No abstract

No abstract

The isolation and characterisation of single cells from a heterogeneous population are important processes in cell biology, immunology, stem cell research, and cancer research. In the development of novel cell-based therapies, there is a considerable need to target specific cell types to allow for further analysis and amplification ex vivo. We introduce, herein, the use of droplet-based microfluidics as a platform technology for the identification and quantification of distinct cell phenotypes. Using molecular labelling of specific cell populations by antibodies and fluorescent dyes, detection of single cells encapsulated within picolitre-sized aqueous droplets can be performed using high-sensitivity confocal fluorescence detection. Specifically, rare progenitor cells were immunodetected within a heterogeneous population of cells isolated from human periosteal tissue. Using this model human cell population, the accuracy and reproducibility of the droplet system were tested and the results were verified using conventional flow cytometry. It was found that the quantitation of phenotypic subpopulations measured using both techniques is directly comparable. Accordingly, this study demonstrates the biological capacity of droplet-based microfluidics for cellular analysis and provides a necessary first step towards the development of a novel cell sorting technology.

BackgroundSocial media analysis has rarely been applied to the study of specific questions in outcomes research.ObjectiveThe aim was to test the applicability of social media analysis to outcomes research using automated listening combined with filtering and analysis of data by specialists. After validation, the process was applied to the study of patterns of treatment switching in multiple sclerosis (MS).MethodsA comprehensive listening and analysis process was developed that blended automated listening with filtering and analysis of data by life sciences-qualified analysts and physicians. The population was patients with MS from the United States. Data sources were Facebook, Twitter, blogs, and online forums. Sources were searched for mention of specific oral, injectable, and intravenous (IV) infusion treatments. The representativeness of the social media population was validated by comparison with community survey data and with data from three large US administrative claims databases: MarketScan, PharMetrics Plus, and Department of Defense.ResultsA total of 10,260 data points were sampled for manual review: 3025 from Twitter, 3771 from Facebook, 2773 from Internet forums, and 691 from blogs. The demographics of the social media population were similar to those reported from community surveys and claims databases. Mean age was 39 (SD 11) years and 14.56% (326/2239) of the population was older than 50 years. Women, patients aged 30 to 49 years, and those diagnosed for more than 10 years were represented by more data points than other patients were. Women also accounted for a large majority (82.6%, 819/991) of reported switches. Two-fifths of switching patients had lived with their disease for more than 10 years since diagnosis. Most reported switches (55.05%, 927/1684) were from injectable to oral drugs with switches from IV therapies to orals the second largest switch (15.38%, 259/1684). Switches to oral drugs accounted for more than 80% (927/1114) of the switches away from injectable therapies. Four reasons accounted for more than 90% of all switches: severe side effects, lack of efficacy, physicians’ advice, and greater ease of use. Side effects were the main reason for switches to oral or to injectable therapies and search for greater efficacy was the most important factor in switches to IV therapies. Cost of medication was the reason for switching in less than 0.5% of patients.ConclusionsSocial intelligence can be applied to outcomes research with power to analyze MS patients’ personal experiences of treatments and to chart the most common reasons for switching between therapies.

BACKGROUND & PURPOSETo describe methodology, interim baseline, and longitudinal magnetic resonance imaging (MRI) acquisition parameter characteristics of the multiple sclerosis clinical outcome and MRI in the United States (MS‐MRIUS).MATERIAL & METHODSThe MS‐MRIUS is an ongoing longitudinal and retrospective study of MS patients on fingolimod. Clinical and brain MRI image scan data were collected from 600 patients across 33 MS centers in the United States. MRI brain outcomes included change in whole‐brain volume, lateral ventricle volume, T2‐ and T1‐lesion volumes, and new/enlarging T2 and gadolinium‐enhancing lesions.RESULTSInterim baseline and longitudinal MRI acquisition parameters results are presented for 252 patients. Mean age was 44 years and 81% were female. Forty percent of scans had 3‐dimensional (3D) T1 sequence in the preindex period, increasing to 50% in the postindex period. Use of 2‐dimensional (2D) T1 sequence decreased over time from 85% in the preindex period to 65% in the postindex. About 95% of the scans with FLAIR and 2D T1‐WI were considered acceptable or good quality compared to 99–100% with 3D T1‐WI. There were notable changes in MRI hardware, software, and coil (39.5% in preindex to index and 50% in index to postindex). MRI sequence parameters (orientation, thickness, or protocol) differed for 36%, 29%, and 20% of index/postindex scans for FLAIR, 2D T1‐WI, and 3D T1‐WI, respectively.CONCLUSIONSThe MS‐MRIUS study linked the clinical and brain MRI outcomes into an integrated database to create a cohort of fingolimod patients in real‐world practice. Variability was observed in MRI acquisition protocols overtime.