Qualification of a Null Lens Using Image-Based Phase Retrieval

In measuring the figure error of an aspheric optic using a null lens, the wavefront contribution from the null lens must be independently and accurately characterized in order to isolate the optical performance of the aspheric optic alone. Various techniques can be used to characterize such a null lens, including interferometry, profilometry and image-based methods. Only image-based methods, such as phase retrieval, can measure the null-lens wavefront in situ - in single-pass, and at the same conjugates and in the same alignment state in which the null lens will ultimately be used - with no additional optical components. Due to the intended purpose of a Dull lens (e.g., to null a large aspheric wavefront with a near-equal-but-opposite spherical wavefront), characterizing a null-lens wavefront presents several challenges to image-based phase retrieval: Large wavefront slopes and high-dynamic-range data decrease the capture range of phase-retrieval algorithms, increase the requirements on the fidelity of the forward model of the optical system, and make it difficult to extract diagnostic information (e.g., the system F/#) from the image data. In this paper, we present a study of these effects on phase-retrieval algorithms in the context of a null lens used in component development for the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission. Approaches for mitigation are also discussed

Abnormal lateralization of functional connectivity between language and default mode regions in autism

Background: Lateralization of brain structure and function occurs in typical development, and abnormal lateralization is present in various neuropsychiatric disorders. Autism is characterized by a lack of left lateralization in structure and function of regions involved in language, such as Broca and Wernicke areas. Methods: Using functional connectivity magnetic resonance imaging from a large publicly available sample (n = 964), we tested whether abnormal functional lateralization in autism exists preferentially in language regions or in a more diffuse pattern across networks of lateralized brain regions. Results: The autism group exhibited significantly reduced left lateralization in a few connections involving language regions and regions from the default mode network, but results were not significant throughout left- and right-lateralized networks. There is a trend that suggests the lack of left lateralization in a connection involving Wernicke area and the posterior cingulate cortex associates with more severe autism. Conclusions: Abnormal language lateralization in autism may be due to abnormal language development rather than to a deficit in hemispheric specialization of the entire brain

Multisite functional connectivity MRI classification of autism: ABIDE results

Background:: Systematic differences in functional connectivity MRI metrics have been consistently observed in autism, with predominantly decreased cortico-cortical connectivity. Previous attempts at single subject classification in high-functioning autism using whole brain point-to-point functional connectivity have yielded about 80% accurate classification of autism vs. control subjects across a wide age range. We attempted to replicate the method and results using the Autism Brain Imaging Data Exchange (ABIDE) including resting state fMRI data obtained from 964 subjects and 16 separate international sites. Methods:: For each of 964 subjects, we obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the gray matter (26.4 million “connections”) after preprocessing that included motion and slice timing correction, coregistration to an anatomic image, normalization to standard space, and voxelwise removal by regression of motion parameters, soft tissue, CSF, and white matter signals. Connections were grouped into multiple bins, and a leave-one-out classifier was evaluated on connections comprising each set of bins. Age, age-squared, gender, handedness, and site were included as covariates for the classifier. Results:: Classification accuracy significantly outperformed chance but was much lower for multisite prediction than for previous single site results. As high as 60% accuracy was obtained for whole brain classification, with the best accuracy from connections involving regions of the default mode network, parahippocampaland fusiform gyri, insula, Wernicke Area, and intraparietal sulcus. The classifier score was related to symptom severity, social function, daily living skills, and verbal IQ. Classification accuracy was significantly higher for sites with longer BOLD imaging times. Conclusions:: Multisite functional connectivity classification of autism outperformed chance using a simple leave-one-out classifier, but exhibited poorer accuracy than for single site results. Attempts to use multisite classifiers will likely require improved classification algorithms, longer BOLD imaging times, and standardized acquisition parameters for possible future clinical utility

Wavefront-Error Performance Characterization for the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM) Science Instruments

The science instruments (SIs) comprising the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM) were tested in three cryogenic-vacuum test campaigns in the NASA Goddard Space Flight Center (GSFC)'s Space Environment Simulator (SES) test chamber. In this paper, we describe the results of optical wavefront-error performance characterization of the SIs. The wavefront error is determined using image-based wavefront sensing, and the primary data used by this process are focus sweeps, a series of images recorded by the instrument under test in its as-used configuration, in which the focal plane is systematically changed from one image to the next. High-precision determination of the wavefront error also requires several sources of secondary data, including 1) spectrum, apodization, and wavefront-error characterization of the optical ground-support equipment (OGSE) illumination module, called the OTE Simulator (OSIM), 2) F-number and pupil-distortion measurements made using a pseudo-nonredundant mask (PNRM), and 3) pupil geometry predictions as a function of SI and field point, which are complicated because of a tricontagon-shaped outer perimeter and small holes that appear in the exit pupil due to the way that different light sources are injected into the optical path by the OGSE. One set of wavefront-error tests, for the coronagraphic channel of the Near-Infrared Camera (NIRCam) Longwave instruments, was performed using data from transverse translation diversity sweeps instead of focus sweeps, in which a sub-aperture is translated and/or rotated across the exit pupil of the system. Several optical-performance requirements that were verified during this ISIM-level testing are levied on the uncertainties of various wavefront-error-related quantities rather than on the wavefront errors themselves. This paper also describes the methodology, based on Monte Carlo simulations of the wavefront-sensing analysis of focus-sweep data, used to establish the uncertainties of the wavefront-error maps

A State-of-the-Art Compact Surface Drifter Reveals Pathways of Floating Marine Litter in the German Bight

Lagrangian observations are important for the understanding of complex transport patterns of floating macroscopic litter items at the ocean surface. Satellite-tracked drifters and numerical models are an important source of information relevant to transport processes as well as distribution patterns of floating marine litter (FML) on a regional to global scale. Sub-mesoscale processes in coastal and estuarine systems have an enormous impact on pathways and accumulation zones of FML and are yet to be fully understood. Here we present a state-of-the-art, low-cost and robust design of a satellite-tracked drifter applicable in studying complex pathways and sub-mesoscale dynamics of floating litter in tidally influenced coastal and estuarine systems. It is compact, lightweight <5 kg, capable of refloating, easily recovered and modified. The drifter motion resolves currents of the ocean surface layer (top 0.5 m layer) taking into account wind induced motions. We further showcase findings from seven of our custom-made drifters deployed from RV Heincke and RV Senckenberg in the German Bight during spring and autumn 2017. Drifter velocities were computed from high resolved drifter position data and compared to local wind field observations. It was noted that the net transport of the drifters in areas far away from the coast was dominated by wind-driven surface currents, 1% of the wind speed, whereas the transport pattern in coastal areas was mainly overshadowed by local small-scale processes like tidal jet currents, interactions with a complex shoreline and fronts generated by riverine freshwater plumes

Impact of the Specific Mutation in KRAS Codon 12 Mutated Tumors on Treatment Efficacy in Patients with Metastatic Colorectal Cancer Receiving Cetuximab-Based First-Line Therapy: A Pooled Analysis of Three Trials

Purpose: This study investigated the impact of specific mutations in codon 12 of the Kirsten-ras (KRAS) gene on treatment efficacy in patients with metastatic colorectal cancer (mCRC). Patients: Overall, 119 patients bearing a KRAS mutation in codon 12 were evaluated. All patients received cetuximab-based first-line chemotherapy within the Central European Cooperative Oncology Group (CECOG), AIO KRK-0104 or AIO KRK-0306 trials. Results: Patients with KRAS codon 12 mutant mCRC showed a broad range of outcome when treated with cetuximab-based first-line regimens. Patients with tumors bearing a KRAS p.G12D mutation showed a strong trend to a more favorable outcome compared to other mutations (overall survival 23.3 vs. 14-18 months; hazard ratio 0.66, range 0.43-1.03). An interaction model illustrated that KRAS p.G12C was associated with unfavorable outcome when treated with oxaliplatin plus cetuximab. Conclusion: The present analysis suggests that KRAS codon 12 mutation may not represent a homogeneous entity in mCRC when treated with cetuximab-based first-line therapy. Copyright (C) 2012 S. Karger AG, Base

Two Gα i1 Rate-Modifying Mutations Act in Concert to Allow Receptor-Independent, Steady-State Measurements of RGS Protein Activity

RGS proteins are critical modulators of G protein-coupled receptor (GPCR) signaling given their ability to deactivate Gα subunits via “GTPase-accelerating protein” (GAP) activity. Their selectivity for specific GPCRs makes them attractive therapeutic targets. However, measuring GAP activity is complicated by slow GDP release from Gα and lack of solution-phase assays for detecting free GDP in the presence of excess GTP. To overcome these hurdles, we developed a Gαi1 mutant with increased GDP dissociation and decreased GTP hydrolysis, enabling detection of GAP activity using steady-state GTP hydrolysis. Gαi1(R178M/A326S) GTPase activity was stimulated 6~12 fold by RGS proteins known to act on Gαi subunits, and not affected by those unable to act on Gαi, demonstrating that the Gα/RGS domain interaction selectivity was not altered by mutation. Gαi1(R178M/A326S) interacted with RGS proteins with expected binding specificity and affinities. To enable non-radioactive, homogenous detection of RGS protein effects on Gαi1(R178M/A326S), we developed a Transcreener® fluorescence polarization immunoassay based on a monoclonal antibody that recognizes GDP with greater than 100-fold selectivity over GTP. Combining Gαi1(R178M/A326S) with a homogenous, fluorescence-based GDP detection assay provides a facile means to explore the targeting of RGS proteins as a new approach for selective modulation of GPCR signaling

scMRI Reveals Large-Scale Brain Network Abnormalities in Autism

Autism is a complex neurological condition characterized by childhood onset of dysfunction in multiple cognitive domains including socio-emotional function, speech and language, and processing of internally versus externally directed stimuli. Although gross brain anatomic differences in autism are well established, recent studies investigating regional differences in brain structure and function have yielded divergent and seemingly contradictory results. How regional abnormalities relate to the autistic phenotype remains unclear. We hypothesized that autism exhibits distinct perturbations in network-level brain architecture, and that cognitive dysfunction may be reflected by abnormal network structure. Network-level anatomic abnormalities in autism have not been previously described. We used structural covariance MRI to investigate network-level differences in gray matter structure within two large-scale networks strongly implicated in autism, the salience network and the default mode network, in autistic subjects and age-, gender-, and IQ-matched controls. We report specific perturbations in brain network architecture in the salience and default-mode networks consistent with clinical manifestations of autism. Extent and distribution of the salience network, involved in social-emotional regulation of environmental stimuli, is restricted in autism. In contrast, posterior elements of the default mode network have increased spatial distribution, suggesting a ‘posteriorization’ of this network. These findings are consistent with a network-based model of autism, and suggest a unifying interpretation of previous work. Moreover, we provide evidence of specific abnormalities in brain network architecture underlying autism that are quantifiable using standard clinical MRI

RGS21, A Regulator of Taste and Mucociliary Clearance?

Motile cilia of airway epithelial cells help to expel harmful inhaled material. Activation of bitterant-responsive G protein-coupled receptors (GPCRs) is believed to potentiate cilia beat frequency and mucociliary clearance. In this study, we investigated whether regulator of G protein signaling-21 (RGS21) has the potential to modulate signaling pathways connected to airway mucociliary clearance, given that RGS proteins modulate GPCR signaling by acting as GTPase-accelerating proteins (GAPs) for the Gα subunits of heterotrimeric G proteins

Head injury from falls in children younger than 6 years of age

The risk of serious head injury (HI) from a fall in a young child is ill defined. The relationship between the object fallen from and prevalence of intracranial injury (ICI) or skull fracture is described. Method Cross-sectional study of HIs from falls in children (<6 years) admitted to UK hospitals, analysed according to the object fallen from and associated Glasgow Coma Score (GCS) or alert, voice, pain, unresponsive (AVPU) and CT scan results. Results Of 1775 cases ascertained (median age 18 months, 54.7% boys), 87% (1552) had a GCS=15/AVPU=alert. 19.3% (342) had a CT scan: 32% (110/342) were abnormal; equivalent to 5.9% of the overall population, 16.9% (58) had isolated skull fractures and 13.7% (47) had ICI (49% (23/47) had an associated skull fracture). The prevalence of ICI increased with neurological compromise; however, 12% of children with a GCS=15/AVPU=alert had ICI. When compared to falls from standing, falls from a person's arms (233 children (mean age 1 year)) had a significant relative OR for a skull fracture/ICI of 6.94 (95% CI 3.54 to 13.6), falls from a building (eg, window or attic) (mean age 3 years) OR 6.84 (95% CI 2.65 to 17.6) and from an infant or child product (mean age 21 months) OR 2.75 (95% CI 1.36 to 5.65). Conclusions Most HIs from a fall in these children admitted to hospital were minor. Infants, dropped from a carer's arms, those who fell from infant products, a window, wall or from an attic had the greatest chance of ICI or skull fracture. These data inform prevention and the assessment of the likelihood of serious injury when the object fallen from is known