DNA exchange in bacteria via conjugative plasmids is believed to be among the most important contributing factors to the rapid evolution- and diversification rates observed in bacterial species. The IncX1 plasmids are particularly interesting in relation to enteric bacteria, and typically carry genetic loads like antibiotic resistance genes and virulence factors. So far, however, a “pure” version of these molecular parasites, without genetic loads, has yet to be isolated from the environment. Here we report the construction of pX1.0, a fully synthesized IncX1 plasmid capable of horizontal transfer between different enteric bacteria. The designed pX1.0 sequence was derived from the consensus gene content of five IncX1 plasmids and three other, more divergent, members of the same phylogenetic group. The pX1.0 plasmid was shown to replicate stably in E. coli with a plasmid DNA per total DNA ratio corresponding to approximately 3–9 plasmids per chromosome depending on the growth phase of the host. Through conjugation, pX1.0 was able to self-transfer horizontally into an isogenic strain of E. coli as well as into two additional species belonging to the family Enterobacteriaceae. Our results demonstrate the immediate applicability of recent advances made within the field of synthetic biology for designing and constructing DNA systems, previously existing only in silica

SCOTROC 2B: feasibility of carboplatin followed by docetaxel or docetaxel–irinotecan as first-line therapy for ovarian cancer

The feasibility of combination irinotecan, carboplatin and docetaxel chemotherapy as first-line treatment for advanced epithelial ovarian carcinoma was assessed. One hundred patients were randomised to receive four 3-weekly cycles of carboplatin (area under the curve (AUC) 7) followed by four 3-weekly cycles of docetaxel 100 mg m−2 (arm A, n=51) or docetaxel 60 mg m−2 with irinotecan 200 mg m−2 (arm B, n=49). Neither arm met the formal feasibility criterion of an eight-cycle treatment completion rate that was statistically greater than 60% (arm A 71% (90% confidence interval (CI) 58–81%; P=0.079; arm B 67% (90% CI 55–78%; P=0.184)). Median-dose intensities were >85% of planned dose for all agents. In arms A and B, 15.6 and 12.2% of patients, respectively, withdrew owing to treatment-related toxicity. Grade 3–4 sensory neurotoxicity was more common in arm A (1.9 vs 0%) and grade 3–4 diarrhoea was more common in arm B (0.6 vs 3.5%). Of patients with radiologically evaluable disease at baseline, 50 and 48% responded to therapy in arms A and B, respectively; at median 17.1 months' follow-up, median progression-free survival was 17.1 and 15.9 months, respectively. Although both arms just failed to meet the formal statistical feasibility criteria, the observed completion rates of around 70% were reasonable. The addition of irinotecan to first-line carboplatin and docetaxel chemotherapy was generally well tolerated although associated with increased gastrointestinal toxicity. Further exploratory studies of topoisomerase-I inhibitors in this setting may be warranted

Inference of reticulate evolutionary histories by maximum likelihood: the performance of information criteria

Background: Maximum likelihood has been widely used for over three decades to infer phylogenetic trees from molecular data. When reticulate evolutionary events occur, several genomic regions may have conflicting evolutionary histories, and a phylogenetic network may provide a more adequate model for representing the evolutionary history of the genomes or species. A maximum likelihood (ML) model has been proposed for this case and accounts for both mutation within a genomic region and reticulation across the regions. However, the performance of this model in terms of inferring information about reticulate evolution and properties that affect this performance have not been studied. Results: In this paper, we study the effect of the evolutionary diameter and height of a reticulation event on its identifiability under ML. We find both of them, particularly the diameter, have a significant effect. Further, we find that the number of genes (which can be generalized to the concept of "non-recombining genomic regions") that are transferred across a reticulation edge affects its detectability. Last but not least, a fundamental challenge with phylogenetic networks is that they allow an arbitrary level of complexity, giving rise to the model selection problem. We investigate the performance of two information criteria, the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), for addressing this problem. We find that BIC performs well in general for controlling the model complexity and preventing ML from grossly overestimating the number of reticulation events. Conclusion: Our results demonstrate that BIC provides a good framework for inferring reticulate evolutionary histories. Nevertheless, the results call for caution when interpreting the accuracy of the inference particularly for data sets with particular evolutionary features

Hospital service areas – a new tool for health care planning in Switzerland

BACKGROUND: The description of patient travel patterns and variations in health care utilization may guide a sound health care planning process. In order to accurately describe these differences across regions with homogeneous populations, small area analysis (SAA) has proved as a valuable tool to create appropriate area models. This paper presents the methodology to create and characterize population-based hospital service areas (HSAs) for Switzerland. METHODS: We employed federal hospital discharge data to perform a patient origin study using small area analysis. Each of 605 residential regions was assigned to one of 215 hospital provider regions where the most frequent number of discharges took place. HSAs were characterized geographically, demographically, and through health utilization indices and rates that describe hospital use. We introduced novel planning variables extracted from the patient origin study and investigated relationships among health utilization indices and rates to understand patient travel patterns for hospital use. Results were visualized as maps in a geographic information system (GIS). RESULTS: We obtained 100 HSAs using a patient origin matrix containing over four million discharges. HSAs had diverse demographic and geographic characteristics. Urban HSAs had above average population sizes, while mountainous HSAs were scarcely populated but larger in size. We found higher localization of care in urban HSAs and in mountainous HSAs. Half of the Swiss population lives in service areas where 65% of hospital care is provided by local hospitals. CONCLUSION: Health utilization indices and rates demonstrated patient travel patterns that merit more detailed analyses in light of political, infrastructural and developmental determinants. HSAs and health utilization indices provide valuable information for health care planning. They will be used to study variation phenomena in Swiss health care