Search results for: Mike Kerr

Authors: Yazan S. Khaled, Shazana Shamsuddin, Jim Tiernan, Mike McPherson, Thomas Hughes, Paul Millner, David G. Jayne

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Introduction: There is a need for real-time imaging of colorectal cancer (CRC) to allow tailored surgery to the disease stage. Fluorescence guided laparoscopic imaging of primary colorectal cancer and the draining lymphatics would potentially bring stratified surgery into clinical practice and realign future CRC management to the needs of patients. Fluorescent nanoparticles can offer many advantages in terms of intra-operative imaging and therapy (theranostic) in comparison with traditional soluble reagents. Nanoparticles can be functionalised with diverse reagents and then targeted to the correct tissue using an antibody or Affimer (artificial binding protein). We aimed to develop and test fluorescent silica nanoparticles and targeted against CRC using an anti-carcinoembryonic antigen (CEA) Affimer (Aff). Methods: Anti-CEA and control Myoglobin Affimer binders were subcloned into the expressing vector pET11 followed by transformation into BL21 Star™ (DE3) E.coli. The expression of Affimer binders was induced using 0.1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG). Cells were harvested, lysed and purified using nickle chelating affinity chromatography. The photosensitiser Foslip (soluble analogue of 5,10,15,20-Tetra(m-hydroxyphenyl) chlorin) was incorporated into the core of silica nanoparticles using water-in-oil microemulsion technique. Anti-CEA or control Affs were conjugated to silica nanoparticles surface using sulfosuccinimidyl-4-(N-maleimidomethyl) cyclohexane-1-carboxylate (sulfo SMCC) chemical linker. Binding of CEA-Aff or control nanoparticles to colorectal cancer cells (LoVo, LS174T and HC116) was quantified in vitro using confocal microscopy. Results: The molecular weights of the obtained band of Affimers were ~12.5KDa while the diameter of functionalised silica nanoparticles was ~80nm. CEA-Affimer targeted nanoparticles demonstrated 9.4, 5.8 and 2.5 fold greater fluorescence than control in, LoVo, LS174T and HCT116 cells respectively (p < 0.002) for the single slice analysis. A similar pattern of successful CEA-targeted fluorescence was observed in the maximum image projection analysis, with CEA-targeted nanoparticles demonstrating 4.1, 2.9 and 2.4 fold greater fluorescence than control particles in LoVo, LS174T, and HCT116 cells respectively (p < 0.0002). There was no significant difference in fluorescence for CEA-Affimer vs. CEA-Antibody targeted nanoparticles. Conclusion: We are the first to demonstrate that Foslip-doped silica nanoparticles conjugated to anti-CEA Affimers via SMCC allowed tumour cell-specific fluorescent targeting in vitro, and had shown sufficient promise to justify testing in an animal model of colorectal cancer. CEA-Affimer appears to be a suitable targeting molecule to replace CEA-Antibody. Targeted silica nanoparticles loaded with Foslip photosensitiser is now being optimised to drive photodynamic killing, via reactive oxygen generation.

Keywords: colorectal cancer, silica nanoparticles, Affimers, antibodies, imaging

Procedia PDF Downloads 213

Authors: Peter Heimerl, Alexander Plaikner, Mike Peters

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Background and Significance of the Study: Family-run businesses are a decisive economic factor in the Alpine tourism and leisure industry. Within the next years, it is expected that a large number of family-run small and medium-sized businesses will transfer ownership due to demographic developments. Four stages of succession processes can be identified by several empirical studies: (1) the preparation phase, (2) the succession planning phase, (3) the development of the succession concept, (4) and the implementation of the business transfer. Family business research underlines the importance of individual's and family’s values: Especially leadership values address mainly the first phase, which strongly determines the following stages. Aim of the Study: The study aims at answering the following research question: Which leadership values are dominating during succession processes in family-run businesses in Austrian Alpine tourism industry? Methodology: Twenty-two problem-centred individual interviews with 11 transferors and their 11 transferees were conducted. Data analysis was carried out using the software program MAXQDA following an inductive approach to data coding. Major Findings: Data analysis shows that nine values particularly influence succession processes, especially during the vulnerable preparation phase. Participation is the most-dominant value (162 references). It covers a style of cooperation, communication, and controlling. Discipline (142) is especially prevailing from the transferor's perspective. It addresses entrepreneurial honesty and customer orientation. Development (138) is seen as an important value, but it can be distinguished between transferors and transferees. These are mainly focused on strategic positioning and new technologies. Trust (105) is interpreted as a basic prerequisite to run the family firm smoothly. Interviewees underline the importance to be able to take a break from family-business management; however, this is only possible when openness and honesty constitute trust within the family firm. Loyalty (102): Almost all interviewees perceive that they can influence the loyalty of the employees through their own role models. A good work-life balance (90) is very important to most of the transferors, especially for their employees. Despite the communicated importance of a good work-life-balance, but however, mostly the commitment to the company is prioritised. Considerations of regionality (82) and regional responsibility are also frequently raised. Appreciation (75) is of great importance to both the handover and the takeover generation -as appreciation towards the employees in the company and especially in connection with the family. Familiarity (66) and the blurring of the boundaries between private and professional life are very common, especially in family businesses. Familial contact and open communication with employees which is mentioned in almost all handing over. Conclusions: In the preparation phase of succession, successors and incumbents have to consider and discuss their leadership and family values of family-business management. Quite often, assistance is needed to commonly and openly discuss these values in the early stages of succession processes. A large majority of handovers fail because of these values. Implications can be drawn to support family businesses, e.g., consulting initiatives at chambers of commerce and business consultancies must address this problem.

Keywords: leadership values, family business, succession processes, succession phases

Procedia PDF Downloads 64

Authors: Jessica Terese Mueller, Christoph Breitsprecher, Mike Oliver Mosko

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Due to an unusually high number of asylum seekers entering Germany over the course of the past few years, the need for community interpreters has increased dramatically, in order to make the communication between asylum seekers and various actors in social and governmental agencies possible. In the field of social work in particular, there are community interpreters who possess a wide spectrum of qualifications spanning from state-certified professional interpreters with graduate degrees to lay or ad-hoc interpreters with little to no formal training. To the best of our knowledge, Germany has no official national quality standards for the training of community interpreters at present, which would serve to professionalise this field as well as to assure a certain degree of quality in the training programmes offered. Given the current demand for trained community interpreters, there is a growing number of training programmes geared toward qualifying community interpreters who work with asylum seekers in Germany. These training programmes range from short one-day workshops to graduate programmes with specialisations in Community Interpreting. As part of a larger project to develop quality standards for the qualification of community interpreters working with asylum seekers in the field of social work, a needs assessment was performed in the city-state of Hamburg and the state of North Rhine Westphalia in the form of focus groups and individual interviews with relevant actors in the field in order to determine the content and practical knowledge needed for community interpreters from the perspectives of those who work in and rely on this field. More specifically, social workers, volunteers, certified language and cultural mediators, paid and volunteer community interpreters and asylum seekers were invited to take part in focus groups in both locations, and asylum seekers, training providers, researchers, linguists and other national and international experts were individually interviewed. The responses collected in these focus groups and interviews have been analysed using Mayring’s concept of content analysis. In general, the responses indicate a high degree of overlap related to certain categories as well as some categories which seemed to be of particular importance to certain groups individually, while showing little to no relevance for other groups. For example, the topics of accuracy and transparency of the interpretations, as well as professionalism and ethical concerns were touched on in some form in most groups. Some group-specific topics which are the focus of experts were topics related to interpreting techniques and more concretely described theoretical and practical knowledge which should be covered in training programmes. Social workers and volunteers generally concentrated on issues regarding the role of the community interpreters and the importance of setting and clarifying professional boundaries. From the perspective of service receivers, asylum seekers tended to focus on the importance of having access to interpreters who are from their home region or country and who speak the same regiolect, dialect or variety as they do in order to prevent misunderstandings or misinterpretations which might negatively affect their asylum status. These results indicate a certain degree of consensus with trainings offered internationally for community interpreters.

Keywords: asylum seekers, community interpreting, needs assessment, quality standards, training

Procedia PDF Downloads 136

Authors: Jing Zhang, Yvonne Reinwald, Nick Poulson, Alicia El Haj, Chung See, Mike Somekh, Melissa Mather

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Biomedical imaging of native tissue using light offers the potential to obtain excellent structural and functional information in a non-invasive manner with good temporal resolution. Image contrast can be derived from intrinsic absorption, fluorescence, or scatter, or through the use of extrinsic contrast. A major challenge in applying optical microscopy to in vivo tissue imaging is the effects of light attenuation which limits light penetration depth and achievable imaging resolution. Recently Selective Plane Illumination Microscopy (SPIM) has been used to map the 3D distribution of fluorophores dispersed in biological structures. In this approach, a focused sheet of light is used to illuminate the sample from the side to excite fluorophores within the sample of interest. Images are formed based on detection of fluorescence emission orthogonal to the illumination axis. By scanning the sample along the detection axis and acquiring a stack of images, 3D volumes can be obtained. The combination of rapid image acquisition speeds with the low photon dose to samples optical sectioning provides SPIM is an attractive approach for imaging biological samples in 3D. To date all implementations of SPIM rely on the use of fluorescence reporters be that endogenous or exogenous. This approach has the disadvantage that in the case of exogenous probes the specimens are altered from their native stage rendering them unsuitable for in vivo studies and in general fluorescence emission is weak and transient. Here we present for the first time to our knowledge a label-free implementation of SPIM that has downstream applications in the clinical setting. The experimental set up used in this work incorporates both label-free and fluorescent illumination arms in addition to a high specification camera that can be partitioned for simultaneous imaging of both fluorescent emission and scattered light from intrinsic sources of optical contrast in the sample being studied. This work first involved calibration of the imaging system and validation of the label-free method with well characterised fluorescent microbeads embedded in agarose gel. 3D constructs of mammalian cells cultured in agarose gel with varying cell concentrations were then imaged. A time course study to track cell proliferation in the 3D construct was also carried out and finally a native tissue sample was imaged. For each sample multiple images were obtained by scanning the sample along the axis of detection and 3D maps reconstructed. The results obtained validated label-free SPIM as a viable approach for imaging cells in a 3D gel construct and native tissue. This technique has the potential use in a near-patient environment that can provide results quickly and be implemented in an easy to use manner to provide more information with improved spatial resolution and depth penetration than current approaches.

Keywords: bioimaging, optics, selective plane illumination microscopy, tissue imaging

Procedia PDF Downloads 222

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

Procedia PDF Downloads 62