The influence of retropatellar fat preservation on the positioning of the tibial component of total knee arthroplasty

Background: The good clinical-functional outcomes of total knee arthroplasty (TKA) depend on several factors, such as the surgical time and the adequate positioning of the prosthesis components. The present study aims to evaluate whether the preservation of retropatellar fat pad during the surgical act influences the rotational alignment of the tibial component and the surgical time of the procedure. Methods: The study was carried out with 50 patients operated on by the main author, who were randomly divided into two groups, experimental and control. For the evaluation of the positioning of the tibial component, the patients underwent computed tomography (CT) four weeks after the surgery, on average. Casuistry was determined by pilot study with the first five patients of each group. For the sample calculation, the t-student test was used for two independent samples. Results: All patients presented internal rotation of the tibial component, with no statistical difference in mean rotation between the experimental and control groups. When there was complete detachment of the fat in the experimental group, the tibial component showed greater external rotation, with a statistical difference. Surgical time was shorter in the experimental group, varying in this group according to the degree of osteoarthrosis. Conclusions: Maintenance of retropatellar fat pad did not influence the rotational alignment of the tibial component; however, in patients with advanced osteoarthrosis, such maintenance increases the surgical time

COMPARISON OF INDIVIDUAL MUSCLE CONTRIBUTIONS TO GROUND REACTION FORCES DURING JUMP AND CHANGE OF DIRECTION TESTING AFTER ANTERIOR CRUCIATE LIGAMENT RECONSTRUCTION

The purpose of this study was to identify the main muscle contributions across a battery of different tasks commonly used to evaluate an athlete’s readiness to return to sport after anterior cruciate ligament injury (ACL) and following ACL reconstruction. These injuries are mostly related to landing and change of direction movements and, due to its high incidence, efforts must be made to better understand the knee soft tissue mechanisms during these types of tasks. Data from a single athlete were analysed for this study. Scaled generic musculoskeletal models, consisting of 12 segments, 23 degrees of freedom and 92 musculotendon actuators were used in OpenSim. The quadriceps were the main contributors to ground reaction forces along the anterior/posterior direction, and, aided by the soleus and gastrocnemii, counteracted most of the effects applied by gravity along the vertical direction. The main contributors to the ground reaction forces during all the tasks are the same muscles that are intimately related to ACL loading, thus making these tasks useful for injury rehabilitation programs

Gateway vectors for efficient artificial gene assembly in vitro and expression in yeast Saccharomyces cerevisiae

Peer reviewedPublisher PD

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

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