Error-Correcting Output Codes in Classification of Human Induced Pluripotent Stem Cell Colony Images.

The purpose of this paper is to examine how well the human induced pluripotent stem cell (hiPSC) colony images can be classified using error-correcting output codes (ECOC). Our image dataset includes hiPSC colony images from three classes (bad, semigood, and good) which makes our classification task a multiclass problem. ECOC is a general framework to model multiclass classification problems. We focus on four different coding designs of ECOC and apply to each one of them k-Nearest Neighbor (k-NN) searching, naïve Bayes, classification tree, and discriminant analysis variants classifiers. We use Scaled Invariant Feature Transformation (SIFT) based features in classification. The best accuracy (62.4%) is obtained with ternary complete ECOC coding design and k-NN classifier (standardized Euclidean distance measure and inverse weighting). The best result is comparable with our earlier research. The quality identification of hiPSC colony images is an essential problem to be solved before hiPSCs can be used in practice in large-scale. ECOC methods examined are promising techniques for solving this challenging problem.

Machine Learning Approach to Automated Quality Identification of Human Induced Pluripotent Stem Cell Colony Images.

The focus of this research is on automated identification of the quality of human induced pluripotent stem cell (iPSC) colony images. iPS cell technology is a contemporary method by which the patient's cells are reprogrammed back to stem cells and are differentiated to any cell type wanted. iPS cell technology will be used in future to patient specific drug screening, disease modeling, and tissue repairing, for instance. However, there are technical challenges before iPS cell technology can be used in practice and one of them is quality control of growing iPSC colonies which is currently done manually but is unfeasible solution in large-scale cultures. The monitoring problem returns to image analysis and classification problem. In this paper, we tackle this problem using machine learning methods such as multiclass Support Vector Machines and several baseline methods together with Scaled Invariant Feature Transformation based features. We perform over 80 test arrangements and do a thorough parameter value search. The best accuracy (62.4%) for classification was obtained by using a k-NN classifier showing improved accuracy compared to earlier studies.

Mutation-Specific Phenotypes in hiPSC-Derived Cardiomyocytes Carrying Either Myosin-Binding Protein C Or α-Tropomyosin Mutation for Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a genetic cardiac disease, which affects the structure of heart muscle tissue. The clinical symptoms include arrhythmias, progressive heart failure, and even sudden cardiac death but the mutation carrier can also be totally asymptomatic. To date, over 1400 mutations have been linked to HCM, mostly in genes encoding for sarcomeric proteins. However, the pathophysiological mechanisms of the disease are still largely unknown. Two founder mutations for HCM in Finland are located in myosin-binding protein C (MYBPC3-Gln1061X) and α-tropomyosin (TPM1-Asp175Asn) genes. We studied the properties of HCM cardiomyocytes (CMs) derived from patient-specific human induced pluripotent stem cells (hiPSCs) carrying either MYBPC3-Gln1061X or TPM1-Asp175Asn mutation. Both types of HCM-CMs displayed pathological phenotype of HCM but, more importantly, we found differences between CMs carrying either MYBPC3-Gln1061X or TPM1-Asp175Asn gene mutation in their cellular size, Ca(2+) handling, and electrophysiological properties, as well as their gene expression profiles. These findings suggest that even though the clinical phenotypes of the patients carrying either MYBPC3-Gln1061X or TPM1-Asp175Asn gene mutation are similar, the genetic background as well as the functional properties on the cellular level might be different, indicating that the pathophysiological mechanisms behind the two mutations would be divergent as well.

CytoSpectre: a tool for spectral analysis of oriented structures on cellular and subcellular levels.

BACKGROUND: Orientation and the degree of isotropy are important in many biological systems such as the sarcomeres of cardiomyocytes and other fibrillar structures of the cytoskeleton. Image based analysis of such structures is often limited to qualitative evaluation by human experts, hampering the throughput, repeatability and reliability of the analyses. Software tools are not readily available for this purpose and the existing methods typically rely at least partly on manual operation. RESULTS: We developed CytoSpectre, an automated tool based on spectral analysis, allowing the quantification of orientation and also size distributions of structures in microscopy images. CytoSpectre utilizes the Fourier transform to estimate the power spectrum of an image and based on the spectrum, computes parameter values describing, among others, the mean orientation, isotropy and size of target structures. The analysis can be further tuned to focus on targets of particular size at cellular or subcellular scales. The software can be operated via a graphical user interface without any programming expertise. We analyzed the performance of CytoSpectre by extensive simulations using artificial images, by benchmarking against FibrilTool and by comparisons with manual measurements performed for real images by a panel of human experts. The software was found to be tolerant against noise and blurring and superior to FibrilTool when analyzing realistic targets with degraded image quality. The analysis of real images indicated general good agreement between computational and manual results while also revealing notable expert-to-expert variation. Moreover, the experiment showed that CytoSpectre can handle images obtained of different cell types using different microscopy techniques. Finally, we studied the effect of mechanical stretching on cardiomyocytes to demonstrate the software in an actual experiment and observed changes in cellular orientation in response to stretching. CONCLUSIONS: CytoSpectre, a versatile, easy-to-use software tool for spectral analysis of microscopy images was developed. The tool is compatible with most 2D images and can be used to analyze targets at different scales. We expect the tool to be useful in diverse applications dealing with structures whose orientation and size distributions are of interest. While designed for the biological field, the software could also be useful in non-biological applications.

Signal analysis and classification methods for the calcium transient data of stem cell-derived cardiomyocytes.

Calcium cycling is crucial in the excitation-contraction coupling of cardiomyocytes, and therefore has a key role in cardiac functionality. Cardiac disorders and different drugs alter the calcium transients of cardiomyocytes and can cause serious dysfunction of the heart. New insights into this biochemical phenomena can be achieved by studying and analyzing calcium transients. Calcium transients of spontaneously beating human induced pluripotent stem cell-derived cardiomyocytes were recorded for a data set of 280 signals. Our objective was to develop and program procedures: (1) to automatically detect cycling peaks from signals and to classify the peaks of signals as either normal or abnormal, and (2) on the basis of the preceding peak detection results, to classify the entire signals into either a normal class or an abnormal class. We obtained a classification accuracy of approximately 80% compared to class decisions made separately by an experienced researcher, which is promising for the further development of an automatic classification approach. Automated classification software would be beneficial in the future for analyzing cardiomyocyte functionality on a large scale when screening for the adverse cardiac effects of new potential compounds, and also in future clinical applications.

Attitudes of significant others of people with Ménière's disease vary from coping to victimization.

OBJECTIVE: To explore the impact, reactions and coping methods of the significant others (SOs) of people with Ménière's disease (MD). DESIGN: SOs of people with MD were asked to answer open-ended questions reporting the 'life effects' and 'positive experiences' they have had as a result of the partner's condition. The replies to the 'life effects' question was categorized using the WHO-ICF framework. The responses of 'life effects' from this study and the 'positive experiences' reported in a recent study ( Manchaiah et al, 2013 ) were evaluated with K-means clustering analysis. STUDY SAMPLE: Eighty-eight SOs (42 male, 42 female, and four did not state gender). RESULTS: While the SOs mainly listed their own problems, a significant number of responses related to the problems of their partner. Personal perspectives tended to focus on the consequences of their partner's condition, whereas in perspectives of their partner they focussed on his/her symptoms. Further, replies from 81 SOs were used in evaluation of responses and were classified into four categories: constrained life attitude; disease burden attitude; care and support attitude; and social isolation attitude. CONCLUSIONS: The results of this study support the importance of including the SO of people with MD in the rehabilitation process.

Disease Profiling for Computerized Peer Support of Ménière's Disease.

BACKGROUND: Peer support is an emerging form of person-driven active health care. Chronic conditions such as Ménière's disease (a disorder of the inner ear) need continuing rehabilitation and support that is beyond the scope of routine clinical medical practice. Hence, peer-support programs can be helpful in supplementing some of the rehabilitation aspects. OBJECTIVE: The aim of this study was to design a computerized data collection system for the peer support of Menière's disease that is capable in profiling the subject for diagnosis and in assisting with problem solving. METHODS: The expert program comprises several data entries focusing on symptoms, activity limitations, participation restrictions, quality of life, attitude and personality trait, and an evaluation of disease-specific impact. Data was collected from 740 members of the Finnish Ménière's Federation and utilized in the construction and evaluation of the program. RESULTS: The program verifies the diagnosis of a person by using an expert system, and the inference engine selects 50 cases with matched symptom severity by using a nearest neighbor algorithm. These cases are then used as a reference group to compare with the person's attitude, sense of coherence, and anxiety. The program provides feedback for the person and uses this information to guide the person through the problem-solving process. CONCLUSIONS: This computer-based peer-support program is the first example of an advanced computer-oriented approach using artificial intelligence, both in the profiling of the disease and in profiling the person's complaints for hearing loss, tinnitus, and vertigo.

Aural fullness in Ménière's disease.

OBJECTIVE: Aural fullness in Ménière's disease and the predisposing and consequential factors were investigated and possible consequences of aural fullness on participation activity were explored. METHODS: 726 subjects of the Finnish Ménière Association replied to a questionnaire focusing on symptoms of Ménière's disease, sense of coherence, attitude, participation restriction, and general health-related quality of life (EQ-5D). In the analysis, the severity of the disease was controlled. RESULTS: 68% of the subjects had aural fullness and in 37% it was moderate or strong. Aural fullness was rated as the worst problem by 4.4% of the subjects. Females reported more aural fullness than males. Tinnitus, hyperacusis and balance problems were significant predictors of aural fullness. Aural fullness was associated with reduced quality of life and complaints such as vertigo attacks, balance problems and hearing loss. Analysis based on participation restriction indicated that severe aural fullness leads to social isolation. CONCLUSIONS: Largely, psychological factors and personal traits modify problems experienced by aural fullness. Relaxation was the only statistically significant method that alleviated aural fullness.

The sense of coherence in patients with Menière's disease.

OBJECTIVE: To investigate how the ability to adapt, measured by the sense of coherence (SOC), is related to specific complaints of Menière's disease (MD) and the disease specific and general health related quality of life (EQ-5D) and on disease specific impact of the disease (MD-impact). METHODS: Postal survey, including a structured questionnaire on EQ-5D, SOC, symptoms, positive experiences, and the impact of MD, was sent to the members of the Finnish Menière Federation, reporting a diagnosis compatible with the condition. A sample of 547 members replied and were analyzed. RESULTS: The SOC reflected the disabilities caused by symptoms of MD and psychosocial factors including verbal score scale (VSS) anxiety (p<0.01) and loss of vitality (p<0.001). Higher SOC scores were related to better scores in EQ-5D and lower scores in MD-impact. Positive attitudes consequential to MD were associated with higher SOC scores reflecting better control over the consequences of disease. CONCLUSION: SOC is an element of patient's attitude toward illness and correlates with perceived good health. Patients with higher SOC scores are more content with their quality of life. Future research should focus on whether influencing modifiable psychological factors, such as positive attitudes, could improve adaptive ability in MD.

Risk factors of falls in community dwelling active elderly.

OBJECTIVE: To search for measures to describe and relate to accidental falls in community dwelling elderly. METHOD: A EuroQol EQ-5D questionnaire based on a patient's otoneurological case history provided a general health related quality of life measure, a fall history for the last 3 months and force platform measures for 96 active elderly from a pensioner organization. RESULTS: On average, the elderly experienced 0.3 falls over the preceding three months. A fall was seen to cause a significant deterioration in the quality of life and vertigo and caused fear of falling. The postural instability correlated with falls. Vertigo was present among 42% and was most commonly characterized as episodic and rotatory in factorial analysis items relating to vertigo correlated to falls and balance complaints. Four factors were identified and three of these correlated with falls. Vestibular failure correlated to a fall occurring when a person was rising up; Movement intolerance correlated with falls due to slips and trips, and Near-syncope factor correlated to falls for other reasons. In posturography, the variable measuring critical time describing the memory based "closed loop" control of postural stability carried a risk for accidental fall with an odds ratio of 6. The variable measuring zero crossing velocity showed a high rate of velocity change around the neutral position of stance. CONCLUSION: Vertigo and poor postural stability were the major reasons for falls in the active elderly. In ageing, postural control is shifted towards open loop control (visual, proprioception, exteroception and vestibular) instead of closed loop control and is a factor that contributes to a fall.