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- Åstrand, Anders, et al.
(författare)
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Prostate cancer detection with a tactile resonance sensor : measurement considerations and clinical setup
- 2017
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Ingår i: Sensors. - Switzerland : MDPI AG. - 1424-8220. ; 17:11
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Tidskriftsartikel (refereegranskat)abstract
- Tumors in the human prostate are usually stiffer compared to surrounding non-malignant glandular tissue, and tactile resonance sensors measuring stiffness can be used to detect prostate cancer. To explore this further, we used a tactile resonance sensor system combined with a rotatable sample holder where whole surgically removed prostates could be attached to detect tumors on, and beneath, the surface ex vivo. Model studies on tissue phantoms made of silicone and porcine tissue were performed. Finally, two resected human prostate glands were studied. Embedded stiff silicone inclusions placed 4 mm under the surface could be detected in both the silicone and biological tissue models, with a sensor indentation of 0.6 mm. Areas with different amounts of prostate cancer (PCa) could be distinguished from normal tissue (p < 0.05), when the tumor was located in the anterior part, whereas small tumors located in the dorsal aspect were undetected. The study indicates that PCa may be detected in a whole resected prostate with an uneven surface and through its capsule. This is promising for the development of a clinically useful instrument to detect prostate cancer during surgery.
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- Åstrand, Anders, et al.
(författare)
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The first study on whole human prostate ex vivo using a tactile resonance sensor for cancer detection
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Prostate cancer (PCa) is the most common form of cancer among males in Europe and the USA. A prostatectomy i.e. the removal of the prostate is the most common form of curative treatment. Prostate cancer can be suspected by a blood test for a prostate specific antigen (PSA) and a digital rectal examination (DRE) where a physician palpates the prostate through the rectum and where stiff nodules on the prostate is an indication for PCa. The final diagnosis of PCa is made by microscopic evaluation of ultrasound-guided biopsies taken from suspicious parts of the gland. After a prostatectomy the entire prostate is histopathologically analysed. One area of interest is the superficial part of the prostate gland as tumour growth on the surface suggests that the cancer has spread to other parts of the body. Tactile resonance sensors can be used to detect areas of different stiffness in soft tissue through a stiffness parameter. It is suggested that tactile resonance sensors can be used to detect prostate cancer since tumours in the human prostate usually is stiffer compared to surrounding healthy glandular tissue. The aim of the study was to detect tumours on, and beneath the surface, of whole human prostate glands ex vivo using a tactile resonance sensor system (TRSS). Model studies on spherical shaped tissue phantoms made of silicone and porcine tissue were performed to evaluate the ability of the TRSS to detect stiffer volumes at a distance beneath the surface. Finally two resected human prostate glands ex vivo from patients undergoing surgery for prostate cancer were studied. From the results it was concluded that the clamping force from the rotatable sample holder did not affect the magnitude of the stiffness parameter for the silicone samples. For the porcine muscle samples, the stiffness parameter showed to be affected by clamping forces larger than about 800 mN. The embedded stiff silicone nodules placed about 4 mm under the surface could be detected in both the silicone and biological tissue models with a sensor indentation distance of 0.6 mm. The measurements on resected whole human prostates showed that areas with elevated stiffness parameter values correlated (p < 0.05) with areas where cancer tumours were detected using histolopathological evaluation of the prostate. The tumours were significantly stiffer than the healthy tissue in the dorsal region. This is promising for the development of a clinically useful instrument to detect superficial prostate cancer.
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- Abebe, Admas Alemu, et al.
(författare)
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Genomic selection in plant breeding: key factors shaping two decades of progress
- 2024
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Ingår i: Molecular Plant. - 1674-2052 .- 1752-9867. ; 17, s. 552-578
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Forskningsöversikt (refereegranskat)abstract
- Genomic selection, the application of genomic prediction (GP) models to select candidate individuals, has significantly advanced in the past two decades, effectively accelerating genetic gains in plant breeding. This article provides a holistic overview of key factors that have influenced GP in plant breeding during this period. We delved into the pivotal roles of training population size and genetic diversity, and their relationship with the breeding population, in determining GP accuracy. Special emphasis was placed on optimizing training population size. We explored its benefits and the associated diminishing returns beyond an optimum size. This was done while considering the balance between resource allocation and maximizing prediction accuracy through current optimization algorithms. The density and distribution of single-nucleotide polymorphisms, level of linkage disequilibrium, genetic complexity, trait heritability, statistical machine-learning methods, and non-additive effects are the other vital factors. Using wheat, maize, and potato as examples, we summarize the effect of these factors on the accuracy of GP for various traits. The search for high accuracy in GP—theoretically reaching one when using the Pearson’s correlation as a metric—is an active research area as yet far from optimal for various traits. We hypothesize that with ultra-high sizes of genotypic and phenotypic datasets, effective training population optimization methods and support from other omics approaches (transcriptomics, metabolomics and proteomics) coupled with deep-learning algorithms could overcome the boundaries of current limitations to achieve the highest possible prediction accuracy, making genomic selection an effective tool in plant breeding.
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- Ballo, Ahmed, 1978, et al.
(författare)
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Bone response to physical-vapour-deposited titanium dioxide coatings on titanium implants
- 2013
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Ingår i: Clinical Oral Implants Research. - : Wiley. - 0905-7161 .- 1600-0501. ; 24:9, s. 1009-1017
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: The aim of this study was to investigate the correlation between coating thickness and the crystal structure of physical-vapour-deposited (PVD) titanium dioxide coatings, and to evaluate their in vivo biocompatibility. Materials and methods: The PVD TiO 2 coatings of different thickness were deposited on machined titanium grade 2 screw-shaped implants. Non-coated titanium implants were used as controls. Coating properties such as thickness, crystal structure, coating morphology and roughness were characterized. Forty-eight implants were placed randomly into both tibias of 16 rats. The animals were euthanized 7 and 28 days postsurgery and block biopsies were prepared for histology, histomorphometry and SEM analysis. Results: The thicknesses of the PVDTiO 2 coatings were 120 and 1430 nm respectively. Histologically, new bone formed on all implant surfaces. The mean percentage of newly formed bone in contact with the implant (BIC) was significantly higher at early healing time (7 days) for the 120 nm thick PVD coating (39 ± 14%) than for both the 1430 nm thick PVD coating (22 ± 10%) (P = 0.043) and the machined surface (22 ± 9%) (P = 0.028). This difference was no longer evident after 28 days (P = 0.867). Conclusion: Bone formation and bone-to-implant contact are achieved to the same degree for TiO 2 surface modifications prepared by a PVD process as clinically used, machined titanium. Furthermore, a relatively thinner PVD coating promotes a higher degree of bone apposition shortly after implantation, thereby providing rationales for exploring the potential clinical use of these modifications.
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- Bejhed, Johan, et al.
(författare)
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Numerical modeling and verification of gas flow through a network of crossed narrow v-grooves
- 2006
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Ingår i: Journal of Micromechanics and Microengineering. - : IOP Publishing. - 0960-1317 .- 1361-6439. ; 16:10, s. 2006-2013
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Tidskriftsartikel (refereegranskat)abstract
- The gas flow through a network of crossing thin micro-machined channels has been successfully modeled and simulated. The crossings are formed by two sets of v-grooves that intersect as two silicon wafers are bonded together. The gas is distributed from inlets via a manifold of channels to the narrow v-grooves. The narrow v-grooves could work as a particle filter. The fluidic model is derived from the Navier–Stokes equation and assumes laminar isothermal flow and incorporates small Knudsen number corrections and Poiseuille number calculations. The simulations use the finite element method. Several elements of the full crossing network model are treated separately before lumping them together: the straight v-grooves, a single crossing in an infinite set and a set of exactly four crossings along the flow path. The introduction of a crossing effectively corresponds to a virtual reduction of the length of the flow path, thereby defining a new effective length. The first and last crossings of each flow path together contribute to a pressure drop equal to that from three ordinary crossings. The derived full network model has been compared to previous experimental results on several differently shaped crossed v-groove networks. Within the experimental errors, the model corresponds to the mass flow and pressure drop measurements. The main error source is the uncertainty in v-groove width which has a profound impact on the fluidic behavior.
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