Advanced micro and nano manufacturing technologies used in medical domain

This paper focuses on the aspects of advanced manufacturing technologies, namely micro and nano manufacturing (MNM) capabilities which are particularly relevant to medical domain. In recent years, the so called disruptive technologies have enabled engineers and clinicians to collaborate in solving complex problems which require advanced MNM capabilities to develop medical applications. As a result what was nearly impossible a few years ago, due to limitations in machining and manufacturability of micro and nano scale artefacts, are now made possible thanks to innovative manufacturing processes and technologies. The potential medical applications of the new MNM methods are immense and in this paper four potential uses, namely as medical devices, lab on chips, and brain implants are presented and discussed. These works were based on different projects undertaken by researchers at Cardiff University, UK. The manufacturing costs, though initially high, are expected to reduce over time as the technologies mature and become more widely available. Introducing these MNM technologies and disseminating these results to healthcare engineering, for a better quality of medical diagnosis and treatments with cost-effective solutions, will greatly benefit the majority of population who live in the developing countries in receiving appropriate and affordable medical care to achieve improvements in their quality of life

Inter-muscular coherence in speed skaters with skater's cramp

Introduction: Skater's cramp is a career-ending movement disorder in expert speed skaters noted to be a likely task-specific dystonia. In other movement disorders, including task-specific dystonia, studies have found evidence of central dysregulation expressed as higher inter-muscular coherence. We looked at whether inter-muscular coherence was higher in affected skaters as a possible indicator that it is centrally driven, and by extension further evidence it is a task-specific dystonia.Methods: In 14 affected and 14 control skaters we calculated inter-muscular coherence in the theta-band in a stationary task where tonic muscle activation was measured at 10%, 20% and 50% of maximum voluntary contraction. Additionally, we calculated wavelet coherence while skating at key moments in the stroke cycle.Results: Coherence did not differ in the stationary activation task. While skating, coherence was higher in the impacted leg of affected skaters compared to their non-impacted leg, p = .05, η2 = 0.031, and amplitude of electromyography correlated with coherence in the impacted leg, p = .009, R2adjusted = 0.41. A sub-group of severely affected skaters (n = 6) had higher coherence in the impacted leg compared to the left and right leg of controls, p = .02, Cohen's d = 1.59 and p = .01, Cohen's d = 1.63 respectively. Results were less clear across the entire affected cohort probably due to a diverse case-mix.Conclusion: Our results of higher coherence in certain severe cases of skater's cramp is preliminary evidence of a central dysregulation, making the likelihood it is a task-specific dystonia higher.</p

Heavy Carriers and Non-Drude Optical Conductivity in MnSi

Optical properties of the weakly helimagnetic metal MnSi have been determined in the photon energy range from 2 meV to 4.5 eV using the combination of grazing incidence reflectance at 80 degrees (2 meV to 0.8 eV) and ellipsometry (0.8 to 4.5 eV). As the sample is cooled below 100 K the effective mass becomes strongly frequency dependent at low frequencies, while the scattering rate developes a linear frequency dependence. The complex optical conductivity can be described by the phenomenological relation \sigma(\omega,T) \propto (\Gamma(T)+i\omega)^{-1/2} used for cuprates and ruthenates.Comment: 5 pages, ReVTeX 4, 5 figures in eps forma

Positive Feedbacks in Seagrass Ecosystems – Evidence from Large-Scale Empirical Data

Positive feedbacks cause a nonlinear response of ecosystems to environmental change and may even cause bistability. Even though the importance of feedback mechanisms has been demonstrated for many types of ecosystems, their identification and quantification is still difficult. Here, we investigated whether positive feedbacks between seagrasses and light conditions are likely in seagrass ecosystems dominated by the temperate seagrass Zostera marina. We applied a combination of multiple linear regression and structural equation modeling (SEM) on a dataset containing 83 sites scattered across Western Europe. Results confirmed that a positive feedback between sediment conditions, light conditions and seagrass density is likely to exist in seagrass ecosystems. This feedback indicated that seagrasses are able to trap and stabilize suspended sediments, which in turn improves water clarity and seagrass growth conditions. Furthermore, our analyses demonstrated that effects of eutrophication on light conditions, as indicated by surface water total nitrogen, were on average at least as important as sediment conditions. This suggests that in general, eutrophication might be the most important factor controlling seagrasses in sheltered estuaries, while the seagrass-sediment-light feedback is a dominant mechanism in more exposed areas. Our study demonstrates the potentials of SEM to identify and quantify positive feedbacks mechanisms for ecosystems and other complex systems

Positive Feedbacks in Seagrass Ecosystems – Evidence from Large-Scale Empirical Data

Positive feedbacks cause a nonlinear response of ecosystems to environmental change and may even cause bistability. Even though the importance of feedback mechanisms has been demonstrated for many types of ecosystems, their identification and quantification is still difficult. Here, we investigated whether positive feedbacks between seagrasses and light conditions are likely in seagrass ecosystems dominated by the temperate seagrass Zostera marina. We applied a combination of multiple linear regression and structural equation modeling (SEM) on a dataset containing 83 sites scattered across Western Europe. Results confirmed that a positive feedback between sediment conditions, light conditions and seagrass density is likely to exist in seagrass ecosystems. This feedback indicated that seagrasses are able to trap and stabilize suspended sediments, which in turn improves water clarity and seagrass growth conditions. Furthermore, our analyses demonstrated that effects of eutrophication on light conditions, as indicated by surface water total nitrogen, were on average at least as important as sediment conditions. This suggests that in general, eutrophication might be the most important factor controlling seagrasses in sheltered estuaries, while the seagrass-sediment-light feedback is a dominant mechanism in more exposed areas. Our study demonstrates the potentials of SEM to identify and quantify positive feedbacks mechanisms for ecosystems and other complex systems

Optimal selection for BRCA1 and BRCA2 mutation testing using a combination of ' easy to apply ' probability models

To establish an efficient, reliable and easy to apply risk assessment tool to select families with breast and/or ovarian cancer patients for BRCA mutation testing, using available probability models. In a retrospective study of 263 families with breast and/or ovarian cancer patients, the utility of the Frank (Myriad), Gilpin (family history assessment tool) and Evans (Manchester) model was analysed, to select 49 BRCA mutation-positive families. For various cutoff levels and combinations, the sensitivity and specificity were calculated and compared. The best combinations were subsequently validated in additional sets of families. Comparable sensitivity and specificity were obtained with the Gilpin and Evans models. They appeared to be complementary to the Frank model. To obtain an optimal sensitivity, five ‘additional criteria' were introduced that are specific for the selection of small or uninformative families. The optimal selection is made by the combination ‘Frank ⩾16% or Evans2 ⩾12 or one of five additional criteria'. The efficiency of the selection of families for mutation testing of BRCA1 and BRCA2 can be optimised by using a combination of available easy to apply risk assessment models

MR thermometry characterization of a hyperthermia ultrasound array designed using the k-space computational method

BACKGROUND: Ultrasound induced hyperthermia is a useful adjuvant to radiation therapy in the treatment of prostate cancer. A uniform thermal dose (43°C for 30 minutes) is required within the targeted cancerous volume for effective therapy. This requires specific ultrasound phased array design and appropriate thermometry method. Inhomogeneous, acoustical, three-dimensional (3D) prostate models and economical computational methods provide necessary tools to predict the appropriate shape of hyperthermia phased arrays for better focusing. This research utilizes the k-space computational method and a 3D human prostate model to design an intracavitary ultrasound probe for hyperthermia treatment of prostate cancer. Evaluation of the probe includes ex vivo and in vivo controlled hyperthermia experiments using the noninvasive magnetic resonance imaging (MRI) thermometry. METHODS: A 3D acoustical prostate model was created using photographic data from the Visible Human Project(®). The k-space computational method was used on this coarse grid and inhomogeneous tissue model to simulate the steady state pressure wavefield of the designed phased array using the linear acoustic wave equation. To ensure the uniformity and spread of the pressure in the length of the array, and the focusing capability in the width of the array, the equally-sized elements of the 4 × 20 elements phased array were 1 × 14 mm. A probe was constructed according to the design in simulation using lead zerconate titanate (PZT-8) ceramic and a Delrin(® )plastic housing. Noninvasive MRI thermometry and a switching feedback controller were used to accomplish ex vivo and in vivo hyperthermia evaluations of the probe. RESULTS: Both exposimetry and k-space simulation results demonstrated acceptable agreement within 9%. With a desired temperature plateau of 43.0°C, ex vivo and in vivo controlled hyperthermia experiments showed that the MRI temperature at the steady state was 42.9 ± 0.38°C and 43.1 ± 0.80°C, respectively, for 20 minutes of heating. CONCLUSION: Unlike conventional computational methods, the k-space method provides a powerful tool to predict pressure wavefield in large scale, 3D, inhomogeneous and coarse grid tissue models. Noninvasive MRI thermometry supports the efficacy of this probe and the feedback controller in an in vivo hyperthermia treatment of canine prostate

Cross validation of bi-modal health-related stress assessment

This study explores the feasibility of objective and ubiquitous stress assessment. 25 post-traumatic stress disorder patients participated in a controlled storytelling (ST) study and an ecologically valid reliving (RL) study. The two studies were meant to represent an early and a late therapy session, and each consisted of a "happy" and a "stress triggering" part. Two instruments were chosen to assess the stress level of the patients at various point in time during therapy: (i) speech, used as an objective and ubiquitous stress indicator and (ii) the subjective unit of distress (SUD), a clinically validated Likert scale. In total, 13 statistical parameters were derived from each of five speech features: amplitude, zero-crossings, power, high-frequency power, and pitch. To model the emotional state of the patients, 28 parameters were selected from this set by means of a linear regression model and, subsequently, compressed into 11 principal components. The SUD and speech model were cross-validated, using 3 machine learning algorithms. Between 90% (2 SUD levels) and 39% (10 SUD levels) correct classification was achieved. The two sessions could be discriminated in 89% (for ST) and 77% (for RL) of the cases. This report fills a gap between laboratory and clinical studies, and its results emphasize the usefulness of Computer Aided Diagnostics (CAD) for mental health care

Expression of the stem cell marker ALDH1 in BRCA1 related breast cancer

Introduction The BRCA1 protein makes mammary stem cells differentiate into mature luminal and myoepithelial cells. If a BRCA1 mutation results in a differentiation block, an enlarged stem cell component might be present in the benign tissue of BRCA1 mutation carriers, and these mammary stem cells could be the origin of BRCA1 related breast cancer. Since ALDH1 is a marker of both mammary stem cells and breast cancer stem cells, we compared ALDH1 expression in malignant tissue of BRCA1 mutation carriers to non-carriers. Methods Forty-one BRCA1 related breast cancers and 41 age-matched sporadic breast cancers were immunohistochemically stained for ALDH1. Expression in epithelium and stroma was scored and compared. Results Epithelial (P=0.001) and peritumoral (P=0.001) ALDH1 expression was significantly higher in invasive BRCA1 related carcinomas compared to sporadic carcinomas. Intratumoral stromal ALDH1 expression was similarly high in both groups. ALDH1 tumor cell expression was an independent predictor of BRCA1 mutation status. Conclusion BRCA1 related breast cancers showed significantly more frequent epithelial ALDH1 expression, indicating that these hereditary tumors have an enlarged cancer stem cell component. Besides, (peritumoral) stromal ALDH1 expression was also more frequent in BRCA1 mutation carriers. ALDH1 may therefore be a diagnostic marker and a therapeutic target of BRCA1 related breast cancer