Investigating microstructural variation in the human hippocampus using non-negative matrix factorization

In this work we use non-negative matrix factorization to identify patterns of microstructural variance in the human hippocampus. We utilize high-resolution structural and diffusion magnetic resonance imaging data from the Human Connectome Project to query hippocampus microstructure on a multivariate, voxelwise basis. Application of non-negative matrix factorization identifies spatial components (clusters of voxels sharing similar covariance patterns), as well as subject weightings (individual variance across hippocampus microstructure). By assessing the stability of spatial components as well as the accuracy of factorization, we identified 4 distinct microstructural components. Furthermore, we quantified the benefit of using multiple microstructural metrics by demonstrating that using three microstructural metrics (T1-weighted/T2-weighted signal, mean diffusivity and fractional anisotropy) produced more stable spatial components than when assessing metrics individually. Finally, we related individual subject weightings to demographic and behavioural measures using a partial least squares analysis. Through this approach we identified interpretable relationships between hippocampus microstructure and demographic and behavioural measures. Taken together, our work suggests non-negative matrix factorization as a spatially specific analytical approach for neuroimaging studies and advocates for the use of multiple metrics for data-driven component analyses

Measuring access: how accurate are patient-reported waiting times?

Introduction: A national audit of waiting times in England’s genitourinary medicine clinics measures patient access. Data are collected by patient questionnaires, which rely upon patients’ recollection of first contact with health services, often several days previously. The aim of this study was to assess the accuracy of patient-reported waiting times. Methods: Data on true waiting times were collected at the time of patient booking over a three-week period and compared with patient-reported data collected upon clinic attendance. Factors contributing to patient inaccuracy were explored. Results: Of 341 patients providing initial data, 255 attended; 207 as appointments and 48 ‘walk-in’. The accuracy of patient-reported waiting times overall was 52% (133/255). 85% of patients (216/255) correctly identified themselves as seen within or outside of 48 hours. 17% of patients (17/103) seen within 48 hours reported a longer waiting period, whereas 20% of patients (22/108) reporting waits under 48 hours were seen outside that period. Men were more likely to overestimate their waiting time (10.4% versus 3.1% p<0.02). The sensitivity of patient-completed questionnaires as a tool for assessing waiting times of less than 48 hours was 83.5%. The specificity and positive predictive value were 85.5% and 79.6%, respectively. Conclusion: The overall accuracy of patient reported waiting times was poor. Although nearly one in six patients misclassified themselves as being seen within or outside of 48 hours, given the under and overreporting rates observed, the overall impact on Health Protection Agency waiting time data is likely to be limited

A miniature UV-VIS spectrometer for the surface of Mars

A miniature spectrometer is in the process of development for a future Mars mission, to measure the UV-VIS spectrum encountered at the martian surface. With an intended mass of ~100 g, the spectrometer is planned as part of the ESA ExoMars mission

Impact of symptom burden and health‐related quality of life (HRQOL) on esophageal motor diagnoses

BackgroundHigh‐resolution manometry (HRM) categorizes esophageal motor processes into specific Chicago Classification (CC) diagnoses, but the clinical impact of these motor diagnoses on symptom burden remain unclear.MethodsTwo hundred and eleven subjects (56.8±1.0 years, 66.8% F) completed symptom questionnaires (GERDQ, Mayo dysphagia questionnaire [MDQ], visceral sensitivity index, short‐form 36, dominant symptom index, and global symptom severity [GSS] on a 100‐mm visual analog scale) prior to HRM. Subjects were stratified according to CC v3.0 and by dominant presenting symptom; contraction wave abnormalities (CWA) were evaluated within “normal” CC. Symptom burden, impact of diagnoses, and HRQOL were compared within and between cohorts.Key ResultsMajor motor disorders had highest global symptom burden (P=.02), “normal” had lowest (P<.01). Dysphagia (MDQ) was highest with esophageal outflow obstruction (P=.02), but reflux symptoms (GERDQ) were similar in CC cohorts (P=ns). Absent contractility aligned best with minor motor disorders. Consequently, pathophysiologic categorization into outflow obstruction, hypermotility, and hypomotility resulted in a gradient of decreasing dysphagia and increasing reflux burden (P<.05 across groups); GSS (P=.05) was highest with hypomotility and lowest with “normal” (P=.002). Within the “normal” cohort, 33.3% had CWA; this subgroup had symptom burden similar to hypermotility. Upon stratification by symptoms, symptom burden (GSS, MDQ, HRQOL) was most profound with dysphagia.Conclusions and InferencesChicago Classification v3.0 diagnoses identify subjects with highest symptom burden, but pathophysiologic categorization may allow better stratification by symptom type and burden. Contraction wave abnormalities are clinically relevant and different from true normal motor function. Transit symptoms have highest yield for a motor diagnosis.The interrelationship between esophageal symptom characteristics, symptom burden, and motor diagnoses (Chicago Classification v 3.0) were further studied by obtaining validated self‐report questionnaires in 211 patients undergoing esophageal high‐resolution manometry (HRM). Chicago Classification diagnoses (outflow obstruction, major disorders) were associated with the highest symptom burden. Symptom characteristics were best characterized by pathophysiologic categorization of motor disorders into outflow obstruction, hypermotility disorders, and hypomotility disorders. Contraction wave abnormalities in patients without a motor disorder (according to Chicago Classification) had distinct symptom characteristics and symptom burden that aligned best with hypermotility disorders.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136428/1/nmo12970_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136428/2/nmo12970.pd

The Distribution of High Redshift Galaxy Colors: Line of Sight Variations in Neutral Hydrogen Absorption

We model, via Monte Carlo simulations, the distribution of observed U-B, B-V, V-I galaxy colors in the range 1.75<z<5 caused by variations in the line-of-sight opacity due to neutral hydrogen (HI). We also include HI internal to the source galaxies. Even without internal HI absorption, comparison of the distribution of simulated colors to the analytic approximations of Madau (1995) and Madau et al (1996) reveals systematically different mean colors and scatter. Differences arise in part because we use more realistic distributions of column densities and Doppler parameters. However, there are also mathematical problems of applying mean and standard deviation opacities, and such application yields unphysical results. These problems are corrected using our Monte Carlo approach. Including HI absorption internal to the galaxies generaly diminishes the scatter in the observed colors at a given redshift, but for redshifts of interest this diminution only occurs in the colors using the bluest band-pass. Internal column densities < 10^17 cm^2 do not effect the observed colors, while column densities > 10^18 cm^2 yield a limiting distribution of high redshift galaxy colors. As one application of our analysis, we consider the sample completeness as a function of redshift for a single spectral energy distribution (SED) given the multi-color selection boundaries for the Hubble Deep Field proposed by Madau et al (1996). We argue that the only correct procedure for estimating the z>3 galaxy luminosity function from color-selected samples is to measure the (observed) distribution of redshifts and intrinsic SED types, and then consider the variation in color for each SED and redshift. A similar argument applies to the estimation of the luminosity function of color-selected, high redshift QSOs.Comment: accepted for publication in ApJ; 25 pages text, 14 embedded figure

A survey on security issues and solutions at different layers of Cloud computing

Cloud computing offers scalable on-demand services to consumers with greater flexibility and lesser infrastructure investment. Since Cloud services are delivered using classical network protocols and formats over the Internet, implicit vulnerabilities existing in these protocols as well as threats introduced by newer architectures raise many security and privacy concerns. In this paper, we survey the factors affecting Cloud computing adoption, vulnerabilities and attacks, and identify relevant solution directives to strengthen security and privacy in the Cloud environment