Major differences in organization and availability of health care and medicines for HIV/TB coinfected patients across Europe

OBJECTIVES The aim of the study was to investigate the organization and delivery of HIV and tuberculosis (TB) health care and to analyse potential differences between treatment centres in Eastern (EE) and Western Europe (WE). METHODS Thirty-eight European HIV and TB treatment centres participating in the TB:HIV study within EuroCoord completed a survey on health care management for coinfected patients in 2013 (EE: 17 respondents; WE:21; 76% of all TB:HIV centres). Descriptive statistics were obtained for regional comparisons. The reported data on health care strategies were compared with actual clinical practice at patient level via data derived from the TB:HIV study. RESULTS Respondent centres in EE comprised: Belarus (n = 3), Estonia (1), Georgia (1), Latvia (1), Lithuania (1), Poland (4), Romania (1), the Russian Federation (4) and Ukraine (1); those in WE comprised: Belgium (1), Denmark (1), France (1), Italy (7), Spain (2), Switzerland (1) and UK (8). Compared with WE, treatment of HIV and TB in EE are less often located at the same site (47% in EE versus 100% in WE; P < 0.001) and less often provided by the same doctors (41% versus 90%, respectively; P = 0.002), whereas regular screening of HIV-infected patients for TB (80% versus 40%, respectively; P = 0.037) and directly observed treatment (88% versus 20%, respectively; P < 0.001) were more common in EE. The reported availability of rifabutin and second- and third-line anti-TB drugs was lower, and opioid substitution therapy (OST) was available at fewer centres in EE compared with WE (53% versus 100%, respectively; P < 0.001). CONCLUSIONS Major differences exist between EE and WE in relation to the organization and delivery of health care for HIV/TB-coinfected patients and the availability of anti-TB drugs and OST. Significant discrepancies between reported and actual clinical practices were found in EE.

The stable carbon isotopic composition of Daphnia ephippia in small, temperate lakes reflects in-lake methane availability

Daphnia can ingest methane-oxidizing bacteria and incorporate methanogenic carbon into their biomass, leading to low stable carbon isotope ratios (expressed as δ13C values) of their tissue. Therefore, δ13C analysis of Daphnia resting eggs (ephippia) in lake sediment records can potentially be used to reconstruct past in-lake availability of methane (CH4). However, detailed multilake studies demonstrating that δ13C values of recently deposited Daphnia ephippia (δ13Cephippia) are systematically related to in-lake CH4 concentrations (CH4aq) are still missing. We measured δ13Cephippia from surface sediments of 15 small lakes in Europe, and compared these values with late-summer CH4aq. δ13Cephippia ranged from −51.6‰ to −25.9‰, and was strongly correlated with CH4aq in the surface water and above the sediment (r −0.73 and −0.77, respectively), whereas a negative rather than the expected positive correlation was found with δ13C values of carbon dioxide (CO2) (r −0.54), and no correlation was observed with CO2aq. At eight sites, offsets between δ13 CCO2 and δ13Cephippia exceeded offsets between δ13 CCO2 and δ13Calgae reported in literature. δ13Cephippia was positively correlated with δ13C values of sedimentary organic matter (r 0.54), but up to 20.7‰ lower in all except one of the lakes (average −6.1‰). We conclude that incorporation of methanogenic carbon prior to ephippia formation must have been widespread by Daphnia in our study lakes, especially those with high CH4aq. Our results suggest a systematic relationship between δ13Cephippia values and CH4aq in small temperate lakes, and that δ13Cephippia analysis on sediment records may provide insights into past changes in in-lake CH4aq.

Associating optical measurements and estimating orbits of geocentric objects through population-based meta-heuristic methods

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both, the correct associations among the observations and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. The number S corresponds to the number of fences involved in the problem. Each fence consists of a set of observations where each observation belongs to a different object. The S ≥ 3 MTT problem is an NP-hard combinatorial optimization problem. There are two general ways to solve this. One way is to seek the optimum solution, this can be achieved by applying a branch-and- bound algorithm. When using these algorithms the problem has to be greatly simplified to keep the computational cost at a reasonable level. Another option is to approximate the solution by using meta-heuristic methods. These methods aim to efficiently explore the different possible combinations so that a reasonable result can be obtained with a reasonable computational effort. To this end several population-based meta-heuristic methods are implemented and tested on simulated optical measurements. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.

An MILP-based heuristic for staff scheduling problems with acceptance levels

We present a real-world staff-assignment problem that was reported to us by a provider of an online workforce scheduling software. The problem consists of assigning employees to work shifts subject to a large variety of requirements related to work laws, work shift compatibility, workload balancing, and personal preferences of employees. A target value is given for each requirement, and all possible deviations from these values are associated with acceptance levels. The objective is to minimize the total number of deviations in ascending order of the acceptance levels. We present an exact lexicographic goal programming MILP formulation and an MILP-based heuristic. The heuristic consists of two phases: in the first phase a feasible schedule is built and in the second phase parts of the schedule are iteratively re-optimized by applying an exact MILP model. A major advantage of such MILP-based approaches is the flexibility to account for additional constraints or modified planning objectives, which is important as the requirements may vary depending on the company or planning period. The applicability of the heuristic is demonstrated for a test set derived from real-world data. Our computational results indicate that the heuristic is able to devise optimal solutions to non-trivial problem instances, and outperforms the exact lexicographic goal programming formulation on medium- and large-sized problem instances.

A heuristic approach for scheduling assessment centers

Human resources managers often use assessment centers to evaluate candidates for a job position. During an assessment center, the candidates perform a series of exercises. The exercises require one or two assessors (e.g., managers or psychologists) that observe and evaluate the candidate. If an exercise is designed as a role-play, an actor is required as well which plays, e.g., an unhappy customer with whom the candidate has to deal with. Besides performing the exercises, the candidates have a lunch break within a prescribed time window. Each candidate should be observed by approximately half the number of the assessors. Moreover, an assessor cannot be assigned to a candidate if they personally know each other. The planning problem consists of determining (1) resource-feasible start times of all exercises and lunch breaks and (2) a feasible assignment of assessors to candidates, such that the assessment center duration is minimized. We propose a list-scheduling heuristic that generates feasible schedules for such assessment centers. We develop novel procedures for devising an appropriate scheduling list and for incorporating the problem-specific constraints. Our computational results indicate that our approach is capable of devising optimal or near-optimal solutions to real-world instances within short CPU time.

Human impacts and aridity differentially alter soil N availability in drylands worldwide

Aims Climate and human impacts are changing the nitrogen (N) inputs and losses in terrestrial ecosystems. However, it is largely unknown how these two major drivers of global change will simultaneously influence the N cycle in drylands, the largest terrestrial biome on the planet. We conducted a global observational study to evaluate how aridity and human impacts, together with biotic and abiotic factors, affect key soil variables of the N cycle. Location Two hundred and twenty-four dryland sites from all continents except Antarctica widely differing in their environmental conditions and human influence. Methods Using a standardized field survey, we measured aridity, human impacts (i.e. proxies of land uses and air pollution), key biophysical variables (i.e. soil pH and texture and total plant cover) and six important variables related to N cycling in soils: total N, organic N, ammonium, nitrate, dissolved organic:inorganic N and N mineralization rates. We used structural equation modelling to assess the direct and indirect effects of aridity, human impacts and key biophysical variables on the N cycle. Results Human impacts increased the concentration of total N, while aridity reduced it. The effects of aridity and human impacts on the N cycle were spatially disconnected, which may favour scarcity of N in the most arid areas and promote its accumulation in the least arid areas. Main conclusions We found that increasing aridity and anthropogenic pressure are spatially disconnected in drylands. This implies that while places with low aridity and high human impact accumulate N, most arid sites with the lowest human impacts lose N. Our analyses also provide evidence that both increasing aridity and human impacts may enhance the relative dominance of inorganic N in dryland soils, having a negative impact on key functions and services provided by these ecosystems.

Impact of fee schedules and approved doctor's list on physician availability in the Texas Workers' Compensation Program

The purpose of this study was to examine and describe the changes in physician provider workforce, before and after two regulatory changes were implemented by the Texas Workers' Compensation Commission (TWCC) in August and September of 2003: Fee schedules and the Approved Doctor's List (ADL). The number and type of physicians who participated in the program after the changes went into effect were measured and compared to projections based on natural attrition. In addition, interviews with key stakeholders were conducted regarding the program changes. ^ Collectively, this evidence suggests that physician response followed the same patterns as shown in previous research. The number of physicians who continued to participate and bill the Texas workers' compensation program decreased significantly as a result of the regulatory changes. The consequences of these changes on access and quality of care need to be documented with empirical research. The availability of physicians in the workforce is linked to access to care. The type and location of physicians who remained in the system also have impact on quality and access to care. ^

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

Food availability in the home and dietary intake of the Harris County Department of Education Head Start population

Background. The prevalence of obesity and overweight children has been an ongoing health epidemic in the US for the last several decades. The problem has consistently worsened and has disproportionately been the most prevalent among low socioeconomic status (SES) populations. Food availability in the home has been suggested to be a potential factor related to overweight and obesity, as availability is likely associated with intake. Food availability of low SES preschool aged children has not been well examined. The purpose of this study was to explore the food environment of the Harris County Department of Education (HCDE) Head Start population, and describe reported frequency of intake of particular food groups. The effect of food availability on reported intake was also examined.^ Methods. This was a cross-sectional study of secondary data analysis. Data obtained from 17 HCDE Head Start Centers was analyzed using PASW 18 Statistical Software. Demographic analyses included population, age, gender, race, parent occupation, type of home, and language spoken in the home. Descriptive statistics included reported availability of foods in the home as well as frequency of intake.^ Regression analysis examined the relationship of availability of foods on intake. The food categories included were: dark leafy green and orange vegetables, other vegetables, fruits, soda, salty snacks, and sweet snacks. For both vegetable categories reported intake of fresh, frozen, and canned vegetables were included. For the fruit category, intake of fresh, frozen, canned, and dried fruits were reported.^ Results. Results showed that 90-95% of parents reported having vegetables and fruits available in the home. However, the only significant relationship between availability and intake was for fresh fruit and dried fruit. No associations were seen among the vegetable groups. Other vegetables (bell peppers, eggplant, tomatoes, onions, iceberg lettuce, asparagus) that were frozen, approached significance for availability on intake, however once adjusted for confounders the relationship was no longer present. Among soda, salty snacks, and sweet snacks the only significant relationship was seen for soda availability and intake. Salty snacks and sweet snacks presence in the home was not a predictor of increased frequency of intake.^ Conclusions. This research supported the hypothesis that availability of foods has an impact on intake for fresh fruits, dried fruits and soda. No associations were seen for vegetables, salty snacks and sweet snacks. Additionally, most of the parents reported having fruits and vegetables in the home, but reported intakes were not meeting the Dietary Guidelines for Americans recommendations. Strengths of the study included the large sample size taken from numerous HCDE Head Start Centers. Limitations included questionable reliability of participant’s responses, ability to generalize to other populations, and the use of secondary data rather than prospectively collected data.^