Poor accuracy of freehand cup positioning during total hip arthroplasty

Several studies have demonstrated a correlation between the acetabular cup position and the risk of dislocation, wear and range of motion after total hip arthroplasty. The present study was designed to evaluate the accuracy of the surgeon’s estimated position of the cup after freehand placement in total hip replacement. Peroperative estimated abduction and anteversion of 200 acetabular components (placed by three orthopaedic surgeons and nine residents) were compared with measured outcomes (according to Pradhan) on postoperative radiographs. Cups were placed in 49.7° (SD 6.7) of abduction and 16.0° (SD 8.1) of anteversion. Estimation of placement was 46.3° (SD 4.3) of abduction and 14.6° (SD 5.9) of anteversion. Of more interest is the fact that for the orthopaedic surgeons the mean inaccuracy of estimation was 4.1° (SD 3.9) for abduction and 5.2° (SD 4.5) for anteversion and for their residents this was respectively, 6.3° (SD 4.6) and 5.7° (SD 5.0). Significant differences were found between orthopaedic surgeons and residents for inaccuracy of estimation for abduction, not for anteversion. Body mass index, sex, (un)cemented fixation and surgical approach (anterolateral or posterolateral) were not significant factors. Based upon the inaccuracy of estimation, the group’s chance on future cup placement within Lewinnek’s safe zone (5–25° anteversion and 30–50° abduction) is 82.7 and 85.2% for anteversion and abduction separately. When both parameters are combined, the chance of accurate placement is only 70.5%. The chance of placement of the acetabular component within 5° of an intended position, for both abduction and anteversion is 21.5% this percentage decreases to just 2.9% when the tolerated error is 1°. There is a tendency to underestimate both abduction and anteversion. Orthopaedic surgeons are superior to their residents in estimating abduction of the acetabular component. The results of this study indicate that freehand placement of the acetabular component is not a reliable method

Improved Bevirimat resistance prediction by combination of structural and sequence-based classifiers

<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors such as Bevirimat are a new class of antiretroviral drugs that hamper the cleavage of HIV-1 proteins into their functional active forms. They bind to these preproteins and inhibit their cleavage by the HIV-1 protease, resulting in non-functional virus particles. Nevertheless, there exist mutations in this region leading to resistance against Bevirimat. Highly specific and accurate tools to predict resistance to maturation inhibitors can help to identify patients, who might benefit from the usage of these new drugs.</p> <p>Results</p> <p>We tested several methods to improve Bevirimat resistance prediction in HIV-1. It turned out that combining structural and sequence-based information in classifier ensembles led to accurate and reliable predictions. Moreover, we were able to identify the most crucial regions for Bevirimat resistance computationally, which are in line with experimental results from other studies.</p> <p>Conclusions</p> <p>Our analysis demonstrated the use of machine learning techniques to predict HIV-1 resistance against maturation inhibitors such as Bevirimat. New maturation inhibitors are already under development and might enlarge the arsenal of antiretroviral drugs in the future. Thus, accurate prediction tools are very useful to enable a personalized therapy.</p

Predicting Bevirimat resistance of HIV-1 from genotype

<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors are a new class of antiretroviral drugs. Bevirimat (BVM) was the first substance in this class of inhibitors entering clinical trials. While the inhibitory function of BVM is well established, the molecular mechanisms of action and resistance are not well understood. It is known that mutations in the regions CS p24/p2 and p2 can cause phenotypic resistance to BVM. We have investigated a set of p24/p2 sequences of HIV-1 of known phenotypic resistance to BVM to test whether BVM resistance can be predicted from sequence, and to identify possible molecular mechanisms of BVM resistance in HIV-1.</p> <p>Results</p> <p>We used artificial neural networks and random forests with different descriptors for the prediction of BVM resistance. Random forests with hydrophobicity as descriptor performed best and classified the sequences with an area under the Receiver Operating Characteristics (ROC) curve of 0.93 ± 0.001. For the collected data we find that p2 sequence positions 369 to 376 have the highest impact on resistance, with positions 370 and 372 being particularly important. These findings are in partial agreement with other recent studies. Apart from the complex machine learning models we derived a number of simple rules that predict BVM resistance from sequence with surprising accuracy. According to computational predictions based on the data set used, cleavage sites are usually not shifted by resistance mutations. However, we found that resistance mutations could shorten and weaken the <it>α</it>-helix in p2, which hints at a possible resistance mechanism.</p> <p>Conclusions</p> <p>We found that BVM resistance of HIV-1 can be predicted well from the sequence of the p2 peptide, which may prove useful for personalized therapy if maturation inhibitors reach clinical practice. Results of secondary structure analysis are compatible with a possible route to BVM resistance in which mutations weaken a six-helix bundle discovered in recent experiments, and thus ease Gag cleavage by the retroviral protease.</p

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Machine learning on normalized protein sequences

<p>Abstract</p> <p>Background</p> <p>Machine learning techniques have been widely applied to biological sequences, e.g. to predict drug resistance in HIV-1 from sequences of drug target proteins and protein functional classes. As deletions and insertions are frequent in biological sequences, a major limitation of current methods is the inability to handle varying sequence lengths.</p> <p>Findings</p> <p>We propose to normalize sequences to uniform length. To this end, we tested one linear and four different non-linear interpolation methods for the normalization of sequence lengths of 19 classification datasets. Classification tasks included prediction of HIV-1 drug resistance from drug target sequences and sequence-based prediction of protein function. We applied random forests to the classification of sequences into "positive" and "negative" samples. Statistical tests showed that the linear interpolation outperforms the non-linear interpolation methods in most of the analyzed datasets, while in a few cases non-linear methods had a small but significant advantage. Compared to other published methods, our prediction scheme leads to an improvement in prediction accuracy by up to 14%.</p> <p>Conclusions</p> <p>We found that machine learning on sequences normalized by simple linear interpolation gave better or at least competitive results compared to state-of-the-art procedures, and thus, is a promising alternative to existing methods, especially for protein sequences of variable length.</p

Rationale and Plan for Vitamin D Food Fortification : A Review and Guidance Paper

Vitamin D deficiency can lead to musculoskeletal diseases such as rickets and osteomalacia, but vitamin D supplementation may also prevent extraskeletal diseases such as respiratory tract infections, asthma exacerbations, pregnancy complications and premature deaths. Vitamin D has a unique metabolism as it is mainly obtained through synthesis in the skin under the influence of sunlight (i.e., ultraviolet-B radiation) whereas intake by nutrition traditionally plays a relatively minor role. Dietary guidelines for vitamin D are based on a consensus that serum 25-hydroxyvitamin D (25[OH]D) concentrations are used to assess vitamin D status, with the recommended target concentrations ranging from >= 25 to >= 50 nmol/L (>= 10->= 20 ng/mL), corresponding to a daily vitamin D intake of 10 to 20 mu g (400-800 international units). Most populations fail to meet these recommended dietary vitamin D requirements. In Europe, 25(OH)D concentrations <30 nmol/L (12 ng/mL) and <50 nmol/L (20 ng/mL) are present in 13.0 and 40.4% of the general population, respectively. This substantial gap between officially recommended dietary reference intakes for vitamin D and the high prevalence of vitamin D deficiency in the general population requires action from health authorities. Promotion of a healthier lifestyle with more outdoor activities and optimal nutrition are definitely warranted but will not erase vitamin D deficiency and must, in the case of sunlight exposure, be well balanced with regard to potential adverse effects such as skin cancer. Intake of vitamin D supplements is limited by relatively poor adherence (in particular in individuals with low-socioeconomic status) and potential for overdosing. Systematic vitamin D food fortification is, however, an effective approach to improve vitamin D status in the general population, and this has already been introduced by countries such as the US, Canada, India, and Finland. Recent advances in our knowledge on the safety of vitamin D treatment, the dose-response relationship of vitamin D intake and 25(OH)D levels, as well as data on the effectiveness of vitamin D fortification in countries such as Finland provide a solid basis to introduce and modify vitamin D food fortification in order to improve public health with this likewise cost-effective approach.Peer reviewe

Collateral circulation: Past and present

Following an arterial occlusion outward remodeling of pre-existent inter-connecting arterioles occurs by proliferation of vascular smooth muscle and endothelial cells. This is initiated by deformation of the endothelial cells through increased pulsatile fluid shear stress (FSS) caused by the steep pressure gradient between the high pre-occlusive and the very low post-occlusive pressure regions that are interconnected by collateral vessels. Shear stress leads to the activation and expression of all NOS isoforms and NO production, followed by endothelial VEGF secretion, which induces MCP-1 synthesis in endothelium and in the smooth muscle of the media. This leads to attraction and activation of monocytes and T-cells into the adventitial space (peripheral collateral vessels) or attachment of these cells to the endothelium (coronary collaterals). Mononuclear cells produce proteases and growth factors to digest the extra-cellular scaffold and allow motility and provide space for the new cells. They also produce NO from iNOS, which is essential for arteriogenesis. The bulk of new tissue production is carried by the smooth muscles of the media, which transform their phenotype from a contractile into a synthetic and proliferative one. Important roles are played by actin binding proteins like ABRA, cofilin, and thymosin beta 4 which determine actin polymerization and maturation. Integrins and connexins are markedly up-regulated. A key role in this concerted action which leads to a 2-to-20 fold increase in vascular diameter, depending on species size (mouse versus human) are the transcription factors AP-1, egr-1, carp, ets, by the Rho pathway and by the Mitogen Activated Kinases ERK-1 and -2. In spite of the enormous increase in tissue mass (up to 50-fold) the degree of functional restoration of blood flow capacity is incomplete and ends at 30% of maximal conductance (coronary) and 40% in the vascular periphery. The process of arteriogenesis can be drastically stimulated by increases in FSS (arterio-venous fistulas) and can be completely blocked by inhibition of NO production, by pharmacological blockade of VEGF-A and by the inhibition of the Rho-pathway. Pharmacological stimulation of arteriogenesis, important for the treatment of arterial occlusive diseases, seems feasible with NO donors