Noise filtering and nonparametric analysis of microarray data underscores discriminating markers of oral, prostate, lung, ovarian and breast cancer

BACKGROUND: A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identify potential targets for drug development, and can aid in evaluating treatment efficacy and predicting patient outcome. Microarray technology has enabled marker discovery from human cells by permitting measurement of steady-state mRNA levels derived from thousands of genes. However many challenging and unresolved issues regarding the acquisition and analysis of microarray data remain, such as accounting for both experimental and biological noise, transcripts whose expression profiles are not normally distributed, guidelines for statistical assessment of false positive/negative rates and comparing data derived from different research groups. This study addresses these issues using Affymetrix HG-U95A and HG-U133 GeneChip data derived from different research groups. RESULTS: We present here a simple non parametric approach coupled with noise filtering to identify sets of genes differentially expressed between the normal and cancer states in oral, breast, lung, prostate and ovarian tumors. An important feature of this study is the ability to integrate data from different laboratories, improving the analytical power of the individual results. One of the most interesting findings is the down regulation of genes involved in tissue differentiation. CONCLUSIONS: This study presents the development and application of a noise model that suppresses noise, limits false positives in the results, and allows integration of results from individual studies derived from different research groups

Community-based benchmarking improves spike rate inference from two-photon calcium imaging data

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience

Inside-Out Regulation of ICAM-1 Dynamics in TNF-α-Activated Endothelium

Background: During transendothelial migration, leukocytes use adhesion molecules, such as ICAM-1, to adhere to the endothelium. ICAM-1 is a dynamic molecule that is localized in the apical membrane of the endothelium and clusters upon binding to leukocytes. However, not much is known about the regulation of ICAM-1 clustering and whether membrane dynamics are linked to the ability of ICAM-1 to cluster and bind leukocyte integrins. Therefore, we studied the dynamics of endothelial ICAM-1 under non-clustered and clustered conditions. Principal Findings: Detailed scanning electron and fluorescent microscopy showed that the apical surface of endothelial cells constitutively forms small filopodia-like protrusions that are positive for ICAM-1 and freely move within the lateral plane of the membrane. Clustering of ICAM-1, using anti-ICAM-1 antibody-coated beads, efficiently and rapidly recruits ICAM-1. Using fluorescence recovery after photo-bleaching (FRAP), we found that clustering increased the immobile fraction of ICAM-1, compared to non-clustered ICAM-1. This shift required the intracellular portion of ICAM-1. Moreover, biochemical assays showed that ICAM-1 clustering recruited beta-actin and filamin. Cytochalasin B, which interferes with actin polymerization, delayed the clustering of ICAM-1. In addition, we could show that cytochalasin B decreased the immobile fraction of clustered ICAM-1-GFP, but had no effect on non-clustered ICAM-1. Also, the motor protein myosin-II is recruited to ICAM-1 adhesion sites and its inhibition increased the immobile fraction of both non-clustered and clustered ICAM-1. Finally, blocking Rac1 activation, the formation of lipid rafts, myosin-II activity or actin polymerization, but not Src, reduced the adhesive function of ICAM-1, tested under physiological flow conditions. Conclusions: Together, these findings indicate that ICAM-1 clustering is regulated in an inside-out fashion through the actin cytoskeleton. Overall, these data indicate that signaling events within the endothelium are required for efficient ICAM-1-mediated leukocyte adhesio

An OBSL1-Cul7Fbxw8 Ubiquitin Ligase Signaling Mechanism Regulates Golgi Morphology and Dendrite Patterning

The elaboration of dendrites in neurons requires secretory trafficking through the Golgi apparatus, but the mechanisms that govern Golgi function in neuronal morphogenesis in the brain have remained largely unexplored. Here, we report that the E3 ubiquitin ligase Cul7Fbxw8 localizes to the Golgi complex in mammalian brain neurons. Inhibition of Cul7Fbxw8 by independent approaches including Fbxw8 knockdown reveals that Cul7Fbxw8 is selectively required for the growth and elaboration of dendrites but not axons in primary neurons and in the developing rat cerebellum in vivo. Inhibition of Cul7Fbxw8 also dramatically impairs the morphology of the Golgi complex, leading to deficient secretory trafficking in neurons. Using an immunoprecipitation/mass spectrometry screening approach, we also uncover the cytoskeletal adaptor protein OBSL1 as a critical regulator of Cul7Fbxw8 in Golgi morphogenesis and dendrite elaboration. OBSL1 forms a physical complex with the scaffold protein Cul7 and thereby localizes Cul7 at the Golgi apparatus. Accordingly, OBSL1 is required for the morphogenesis of the Golgi apparatus and the elaboration of dendrites. Finally, we identify the Golgi protein Grasp65 as a novel and physiologically relevant substrate of Cul7Fbxw8 in the control of Golgi and dendrite morphogenesis in neurons. Collectively, these findings define a novel OBSL1-regulated Cul7Fbxw8 ubiquitin signaling mechanism that orchestrates the morphogenesis of the Golgi apparatus and patterning of dendrites, with fundamental implications for our understanding of brain development

Cavernous Malformations of the Central Nervous System: An International Consensus Statement

Introduction: Cavernous malformations (CM) of the central nervous system constitute rare vascular lesions. They are usually asymptomatic, which has allowed their management to become quite debatable. Even when they become symptomatic their optimal mode and timing of treatment remains controversial. Research question: A consensus may navigate neurosurgeons through the decision-making process of selecting the optimal treatment for asymptomatic and symptomatic CMs. Material and methods: A 17-item questionnaire was developed to address controversial issues in relation to aspects of the treatment, surgical planning, optimal surgical strategy for specific age groups, the role of stereotactic radiosurgery, as well as a follow-up pattern. Consequently, a three-stage Delphi process was ran through 19 invited experts with the goal of reaching a consensus. The agreement rate for reaching a consensus was set at 70%. Results: A consensus for surgical intervention was reached on the importance of the patient’s age, symptomatology, and hemorrhagic recurrence; and the CM’s location and size. The employment of advanced MRI techniques is considered of value for surgical planning. Observation for asymptomatic eloquent or deep-seated CMs represents the commonest practice among our panel. Surgical resection is considered when a deep-seated CM becomes symptomatic or after a second bleeding episode. Asymptomatic, image-proven hemorrhages constituted no indication for surgical resection for our panelists. Consensus was also reached on not resecting any developmental venous anomalies, and on resecting the associated hemosiderin rim only in epilepsy cases. Discussion and conclusion: Our Delphi consensus provides an expert common practice for specific controversial issues of CM patient management

Quality indicators for patients with traumatic brain injury in European intensive care units

Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe

Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches