3D Direct Printing of Silicone Meniscus Implant Using a Novel Heat-Cured Extrusion-Based Printer

The first successful direct 3D printing, or additive manufacturing (AM), of heat-cured silicone meniscal implants, using biocompatible and bio-implantable silicone resins is reported. Silicone implants have conventionally been manufactured by indirect silicone casting and molding methods which are expensive and time-consuming. A novel custom-made heat-curing extrusion-based silicone 3D printer which is capable of directly 3D printing medical silicone implants is introduced. The rheological study of silicone resins and the optimization of critical process parameters are described in detail. The surface and cross-sectional morphologies of the printed silicone meniscus implant were also included. A time-lapsed simulation study of the heated silicone resin within the nozzle using computational fluid dynamics (CFD) was done and the results obtained closely resembled real time 3D printing. Solidworks one-convection model simulation, when compared to the on-off model, more closely correlated with the actual probed temperature. Finally, comparative mechanical study between 3D printed and heat-molded meniscus is conducted. The novel 3D printing process opens up the opportunities for rapid 3D printing of various customizable medical silicone implants and devices for patients and fills the current gap in the additive manufacturing industry

Detection and characterisation of defects in directed energy deposited multi-material components using full waveform inversion and reverse time migration

Directed energy deposition (DED) is capable in producing complex or high-value components with good mechanical properties. Despite these potential advantages, the quality and integrity of multi-material DED parts, remains a challenging issue that limits its wide applications. Material porosity in multi-material components is detrimental since it may lead to premature structural failure. This paper proposes a two-stage ultrasonic method to characterise the internal structure to enhance the understanding of the process parameters on material porosity. In this method, the low-frequency model building aims at reconstructing background structure and the high-frequency imaging targets at small defects. The first stage is based on the gradient sampling full-waveform inversion for the estimation of the velocity model, which is then used as the initial model for the reverse time migration for reflectivity. The experimental results show that accurate reconstructions of the interface between two materials and defects in multi-material DED components can be achieved

3D Printed Silicone Meniscus Implants: Influence of the 3D Printing Process on Properties of Silicone Implants

Osteoarthritis of the knee with meniscal pathologies is a severe meniscal pathology suffered by the aging population worldwide. However, conventional meniscal substitutes are not 3D-printable and lack the customizability of 3D printed implants and are not mechanically robust enough for human implantation. Similarly, 3D printed hydrogel scaffolds suffer from drawbacks of being mechanically weak and as a result patients are unable to execute immediate post-surgical weight-bearing ambulation and rehabilitation. To solve this problem, we have developed a 3D silicone meniscus implant which is (1) cytocompatible, (2) resistant to cyclic loading and mechanically similar to native meniscus, and (3) directly 3D printable. The main focus of this study is to determine whether the purity, composition, structure, dimensions and mechanical properties of silicone implants are affected by the use of a custom-made in-house 3D-printer. We have used the phosphate buffer saline (PBS) absorption test, Fourier transform infrared (FTIR) spectroscopy, surface profilometry, thermo-gravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), differential scanning calorimetry (DSC), and scanning electron microscopy (SEM) to effectively assess and compare material properties between molded and 3D printed silicone samples

Detection of Pneumocystis DNA in samples from patients suspected of bacterial pneumonia- a case-control study

BACKGROUND: Pneumocystis jiroveci (formerly known as P. carinii f.sp. hominis) is an opportunistic fungus that causes Pneumocystis pneumonia (PCP) in immunocompromised individuals. Pneumocystis jiroveci can be detected by polymerase chain reaction (PCR). To investigate the clinical importance of a positive Pneumocystis-PCR among HIV-uninfected patients suspected of bacterial pneumonia, a retrospective matched case-control study was conducted. METHODS: Respiratory samples from 367 patients suspected of bacterial pneumonia were analysed by PCR amplification of Pneumocystis jiroveci. To compare clinical factors associated with carriage of P. jiroveci, a case-control study was done. For each PCR-positive case, four PCR-negative controls, randomly chosen from the PCR-negative patients, were matched on sex and date of birth. RESULTS: Pneumocystis-DNA was detected in 16 (4.4%) of patients. The median age for PCR-positive patients was higher than PCR-negative patients (74 vs. 62 years, p = 0.011). PCR-positive cases had a higher rate of chronic or severe concomitant illness (15 (94%)) than controls (32 (50%)) (p = 0.004). Twelve (75%) of the 16 PCR positive patients had received corticosteroids, compared to 8 (13%) of the 64 PCR-negative controls (p < 0.001). Detection of Pneumocystis-DNA was associated with a worse prognosis: seven (44%) of patients with positive PCR died within one month compared to nine (14%) of the controls (p = 0.01). None of the nine PCR-positive patients who survived had developed PCP at one year of follow-up. CONCLUSIONS: Our data suggest that carriage of Pneumocystis jiroveci is associated with old age, concurrent disease and steroid treatment. PCR detection of P. jiroveci has low specificity for diagnosing PCP among patients without established immunodeficiency. Whether overt infection is involved in the poorer prognosis or merely reflects sub-clinical carriage is not clear. Further studies of P. jiroveci in patients receiving systemic treatment with corticosteroids are warranted

3D Printed Silicone Meniscus Implants: Influence of the 3D Printing Process on Properties of Silicone Implants

Osteoarthritis of the knee with meniscal pathologies is a severe meniscal pathology suffered by the aging population worldwide. However, conventional meniscal substitutes are not 3D-printable and lack the customizability of 3D printed implants and are not mechanically robust enough for human implantation. Similarly, 3D printed hydrogel scaffolds suffer from drawbacks of being mechanically weak and as a result patients are unable to execute immediate post-surgical weight-bearing ambulation and rehabilitation. To solve this problem, we have developed a 3D silicone meniscus implant which is (1) cytocompatible, (2) resistant to cyclic loading and mechanically similar to native meniscus, and (3) directly 3D printable. The main focus of this study is to determine whether the purity, composition, structure, dimensions and mechanical properties of silicone implants are affected by the use of a custom-made in-house 3D-printer. We have used the phosphate buffer saline (PBS) absorption test, Fourier transform infrared (FTIR) spectroscopy, surface profilometry, thermo-gravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), differential scanning calorimetry (DSC), and scanning electron microscopy (SEM) to effectively assess and compare material properties between molded and 3D printed silicone samples

Risk measures for direct real estate investments with non-normal or unknown return distributions

The volatility of returns is probably the most widely used risk measure for real estate. This is rather surprising since a number of studies have cast doubts on the view that volatility can capture the manifold risks attached to properties and corresponds to the risk attitude of investors. A central issue in this discussion is the statistical properties of real estate returns—in contrast to neoclassical capital market theory they are mostly non-normal and often unknown, which render many statistical measures useless. Based on a literature review and an analysis of data from Germany we provide evidence that volatility alone is inappropriate for measuring the risk of direct real estate. We use a unique data sample by IPD, which includes the total returns of 939 properties across different usage types (56% office, 20% retail, 8% others and 16% residential properties) from 1996 to 2009, the German IPD Index, and the German Property Index. The analysis of the distributional characteristics shows that German real estate returns in this period were not normally distributed and that a logistic distribution would have been a better fit. This is in line with most of the current literature on this subject and leads to the question which indicators are more appropriate to measure real estate risks. We suggest that a combination of quantitative and qualitative risk measures more adequately captures real estate risks and conforms better with investor attitudes to risk. Furthermore, we present criteria for the purpose of risk classification

Influence of the initial chemical conditions on the rational design of silica particles

The influence of the water content in the initial composition on the size of silica particles produced using the Stöber process is well known. We have shown that there are three morphological regimes defined by compositional boundaries. At low water levels (below stoichiometric ratio of water:tetraethoxysilane), very high surface area and aggregated structures are formed; at high water content (>40 wt%) similar structures are also seen. Between these two boundary conditions, discrete particles are formed whose size are dictated by the water content. Within the compositional regime that enables the classical Stöber silica, the structural evolution shows a more rapid attainment of final particle size than the rate of formation of silica supporting the monomer addition hypothesis. The clearer understanding of the role of the initial composition on the output of this synthesis method will be of considerable use for the establishment of reliable reproducible silica production for future industrial adoption

Radiative Transfer for Exoplanet Atmospheres

Remote sensing of the atmospheres of distant worlds motivates a firm understanding of radiative transfer. In this review, we provide a pedagogical cookbook that describes the principal ingredients needed to perform a radiative transfer calculation and predict the spectrum of an exoplanet atmosphere, including solving the radiative transfer equation, calculating opacities (and chemistry), iterating for radiative equilibrium (or not), and adapting the output of the calculations to the astronomical observations. A review of the state of the art is performed, focusing on selected milestone papers. Outstanding issues, including the need to understand aerosols or clouds and elucidating the assumptions and caveats behind inversion methods, are discussed. A checklist is provided to assist referees/reviewers in their scrutiny of works involving radiative transfer. A table summarizing the methodology employed by past studies is provided.Comment: 7 pages, no figures, 1 table. Filled in missing information in references, main text unchange

Prediction of Co-Receptor Usage of HIV-1 from Genotype

Human Immunodeficiency Virus 1 uses for entry into host cells a receptor (CD4) and one of two co-receptors (CCR5 or CXCR4). Recently, a new class of antiretroviral drugs has entered clinical practice that specifically bind to the co-receptor CCR5, and thus inhibit virus entry. Accurate prediction of the co-receptor used by the virus in the patient is important as it allows for personalized selection of effective drugs and prognosis of disease progression. We have investigated whether it is possible to predict co-receptor usage accurately by analyzing the amino acid sequence of the main determinant of co-receptor usage, i.e., the third variable loop V3 of the gp120 protein. We developed a two-level machine learning approach that in the first level considers two different properties important for protein-protein binding derived from structural models of V3 and V3 sequences. The second level combines the two predictions of the first level. The two-level method predicts usage of CXCR4 co-receptor for new V3 sequences within seconds, with an area under the ROC curve of 0.937±0.004. Moreover, it is relatively robust against insertions and deletions, which frequently occur in V3. The approach could help clinicians to find optimal personalized treatments, and it offers new insights into the molecular basis of co-receptor usage. For instance, it quantifies the importance for co-receptor usage of a pocket that probably is responsible for binding sulfated tyrosine

A comprehensive study on the role of the Yersinia pestis virulence markers in an animal model of pneumonic plague

We determined the role of Yersinia pestis virulence markers in an animal model of pneumonic plague. Eleven strains of Y. pestis were characterized using PCR assays to detect the presence of known virulence genes both encoded by the three plasmids as well as chromosomal markers. The virulence of all Y. pestis strains was compared in a mouse model for pneumonic plague. The presence of all known virulence genes correlated completely with virulence in the Balb/c mouse model. Strains which lacked HmsF initially exhibited visible signs of disease whereas all other strains (except wild-type strains) did not exhibit any disease signs. Forty-eight hours post-infection, mice which had received HmsF– strains regained body mass and were able to control infection; those infected with strains possessing a full complement of virulence genes suffered from fatal disease. The bacterial loads observed in the lung and other tissues reflected the observed clinical signs as did the cytokine changes measured in these animals. We can conclude that all known virulence genes are required for the establishment of pneumonic plague in mammalian animal models, the role of HmsF being of particular importance in disease progression