A Bayesian Multivariate Functional Dynamic Linear Model

We present a Bayesian approach for modeling multivariate, dependent functional data. To account for the three dominant structural features in the data--functional, time dependent, and multivariate components--we extend hierarchical dynamic linear models for multivariate time series to the functional data setting. We also develop Bayesian spline theory in a more general constrained optimization framework. The proposed methods identify a time-invariant functional basis for the functional observations, which is smooth and interpretable, and can be made common across multivariate observations for additional information sharing. The Bayesian framework permits joint estimation of the model parameters, provides exact inference (up to MCMC error) on specific parameters, and allows generalized dependence structures. Sampling from the posterior distribution is accomplished with an efficient Gibbs sampling algorithm. We illustrate the proposed framework with two applications: (1) multi-economy yield curve data from the recent global recession, and (2) local field potential brain signals in rats, for which we develop a multivariate functional time series approach for multivariate time-frequency analysis. Supplementary materials, including R code and the multi-economy yield curve data, are available online

Spatiotemporal mixed modeling of multi-subject task fMRI via method of moments

Estimating spatiotemporal models for multi-subject fMRI is computationally challenging. We propose a mixed model for localization studies with spatial random effects and time-series errors. We develop method-of-moment estimators that leverage population and spatial information and are scalable to massive datasets. In simulations, subject-specific estimates of activation are considerably more accurate than the standard voxel-wise general linear model. Our mixed model also allows for valid population inference. We apply our model to cortical data from motor and theory of mind tasks from the Human Connectome Project (HCP). The proposed method results in subject-specific predictions that appear smoother and less noisy than those from the popular single-subject univariate approach. In particular, the regions of motor cortex associated with a left-hand finger-tapping task appear to be more clearly delineated. Subject-specific maps of activation from task fMRI are increasingly used in pre-surgical planning for tumor removal and in locating targets for transcranial magnetic stimulation. Our findings suggest that using spatial and population information is a promising avenue for improving clinical neuroimaging

Comparison of Vaginal Hysterectomy Techniques and Interventions for Benign Indications: A Systematic Review

OBJECTIVE: To create evidence-based clinical practice guidelines based on a systematic review of published literature regarding the risks and benefits of available preoperative, intraoperative, and postoperative technical steps and interventions at the time of vaginal hysterectomy for benign indications. DATA SOURCES: We systematically searched the literature to identify studies that compared technical steps or interventions during the preoperative, intraoperative, and postoperative periods surrounding vaginal hysterectomy. We searched MEDLINE, Cochrane Central Register of Controlled Trials, Health Technology Assessments, and ClinicalTrials.gov from their inception until April 10, 2016, using the MeSH term "Hysterectomy, Vaginal" and associated text words. We included comparative studies, single-group studies, and systematic reviews published in English. METHODS OF STUDY SELECTION: We double-screened 4,250 abstracts, identifying 60 eligible studies. Discrepancies were adjudicated by a third reviewer. We followed standard systematic review methodology and the Grades for Recommendation, Assessment, Development and Evaluation approach to evaluate the evidence and generate guideline recommendations. TABULATION, INTEGRATION, AND RESULTS: Because of limited literature, only 16 perioperative risks, technical steps, and interventions were identified: obesity, large uteri, prior surgery, gonadotropin-releasing hormone agonists, vaginal antisepsis, bilateral salpingo-oophorectomy, morcellation, apical closure, uterine sealers, hemostatic injectants, hot cone, retractor, cystoscopy, vaginal packing, bladder management, and accustimulation. We organized and reported these as four domains: patient selection, preoperative, intraoperative, and postoperative. We did not identify any patient characteristics precluding a vaginal approach; chlorhexidine or povidone is appropriate for vaginal antisepsis; vasopressin decreases blood loss by 130 cc; tissue-sealing devices decrease blood loss by 44 cc and operative time by 15 minutes with uncertain complication implications; vertical cuff closure results in 1-cm increased vaginal length; either peritoneum or epithelium can be used for colpotomy closure; and routine vaginal packing is not advised. CONCLUSION: Minimal data exist to guide surgeons with respect to planning and performing a vaginal hysterectomy. This study identifies available information and future areas for investigation

Anticipatory nausea in cyclical vomiting

BACKGROUND: Cyclical Vomiting Syndrome (CVS) is characterised by discrete, unexplained episodes of intense nausea and vomiting, and mainly affects children and adolescents. Comprehending Cyclical Vomiting Syndrome requires awareness of the severity of nausea experienced by patients. As a subjective symptom, nausea is easily overlooked, yet is the most distressing symptom for patients and causes many behavioural changes during attacks. CASE PRESENTATION: This first-hand account of one patient's experience of Cyclical Vomiting Syndrome shows how severe nausea contributed to the development of anticipatory nausea and vomiting (ANV), a conditioned response frequently observed in chemotherapy patients. This conditioning apparently worsened the course of the patient's disease. Anticipatory nausea and vomiting has not previously been recognised in Cyclical Vomiting Syndrome, however predictors of its occurrence in oncology patients indicate that it could complicate many cases. CONCLUSION: We suggest a model whereby untreated severe and prolonged nausea provokes anxiety about further cyclical vomiting attacks. This anxiety facilitates conditioning, thus increasing the range of triggers in a self-perpetuating manner. Effective management of the nausea-anxiety feedback loop can reduce the likelihood of anticipatory nausea and vomiting developing in other patients

The Case for Adaptive Neuromodulation to Treat Severe Intractable Mental Disorders

Mental disorders are a leading cause of disability worldwide, and available treatments have limited efficacy for severe cases unresponsive to conventional therapies. Neurosurgical interventions, such as lesioning procedures, have shown success in treating refractory cases of mental illness, but may have irreversible side effects. Neuromodulation therapies, specifically Deep Brain Stimulation (DBS), may offer similar therapeutic benefits using a reversible (explantable) and adjustable platform. Early DBS trials have been promising, however, pivotal clinical trials have failed to date. These failures may be attributed to targeting, patient selection, or the “open-loop” nature of DBS, where stimulation parameters are chosen ad hoc during infrequent visits to the clinician’s office that take place weeks to months apart. Further, the tonic continuous stimulation fails to address the dynamic nature of mental illness; symptoms often fluctuate over minutes to days. Additionally, stimulation-based interventions can cause undesirable effects if applied when not needed. A responsive, adaptive DBS (aDBS) system may improve efficacy by titrating stimulation parameters in response to neural signatures (i.e., biomarkers) related to symptoms and side effects. Here, we present rationale for the development of a responsive DBS system for treatment of refractory mental illness, detail a strategic approach for identification of electrophysiological and behavioral biomarkers of mental illness, and discuss opportunities for future technological developments that may harness aDBS to deliver improved therapy

Urbanisation generates multiple trait syndromes for terrestrial animal taxa worldwide

Cities can host significant biological diversity. Yet, urbanisation leads to the loss of habitats, species, and functional groups. Understanding how multiple taxa respond to urbanisation globally is essential to promote and conserve biodiversity in cities. Using a dataset encompassing six terrestrial faunal taxa (amphibians, bats, bees, birds, carabid beetles and reptiles) across 379 cities on 6 continents, we show that urbanisation produces taxon-specific changes in trait composition, with traits related to reproductive strategy showing the strongest response. Our findings suggest that urbanisation results in four trait syndromes (mobile generalists, site specialists, central place foragers, and mobile specialists), with resources associated with reproduction and diet likely driving patterns in traits associated with mobility and body size. Functional diversity measures showed varied responses, leading to shifts in trait space likely driven by critical resource distribution and abundance, and taxon-specific trait syndromes. Maximising opportunities to support taxa with different urban trait syndromes should be pivotal in conservation and management programmes within and among cities. This will reduce the likelihood of biotic homogenisation and helps ensure that urban environments have the capacity to respond to future challenges. These actions are critical to reframe the role of cities in global biodiversity loss.info:eu-repo/semantics/publishedVersio