A variety of mediators are involved in the pathophysiology of a number of clinical conditions. Among them histamine-releasing factors (HRF) act as secretagogue for basophils and mast cells to cause cell degranulation and histamine release. Studies on the kinetics of HRF production by activated mononuclear cells (MNC) have suggested an active synthesis of this cytokine. Using a [35S]-metabolic cell labeling method, we first analyzed the capacity of MNC from patients with allergic rhinitis to ragweed to actively synthesize HRF. We then found that stimulation of MNC with allergen promoted a synthesis of large quantities of proteins, including a protein of about 30 kDa. Secondly, we developed a method for the enrichment of HRF molecules from crude supernatants of ragweed-stimulated MNC using ion exchange and gel filtration chromatography. We observed that the yield of HRF activity is seen just before the chymotrypsinogen marker. The estimated molecular weight was 30-35 kDa.

The blood oxygen-level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal depends on an interplay of cerebral blood flow (CBF), oxygen metabolism, and cerebral blood volume. Despite wide usage of BOLD fMRI, it is not clear how these physiological components create the BOLD signal. Here, baseline CBF and its dynamics evoked by a brief stimulus (2 s) in human visual cortex were measured at 3T. We found a stereotypical CBF response: immediate increase, rising to a peak a few second after the stimulus, followed by a significant undershoot. The BOLD hemodynamic response function (HRF) was also measured in the same session. Strong correlations between HRF and CBF peak responses indicate that the flow responses evoked by neural activation in nearby gray matter drive the early HRF. Remarkably, peak CBF and HRF were also strongly modulated by baseline perfusion. The CBF undershoot was reliable and significantly correlated with the HRF undershoot. However, late-time dynamics of the HRF and CBF suggest that oxygen metabolism can also contribute to the HRF undershoot. Combined measurement of the CBF and HRF for brief neural activation is a useful tool to understand the temporal dynamics of neurovascular and neurometabolic coupling.

OBJECTIVE

The objective of this study was to investigate whether previously reported early blood oxygen level dependent (BOLD) changes in epilepsy could occur as a result of the modelling techniques rather than physiological changes.

METHODS

EEG-fMRI data were analysed from seven patients with focal epilepsy, six control subjects undergoing a visual experiment, in addition to simulations. In six separate analyses the event timing was shifted by either -9,-6,-3,+3,+6 or +9 s relative to the onset of the interictal epileptiform discharge (IED) or stimulus.

RESULTS

The visual dataset and simulations demonstrated an overlap between modelled haemodynamic response function (HRF) at event onset and at ± 3 s relative to onset, which diminished at ± 6s. Pre-spike analysis at -6s improved concordance with the assumed IED generating lobe relative to the standard HRF in 43% of patients.

CONCLUSIONS

The visual and simulated dataset findings indicate a form of "temporal bleeding", an overlap between the modelled HRF at time 0 and at ± 3s which attenuated at ± 6s. Pre-spike analysis at -6s may improve concordance.

CONCLUSIONS

This form of analysis should be performed at 6s prior to onset of IED to minimise temporal bleeding effect. The results support the presence of relevant BOLD responses occurring prior to IEDs.

Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG-fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG-fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG-fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.

Keywords: BOLD response; EEG-fMRI; IED; epilepsy; epileptic foci; localization; seizure onset zone.

In this experimental study, particulate matter (PM) characterizations of different low-temperature combustion (LTC) strategies have been compared with conventional compression ignition (CI) combustion for finding out a sustainable and cleaner transport solution. LTC strategies included premixed charge compression ignition (PCCI) and reactivity-controlled compression ignition (RCCI) combustion. Particulate sampling and characterization were carried out in a single-cylinder diesel engine. All engine tests were performed at 1, 2, 3, 4 bar brake mean effective pressure (BMEP) at 1500 rpm. CI and PCCI combustion experiments were performed using mineral diesel as the test fuel. However, mineral diesel and methanol were used as high reactivity fuel (HRF) and low reactivity fuel (LRF), respectively in the RCCI combustion strategy. For all combustion strategies, fuel injection pressure (FIP) was kept constant at 500 bar. However, the number of injections and start of injection (SoI) timings were varied to optimize the engine performance. Results showed that the RCCI combustion strategy emitted a relatively lower concentration of particles than the other two strategies (PCCI and CI). A relatively higher number concentration of accumulation mode particles (AMP) compared to nucleation mode particles (NMP) in the exhaust of the RCCI combustion strategy was an important finding of this study. Number-size and mass-size distributions of particles emitted from different strategies also exhibited the dominant concentration of particles in the CI combustion strategy. PM bound trace metal analysis was yet another critical aspect of this study, which showed that both RCCI and PCCI strategies emitted a relatively lower concentration of trace metals than the conventional CI combustion strategy. Parametric analysis of different PM characteristics and NOx-PM trade-off analysis also demonstrated the importance of LTC strategies over the conventional CI combustion strategy. Overall, this study demonstrated that all LTC strategies could be used for PM and NOx reduction; however, the RCCI combustion strategy was more dominant in NOx and PM reduction, in addition to having an excellent capability of using alternative fuel in the quest for developing sustainable transport solution.

Keywords: Conventional compression ignition; Particulates; Premixed charged compression ignition; Reactivity-controlled compression ignition; Trace metal.

Previous work investigated a range of spatio-temporal constraints for fMRI data analysis to provide robust detection of neural activation. We present a mixture-based method for the spatio-temporal modelling of fMRI data. This approach assumes that fMRI time series are generated by a probabilistic superposition of a small set of spatio-temporal prototypes (mixture components). Each prototype comprises a temporal model that explains fMRI signals on a single voxel and the model's "region of influence" through a spatial prior over the voxel space. As the key ingredient of our temporal model, the Hidden Process Model (HPM) framework proposed in Hutchinson et al. (2009) is adopted to infer the overlapping cognitive processes triggered by stimuli. Unlike the original HPM framework, we use a parametric model of Haemodynamic Response Function (HRF) so that biological constraints are naturally incorporated in the HRF estimation. The spatial priors are defined in terms of a parameterised distribution. Thus, the total number of parameters in the model does not depend on the number of voxels. The resulting model provides a conceptually principled and computationally efficient approach to identify spatio-temporal patterns of neural activation from fMRI data, in contrast to most conventional approaches in the literature focusing on the detection of spatial patterns. We first verify the proposed model in a controlled experimental setting using synthetic data. The model is further validated on real fMRI data obtained from a rapid event-related visual recognition experiment (Mayhew et al., 2012). Our model enables us to evaluate in a principled manner the variability of neural activations within individual regions of interest (ROIs). The results strongly suggest that, compared with occipitotemporal regions, the frontal ones are less homogeneous, requiring two HPM prototypes per region. Despite the rapid event-related experimental design, the model is capable of disentangling the perceptual judgement and motor response processes that are both activated in the frontal ROIs. Spatio-temporal heterogeneity in the frontal regions seems to be associated with diverse dynamic localizations of the two hidden processes in different subregions of frontal ROIs.

We have developed a novel, computer-assisted operation method for minimal-invasive total hip replacement (THR) following the concept of "femur first/combined anteversion," which incorporates various aspects of performing a functional optimization of the prosthetic stem and cup position (CAS FF). The purpose of this study is to assess whether the hip joint reaction forces and patient's gait parameters are being improved by CAS FF in relation to conventional THR (CON). We enrolled 60 patients (28 CAS FF/32 CON) and invited them for gait analysis at three time points (preoperatively, postop six months, and postop 12 months). Data retrieved from gait analysis was processed using patient-specific musculoskeletal models. The target parameters were hip reaction force magnitude (hrf), symmetries, and orientation with respect to the cup. Hrf in the CAS FF group were closer to a young healthy normal. Phase-shift symmetry showed an increase in the CAS FF group. Hrf orientation in the CAS FF group was closer to optimum, though no edge or rim-loading occurred in the CON group as well. The CAS FF group showed an improved hrf orientation in an early stage and a trend to an improved long-term outcome.

Foot strike patterns influence the running efficiency and may be an injury risk. However, differences in the leg stiffness between runners with habitual forefoot (hFFS) and habitual rearfoot (hRFS) strike patterns remain unclear. This study aimed at determining the differences in the stiffness, associated loading rate, and kinematic performance between runners with hFFS and hRFS during running. Kinematic and kinetic data were collected amongst 39 runners with hFFS and 39 runners with hRFS running at speed of 3.3 m/s, leg stiffness (Kleg), and vertical stiffness (Kvert), and impact loads were calculated. Results found that runners with hFFS had greater Kleg (P = 0.010, Cohen's d = 0.60), greater peak vertical ground reaction force (vGRF) (P = 0.040, Cohen's d = 0.47), shorter contact time(t _c ) (P < 0.001, Cohen's d = 0.85), and smaller maximum leg compression (ΔL ) (P = 0.002, Cohen's d = 0.72) compared with their hRFS counterparts. Runners with hFFS had lower impact peak (IP) (P < 0.001, Cohen's d = 1.65), vertical average loading rate (VALR) (P < 0.001, Cohen's d = 1.20), and vertical instantaneous loading rate (VILR) (P < 0.001, Cohen's d = 1.14) compared with runners with hRFS. Runners with hFFS landed with a plantar flexed ankle, whereas runners with hRFS landed with a dorsiflexed ankle (P < 0.001, Cohen's d = 3.35). Runners with hFFS also exhibited more flexed hip (P = 0.020, Cohen's d = 0.61) and knee (P < 0.001, Cohen's d = 1.15) than runners with hRFS at initial contact. These results might indicate that runners with hFFS were associated with better running economy through the transmission of elastic energy.

Histamine releasing factor/translationally controlled tumor protein (HRF/TCTP) stimulates cancer progression and allergic responses, but the role of HRF/TCTP in rheumatoid arthritis (RA) remains undefined. In this study, we explored the pathogenic significance of HRF/TCTP and evaluated the therapeutic effects of HRF/TCTP blockade in RA. HRF/TCTP transgenic (TG) and knockdown (KD) mice with collagen-induced arthritis (CIA) were used to determine the experimental phenotypes of RA. HRF/TCTP levels in the sera of RA patients were measured and compared to those from patients with osteoarthritis (OA), ankylosing spondylitis, Behçet's disease, and healthy controls. HRF/TCTP expression was also assessed in the synovium and fibroblast-like synoviocytes (FLSs) obtained from RA or OA patients. Finally, we assessed the effects of HRF/TCTP and dimerized HRF/TCTP-binding peptide-2 (dTBP2), an HRF/TCTP inhibitor, in RA-FLSs and CIA mice. Our clinical, radiological, histological, and biochemical analyses indicate that inflammatory responses and joint destruction were increased in HRF/TCTP TG mice and decreased in KD mice compared to wild-type littermates. HRF/TCTP levels in the sera, synovial fluid, synovium, and FLSs were higher in patients with RA than in control groups. Serum levels of HRF/TCTP correlated well with RA disease activity. The tumor-like aggressiveness of RA-FLSs was exacerbated by HRF/TCTP stimulation and ameliorated by dTBP2 treatment. dTBP2 exerted protective and therapeutic effects in CIA mice and had no detrimental effects in a murine tuberculosis model. Our results indicate that HRF/TCTP is a novel biomarker and therapeutic target for the diagnosis and treatment of RA.

In this paper, we used time-domain functional near infrared spectroscopy (TD-fNIRS) to evaluate the haemodynamic response function (HRF) in the occipital cortex following visual stimulation in glaucomatous eyes as compared to healthy eyes. A total of 98 subjects were enrolled in the study and clinically classified as healthy subjects, glaucoma patients (primary open-angle glaucoma) and mixed subjects (i.e. with a different classification for the two eyes). After quality check data were used from HRF of 73 healthy and 62 glaucomatous eyes. The amplitudes of the oxygenated and deoxygenated haemoglobin concentrations, together with their latencies with respect to the stimulus onset, were estimated by fitting their time course with a canonical HRF. Statistical analysis showed that the amplitudes of both haemodynamic parameters show a significant association with the pathology and a significant discriminating ability, while no significant result was found for latencies. Overall, our findings together with the ease of use and noninvasiveness of TD-NIRS, make this technique a promising candidate as a supporting tool for a better evaluation of the glaucoma pathology.

Recent developments in fMRI acquisition techniques now enable fast sampling with whole-brain coverage, suggesting fMRI can be used to track changes in neural activity at increasingly rapid timescales. When images are acquired at fast rates, the limiting factor for fMRI temporal resolution is the speed of the hemodynamic response. Given that HRFs may vary substantially in subcortical structures, characterizing the speed of subcortical hemodynamic responses, and how the hemodynamic response shape changes with stimulus duration (i.e. the hemodynamic nonlinearity), is needed for designing and interpreting fast fMRI studies of these regions. We studied the temporal properties and nonlinearities of the hemodynamic response function (HRF) across the human subcortical visual system, imaging superior colliculus (SC), lateral geniculate nucleus of the thalamus (LGN) and primary visual cortex (V1) with high spatiotemporal resolution 7 Tesla fMRI. By presenting stimuli of varying durations, we mapped the timing and nonlinearity of hemodynamic responses in these structures at high spatiotemporal resolution. We found that the hemodynamic response is consistently faster and narrower in subcortical structures than in cortex. However, the nonlinearity in LGN is similar to that in cortex, with shorter duration stimuli eliciting larger and faster responses than would have been predicted by a linear model. Using oscillatory visual stimuli, we tested the frequency response in LGN and found that its BOLD response tracked high-frequency (0.5 Hz) oscillations. The LGN response magnitudes were comparable to V1, allowing oscillatory BOLD signals to be detected in LGN despite the small size of this structure. These results suggest that the increase in the speed and amplitude of the hemodynamic response when neural activity is brief may be the key physiological driver of fast fMRI signals, enabling detection of high-frequency oscillations with fMRI. We conclude that subcortical visual structures exhibit fast and nonlinear hemodynamic responses, and that these dynamics enable detection of fast BOLD signals even within small deep brain structures when imaging is performed at ultra-high field.

Traditional knowledge guides the use of plants for restricted therapeutic indications, but their pharmacological actions may be found beyond their ethnic therapeutic indications employing emerging computational tools. In this context, the present study was envisaged to explore the novel pharmacological effect of Achyranthes aspera (A. aspera) using PASS and PharmaExpert software tools. Based on the predicted mechanisms of the antidepressant effect for all analysed phytoconstituents of A. aspera, one may suggest its significant antidepressant action. The possible mechanism of this novel pharmacological effect is the enhancement of serotonin release, in particular caused by hexatriacontane. Therefore, pharmacological validation of the methanolic extract, hexatriacontane rich (HRF) and hexatriacontane lacking fraction (HLF) of A. aspera was carried out using the Forced Swimming Test and Tail suspension test in mice. The cortical and hippocampal monoamine and their metabolite levels were measured using high performance liquid chromatography (HPLC). A. aspera methanolic extract, HRF treatments showed a significant antidepressant effect comparable to imipramine. Further, the corresponding surge in cortical and hippocampal monoamine and their metabolite levels was also observed with these treatments. In conclusion, A. aspera has shown a significant antidepressant effect, possibly due to hexatriacontane, by raising monoamine levels.

The BOLD fMRI response in the cortex is often assumed to reflect changes in excitatory neural activity. However, the contribution of inhibitory neurons to BOLD fMRI is unclear. Here, the role of inhibitory and excitatory activity was examined using multimodal approaches: electrophysiological recording, 15.2 T fMRI, optical intrinsic signal imaging, and modeling. Inhibitory and excitatory neuronal activity in the somatosensory cortex were selectively modulated by 20-s optogenetic stimulation of VGAT-ChR2 and CaMKII-ChR2 mice, respectively. Somatosensory stimulation and optogenetic stimulation of excitatory neurons induced positive BOLD responses in the somatosensory network, whereas stimulation of inhibitory neurons produced biphasic responses at the stimulation site, initial positive and later negative BOLD signals, and negative BOLD responses at downstream sites. When the stimulation duration was reduced to 5 s, the hemodynamic response of VGAT-ChR2 mice to optogenetic stimulation was only positive. Lastly, modeling performed from neuronal and hemodynamic data shows that the hemodynamic response function (HRF) of excitatory neurons is similar across different conditions, whereas the HRF of inhibitory neurons is highly sensitive to stimulation frequency and peaks earlier than that of excitatory neurons. Our study provides insights into the neurovascular coupling of excitatory and inhibitory neurons and the interpretation of BOLD fMRI signals.

Keywords: BOLD; excitatory neurons; inhibitory neurons; neurovascular coupling; optogenetic fMRI.

This study investigates the role of Perceived Athletic Competence (PAC) and Health-Related Fitness (HRF) in mediating the reciprocal relationship between Motor Competence (MC) and Physical Activity (PA) during the transition from primary to secondary school. MC, PA, PAC and HRF were measured in 224 participants (baseline age 12.26 ± .037 years; 51% female) in final year of primary school and one year later in first year of secondary school. Path analysis in AMOS 23 was used to test the mediating influence of PAC and HRF on the MC-PA relationship. Fit indices showed that, in both directions, HRF and PAC mediated the relationship between MC and PA (PA predicting MC; χ2 = 3.91, p = .272, CFI = .99, RMSEA = .04. MC predicting PA: χ2 = 6.46, p = .167, CFI = .99, RMSEA = .04). Pathways were stronger through HRF than through PAC, indicating that HRF is the more substantial mediator of the MC-PA relationship during the school transition. Pathways were stronger in the direction of PA predicting MC than in the reverse direction. Interventions seeking to influence PA and MC across the school transition should focus on HRF as it is a primary mediator of the MC-PA relationship.

The purposes of the study were: (1) to investigate the associations between fundamental motor skills (FMS), health-related fitness (HRF) and physical activity (PA) during middle childhood; and (2) to examine whether HRF serves as a mediator in these pathways. The participants were 342 children (156 girls; Mage = 8.40, SD = 0.50) recruited in Texas. Children's FMS (locomotor and ball skills) were assessed. School-based PA that included light, moderate, and vigorous PA was captured by accelerometers. The FITNESSGRAM battery was used to measure children's HRF, including body composition, cardiorespiratory fitness, and muscular fitness. Structural equation models were used to evaluate two proposed models (model-1 = FMS»HRF»PA; model-2 = PA»HRF»FMS). Both locomotor and ball skills were associated with all components of HRF (p < 0.01), but not PA. The SEM analyses supported associations between FMS, HRF and PA, with sound goodness-of-fit indices: (1) model-1: CFI = 0.95; RMSEA = 0.072; and (2) model-2: CFI = 0.95; RMSEA = 0.071, respectively. The relationship between FMS and PA was fully mediated by the HRF in both directions. The behavioral mechanism (e.g., maintaining appropriate levels of HRF) provides meaningful insights to understand the obesity trajectory during middle childhood.

Keywords: middle childhood; motor competence; obesity; physical activity; physical fitness.

Background: Models for risk stratification and prediction of outcome, such as the Charlson Comorbidity Index (CCI), the Elixhauser Comorbidity Method (ECM), the 5-factor modified Frailty Index (mFI-5), and the Hospital Frailty Risk Score (HFRS) have been validated in orthopedic surgery. The aim of this study is to compare the predictive power of these models in total hip and knee replacement.

Methods: In a retrospective analysis of 8250 patients who had undergone total joint replacement between 2011 and 2019, CCI, ECM, mFI-5, and HFRS were calculated for each patient. Receiver operating characteristic curve plots were generated and the area under the curve (AUC) was compared between each score with regard to adverse events such as transfusion, surgical, medical, and other complications. Multivariate logistic regression models were used to assess the relationship among risk stratification models, demographic factors, and postoperative adverse events.

Results: In prediction of surgical complications, HFRS performed best (AUC: 0.719, P < .001), followed by ECM (AUC: 0.578, P < .001), mFI-5 (AUC: 0.564, P = .003), and CCI (AUC: 0.555, P = .012). With regard to medical complications, other complications, and transfusion, HFRS also was superior to ECM, mFI-5, and CCI. Multivariate logistic regression analyses revealed HFRS as an independent risk stratification model associated with all captured adverse events (P ≤ .001).

Conclusion: The HFRS is superior to current risk stratification models in the context of total joint replacement. As the HRFS derives from routinely collected administrative data, healthcare providers can identify at-risk patients without additional effort or expense.

Keywords: CCI; ECM; HFRS; arthroplasty; complications; frailty; hospital frailty risk score; mFI; predicitve ability; risk stratification; total joint replacement.

Automated retinal vessel segmentation is among the most significant application and research topics in ophthalmologic image analysis. Deep learning based retinal vessel segmentation models have attracted much attention in the recent years. However, current deep network designs tend to predominantly focus on vessels which are easy to segment, while overlooking vessels which are more difficult to segment, such as thin vessels or those with uncertain boundaries. To address this critical gap, we propose a new end-to-end deep learning architecture for retinal vessel segmentation: hard attention net (HAnet). Our design is composed of three decoder networks: the first of which dynamically locates which image regions are "hard" or "easy" to analyze, while the other two aim to segment retinal vessels in these "hard" and "easy" regions independently. We introduce attention mechanisms in the network to reinforce focus on image features in the "hard" regions. Finally, a final vessel segmentation map is generated by fusing all decoder outputs. To quantify the network's performance, we evaluate our model on four public fundus photography datasets (DRIVE, STARE, CHASE_DB1, HRF), two recent published color scanning laser ophthalmoscopy image datasets (IOSTAR, RC-SLO), and a self-collected indocyanine green angiography dataset. Compared to existing state-of-the-art models, the proposed architecture achieves better/comparable performances in segmentation accuracy, area under the receiver operating characteristic curve (AUC), and f1-score. To further gauge the ability to generalize our model, cross-dataset and cross-modality evaluations are conducted, and demonstrate promising extendibility of our proposed network architecture.

Accurately segmenting retinal vessel from retinal images is essential for the detection and diagnosis of many eye diseases. However, it remains a challenging task due to (1) the large variations of scale in the retinal vessels and (2) the complicated anatomical context of retinal vessels, including complex vasculature and morphology, the low contrast between some vessels and the background, and the existence of exudates and hemorrhage. It is difficult for a model to capture representative and distinguishing features for retinal vessels under such large scale and semantics variations. Limited training data also make this task even harder. In order to comprehensively tackle these challenges, we propose a novel scale and context sensitive network (a.k.a., SCS^-Net) for retinal vessel segmentation. We first propose a scale-aware feature aggregation (SFA) module, aiming at dynamically adjusting the receptive fields to effectively extract multi-scale features. Then, an adaptive feature fusion (AFF) module is designed to guide efficient fusion between adjacent hierarchical features to capture more semantic information. Finally, a multi-level semantic supervision (MSS) module is employed to learn more distinctive semantic representation for refining the vessel maps. We conduct extensive experiments on the six mainstream retinal image databases (DRIVE, CHASEDB1, STARE, IOSTAR, HRF, and LES-AV). The experimental results demonstrate the effectiveness of the proposed SCS-Net, which is capable of achieving better segmentation performance than other state-of-the-art approaches, especially for the challenging cases with large scale variations and complex context environments.

Keywords: Adaptive feature fusion; Multi-level semantic supervision; Retinal vessel segmentation; Scale-aware feature aggregation.

Objectives: To evaluate the survival and neurodevelopmental impairment (NDI) in extremely low birth weight (ELBW) infants at 18 to 26 months with early hypoxemic respiratory failure (HRF). We also assessed whether African American infants with early HRF had improved outcomes after exposure to inhaled nitric oxide (iNO).

Methods: ELBW infants ≤1000 g and gestational age ≤26 weeks with maximal oxygen ≥60% on either day 1 or day 3 were labeled as "early HRF" and born between 2007 and 2015 in the Neonatal Research Network were included. Using a propensity score regression model, we analyzed outcomes and effects of exposure to iNO overall and separately by race.

Results: Among 7639 ELBW infants born ≤26 weeks, 22.7% had early HRF. Early HRF was associated with a mortality of 51.3%. The incidence of moderate-severe NDI among survivors was 41.2% at 18 to 26 months. Mortality among infants treated with iNO was 59.4%. Female sex (adjusted odds ratio [aOR]: 2.4, 95% confidence interval [CI]: 1.8-3.3), birth weight ≥720 g (aOR: 2.3, 95% CI: 1.7-3.1) and complete course of antenatal steroids (aOR: 1.6, 95% CI: 1.1-2.2) were associated with intact survival. African American infants had a similar incidence of early HRF (21.7% vs 23.3%) but lower exposure to iNO (16.4% vs 21.6%). Among infants with HRF exposed to iNO, intact survival (no death or NDI) was not significantly different between African American and other races (aOR: 1.5, 95% CI: 0.6-3.6).

Conclusions: Early HRF in infants ≤26 weeks' gestation is associated with high mortality and NDI at 18 to 26 months. Use of iNO did not decrease mortality or NDI. Outcomes following iNO exposure were not different in African American infants.