Statistical aspects of omics data analysis using the random compound covariate

BACKGROUND: Dealing with high dimensional markers, such as gene expression data obtained using microarray chip technology or genomics studies, is a key challenge because the numbers of features greatly exceeds the number of biological samples. After selecting biologically relevant genes, how to summarize the expression of selected genes and then further build predicted model is an important issue in medical applications. One intuitive method of addressing this challenge assigns different weights to different features, subsequently combining this information into a single score, named the compound covariate. Investigators commonly employ this score to assess whether an association exists between the compound covariate and clinical outcomes adjusted for baseline covariates. However, we found that some clinical papers concerned with such analysis report bias p-values based on flawed compound covariate in their training data set. RESULTS: We correct this flaw in the analysis and we also propose treating the compound score as a random covariate, to achieve more appropriate results and significantly improve study power for survival outcomes. With this proposed method, we thoroughly assess the performance of two commonly used estimated gene weights through simulation studies. When the sample size is 100, and censoring rates are 50%, 30%, and 10%, power is increased by 10.6%, 3.5%, and 0.4%, respectively, by treating the compound score as a random covariate rather than a fixed covariate. Finally, we assess our proposed method using two publicly available microarray data sets. CONCLUSION: In this article, we correct this flaw in the analysis and the propose method, treating the compound score as a random covariate, can achieve more appropriate results and improve study power for survival outcomes

A Survey on the Status of Smart Healthcare from the Universal Village Perspective

This survey paper discusses the condition of smart healthcare implementation. It discusses the current healthcare problems and how smart healthcare technologies ease the problems. Our group, Universal Village, realizes that the integration and interaction between parties in a system will maximize the effectiveness and benefit for the system. Based on this idea, this paper considers the smart city system as a whole, and talks about how smart healthcare interacts with infrastructures and functions inside and outside of the smart healthcare field. Then, it analyzes how a more powerful integrated system can be built from the smart healthcare system. In the end, several case studies are listed. Based on our analysis and the case studies, this paper then ended with the future prospects of the smart healthcare.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Business Value of IT in Commercial Banks

Many banks have deployed information technology (IT) to serve customers more efficiency in diverse ways. In a competitive business environment, bank managers must simultaneously use multiple service channels to win customers and increase profit. Most prior research on IT investment in the banking industry has focused on the adoption of innovative IT-based service channels such as Internet banking, from customers’ perspective. In this research, we adopt the banks’ perspective to analyze the impact of IT on performance by simultaneously considering the traditional physical channel and alternative IT-based service channels. Our initial findings reveal contrasting strategic rationale supporting the use of ATM-based channel versus more recent Internet-based banking

COMPLEMENTARITY OF THE IMPACT OF ALTERNATIVE SERVICE CHANNELS ON BANK PERFORMANCE

Faced with intense competition, banks have deployed information technology (IT) to serve customers more efficiently and effectively in diverse ways. The challenge bank managers face is in utilizing alternative service channels to win customers and retain competitive advantages. This study investigates the impact of banks’ use of channel mix strategy. We show strong complementarities between traditional branch channel and IT-based self-service channels on performance. The value provided by a channel depends both on its own level of investment and investments in other channels. It can be misleading to examine channels independently or simply view each channel as a substitute for other channels. Even though different channels do substitute each other to some extent, migration of transactions from traditional channels to the IT-based channels may change customers’ overall demand such that it increases demand for all channels by transforming traditional channels to perform more value-added services or serve more profitable customers

Effects of different treatment frequencies of electromagnetic stimulation for urinary incontinence in women:study protocol for a randomized controlled trial

Background: Urinary incontinence is highly prevalent in women while pelvic floor muscle training is recommended as the first-line therapy. However, the exact treatment regimen is poorly understood. Also, patients with pelvic floor muscle damage may have decreased muscle proprioception and cannot contract their muscles properly. Other conservative treatments including electromagnetic stimulation are suggested by several guidelines. Thus, the present study aims to compare the effectiveness of electromagnetic stimulation combined with pelvic floor muscle training as a conjunct treatment for urinary incontinence and different treatment frequencies will be investigated.Methods/design: This is a randomized, controlled clinical trial. We will include 165 patients with urinary incontinence from the outpatient center. Participants who meet the inclusion criteria will be randomly allocated to three groups: the pelvic floor muscle training group (active control group), the low-frequency electromagnetic stimulation group (group 1), and the high-frequency electromagnetic stimulation group (group 2). Both group 1 and group 2 will receive ten sessions of electromagnetic stimulation. Group 1 will be treated twice per week for 5 weeks while group 2 will receive 10 days of continuous treatment. The primary outcome is the change in International Consultation on Incontinence Questionnaire–Short Form cores after the ten sessions of the treatment, while the secondary outcomes include a 3-day bladder diary, pelvic floor muscle function, pelvic organ prolapse quantification, and quality of life assessed by SF-12. All the measurements will be assessed at baseline, after the intervention, and after 3 months of follow-up.Discussion: The present trial is designed to investigate the effects of a conjunct physiotherapy program for urinary incontinence in women. We hypothesize that this strategy is more effective than pelvic floor muscle training alone, and high-frequency electromagnetic stimulation will be superior to the low-frequency magnetic stimulation group

Effects of epidural compression on stellate neurons and thalamocortical afferent fibers in the rat primary somatosensory cortex

A number of neurological disorders such as epidural hematoma can cause compression of cerebral cortex. We here tested the hypothesis that sustained compression of primary somatosensory cortex may affect stellate neurons and thalamocortical afferent (TCA) fibers. A rat model with barrel cortex subjected to bead epidural compression was used. Golgi‑Cox staining analyses showed the shrinkage of dendritic arbors and the stripping of dendritic spines of stellate neurons for at least 3 months post‑lesion. Anterograde tracing analyses exhibited a progressive decline of TCA fiber density in barrel field for 6 months post‑lesion. Due to the abrupt decrease of TCA fiber density at 3 days after compression, we further used electron microscopy to investigate the ultrastructure of TCA fibers at this time. Some TCA fiber terminal profiles with dissolved or darkened mitochondria and fewer synaptic vesicles were distorted and broken. Furthermore, the disruption of mitochondria and myelin sheath was observed in some myelinated TCA fibers. In addition, expressions of oxidative markers 3‑nitrotyrosine and 4‑hydroxynonenal were elevated in barrel field post‑lesion. Treatment of antioxidant ascorbic acid or apocynin was able to reverse the increase of oxidative stress and the decline of TCA fiber density, rather than the shrinkage of dendrites and the stripping of dendritic spines of stellate neurons post‑lesion. Together, these results indicate that sustained epidural compression of primary somatosensory cortex affects the TCA fibers and the dendrites of stellate neurons for a prolonged period. In addition, oxidative stress is responsible for the reduction of TCA fiber density in barrels rather than the shrinkage of dendrites and the stripping of dendritic spines of stellate neurons

Understanding the Impact of Image Quality and Distance of Objects to Object Detection Performance

Deep learning has made great strides for object detection in images. The detection accuracy and computational cost of object detection depend on the spatial resolution of an image, which may be constrained by both the camera and storage considerations. Compression is often achieved by reducing either spatial or amplitude resolution or, at times, both, both of which have well-known effects on performance. Detection accuracy also depends on the distance of the object of interest from the camera. Our work examines the impact of spatial and amplitude resolution, as well as object distance, on object detection accuracy and computational cost. We develop a resolution-adaptive variant of YOLOv5 (RA-YOLO), which varies the number of scales in the feature pyramid and detection head based on the spatial resolution of the input image. To train and evaluate this new method, we created a dataset of images with diverse spatial and amplitude resolutions by combining images from the TJU and Eurocity datasets and generating different resolutions by applying spatial resizing and compression. We first show that RA-YOLO achieves a good trade-off between detection accuracy and inference time over a large range of spatial resolutions. We then evaluate the impact of spatial and amplitude resolutions on object detection accuracy using the proposed RA-YOLO model. We demonstrate that the optimal spatial resolution that leads to the highest detection accuracy depends on the 'tolerated' image size. We further assess the impact of the distance of an object to the camera on the detection accuracy and show that higher spatial resolution enables a greater detection range. These results provide important guidelines for choosing the image spatial resolution and compression settings predicated on available bandwidth, storage, desired inference time, and/or desired detection range, in practical applications