A Novel Framework to Model the Short and Medium Term Mechanical Response of the Medial Gastrocnemius

Musculoskeletal disorders (MSDs) are the second largest cause of disability worldwide and cost the UK National Health Service (NHS) over £4.7 billion yearly. One holistic approach to alleviate this burden is to create in silico models that provide insight into MSDs which will improve diagnostic and therapeutic procedures. This thesis presents a modelling framework that analyses the mechanical behaviour of anatomical skeletal muscles. The anatomical geometry and fibre paths of the medial gastrocnemius muscle were acquired from the Living Human Data Library (LHDL). The medial gastrocnemius model was further sophisticated by incorporating morphological representations of the aponeurosis and myotendon transition region. Having carried out a finite element analysis on the medial gastrocnemius, it was found that the morphology and size of the transition region significantly affected the mechanical response of the muscle. Three illustrative simulations were subsequently carried out on the model, to better understand the muscle’s mechanical response in differing mechanical environments: (1) the effects of high extensions on the muscle’s mechanical response, (2) lengthening of the aponeurosis - a phenomenon often observed following aponeurosis regression - and (3) the stress-strain regime of the muscle when the tendon experiences a laceration and heals over 21 days. These models show the regions that experienced the highest strains were the muscle-tendon transition regions. As MSDs tend to be of a degenerative nature and progress over time, the temporal changes of the mechanical response of skeletal muscle tissue is of great interest. In the penultimate chapter, the medial gastrocnemius was assessed across various remodelling regimes. It was found that the muscle returned to homeostasis only when both the muscle and tendon remodelled – albeit, at different remodelling rates. Whilst this observation seems intuitive, most other growth and remodelling models of skeletal muscles have only remodelled either the muscle or tendon constituent. The model developed in this thesis therefore has the potential to inform multi-scale musculo-skeletal muscle models thus providing a significant contribution to understanding MSDs

Imputation Techniques in Machine Learning – A Survey

Machine learning plays a pivotal role in data analysis and information extraction. However, one common challenge encountered in this process is dealing with missing values. Missing data can find its way into datasets for a variety of reasons. It can result from errors during data collection and management, intentional omissions, or even human errors. It's important to note that most machine learning models are not designed to handle missing values directly. Consequently, it becomes essential to perform data imputation before feeding the data into a machine learning model. Multiple techniques are available for imputing missing values, and the choice of technique should be made judiciously, considering various parameters. An inappropriate choice can disrupt the overall distribution of data values and subsequently impact the model's performance. In this paper, various imputation methods, including Mean, Median, K-nearest neighbors (KNN)-based imputation, Linear Regression, Miss Forest, and MICE are examined

Florid pustular dermatitis of breast: A case report on a unusual complication from acellular dermal matrix use

AbstractIntroductionIdiopathic erythematous reaction of the breast (Red breast syndrome) is a known complication following breast reconstruction with acellular dermal matrix. However pustular dermatitis like presentation is not previously known.Presentation of caseWe present a 42-year-old lady who developed bilateral pustular dermatitis like appearance following breast reconstruction with acellular dermal matrix slings. Though surgical washout was done, both expanders and flex HD could be preserved.DiscussionAcellular dermal matrix use is the only possible explanation for such a presentation and this can be considered a variant of red breast syndrome.ConclusionPustular dermatitis like presentation can be associated with acelluar dermal matrix use and should be considered in similar clinical presentations, since this can avoid unnecessary surgical procedures

Patient preferences for adjuvant radiotherapy in early breast cancer are strongly influenced by treatment received through random assignment

Objective: TARGIT‐A randomised women with early breast cancer to receive external beam radiotherapy (EBRT) or intraoperative radiotherapy (TARGIT‐IORT). This study aimed to identify what extra risk of recurrence patients would accept for per‐ ceived benefits and risks of different radiotherapy treatments. Methods: Patient preferences were determined by self‐rated trade‐off question‐ naires in two studies: Stage (1) 209 TARGIT‐A participants (TARGIT‐IORT n = 108, EBRT n = 101); Stage (2) 123 non‐trial patients yet to receive radiotherapy (pre‐treat‐ ment group), with 85 also surveyed post‐radiotherapy. Patients traded‐off risks of local recurrence in preference selection between TARGIT‐IORT and EBRT. Results: TARGIT‐IORT patients were more accepting of IORT than EBRT patients with 60% accepting the highest increased risk presented (4%–6%) compared to 12% of EBRT patients, and 2% not accepting IORT at all compared to 43% of EBRT pa‐ tients. Pre‐treatment patients were more accepting of IORT than post‐treatment pa‐ tients with 23% accepting the highest increased risk presented compared to 15% of post‐treatment patients, and 15% not accepting IORT at all compared to 41% of pre‐ treatment patients. Conclusions: Breast cancer patients yet to receive radiotherapy accept a higher recurrence risk than the actual risk found in TARGIT‐A. Measured patient preferences are highly influenced by experience of treatment received. This finding challenges the validity of post‐treatment preference studies

Green synthesis of iron nanoparticles using aqueous extract of Turbinaria conoides (J. Agardh) and their anticancer properties

Marine macroalgae produce numerous bioactive compounds with potential pharmacological properties. In this study, macroalga was collected from the Gulf of Mannar, India and identified as, Turbinaria conoides (J. Agardh). The aqueous extract of T. conoides was used to synthesize iron nanoparticles (NPs). The synthesized iron NPs were characterized by X –ray diffraction analysis, Scanning Electron Microscopy, and Transmission Electron Microscopy. The synthesized NPs showed potent activity against DLD1 and HeLa cell lines

Development of fluorescent in situ hybridisation for Cryptosporidium detection reveals zoonotic and anthrioponotic transmission of sporadic cryptosporidiosis in Sydney

Cryptosporidium, is the most common non-viral cause of diarrhea worldwide. Of the 5 described species that contribute to the majority of human infections, C. parvum is of major interest due to its zoonotic potential. A species-specific fluorescence in situ hybridisation probe was designed to the variable region in the small subunit of the 18S rRNA of C. parvum and labeled with Cy3. Probe specificity was validated against a panel of 7 other Cryptosporidium spp. before it was applied to 33 human faecal samples positive for cryptosporidiosis which were obtained during the period from 2006-2007. Results were compared to PCR-RFLP targeting the 18S rDNA. FISH results revealed that 19 of the 33 isolates analysed were identified as C. parvum. Correlation of PCR-RFLP and FISH was statistically significant (P < 0.05), resulting in a calculated correlation coefficient of 0.994. In this study, species identification by FISH and PCR-RFLP provided preliminary evidence to support both anthroponotic and zoonotic transmission of sporadic cases of cryptosporidiosis in the Sydney basin. In conclusion, FISH using a C. parvum-specific probe provided an alternative tool for accurate identification of zoonotic Cryptosporidium which will be applied in the future to both epidemiological and outbreak investigations