Active osseointegration in an ex vivo porcine bone model

Achieving osseointegration is a fundamental requirement for many orthopaedic, oral, and craniofacial implants. Osseointegration typically takes three to 6 months, during which time implants are at risk of loosening. The aim of this study was to investigate whether osseointegration could be actively enhanced by delivering controllable electromechanical stimuli to the periprosthetic bone. First, the osteoconductivity of the implant surface was confirmed using an in vitro culture with murine preosteoblasts. The effects of active treatment on osseointegration were then investigated in a 21-day ex vivo model with freshly harvested cancellous bone cylinders (n = 24; Ø10 mm × 5 mm) from distal porcine femora, with comparisons to specimens treated by a distant ultrasound source and static controls. Cell viability, proliferation and distribution was evident throughout culture. Superior ongrowth of tissue onto the titanium discs during culture was observed in the actively stimulated specimens, with evidence of ten-times increased mineralisation after 7 and 14 days of culture (p < 0.05) and 2.5 times increased expression of osteopontin (p < 0.005), an adhesive protein, at 21 days. Moreover, histological analyses revealed increased bone remodelling at the implant-bone interface in the actively stimulated specimens compared to the passive controls. Active osseointegration is an exciting new approach for accelerating bone growth into and around implants

Load transfer in bone after partial, multi-compartmental, and total knee arthroplasty

Introduction: Arthroplasty-associated bone loss remains a clinical problem: stiff metallic implants disrupt load transfer to bone and, hence, its remodeling stimulus. The aim of this research was to analyze how load transfer to bone is affected by different forms of knee arthroplasty: isolated partial knee arthroplasty (PKA), compartmental arthroplasty [combined partial knee arthroplasty (CPKA), two or more PKAs in the same knee], and total knee arthroplasty (TKA).Methods: An experimentally validated subject-specific finite element model was analyzed native and with medial unicondylar, lateral unicondylar, patellofemoral, bi-unicondylar, medial bicompartmental, lateral bicompartmental, tricompartmental, and total knee arthroplasty. Three load cases were simulated for each: gait, stair ascent, and sit-to-stand. Strain shielding and overstraining were calculated from the differences between the native and implanted states.Results: For gait, the TKA femoral component led to mean strain shielding (30%) more than three times higher than that of PKA (4%–7%) and CPKA (5%–8%). Overstraining was predicted in the proximal tibia (TKA 21%; PKA/CPKA 0%–6%). The variance in the distribution for TKA was an order of magnitude greater than for PKA/CPKA, indicating less physiological load transfer. Only the TKA-implanted femur was sensitive to the load case: for stair ascent and gait, almost the entire distal femur was strain-shielded, whereas during sit-to-stand, the posterior femoral condyles were overstrained.Discussion: TKA requires more bone resection than PKA and CPKA. These finite element analyses suggest that a longer-term benefit for bone is probable as partial and multi-compartmental knee procedures lead to more natural load transfer compared to TKA. High-flexion activity following TKA may be protective of posterior condyle bone resorption, which may help explain why bone loss affects some patients more than others. The male and female bone models used for this research are provided open access to facilitate future research elsewhere

The effect of nodal connectivity and strut density within stochastic titanium scaffolds on osteogenesis

Modern orthopaedic implants use lattice structures that act as 3D scaffolds to enhance bone growth into and around implants. Stochastic scaffolds are of particular interest as they mimic the architecture of trabecular bone and can combine isotropic properties and adjustable structure. The existing research mainly concentrates on controlling the mechanical and biological performance of periodic lattices by adjusting pore size and shape. Still, less is known on how we can control the performance of stochastic lattices through their design parameters: nodal connectivity, strut density and strut thickness. To elucidate this, four lattice structures were evaluated with varied strut densities and connectivity, hence different local geometry and mechanical properties: low apparent modulus, high apparent modulus, and two with near-identical modulus. Pre-osteoblast murine cells were seeded on scaffolds and cultured in vitro for 28 days. Cell adhesion, proliferation and differentiation were evaluated. Additionally, the expression levels of key osteogenic biomarkers were used to assess the effect of each design parameter on the quality of newly formed tissue. The main finding was that increasing connectivity increased the rate of osteoblast maturation, tissue formation and mineralisation. In detail, doubling the connectivity, over fixed strut density, increased collagen type-I by 140%, increased osteopontin by 130% and osteocalcin by 110%. This was attributed to the increased number of acute angles formed by the numerous connected struts, which facilitated the organization of cells and accelerated the cell cycle. Overall, increasing connectivity and adjusting strut density is a novel technique to design stochastic structures which combine a broad range of biomimetic properties and rapid ossification

Passive Biotelemetric Detection of Tibial Debonding in Wireless Battery-Free Smart Knee Implants

Aseptic loosening is the dominant failure mechanism in contemporary knee replacement surgery, but diagnostic techniques are poorly sensitive to the early stages of loosening and poorly specific in delineating aseptic cases from infections. Smart implants have been proposed as a solution, but incorporating components for sensing, powering, processing, and communication increases device cost, size, and risk; hence, minimising onboard instrumentation is desirable. In this study, two wireless, battery-free smart implants were developed that used passive biotelemetry to measure fixation at the implant–cement interface of the tibial components. The sensing system comprised of a piezoelectric transducer and coil, with the transducer affixed to the superior surface of the tibial trays of both partial (PKR) and total knee replacement (TKR) systems. Fixation was measured via pulse-echo responses elicited via a three-coil inductive link. The instrumented systems could detect loss of fixation when the implants were partially debonded (+7.1% PKA, +32.6% TKA, both p p < 0.001). Measurements were robust to variations in positioning of the external reader, soft tissue, and the femoral component. With low cost and small form factor, the smart implant concept could be adopted for clinical use, particularly for generating an understanding of uncertain aseptic loosening mechanisms

Stakeholder-led understanding of the implementation of digital technologies within heart disease diagnosis: a qualitative study protocol

Introduction Cardiovascular diseases are highly prevalent among the UK population, and the quality of care is being reduced due to accessibility and resource issues. Increased implementation of digital technologies into the cardiovascular care pathway has enormous potential to lighten the load on the National Health Service (NHS), however, it is not possible to adopt this shift without embedding the perspectives of service users and clinicians.Methods and analysis A series of qualitative studies will be carried out with the aim of developing a stakeholder-led perspective on the implementation of digital technologies to improve holistic diagnosis of heart disease. This will be a decentralised study with all data collection being carried out online with a nationwide cohort. Four focus groups, each with 5–6 participants, will be carried out with people with lived experience of heart disease, and 10 one-to-one interviews will be carried out with clinicians with experience of diagnosing heart diseases. The data will be analysed using an inductive thematic analysis approach.Ethics and dissemination This study received ethical approval from the Sciences and Technology Cross Research Council at the University of Sussex (reference ER/FM409/1). Participants will be required to provide informed consent via a Qualtrics survey before being accepted into the online interview or focus group. The findings will be disseminated through conference presentations, peer-reviewed publications and to the study participants

The Synchytrium endobioticum AvrSen1 triggers a Hypersensitive Response in Sen1 potatoes while natural variants evade detection

Synchytrium endobioticum is an obligate biotrophic fungus of the phylum Chytridiomycota. It causes potato wart disease, has a world-wide quarantine status and is included on the HHS and USDA Select Agent list. S. endobioticum isolates are grouped in pathotypes based on their ability to evade host-resistance in a set of differential potato varieties. So far, thirty-nine pathotypes are reported. A single dominant gene (Sen1) governs pathotype 1 resistance and we anticipated that the underlying molecular model would involve a pathogen effector (AvrSen1) that is recognized by the host.The S. endobioticum specific secretome of fourteen isolates representing six different pathotypes was screened for effectors specifically present in pathotype 1(D1) isolates but absent in others. We discovered a single AvrSen1 candidate. Expression of this candidate in potato Sen1 plants showed a specific hypersensitive response, which co-segregated with the Sen1 resistance in potato populations. No HR was obtained with truncated genes found in pathotypes that evaded recognition by Sen1. These findings established that our candidate gene was indeed Avrsen1. AvrSen1 is a single copy gene and encodes a 376 amino acid protein without predicted function or functional domains, and is the first effector gene identified in Chytridiomycota

DataSheet1_Load transfer in bone after partial, multi-compartmental, and total knee arthroplasty.docx

Introduction: Arthroplasty-associated bone loss remains a clinical problem: stiff metallic implants disrupt load transfer to bone and, hence, its remodeling stimulus. The aim of this research was to analyze how load transfer to bone is affected by different forms of knee arthroplasty: isolated partial knee arthroplasty (PKA), compartmental arthroplasty [combined partial knee arthroplasty (CPKA), two or more PKAs in the same knee], and total knee arthroplasty (TKA).Methods: An experimentally validated subject-specific finite element model was analyzed native and with medial unicondylar, lateral unicondylar, patellofemoral, bi-unicondylar, medial bicompartmental, lateral bicompartmental, tricompartmental, and total knee arthroplasty. Three load cases were simulated for each: gait, stair ascent, and sit-to-stand. Strain shielding and overstraining were calculated from the differences between the native and implanted states.Results: For gait, the TKA femoral component led to mean strain shielding (30%) more than three times higher than that of PKA (4%–7%) and CPKA (5%–8%). Overstraining was predicted in the proximal tibia (TKA 21%; PKA/CPKA 0%–6%). The variance in the distribution for TKA was an order of magnitude greater than for PKA/CPKA, indicating less physiological load transfer. Only the TKA-implanted femur was sensitive to the load case: for stair ascent and gait, almost the entire distal femur was strain-shielded, whereas during sit-to-stand, the posterior femoral condyles were overstrained.Discussion: TKA requires more bone resection than PKA and CPKA. These finite element analyses suggest that a longer-term benefit for bone is probable as partial and multi-compartmental knee procedures lead to more natural load transfer compared to TKA. High-flexion activity following TKA may be protective of posterior condyle bone resorption, which may help explain why bone loss affects some patients more than others. The male and female bone models used for this research are provided open access to facilitate future research elsewhere.</p

The Synchytrium endobioticum AvrSen1 triggers a Hypersensitive Response in Sen1 potatoes while natural variants evade detection

Synchytrium endobioticum is an obligate biotrophic fungus of the phylum Chytridiomycota. It causes potato wart disease, has a world-wide quarantine status and is included on the HHS and USDA Select Agent list. S. endobioticum isolates are grouped in pathotypes based on their ability to evade host-resistance in a set of differential potato varieties. So far, thirty-nine pathotypes are reported. A single dominant gene (Sen1) governs pathotype 1 resistance and we anticipated that the underlying molecular model would involve a pathogen effector (AvrSen1) that is recognized by the host.The S. endobioticum specific secretome of fourteen isolates representing six different pathotypes was screened for effectors specifically present in pathotype 1(D1) isolates but absent in others. We discovered a single AvrSen1 candidate. Expression of this candidate in potato Sen1 plants showed a specific hypersensitive response, which co-segregated with the Sen1 resistance in potato populations. No HR was obtained with truncated genes found in pathotypes that evaded recognition by Sen1. These findings established that our candidate gene was indeed Avrsen1. AvrSen1 is a single copy gene and encodes a 376 amino acid protein without predicted function or functional domains, and is the first effector gene identified in Chytridiomycota

Stakeholder-led understanding of the implementation of digital technologies within heart disease diagnosis: a qualitative study protocol

Introduction Cardiovascular diseases are highly prevalent among the UK population, and the quality of care is being reduced due to accessibility and resource issues. Increased implementation of digital technologies into the cardiovascular care pathway has enormous potential to lighten the load on the National Health Service (NHS), however, it is not possible to adopt this shift without embedding the perspectives of service users and clinicians. Methods and analysis A series of qualitative studies will be carried out with the aim of developing a stakeholder-led perspective on the implementation of digital technologies to improve holistic diagnosis of heart disease. This will be a decentralised study with all data collection being carried out online with a nationwide cohort. Four focus groups, each with 5-6 participants, will be carried out with people with lived experience of heart disease, and 10 one-to-one interviews will be carried out with clinicians with experience of diagnosing heart diseases. The data will be analysed using an inductive thematic analysis approach. Ethics and dissemination This study received ethical approval from the Sciences and Technology Cross Research Council at the University of Sussex (reference ER/FM409/1). Participants will be required to provide informed consent via a Qualtrics survey before being accepted into the online interview or focus group. The findings will be disseminated through conference presentations, peer-reviewed publications and to the study participants

Exploiting Knowledge of R/Avr Genes to Rapidly Clone a New LZ-NBS-LRR Family of Late Blight Resistance Genes from Potato Linkage Group IV

In addition to the resistance to Phytophthora infestans (Rpi) genes Rpi-blb1 and Rpi-blb2, Solanum bulbocastanum appears to harbor Rpi-blb3 located at a major late blight resistance locus on LG IV, which also harbors Rpi-abpt, R2, R2-like, and Rpi-mcd1 in other Solanum spp. Here, we report the cloning and functional analyses of four Rpi genes, using a map-based cloning approach, allele-mining strategy, Gateway technology, and transient complementation assays in Nicotiana benthamiana. Rpi-blb3, Rpi-abpt, R2, and R2-like contain all signature sequences characteristic of leucine zipper nucleotide binding site leucine-rich repeat (LZ-NBS-LRR) proteins, and share amino-acid sequences 34.9% similar to RPP13 from Arabidopsis thaliana. The LRR domains of all four Rpi proteins are highly homologous whereas LZ and NBS domains are more polymorphic, those of R2 being the most divergent. Clear blocks of sequence affiliation between the four functional resistance proteins and those encoded by additional Rpi-blb3 gene homologs suggest exchange of LZ, NBS, and LRR domains, underlining the modular nature of these proteins. All four Rpi genes recognize the recently identified RXLR effector PiAVR