1,035 research outputs found
A large taper mismatch is one of the key factors behind high wear rates and failure at the taper junction of total hip replacements: A finite element wear analysis.
Total hip replacement (THR) is one of the most successful orthopaedic surgeries; however, failures can occur due to adverse reactions to wear debris. Recently, a large number of failures linked to the release of metal particles from the taper junction between femoral head and femoral stem have been reported. One possible reason for this may be design variations such as taper mismatches associated with the taper and trunnion angles. Could a large taper mismatch lead to inappropriate contact mechanics and increase relative micromotion and thus wear? In this study, 3D finite element (FE) models of a commercial THR from a perfectly matched interface to large taper mismatches and a wear algorithm were used to investigate the extent of wear that could occur at this junction and identify the optimum tolerances in order to reduce the wear. A co-ordinate measuring machine (CMM) was used to analyse the wear depth and volumetric wear rate of the tapers of 54 explanted 36mm diameter Cobalt Chromium femoral heads, which had been in service for 5.1 years in average, to validate the FE analyses. It was found that a large taper mismatch (e.g. 9.12áż˝) results in a high wear rate (2.960mm(3) per million load cycles). Such wear rates can have a major negative effect on the clinical outcomes of these implants. It was also found that even a slight reduction in mismatch significantly reduced the magnitude of the wear rates (0.069mm(3) per million load cycles on average for 6áż˝ taper mismatch). It is recommended that the cone angles of femoral head and femoral trunnion should be manufactured to produce a taper mismatch of less than 6áż˝ at the taper junction
PHS73 Costs Of Pilot Programs In Chicago-Based Centers For Population Health And Health Disparities: A Case For Team-Care?
The impact of femoral head size on the wear evolution at contacting surfaces of total hip prostheses: A finite element analysis.
Total Hip Arthroplasty has been a revolutionary technique in restoring mobility to patients with damaged hip joints. The introduction of modular components of the hip prosthesis allowed for bespoke solutions based on the requirements of the patient. The femoral stem is designed with a conical trunnion to allow for assembly of different femoral head sizes based on surgical requirements. The femoral head diameters for a metal-on-polyethylene hip prosthesis have typically ranged between 22Â mm and 36Â mm and are typically manufactured using Cobalt-Chromium alloy. A smaller femoral head diameter is associated with lower wear of the polyethylene, however, there is a higher risk of dislocation. In this study, a finite element model of a standard commercial hip arthroplasty prosthesis was modelled with femoral head diameters ranging from 22Â mm to 36Â mm to investigate the wear evolution and material loss at both contacting surfaces (acetabular cup and femoral stem trunnion). The finite element model, coupled with a validated in-house wear algorithm modelled a human walking for 10 million steps. The results have shown that as the femoral head size increased, the amount of wear on all contacting surfaces increased. As the femoral head diameter increased from 22 mm to 36 mm, the highly cross-linked polyethylene (XLPE) volumetric wear increased by 61% from 98.6 mm3 to 159.5 mm3 while the femoral head taper surface volumetric wear increased by 21% from 4.18 mm3 to 4.95 mm3. This study has provided an insight into the amount of increased wear as the femoral head size increased which can highlight the life span of these prostheses in the human body
Spatial regularity of InAs-GaAs quantum dots: quantifying the dependence of lateral ordering on growth rate.
The lateral ordering of arrays of self-assembled InAs-GaAs quantum dots (QDs) has been quantified as a function of growth rate, using the Hopkins-Skellam index (HSI). Coherent QD arrays have a spatial distribution which is neither random nor ordered, but intermediate. The lateral ordering improves as the growth rate is increased and can be explained by more spatially regular nucleation as the QD density increases. By contrast, large and irregular 3D islands are distributed randomly on the surface. This is consistent with a random selection of the mature QDs relaxing by dislocation nucleation at a later stage in the growth, independently of each QD's surroundings. In addition we explore the statistical variability of the HSI as a function of the number N of spatial points analysed, and we recommend N > 10(3) to reliably distinguish random from ordered arrays
Weak coupling large-N transitions at finite baryon density
We study thermodynamics of free SU(N) gauge theory with a large number of
colours and flavours on a three-sphere, in the presence of a baryon number
chemical potential. Reducing the system to a holomorphic large-N matrix
integral, paying specific attention to theories with scalar flavours (squarks),
we identify novel third-order deconfining phase transitions as a function of
the chemical potential. These transitions in the complex large-N saddle point
configurations are interpreted as "melting" of baryons into (s)quarks. They are
triggered by the exponentially large (~ exp(N)) degeneracy of light baryon-like
states, which include ordinary baryons, adjoint-baryons and baryons made from
different spherical harmonics of flavour fields on the three-sphere. The phase
diagram of theories with scalar flavours terminates at a phase boundary where
baryon number diverges, representing the onset of Bose condensation of squarks.Comment: 38 pages, 7 figure
Transkingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions
Improvements in sequencing technologies and reduced experimental costs have
resulted in a vast number of studies generating high-throughput data. Although
the number of methods to analyze these "omics" data has also increased,
computational complexity and lack of documentation hinder researchers from
analyzing their high-throughput data to its true potential. In this chapter we
detail our data-driven, transkingdom network (TransNet) analysis protocol to
integrate and interrogate multi-omics data. This systems biology approach has
allowed us to successfully identify important causal relationships between
different taxonomic kingdoms (e.g. mammals and microbes) using diverse types of
data
Novel associations for hypothyroidism include known autoimmune risk loci
Hypothyroidism is the most common thyroid disorder, affecting about 5% of the general population. Here we present the first large genome-wide association study of hypothyroidism, in 2,564 cases and 24,448 controls from the customer base of 23andMe, Inc., a personal genetics company. We identify four genome-wide significant associations, two of which are well known to be involved with a large spectrum of autoimmune diseases: rs6679677 near _PTPN22_ and rs3184504 in _SH2B3_ (p-values 3.5e-13 and 3.0e-11, respectively). We also report associations with rs4915077 near _VAV3_ (p-value 8.3e-11), another gene involved in immune function, and rs965513 near _FOXE1_ (p-value 3.1e-14). Of these, the association with _PTPN22_ confirms a recent small candidate gene study, and _FOXE1_ was previously known to be associated with thyroid-stimulating hormone (TSH) levels. Although _SH2B3_ has been previously linked with a number of autoimmune diseases, this is the first report of its association with thyroid disease. The _VAV3_ association is novel. These results suggest heterogeneity in the genetic etiology of hypothyroidism, implicating genes involved in both autoimmune disorders and thyroid function. Using a genetic risk profile score based on the top association from each of the four genome-wide significant regions in our study, the relative risk between the highest and lowest deciles of genetic risk is 2.1
The influence of HLA genotype on the development of metal hypersensitivity following joint replacement
\ua9 2022, The Author(s). Background: Over five million joint replacements are performed across the world each year. Cobalt chrome (CoCr) components are used in most of these procedures. Some patients develop delayed-type hypersensitivity (DTH) responses to CoCr implants, resulting in tissue damage and revision surgery. DTH is unpredictable and genetic links have yet to be definitively established. Methods: At a single site, we carried out an initial investigation to identify HLA alleles associated with development of DTH following metal-on-metal hip arthroplasty. We then recruited patients from other centres to train and validate an algorithm incorporating patient age, gender, HLA genotype, and blood metal concentrations to predict the development of DTH. Accuracy of the modelling was assessed using performance metrics including time-dependent receiver operator curves. Results: Using next-generation sequencing, here we determine the HLA genotypes of 606 patients. 176 of these patients had experienced failure of their prostheses; the remaining 430 remain asymptomatic at a mean follow up of twelve years. We demonstrate that the development of DTH is associated with patient age, gender, the magnitude of metal exposure, and the presence of certain HLA class II alleles. We show that the predictive algorithm developed from this investigation performs to an accuracy suitable for clinical use, with weighted mean survival probability errors of 1.8% and 3.1% for pre-operative and post-operative models respectively. Conclusions: The development of DTH following joint replacement appears to be determined by the interaction between implant wear and a patient’s genotype. The algorithm described in this paper may improve implant selection and help direct patient surveillance following surgery. Further consideration should be given towards understanding patient-specific responses to different biomaterials
Addressing the migration of health professionals: the role of working conditions and educational placements
This article provides a brief overview of the global health-worker shortage, which could undermine the Millennium Development Goal to halt and begin to reverse the spread of HIV/AIDS. The current situation suggests that long-term solutions to shortages can only be found by addressing the problem from a global perspective; that is, to eliminate shortages through substantial investments in training and retaining health workers in developed and developing countries, and not through policies that do not work towards solving this underlying problem, such as ones that restrict migration
Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders
Personality is influenced by genetic and environmental factors1
and associated with mental health. However, the underlying
genetic determinants are largely unknown. We identified six
genetic loci, including five novel loci2,3, significantly associated
with personality traits in a meta-analysis of genome-wide
association studies (N = 123,132–260,861). Of these genomewide
significant loci, extraversion was associated with variants
in WSCD2 and near PCDH15, and neuroticism with variants
on chromosome 8p23.1 and in L3MBTL2. We performed a
principal component analysis to extract major dimensions
underlying genetic variations among five personality traits
and six psychiatric disorders (N = 5,422–18,759). The first
genetic dimension separated personality traits and psychiatric
disorders, except that neuroticism and openness to experience
were clustered with the disorders. High genetic correlations
were found between extraversion and attention-deficit–
hyperactivity disorder (ADHD) and between openness and
schizophrenia and bipolar disorder. The second genetic
dimension was closely aligned with extraversion–introversion
and grouped neuroticism with internalizing psychopathology
(e.g., depression or anxiety)
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