Culture of human mesenchymal stem cells on microcarriers in a 5 l stirred-tank bioreactor

For the first time, fully functional human mesenchymal stem cells (hMSCs) have been cultured at the litre-scale on microcarriers in a stirred-tank 5 l bioreactor, (2.5 l working volume) and were harvested via a potentially scalable detachment protocol that allowed for the successful detachment of hMSCs from the cell-microcarrier suspension. Over 12 days, the dissolved O2 concentration was >45 % of saturation and the pH between 7.2 and 6.7 giving a maximum cell density in the 5 l bioreactor of 1.7 × 105 cells/ml; this represents >sixfold expansion of the hMSCs, equivalent to that achievable from 65 fully-confluent T-175 flasks. During this time, the average specific O2 uptake of the cells in the 5 l bioreactor was 8.1 fmol/cell h and, in all cases, the 5 l bioreactors outperformed the equivalent 100 ml spinner-flasks run in parallel with respect to cell yields and growth rates. In addition, yield coefficients, specific growth rates and doubling times were calculated for all systems. Neither the upstream nor downstream bioprocessing unit operations had a discernible effect on cell quality with the harvested cells retaining their immunophenotypic markers, key morphological features and differentiation capacity. © 2013 Springer Science+Business Media Dordrecht.

What is the optimum artificial treament for dry eye?

Dry eye disease is a common clinical condition whose aetiology and management challenges clinicians and researchers alike. Practitioners have a number of dry eye tests available to clinically assess dry eye disease, in order to treat their patients effectively and successfully. This thesis set out to determine the most relevant and successful key tests for dry eye disease diagnosis/ management. There has been very little research on determining the most effective treatment options for these patients; therefore a randomised controlled study was conducted in order to see how different artificial treatments perform compared to each other, whether the preferred treatment could have been predicted from their ocular clinical assessment, and if the preferred treatment subjectively related to the greatest improvement in ocular physiology and tear film stability. This research has found: 1. From the plethora of ocular the tear tests available to utilise in clinical practice, the tear stability tests as measured by the non-invasive tear break (NITBUT) up time and invasive tear break up time (NaFL TBUT) are strongly correlated. The tear volume tests are also related as measured by the phenol red thread (PRT) and tear meniscus height (TMH). Lid Parallel Conjunctival Folds (LIPCOF) and conjunctival staining are significantly correlated to one another. Symptomology and osmolarity were also found to be important tests in order to assess for dry eye. 2. Artificial tear supplements do work for ocular comfort, as well as the ocular surface as observed by conjunctival staining and the reduction LIPCOF. There is no strong evidence of one type of artificial tear supplement being more effective than others, and the data suggest that these improvements are more due to the time than the specific drops. 3. When trying to predict patient preference for artificial tears from baseline measurements, the individual category of artificial tear supplements appeared to have an improvement in at least 1 tear metric. Undoubtedly, from the study the patients preferred artificial tear supplements’ were rated much higher than the other three drops used in the study and their subjective responses were statistically significant than the signs. 4. Patients are also willing to pay for a community dry eye service in their area of £17. In conclusion, the dry eye tests conducted in the study correlate with one another and with the symptoms reported by the patient. Artificial tears do make a difference objectively as well as subjectively. There is no optimum artificial treatment for dry eye, however regular consistent use of artificial eye drops will improve the ocular surface.

Self-adapting parallel metric-space search engine for variable query loads

This research focuses on automatically adapting a search engine size in response to fluctuations in query workload. Deploying a search engine in an Infrastructure as a Service (IaaS) cloud facilitates allocating or deallocating computer resources to or from the engine. Our solution is to contribute an adaptive search engine that will repeatedly re-evaluate its load and, when appropriate, switch over to a dierent number of active processors. We focus on three aspects and break them out into three sub-problems as follows: Continually determining the Number of Processors (CNP), New Grouping Problem (NGP) and Regrouping Order Problem (ROP). CNP means that (in the light of the changes in the query workload in the search engine) there is a problem of determining the ideal number of processors p active at any given time to use in the search engine and we call this problem CNP. NGP happens when changes in the number of processors are determined and it must also be determined which groups of search data will be distributed across the processors. ROP is how to redistribute this data onto processors while keeping the engine responsive and while also minimising the switchover time and the incurred network load. We propose solutions for these sub-problems. For NGP we propose an algorithm for incrementally adjusting the index to t the varying number of virtual machines. For ROP we present an ecient method for redistributing data among processors while keeping the search engine responsive. Regarding the solution for CNP, we propose an algorithm determining the new size of the search engine by re-evaluating its load. We tested the solution performance using a custom-build prototype search engine deployed in the Amazon EC2 cloud. Our experiments show that when we compare our NGP solution with computing the index from scratch, the incremental algorithm speeds up the index computation 2{10 times while maintaining a similar search performance. The chosen redistribution method is 25% to 50% faster than other methods and reduces the network load around by 30%. For CNP we present a deterministic algorithm that shows a good ability to determine a new size of search engine. When combined, these algorithms give an adapting algorithm that is able to adjust the search engine size with a variable workload.