Baculovirus Autographa californica multiple nucleopolyhedrovirus (AcMNPV) replicates in both Spodoptera frugiperda Sf21 and Trichoplusia ni Tn368 cells, whereas AcMNPV defective in hcf-1 (host cell-factor 1) gene productively infects only Sf21 cells, indicating that HCF-1 is indispensable for the AcMNPV productive infection of Tn368 cells. Here, we demonstrated that HCF-1 protein transiently expressed in Tn368 cells promotes the DNA synthesis of Hyphantria cunea MNPV (HycuMNPV), Orygia pseudotsugata MNPV and Bombyx mori NPV, which are normally unable to replicate in Tn368 cells. We also demonstrated that a recombinant HycuMNPV harboring the hcf-1 gene successfully replicates in Tn368 cells, generating substantial yields of progeny viruses and polyhedra. These results indicate that HCF-1 encoded by AcMNPV is an essential viral factor for productive NPV infection of Tn368 cells. Taken together with the previous findings on HRF-1 (host range factor 1), the present results provide strong evidence that viral genes acquired through horizontal gene transfer play an important role in baculovirus evolution, serving to expand the host range of baculoviruses.

Cerebral amyloid angiopathy (CAA) is a small-vessel disease preferentially affecting posterior brain regions. Recent evidence has demonstrated the efficacy of functional MRI in detecting CAA-related neurovascular injury, however, it is unknown whether such perturbations are associated with changes in the hemodynamic response function (HRF). Here we estimated HRFs from two different brain regions from block design activation data, in light of recent findings demonstrating how block designs can accurately reflect HRF parameter estimates while maximizing signal detection. Patients with a diagnosis of probable CAA and healthy controls performed motor and visual stimulation tasks. Time-to-peak (TTP), full-width at half-maximum (FWHM), and area under the curve (AUC) of the estimated HRFs were compared between groups and to MRI features associated with CAA including cerebral microbleed (CMB) count. Motor HRFs in CAA patients showed significantly wider FWHM ( P = 0.006) and delayed TTP ( P = 0.03) compared to controls. In the patient group, visual HRF FWHM was positively associated with CMB count ( P = 0.03). These findings indicate that hemodynamic abnormalities in patients with CAA may be reflected in HRFs estimated from block designs across different brain regions. Moreover, visual FWHM may be linked to structural MR indications associated with CAA.

In an event-related functional MRI data analysis, an accurate and robust extraction of the hemodynamic response function (HRF) and its associated statistics (e.g., magnitude, width, and time to peak) is critical to infer quantitative information about the relative timing of the neuronal events in different brain regions. The aim of this paper is to develop a multiscale adaptive smoothing model (MASM) to accurately estimate HRFs pertaining to each stimulus sequence across all voxels. MASM explicitly accounts for both spatial and temporal smoothness information, while incorporating such information to adaptively estimate HRFs in the frequency domain. One simulation study and a real data set are used to demonstrate the methodology and examine its finite sample performance in HRF estimation, which confirms that MASM significantly outperforms the existing methods including the smooth finite impulse response model, the inverse logit model and the canonical HRF.

In this paper we present a novel wavelet-based Bayesian nonparametric regression model for the analysis of functional magnetic resonance imaging (fMRI) data. Our goal is to provide a joint analytical framework that allows to detect regions of the brain which exhibit neuronal activity in response to a stimulus and, simultaneously, infer the association, or clustering, of spatially remote voxels that exhibit fMRI time series with similar characteristics. We start by modeling the data with a hemodynamic response function (HRF) with a voxel-dependent shape parameter. We detect regions of the brain activated in response to a given stimulus by using mixture priors with a spike at zero on the coefficients of the regression model. We account for the complex spatial correlation structure of the brain by using a Markov random field (MRF) prior on the parameters guiding the selection of the activated voxels, therefore capturing correlation among nearby voxels. In order to infer association of the voxel time courses, we assume correlated errors, in particular long memory, and exploit the whitening properties of discrete wavelet transforms. Furthermore, we achieve clustering of the voxels by imposing a Dirichlet process (DP) prior on the parameters of the long memory process. For inference, we use Markov Chain Monte Carlo (MCMC) sampling techniques that combine Metropolis-Hastings schemes employed in Bayesian variable selection with sampling algorithms for nonparametric DP models. We explore the performance of the proposed model on simulated data, with both block- and event-related design, and on real fMRI data.

The blood oxygen level dependent (BOLD) signal, as measured using functional magnetic resonance imaging (fMRI), is widely used as a proxy for changes in neural activity in the brain. Physiological variables such as heart rate (HR) and respiratory variation (RV) affect the BOLD signal in a way that may interfere with the estimation and detection of true task-related neural activity. This interference is of particular concern when these variables themselves show task-related modulations. We first establish that a simple movement task reliably induces a change in HR but not RV. In group data, the effect of HR on the BOLD response was larger and more widespread throughout the brain than were the effects of RV or phase regressors. The inclusion of HR regressors, but not RV or phase regressors, had a small but reliable effect on the estimated hemodynamic response function (HRF) in M1 and the cerebellum. We next asked whether the inclusion of a nested set of physiological regressors combining phase, RV, and HR significantly improved the model fit in individual participants' data sets. There was a significant improvement from HR correction in M1 for the greatest number of participants, followed by RV and phase correction. These improvements were more modest in the cerebellum. These results indicate that accounting for task-related modulation of physiological variables can improve the detection and estimation of true neural effects of interest.

OBJECTIVE

To assess the macular microcirculation blood flow in patients after conventional surgery for rhegmatogenous retinal detachment (RRD) with Doppler laser scanning (HRF--Heidelberg retinal flowmeter).

METHODS

Thirty patients (13 males and 17 females) in age: 28-68 years, mean age: 58.7 years with unilateral RRD without macular involvement were included in a prospective study. According to the type of buckling procedure the patients were divided into 3 groups: I--encircling band (8 cases), II--encircling band with radial or circumferential buckling (12 cases), III--radial or circumferential buckling (10 cases). In all patients the macular blood flow was measured with Heidelberg retina flowmeter (HRF) before and 4 weeks after scleral buckling procedures. Control group consists of the fellow eyes.

RESULTS

At the baseline examination in a group of eyes with RRD the mean values of macular blood flow were significantly lower comparing to fellow eyes and reached respectively: 298.4 +/- 79.2 AU and 435.6 +/- 121.0 AU (p=0.001) and correlated with the extent of RRD (p<0.05). Four weeks after surgery eyes that underwent the buckling procedures showed the elevation of macular blood flow as compared to the baseline values (p=0.001), however they remain slightly lower as compared to fellow eyes. The macular microcirculation blood flow changes were not influenced by the type of scleral buckling (p=0.2).

CONCLUSIONS

In the eyes with rhegmatogenous retinal detachment without macular involvement the mean macular microcirculation blood flows were lower as compared to fellow eyes. Different buckling procedures for rhegmatogenous retinal detachment influence the macular blood flow, causing its improvement as compared to the preoperative status but they remain lower comparing to fellow eyes.

We present a new algorithm to estimate hemodynamic response function (HRF) and drift components of fMRI data in wavelet domain. The HRF is modeled by both parametric and nonparametric models. The functional Magnetic resonance Image (fMRI) noise is modeled as a fractional brownian motion (fBm). The HRF parameters are estimated in wavelet domain by exploiting the property that wavelet transforms with a sufficient number of vanishing moments decorrelates a fBm process. Using this property, the noise covariance matrix in wavelet domain can be assumed to be diagonal whose entries are estimated using the sample variance estimator at each scale. We study the influence of the sampling rate of fMRI time series and shape assumption of HRF on the estimation performance. Results are presented by adding synthetic HRFs on simulated and null fMRI data. We also compare these methods with an existing method,(1) where correlated fMRI noise is modeled by a second order polynomial functions.

A method of multiplexing holograms by rotating the material or, equivalently, the recording beams is described. Peristropic (Greek for rotation) multiplexing can be combined with other multiplexing methods to increase the storage density of holographic storage systems. Peristrophic multiplexing is experimentally demonstrated with Du Pont's HRF-150 photopolymer film. We multiplexed a total of 295 holograms in a 38-microm-thick photopolymer film by combining peristrophic multiplexing with angle multiplexing.

Horizontal root fractures (HRF) usually affect anterior teeth of male patients as a result of trauma. The consequences can be complex because of combined damage to different tissues, but it has been reported that root fractures undergo healing in majority cases. Diagnosis of HRF must be based on clinical findings, sensibility tests, and radiographic examination. The cone-beam computed tomography (CBCT) has already been proven to be superior among other radiographic modalities for diagnostic imaging of root fractures. However, CBCT in these cases needs to be used in a careful manner, and only when the radiation exposure should be justified by the potential diagnostic benefits and improvement of the treatment results. This case report describes a case of spontaneously healed horizontal root fracture with displacement of the fragments and discusses the usefulness of CBCT in the follow-up of root fractures cases.

The goal of most functional Magnetic Resonance Imaging (fMRI) analyses is to investigate neural activity. Many fMRI analysis methods assume that the temporal dynamics of the hemodynamic response function (HRF) to neural activation is separable from its spatial dynamics. Although there is empirical evidence that the HRF is more complex than suggested by space-time separable canonical HRF models, it is difficult to assess how much information about neural activity is lost when assuming space-time separability. In this study we directly test whether spatiotemporal variability in the HRF that is not captured by separable models contains information about neural signals. We predict intracranially measured neural activity from simultaneously recorded fMRI data using separable and non-separable spatiotemporal deconvolutions of voxel time series around the recording electrode. Our results show that abandoning the spatiotemporal separability assumption consistently improves the decoding accuracy of neural signals from fMRI data. We compare our findings with results from optical imaging and fMRI studies and discuss potential implications for classical fMRI analyses without invasive electrophysiological recordings.

Simultaneous recording of electroencephalography and functional magnetic resonance imaging (EEG-fMRI) has recently been applied for mapping the hemodynamic changes related to epileptic activity. The aim of this study is to compare the hemodynamic response function (HRF) to epileptic spikes in patients with focal cortical dysplasia (FCD) and those with hippocampal sclerosis (HS). In EEG-fMRI studies, the HRF represents the temporal evolution of blood oxygenation level-dependent signal changes. Several studies demonstrated that amplitude and latency of the HRF are variable in patients with epilepsy. However, the consistency of HRF parameters with underlying brain pathology is unknown. In this study, we examined 14 patients with FCD and 12 with unilateral HS selected from our EEG-fMRI database and compared the amplitude and latency of the HRF peak. We analyzed (1) HRFs in peak activation clusters, (2) HRFs in peak deactivation clusters, and (3) the maximum absolute responses within the EEG spike field, activation or deactivation. We found that the HRF peak amplitude in deactivation clusters was larger in the HS group than in the FCD when the deactivation occurred in default mode network (DMN) regions. This result suggests that spikes in patients with HS affect the DMN more strongly than those with FCD. However, if we focus on the maximum absolute t-value in the spike field, there is no significant difference between the two groups. The current study indicates that it is not necessary to use different HRF models for EEG-fMRI studies in patients with FCD and HS.

In functional magnetic resonance imaging (fMRI), the hemodynamic response function (HRF) reflects regulation of regional cerebral blood flow in response to neuronal activation. The HRF varies significantly between individuals. This study investigated the genetic contribution to individual variation in HRF using fMRI data from 125 monozygotic (MZ) and 149 dizygotic (DZ) twin pairs. The resemblance in amplitude, latency, and duration of the HRF in six regions in the frontal and parietal lobes was compared between MZ and DZ twin pairs. Heritability was estimated using an ACE (Additive genetic, Common environmental, and unique Environmental factors) model. The genetic influence on the temporal profile and amplitude of HRF was moderate to strong (24%-51%). The HRF may be used in the genetic analysis of diseases with a cerebrovascular etiology.

BACKGROUND

Big data is becoming ubiquitous in biology, and poses significant challenges in data analysis and interpretation. RNAi screening has become a workhorse of functional genomics, and has been applied, for example, to identify host factors involved in infection for a panel of different viruses. However, the analysis of data resulting from such screens is difficult, with often low overlap between hit lists, even when comparing screens targeting the same virus. This makes it a major challenge to select interesting candidates for further detailed, mechanistic experimental characterization.

RESULTS

To address this problem we propose an integrative bioinformatics pipeline that allows for a network based meta-analysis of viral high-throughput RNAi screens. Initially, we collate a human protein interaction network from various public repositories, which is then subjected to unsupervised clustering to determine functional modules. Modules that are significantly enriched with host dependency factors (HDFs) and/or host restriction factors (HRFs) are then filtered based on network topology and semantic similarity measures. Modules passing all these criteria are finally interpreted for their biological significance using enrichment analysis, and interesting candidate genes can be selected from the modules.

CONCLUSIONS

We apply our approach to seven screens targeting three different viruses, and compare results with other published meta-analyses of viral RNAi screens. We recover key hit genes, and identify additional candidates from the screens. While we demonstrate the application of the approach using viral RNAi data, the method is generally applicable to identify underlying mechanisms from hit lists derived from high-throughput experimental data, and to select a small number of most promising genes for further mechanistic studies.

OBJECTIVE

We sought to determine the predictive value of the PaO₂:FiO₂ ratio (PFR), both independently and in combination with the standard Rapid Shallow Breathing Index (RSBI), for successful extubations in patients with primary hypoxemic respiratory failure (HRF).

METHODS

A retrospective chart review of 154 patients with HRF requiring mechanical ventilation for ≥24 hours was performed. The primary outcome was reintubation within 48 hours.

RESULTS

142 (92%) patients were successfully extubated. Pre-extubation PFR and RSBI values among reintubated and successfully extubated patients were similar. The areas under the curve of the receiver operating characteristic curves using RSBI and PFR were .5 and .62, respectively. A PFR < 200 or RSBI ≥ 70 when the PFR was ≥200 indicated a higher risk of reintubation, with .7 sensitivity and .56 specificity (area under the curve, .69), using a classification and regression tree model.

CONCLUSIONS

Neither the PFR independently nor the PFR in combination with the RSBI in a classification and regression tree model accurately predicted successful extubation in patients with HRF.

Synchrony of brain activity over time describes the functional connectivity between brain regions but does not address the temporal component of this relationship. We propose a complementary method of analysis by introducing the width of cross-correlation curves between functional MRI (fMRI) time series as a metric of the relative duration of synchronous activity between brain regions, or "sustained connectivity". Using resting-state fMRI, cognitive, and demographics data from 1,003 subjects included in the Human Connectome Project, we find that sustained connectivity is a reproducible trait in individuals, heritable, more transient in females, and shows changes with age in early adulthood. Sustained connectivity in sensory brain regions is specifically associated with differences in processing speed across subjects, particularly in men. In contrast, traditional functional connectivity was correlated with a measure of episodic memory, but not with processing speed. Individual differences in hemodynamic response function (HRF) are closely approximated by sustained connectivity and width of the HRF is also correlated with processing speed across individuals, suggesting that variability in hemodynamic response may be influenced by transient versus sustained neural activity rather than simply differences in vascularity and signal transduction. Sustained connectivity may provide new opportunities to study brain dynamics in clinical populations.

OBJECTIVE

This study investigates whether subgroups of different health-related fitness (HrF) profiles exist among girls and boys with complex congenital heart disease (ConHD) and how these are associated with lifestyle behaviors.

METHODS

We measured the cardiorespiratory fitness, muscle strength, and body composition of 158 adolescents aged 13-16 years with previous surgery for a complex ConHD. Data on lifestyle behaviors were collected concomitantly between October 2010 and April 2013. A cluster analysis was conducted to identify profiles with similar HrF. For comparisons between clusters, multivariate analyses of covariance were used to test the differences in lifestyle behaviors.

RESULTS

Three distinct profiles were formed: (1) Robust (43, 27%; 20 girls and 23 boys); (2) Moderately Robust (85, 54%; 37 girls and 48 boys); and (3) Less robust (30, 19%; 9 girls and 21 boys). The participants in the Robust clusters reported leading a physically active lifestyle and participants in the Less robust cluster reported leading a sedentary lifestyle. Diagnoses were evenly distributed between clusters.

CONCLUSIONS

The cluster analysis attributed some of the variability in cardiorespiratory fitness among adolescents with complex ConHD to lifestyle behaviors and physical activity. Profiling of HrF offers a valuable new option in the management of person-centered health promotion.

OBJECTIVE

Health-related fitness (HRF) tests are valid predictors of self-reported mobility difficulties among high-functioning older adults. The aim of the present study was to identify optimal cut-off values for HRF tests predicting self-reported difficulties in walking 2 km (WD).

METHODS

Subjects were 55- to 69-year-old men and women who were free of WD at baseline. The HRF assessment in 1996 included seven test items, and postal questionnaires were used to assess occurrence of new WD in 2002. Analysis of covariance and receiver-operating characteristic analysis were used as statistical methods.

RESULTS

In a 1-km walk, the sensitivity and specificity at the optimal cut-off 10:15 (min:s) for men were 63% and 75%, and at the cut-off 10:47 for women 70% and 71%. In dynamic back extension, the sensitivity and specificity at the optimal cut-off 16.5 (repetitions) were 67% and 65% in men and 82% and 59% at cut-off 13.5 in women. Correspondingly, in backward walking, the sensitivity and specificity at the optimal cut-off 27.7 (seconds) were 65% and 69% in men and 74% and 61% at cutoff 35.0 in women.

CONCLUSIONS

The 1-km walk, dynamic back extension and backward walking tests had the best predictive value for WD. These tests, with identified cut-off values, can be used to screen individuals who are at increased risk of WD. Tests can also be used in physical activity counseling to target activity to those components of HRF that indicate poor fitness and are important for good walking ability.

BACKGROUND

Ventilation with low tidal volume and airway pressure results in a survival benefit in ARDS patients. Previous research suggests that avoiding mechanical ventilation altogether may be beneficial in some cases of respiratory failure. Our hypothesis was that low flow veno-venous extracorporeal CO2 removal (ECCO2R) enables maintenance of a lung protective ventilation strategy or awake spontaneous ventilation despite severe hypercapnic respiratory failure (HRF).

METHODS

Twenty patients with HRF were investigated while mechanically ventilated (N.=14) or breathing spontaneously close to respiratory exhaustion (N.=6). Low flow ECCO2R was performed using a hemoperfusion device with a polypropylene gas-exchanger.

RESULTS

Causes of HRF were severe ARDS (N.=11), COPD (N.=4), chronic lung transplant rejection (N.=3) and cystic fibrosis (N.=2). During the first 8h of ECCO2R, PaCO2 decreased from 10.6 (9.3-12.9) to 7.9 (7.3-9.3) kPa (P<0.001) and pH increased from 7.23 (7.09-7.40) to 7.36 (7.27-7.41) (P<0.05). Thereafter, steady state was achieved while maintaining lung protective tidal volume (4.7 (3.8-6.5) mL/kg) and peak ventilator pressure (28 (27-30) mbar at 24 h). During the first 48 h, thrombocyte count decreased by 52% (P<0.01), Fibrinogen by 38% (P<0.05). Intubation could be avoided in all spontaneously breathing patients. In 4/6 high blood flow extracorporeal circulation was required due to increased oxygen demand. 6/14 mechanically ventilated patients recovered from respiratory support.

CONCLUSIONS

Our results suggest that in mechanically ventilated patients with HRF, low flow ECCO2R supports the maintenance of lung protective tidal volume and peak ventilator pressure. In selected awake patients with acute HRF, it may be a novel treatment approach to avoid mechanical ventilation, hence preventing ventilator- and sedation-associated morbidity and mortality.

Deep venous thrombosis (DVT) and pulmonary embolism (PE) affect high-risk trauma patients (HRTP). Accurate incidence and clinical importance of DVT and PE in HRPT may be overstated. We performed a ten-year retrospective analysis of HRTP of the Pennsylvania Trauma Outcome Study. High-risk factors (HRF) included pelvic fracture (PFx), lower extremity fracture (LEFx), severe head injury (CHI) (AIS - head>> or =3), and spinal cord injury. HRF alone or in combination, age, Injury Severity Score (ISS), and Glasgow Coma Score (GCS) were examined for association with DVT/PE. A total of 73,419 HRTP were included: 1377 (1.9%) had DVT, 365 (0.5%) had PE. The incidence of DVT in level I trauma centers was 2.2 per cent and was 1.5 per cent in level II centers. The lowest incidence of DVT was 1.3 per cent for isolated LEFx; highest was 5.4% for combined PFx, LEFx, and CHI. Variables associated with DVT included age, ISS, and GCS (all P < 0.001). In logistic regression analysis, only ISS was consistently predictive for DVT and PE. Though increased during the past decade, the overall incidence of DVT in HRTP remains below 3 per cent. Only the combination of multiple injuries or an ISS >30 result in DVT incidence of>> or =5 per cent. We believe that current guidelines for screening for DVT may need to be reevaluated.

An accurate estimation of the hemodynamic response function (HRF) in functional magnetic resonance imaging (fMRI) is crucial for a precise spatial and temporal estimate of the underlying neuronal processes. Recent works have proposed non-parametric estimation of the HRF under the hypotheses of linearity and stationarity in time. Biological literature suggests, however, that response magnitude may vary with attention or ongoing activity. We therefore test a more flexible model that allows for the variation of the magnitude of the HRF with time in a maximum likelihood framework. Under this model, the magnitude of the HRF evoked by a single event may vary across occurrences of the same type of event. This model is tested against a simpler model with a fixed magnitude using information theory. We develop a standard EM algorithm to identify the event magnitudes and the HRF. We test this hypothesis on a series of 32 regions (4 ROIS on eight subjects) of interest and find that the more flexible model is better than the usual model in most cases. The important implications for the analysis of fMRI time series for event-related neuroimaging experiments are discussed.

The purpose of this study was to analyze four different cone-beam computed tomography (CBCT) protocols to identify horizontal root fractures (HRF) in endodontically treated teeth, with or without the presence of a metallic post. Thirty extracted single-rooted human premolars were treated endodontically. Afterwards, an observer induced a horizontal fracture in 15 teeth. Each tooth was inserted in an empty mandibular socket and submitted to a computed tomography scan taken with and without the metallic post. The acquisition followed four different protocols, with different fields of view (FOV) and voxel sizes, as follows: FOV 6 X 16 cm/0.2 mm voxel; FOV 6 X 16 cm/0.25 mm voxel; FOV 8 X 8 cm/0.2 mm voxel; FOV 8 X 8 cm/0.25 mm voxel. Two observers checked all the acquisitions within a two-week interval, and the values of sensitivity, specificity, accuracy and kappa were calculated. The sensitivity, specificity and accuracy values were better for the 8 X 8 cm/0.2 mm and 16 X 6 cm/0.25 mm protocols, ranging from 0.60 to 0.86 and 0.53 to 0.80, respectively. The intra- and interobserver concordance ranged from 0.65 to 0.72. The protocols where FOV and voxel were proportional showed better results. The 8 x 8 cm/0.2 mm protocol had the least interference from the metallic artifact. All four protocols showed a decline in values in the presence of the metallic artifact.

A cloned lymphoblast cell line, hRF-1, that secreted human monoclonal IgG4 rheumatoid factor autoantibody was produced by Epstein-Barr virus transformation of lymphocytes from rheumatoid arthritis synovium. The binding of hRF-1 rheumatoid factor to IgG globulins of different mammalian species was similar to the binding specificity of Staphylococcus aureus protein A (SpA) and to antibodies found in the sera from patients with rheumatoid arthritis. hRF-1 also had the same binding pattern to human IgG subclasses as SpA. Direct competition was observed between SpA and hRF-1 in binding IgG Fc. These results provide evidence for structural homology between a bacterial Fc receptor protein (SpA) and the monoclonal IgG rheumatoid factor.