Application of correlated component analysis to dynamic PET time-activity curves denoising.

Positron emission tomography (PET) is a physiological, non-invasive imaging technique, which forms an essential part of nuclear medicine. The data obtained in a PET scan represent the concentration of an administered radiotracer in tissues over time. Quantitative analysis of PET data makes possible the assessments of in-vivo physiological processes. The Logan graphical analysis (LGA) is one of the methods that are used for quantitative analysis of PET data. LGA transforms PET data into a simple linear relationship. The slope of the LGA linear relationship is a physiological quantity denoting receptor availability. This quantity is termed distribution volume ratio (DVR). LGA-based estimates of the DVR are negatively affected by the noise in PET data -leading to the DVR being underestimated. A number of approaches proposed to address this issue have been observed to reduce the bias at the cost precision. An alternative regression method, least-squares cubic (LSC), was recently applied to estimate the DVR in order to reduce the bias. LSC was observed to reduce the bias in the LGA-based estimates. However, slight increases were also observed in the variance of the LSC-based estimates. This calls for methods to act against the variance in the LSC-based estimates. In this study, an alternative method is applied for tTAC denoising. This method is referred to as correlated component analysis (CorrCA). CorrCA transform the data by searching for dimensions of maximum correlation. This technique is closely related to other well-known methods such as principal component analysis and independent component analysis. In this study, the data were denoised by CorrCA (to act against the variance in the estimate) and the DVR was estimated by LSC, which provides for minimal bias. The resulting method LSC-CorrCA, gave less-biased estimated with increased precision. This was observed for both simulation results as well as for clinical data, both for 11C Pittsburgh compound B. Simulation data revealed reduced variances in LCS-CorrCA-based estimates, and the clinical data showed improved contrast between gray and white matter regions.Clinical Relevance-Improved DVR estimates would ease the interpretation of medical images, which will in turn positively influence the clinical processes, from diagnosis to treatment and follow-ups.

[Evaluation of physical activity using smartphones and wearable devices in healthcare: Current situation and future perspectives].

Abstract　With the growing popularity of mobile health (mHealth) devices, including smartphones and wearable devices, information and communications technology has gained high importance in healthcare settings. This study aimed to summarize the current trends in physical activity research wherein mHealth devices are used and provide perspectives for future research. Until recently, questionnaire surveys were primarily used to evaluate physical activity. While questionnaire surveys are effective for subjective evaluation, the use of mHealth devices enables large-scale, real-time, objective evaluation of physical activity. In addition, mHealth devices automatically collect and aggregate data. This allows researchers to perform retrospective analysis of a wide range of indicators of physical activity and health. Particularly, the use of smartphones is highly likely to contribute to large-scale monitoring and health interventions because of their ubiquity. Even though there are fewer users of wearable devices (wrist-worn devices) than those of smartphones, using wearable devices allows for the evaluation of 24-hour movement patterns. The use of wearable devices helps perform further precise analysis that focuses not only on the total amount of physical activity but also on the quality, including measures of intensity, duration, frequency, type, and time. Moreover, some wrist-worn devices measure physiological information such as heart rate and may also provide location information. Combining such data with information from an accelerometer associated with a device may allow for further specific and detailed evaluation of physical activity. The validity of physical activity assessment using major mHealth devices has been confirmed in several studies and is comparable to that of pedometers and accelerometers developed for research purposes. Evaluation of physical activity using mHealth devices involves issues related to the representativeness of the target population and continuity of data, as well as the need for ethical considerations based on privacy policies. While mHealth devices may be used by individuals as a health management tool, it is also expected that the evaluation of physical activity using mHealth devices will be performed in various settings such as epidemiological and clinical studies on physical activity, as well as community services wherein indicators of physical activity are used.

Improving contrast between gray and white matter of Logan graphical analysis' parametric images in positron emission tomography through least-squares cubic regression and principal component analysis.

Logan graphical analysis (LGA) is a method forin vivoquantification of tracer kinetics in positron emission tomography (PET). The shortcoming of LGA is the presence of a negative bias in the estimated parameters for noisy data. Various approaches have been proposed to address this issue. We recently applied an alternative regression method called least-squares cubic (LSC), which considers the errors in both the predictor and response variables to estimate the LGA slope. LSC reduced the bias in non-displaceable binding potential estimates while causing slight increases in the variance. In this study, we combined LSC with a principal component analysis (PCA) denoising technique to counteract the effects of variance on parametric image quality, which was assessed in terms of the contrast between gray and white matter. Tissue time-activity curves were denoised through PCA, prior to estimating the regression parameters using LSC. We refer to this approach as LSC-PCA. LSC-PCA was assessed against OLS-PCA (PCA with ordinary least-squares (OLS)), LSC, and conventional OLS-based LGA. Comparisons were made for simulated11C-carfentanil and11C Pittsburgh compound B (11C-PiB) data, and clinical11C-PiB PET images. PCA-based methods were compared over a range of principal components, varied by the percentage variance they account for in the data. The results showed reduced variances in distribution volume ratio estimates in the simulations for LSC-PCA compared to LSC, and lower bias compared to OLS-PCA and OLS. Contrasts were not significantly improved in clinical data, but they showed a significant improvement in simulation data -indicating a potential advantage of LSC-PCA over OLS-PCA. The effects of bias reintroduction when many principal components are used were also observed in OLS-PCA clinical images. We therefore encourage the use of LSC-PCA. LSC-PCA can allow the use of many principal components with minimal risk of bias, thereby strengthening the interpretation of PET parametric images.

Changes in Autonomic Nervous System and Axillary Temperature Caused by Electric Potential Therapy.

This paper describes two experiments conducted to investigate changes in the autonomic nervous system and axillary temperature caused by electric potential therapy. The former was investigated using a frequency analysis of successive heartbeats (RR intervals) and cortisol in saliva. The experimental results on the RR intervals suggest no significant change in the autonomic nervous system, but those on the saliva cortisol indicate a change in the system during the therapy. The axillary temperature showed a significant increase. The results on the autonomic nervous system seem inconsistent, and these results as well as future directions were discussed.

A strategy to account for noise in the X-variable to reduce underestimation in Logan graphical analysis for quantifying receptor density in positron emission tomography.

BACKGROUND: The Logan graphical analysis (LGA) algorithm is widely used to quantify receptor density for parametric imaging in positron emission tomography (PET). Estimating receptor density, in terms of the non-displaceable binding potential (BPND), from the LGA using the ordinary least-squares (OLS) method has been found to be negatively biased owing to noise in PET data. This is because OLS does not consider errors in the X-variable (predictor variable). Existing bias reduction methods can either only reduce the bias slightly or reduce the bias accompanied by increased variation in the estimates. In this study, we addressed the bias reduction problem by applying a different regression method. METHODS: We employed least-squares cubic (LSC) linear regression, which accounts for errors in both variables as well as the correlation of these errors. Noise-free PET data were simulated, for 11C-carfentanil kinetics, with known BPND values. Statistical noise was added to these data and the BPNDs were re-estimated from the noisy data by three methods, conventional LGA, multilinear reference tissue model 2 (MRTM2), and LSC-based LGA; the results were compared. The three methods were also compared in terms of beta amyloid (A ß) quantification of 11C-Pittsburgh compound B brain PET data for two patients with Alzheimer's disease and differing A ß depositions. RESULTS: Amongst the three methods, for both synthetic and actual data, LSC was the least biased, followed by MRTM2, and then the conventional LGA, which was the most biased. Variations in the LSC estimates were smaller than those in the MRTM2 estimates. LSC also required a shorter computational time than MRTM2. CONCLUSIONS: The results suggest that LSC provides a better trade-off between the bias and variability than the other two methods. In particular, LSC performed better than MRTM2 in all aspects; bias, variability, and computational time. This makes LSC a promising method for BPND parametric imaging in PET studies.

Machine Learning Approach for Predicting New Uses of Existing Drugs and Evaluation of Their Reliabilities.

In this chapter, a new method to evaluate the reliability of predicting new uses of existing drugs was proposed. The prediction was performed with a support vector machine (SVM) using various data. Because the reliability of prediction could not be evaluated based on the output of an SVM, which was binary, the proposed method evaluated the reliability as a product of a distance from the separating hyperplane of the SVM and a similarity between the disease targeted by the drug and a candidate disease. A validation using real data revealed that the performance of the proposed method was promising.

Information Encoding Methods for a Balance Assist Device Using Vibrotactile Feedback.

This study investigates the applicability of information encoding methods for a balance assist device using vibrotactile feedback. In the device, two motors were employed to provide information on the model's sway angle in each of the forward and backward directions. In the experiment involving ten healthy volunteers, two encoding modes with different vibration patterns were compared using an equivalent body model. The influence of proficiency level was also investigated. The results indicated that a simple encoding method outperformed a complex one even after the proficiency level was improved. Further analyses on the input and output of the model indicated the necessity of a time domain signal for encoding feedback information with the complex encoding methodology.

Downregulation of Plasma miR-215 in Chronic Myeloid Leukemia Patients with Successful Discontinuation of Imatinib.

Approximately 40% of chronic myeloid leukemia (CML) patients who discontinue imatinib (IM) therapy maintain undetectable minimal residual disease (UMRD) for more than one year (stopping IM (STOP-IM)). To determine a possible biomarker for STOP-IM CML, we examined plasma miRNA expression in CML patients who were able to discontinue IM. We first screened candidate miRNAs in unselected STOP-IM patients, who had sustained UMRD after discontinuing IM for more than six months, in comparison with healthy volunteers, by using a TaqMan low-density array for plasma or exosomes. Exosomal miR-215 and plasma miR-215 were downregulated in the STOP-IM group compared to the control, indicating that the biological relevance of the plasma miR-215 level is equivalent to that of the exosomal level. Next, we performed real-time quantitative RT-PCR in 20 STOP-IM patients, 32 patients with UMRD on continued IM therapy (IM group) and 28 healthy volunteers. The plasma miRNA-215 level was significantly downregulated in the STOP-IM group (p < 0.0001); we determined the cut-off level and divided the IM group patients into two groups according to whether the plasma miR-215 was downregulated or not. The IM group patients with a low plasma miR-215 level had a significantly higher total IM intake, compared to the patients with elevated miR-215 levels (p = 0.0229). Functional annotation of miR-215 target genes estimated by the Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatic tools involved cell cycle, mitosis, DNA repair and cell cycle checkpoint. Our study suggests a possible role of miR-215 in successful IM discontinuation.

Systemes analysis of interactions between microRNAs and genes in hepatocellular carcinoma.

MicroRNAs (miRNAs) are short noncoding RNAs and can regulate gene expression at the transcriptional and/or translational levels. There is mounting evidence that miRNAs play an important role in the control of the dynamics of localized gene expression. Expression profiling of miRNA in various cancers revealed that miRNA profiles could discriminate malignancies from their counter parts. In this study, to investigate the localized effect of miRNA in cancer, we analyzed gene and miRNA expressions in hepatocellular carcinoma (HCC) and surrounding nontumor tissues. Based on gene expression levels around miRNAs, we investigated how many miRNAs correlated positively/negatively in expression with genes in the vicinity. Next, the Pearson correlation coefficients were compared between the HCC and nontumor tissues. The results imply that the relationship between the intronic miRNAs and their host genes was altered in HCC, and that feedback loops including the host gene, intronic miRNA, target genes might be formed in HCC.

A two-step drug repositioning method based on a protein-protein interaction network of genes shared by two diseases and the similarity of drugs.

The present study proposed a two-step drug repositioning method based on a protein-protein interaction (PPI) network of two diseases and the similarity of the drugs prescribed for one of the two. In the proposed method, first, lists of disease related genes were obtained from a meta-database called Genotator. Then genes shared by a pair of diseases were sought. At the first step of the method, if a drug having its target(s) in the PPI network, the drug was deemed a repositioning candidate. Because targets of many drugs are still unknown, the similarities between the prescribed drugs for a specific disease were used to infer repositioning candidates at the second step. As a first attempt, we applied the proposed method to four different types of diseases: hypertension, diabetes mellitus, Crohn disease, and autism. Some repositioning candidates were found both at the first and second steps.

Development of a compact wireless Laplacian electrode module for electromyograms and its human interface applications.

In this study, we developed a compact wireless Laplacian electrode module for electromyograms (EMGs). One of the advantages of the Laplacian electrode configuration is that EMGs obtained with it are expected to be sensitive to the firing of the muscle directly beneath the measurement site. The performance of the developed electrode module was investigated in two human interface applications: character-input interface and detection of finger movement during finger Braille typing. In the former application, the electrode module was combined with an EMG-mouse click converter circuit. In the latter, four electrode modules were used for detection of finger movements during finger Braille typing. Investigation on the character-input interface indicated that characters could be input stably by contraction of (a) the masseter, (b) trapezius, (c) anterior tibialis and (d) flexor carpi ulnaris muscles. This wide applicability is desirable when the interface is applied to persons with physical disabilities because the disability differs one to another. The investigation also demonstrated that the electrode module can work properly without any skin preparation. Finger movement detection experiments showed that each finger movement was more clearly detectable when comparing to EMGs recorded with conventional electrodes, suggesting that the Laplacian electrode module is more suitable for detecting the timing of finger movement during typing. This could be because the Laplacian configuration enables us to record EMGs just beneath the electrode. These results demonstrate the advantages of the Laplacian electrode module.

Optokinetic stimulation can break Listing's law without induction of eye movement.

OBJECTIVE: Pseudo-images of three-dimensional eye movements captured on an infrared video oculogram can be translated onto a rotational expression around axial vector. This provides a subject's Listing's plane, which moves according to the head's orientation relative to gravity. Optokinetically induced changes in the cognitive gravitational reference frame will affect the context of Listing's plane. The purpose of this study was to estimate the effect of OKS on Listing's plane. METHODS: In this study, we presented vertical optokinetic visual stimulation with fixation targets, which are thought to induce pseudo-inclination of the head, and evaluated changes in the subjects' Listing's plane. RESULTS: We observed no stimulus-induced movement of Listing's plane that corresponded to the assumed pseudo-recognition of a change in verticality. On the other hand, we did observe vergence movement of Listing's plane (in the yaw plane), which corresponded to exposure to diminished and increased gravitational circumstance. In addition, the thickness of Listing's plane significantly increased with the load of each stimulation. CONCLUSION: Vertical OKS leads to a rotation of Listing's plane mainly around a vertical axis. This may represent false exhibition of central compensatory re-weighting with respect to inherent otoconial mass asymmetry resulting from the OKS-mediated loss of the gravity reference. In addition, a OKS-mediated thickening of Listing's plane suggests to us that confusing visual input can reduce the stability of the internal model, which would likely manifest itself as a thickening of Listing's plane. In other words, fluctuation between the build-up and drop-out of vection induced by optokinetic stimulation will cause a thickening of Listing's plane. The thickness of Listing's plane could be a novel clinical parameter for quantitatively evaluating static vestibular function and accuracy of the internal model.

Identification of pathogenesis-related microRNAs in hepatocellular carcinoma by expression profiling.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the liver. Since postoperative recurrence and intrahepatic metastases occur frequently, the postoperative 5-year survival rate is low. To investigate the molecular mechanisms of HCC progression, mRNA as well as microRNA (miRNA) expression levels have been profiled in various studies. However, no previous study has comprehensively compared the expression of miRNAs in HCC patients with various clinical features using the tumor and surrounding non-tumor tissues and normal liver samples. In this study, we profiled the expression of miRNAs in tumor and non-tumor tissues from 40 HCC patients with heterogeneous pathogenesis and 6 surrounding non-tumor tissues from patients with metastatic liver cancer. To identify miRNAs specific to each disease state, we comprehensively compared the expression of miRNAs in various combinations. The results indicate that the expression of many known as well as novel miRNAs was altered in patients with the hepatitis C virus infection compared with those with the hepatitis B virus and without any virus infection. The following miRNAs were downregulated in the tumor and non-tumor tissues, and thus could serve as novel biomarkers for chronic liver diseases: miR-18b*, miR-296-5p, miR-557, miR-581, miR-625*, miR-1228, miR-1249 and miR-2116*. Similarly, miR-129*, miR-146b-3p and miR-448 are novel candidates for HCC biomarkers regardless of virus infection.

Temporal change in IL-6 mRNA and protein expression produced by cyclic stretching of human pulmonary artery endothelial cells.

The time courses of interleukin (IL)-6 gene expression and protein production were examined in human pulmonary artery endothelial cells (HPAECs) subjected to cyclic stretching. IL-6 protein was increased even in cells without stretching. Fold changes determined by dividing the level of IL-6 protein in stretched cells by that in unstretched cells at the same sampling times indicated that IL-6 protein was increased by stretching. At least 1 h of stretching was necessary to elicit an increase of IL-6 protein, and the levels peaked at 3 h after the start of stretching. After withdrawal of stretching, there was no further increase of IL-6 protein. The expression levels of the IL-6 gene were significantly increased by stretching and peaked at 30 min after the start of stretching. The difference in the peak times of IL-6 gene and protein expression likely reflects the process of protein synthesis after the appearance of IL-6 mRNA.

Systems analysis of inflammatory bowel disease based on comprehensive gene information.

BACKGROUND: The rise of systems biology and availability of highly curated gene and molecular information resources has promoted a comprehensive approach to study disease as the cumulative deleterious function of a collection of individual genes and networks of molecules acting in concert. These "human disease networks" (HDN) have revealed novel candidate genes and pharmaceutical targets for many diseases and identified fundamental HDN features conserved across diseases. A network-based analysis is particularly vital for a study on polygenic diseases where many interactions between molecules should be simultaneously examined and elucidated. We employ a new knowledge driven HDN gene and molecular database systems approach to analyze Inflammatory Bowel Disease (IBD), whose pathogenesis remains largely unknown. METHODS AND RESULTS: Based on drug indications for IBD, we determined sibling diseases of mild and severe states of IBD. Approximately 1,000 genes associated with the sibling diseases were retrieved from four databases. After ranking the genes by the frequency of records in the databases, we obtained 250 and 253 genes highly associated with the mild and severe IBD states, respectively. We then calculated functional similarities of these genes with known drug targets and examined and presented their interactions as PPI networks. CONCLUSIONS: The results demonstrate that this knowledge-based systems approach, predicated on functionally similar genes important to sibling diseases is an effective method to identify important components of the IBD human disease network. Our approach elucidates a previously unknown biological distinction between mild and severe IBD states.

Loss of NKX3-1 as a potential marker for an increased risk of occult lymph node metastasis and poor prognosis in oral squamous cell carcinoma.

The prognosis of oral squamous cell carcinoma (OSCC) is significantly dependent on the existence of cervical lymph node metastasis (LNM), with the overall survival rate being much lower in patients with LNM. Primary causes and molecular mechanisms of LNM are still largely unclear. We hypothesized that factors related with cancer progress and/or prognosis in OSCC are revealed by genome-wide investigation of DNA copy number aberrations (CNAs). In order to find biomarkers for occult LNM of OSCC, we comprehensively investigated genomic DNAs from 60 OSCC patients using Affymetrix mapping arrays and statistically analyzed correlations between CNAs of genes and the presence of occult LNM in the patients. The genome-wide CNA study indicated significant correlations between the presence of occult LNM and CNAs of certain genes. Through a literature survey, we narrowed down the candidates and focused on loss of NKX3-1, which is a homeodomain-containing transcription factor. NKX3-1 is known as a tumor suppressor gene in prostate cancer but has never been reported in OSCC. Quantitative RT-PCR and immunohistochemistry (IHC) analyses also showed significantly lower expression of NKX3-1 in the cases with occult LNM, which was further validated by IHC analysis in independent cases. The survival analyses indicated that NKX3-1 loss is a significant risk factor to decrease the disease-free survival (DFS) and the overall survival (OS) rates. This is the first time that the significant association of NKX3-1 loss and occult LNM was indicated in OSCC. The present results suggest that loss of NKX3-1 may be a potential biomarker for occult LNM of OSCC.

Time course of the recovery of three-dimensional eye position in patients with acute cerebellitis.

Listing's plane is a construction derived from eye position and reflects gravitational orientation. The cerebellum plays a key role in orienting and integrating sensory input concerning gravity from visual, vestibular and proprioceptive apparatuses. This suggests that the thickness of Listing's plane could serve as a novel parameter for evaluating the accuracy of the constructed gravity-oriented internal model. We report a case with acute cerebellitis along with data on Listing's plane, calculated from consecutive infrared video-oculogram recordings. We found thickening of Listing's plane at the early stage of the disease, and a gradual reduction of the thickness into normal range in parallel with the recovery of the patient's posture and gate. Notably, clinical improvement of the patient's posture was delayed relative to the normalization of the thickness of Listing's plane. The thickness of Listing's plane reflects the stability of the cerebellar-mediated cognitive gravitational reference frame. This thickness value could serve as a parameter to quantitatively evaluate the function of the constructed internal model. Recovery from cerebellar ataxia (manifested as normalization of the thickness of Listing's plane) was followed by recovery of muscular strength lost during the period the patient was by his disease forced to assume a lying position.

Adaptive thresholds to detect differentially expressed genes in microarray data.

To detect changes in gene expression data from microarrays, a fixed threshold for fold difference is used widely. However, it is not always guaranteed that a threshold value which is appropriate for highly expressed genes is suitable for lowly expressed genes. In this study, aiming at detecting truly differentially expressed genes from a wide expression range, we proposed an adaptive threshold method (AT). The adaptive thresholds, which have different values for different expression levels, are calculated based on two measurements under the same condition. The sensitivity, specificity and false discovery rate (FDR) of AT were investigated by simulations. The sensitivity and specificity under various noise conditions were greater than 89.7% and 99.32%, respectively. The FDR was smaller than 0.27. These results demonstrated the reliability of the method.

Genome-wide integrative analysis revealed a correlation between lengths of copy number segments and corresponding gene expression profile.

Microarray analysis has been applied to comprehensively reveal the abnormalities of DNA copy number (CN) and gene expression in human cancer research during the last decade. These analyses have individually contributed to identify the genes associated with carcinogenesis, progression, metastasis of tumor cells and poor prognosis of cancer patients. However, it is known that the correlation between profiles of CN and gene expression does not highly correlate. Factors which determine the degree of correlation remain largely unexplained. To investigate one such factor, we performed trend analyses between the lengths of CN segments and corresponding gene expression profiles from microarray data in hepatocellular carcinoma (HCC) and colorectal carcinoma (CRC). Significant correlations were observed in CN gain of HCC and CRC (p<0.05). The trend of the CN loss showed a significant correlation in HCC although there was no correlation between the length of CN loss segments and gene expression in CRC. Our findings suggest that the influence of CN on gene expression highly depends on the length of CN region, especially in the case of CN gain. To the best of our knowledge, this is the first study describing the correlation between lengths of CNA segments and expression profiles of corresponding genes.

Adaptive threshold for detecting differentially expressed genes in microarray data - a simulation study to investigate its performance.

To detect changes in gene expression data from DNA microarrays, a fixed threshold value is used in various studies. However, it is not always guaranteed that a threshold value which is appropriate for highly expressed genes is suitable for genes with low expression. To address this issue, we have proposed adaptive threshold, which has different values for different expression levels. In this study, the performance of the adaptive threshold method was investigated through simulations. The sensitivity in various noise conditions was in a range between 72.7 and 100% while the specificity was better than 99% for all noise conditions. These results demonstrated the good performance of the proposed method.