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BackgroundHigh-impact genetic variants associated with neurodevelopmental disorders provide biologically defined entry points for etiological discovery. The 3q29 deletion (3q29Del) is one such variant that confers a ∼40-fold increased risk for schizophrenia, and a ∼30-fold increased risk for autism. However, the specific neural mechanisms underlying this link remain largely unknown.MethodsHere, we report the first in vivo quantitative neuroimaging study in 3q29Del individuals (N=24) and healthy controls (N=1,608) using structural MRI. Given prior reports of posterior fossa abnormalities in 3q29Del, we focus our investigation on the cerebellum and its primary tissue-types. Additionally, we compare the prevalence of cystic/cyst-like malformations of the posterior fossa between 3q29Del participants and controls, and examine the association between neuroanatomical findings and standardized behavioral measures to probe gene-brain-behavior relationships.Results3q29Del participants had smaller cerebellar cortex volumes than controls, both before and after correction for intracranial volume (ICV). 3q29Del participants also had larger cerebellar white matter volumes than controls following ICV-correction. The 3q29Del group displayed an elevated rate of posterior fossa arachnoid cysts and mega cisterna magna findings independent of cerebellar volume. Sex played a moderating role in a subset of findings. Cerebellar white matter volume was positively associated with visual-motor integration skills and cognitive ability, while cystic/cyst-like malformations yielded no behavioral link.ConclusionsAbnormal development of posterior fossa structures may represent neuroimaging-based biomarkers in 3q29Del. Results reveal cerebellar associations with sensorimotor and cognitive deficits in 3q29Del and present a novel point of genetic convergence with cerebellar pathology reported in idiopathic forms of neurodevelopmental disease.

Social-communication skills emerge within the context of rich social interactions, facilitated by an infant's capacity to attend to people and objects in the environment. Disruption in this early neurobehavioral process may decrease the frequency and quality of social interactions and learning opportunities, potentially leading to downstream deleterious effects on social development. This study examined early attention in infant siblings of children with autism spectrum disorder (ASD) who are at risk for social and communication delays. Visual and auditory attention was mapped from age 1 week to 5 months in infants at familial risk for ASD (high risk;N= 41) and low-risk typically developing infants (low risk;N= 39). At 12 months, a subset of participants (N= 40) was administered assessments of social communication and nonverbal cognitive skills. Results revealed that high-risk infants performed lower on attention tasks at 2 and 3 months of age compared to low-risk infants. A significant association between overall attention at 3 months and developmental outcome at 12 months was observed for both groups. These results provide evidence for early vulnerabilities in visual attention for infants at risk for ASD during a period of important neurodevelopmental transition (between 2 and 3 months) when attention has significant implications for social communication and cognitive development.

Objective To characterize children presenting with concerns for autism spectrum disorder (ASD) missed by parent-report screeners and to examine benefits of a combined screening approach with the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) and the Ages and Stages Questionnaire, Third Edition (ASQ-3). Methods Participants included were 154 children aged 16 to 42 months presenting for an evaluation at an autism center. Caregivers completed the M-CHAT-R, ASQ-3, and a demographic questionnaire. Children participated in an autism diagnostic evaluation consisting of the Mullen Scales of Early Learning (Mullen) and Autism Diagnostic Observation Schedule, Second Edition (ADOS-2). Results A total of 124 children (81%) were diagnosed with ASD. The M-CHAT-R identified 85% (n = 105) of these children. Children with ASD missed by the M-CHAT-R had significantly higher scores on the Mullen and significantly lower scores on the ADOS-2. Of the ASQ-3 domains, the majority (n = 102, 82%) of children with ASD failed the communication domain; missed cases showed similar patterns of higher Mullen scores and lower ADOS-2 scores. When adopting a combined screening approach, using a failed screen from either the M-CHAT-R or ASQ-3 communication domain, 93% of children were identified. Parent-reported concerns on an open-ended questionnaire revealed ASD red flags for many missed cases. Conclusion Children with ASD missed by screeners had higher scores on developmental testing and lower scores on the ADOS-2; however, children still performed below average on developmental tests. Our findings suggest that a combined screening approach was most effective for identifying children with ASD from a sample group referred for an ASD evaluation.

Background: Recent clinical practice guidelines from major national organizations, including a joint United States Department of Veterans Affairs (VA) and Department of Defense (DoD) committee, have substantially changed recommendations for the use of the cholesterol-lowering statin medications after years of relative stability. Because statin medications are among the most commonly prescribed treatments in the United States, any change in their use may have significant implications for patients and providers alike. Prior research has shown that effective implementation interventions should be both user centered and specifically chosen to address identified barriers. Objective: The objectives of this study were to identify potential determinants of provider uptake of the new statin guidelines and to use that information to tailor a coordinated and streamlined local quality improvement intervention focused on prescribing appropriate statins. Methods: We employed user-centered design principles to guide the development and testing of a multicomponent guideline implementation intervention to improve statin prescribing. This paper describes the intervention development process whereby semistructured qualitative interviews with providers were conducted to (1) illuminate the knowledge, attitudes, and behaviors of providers and (2) elicit feedback on intervention prototypes developed to align with and support the use of the VA/DoD guidelines. Our aim was to use this information to design a local quality improvement intervention focused on statin prescribing that was tailored to the needs of primary care providers at our facility. Cabana’s Clinical Practice Guidelines Framework for Improvement and Nielsen’s Usability Heuristics were used to guide the analysis of data obtained in the intervention development process. Results: Semistructured qualitative interviews were conducted with 15 primary care Patient Aligned Care Team professionals (13 physicians and 2 clinical pharmacists) at a single VA medical center. Findings highlight that providers were generally comfortable with the paradigm shift to risk-based guidelines but less clear on the need for the VA/DoD guidelines in specific. Providers preferred a clinical decision support tool that helped them calculate patient risk and guide their care without limiting autonomy. They were less comfortable with risk communication and performance measurement systems that do not account for shared decision making. When possible, we incorporated their recommendations into the intervention. Conclusions: By combining qualitative methods and user-centered design principles, we could inform the design of a multicomponent guideline implementation intervention to better address the needs and preferences of providers, including clear and direct language, logical decision prompts with an option to dismiss a clinical decision support tool, and logical ordering of feedback information. Additionally, this process allowed us to identify future design considerations for quality improvement interventions.

BACKGROUND Recent clinical practice guidelines from major national organizations, including a joint United States Department of Veterans Affairs (VA) and Department of Defense (DoD) committee, have substantially changed recommendations for the use of the cholesterol-lowering statin medications after years of relative stability. Because statin medications are among the most commonly prescribed treatments in the United States, any change in their use may have significant implications for patients and providers alike. Prior research has shown that effective implementation interventions should be both user centered and specifically chosen to address identified barriers. OBJECTIVE The objectives of this study were to identify potential determinants of provider uptake of the new statin guidelines and to use that information to tailor a coordinated and streamlined local quality improvement intervention focused on prescribing appropriate statins. METHODS We employed user-centered design principles to guide the development and testing of a multicomponent guideline implementation intervention to improve statin prescribing. This paper describes the intervention development process whereby semistructured qualitative interviews with providers were conducted to (1) illuminate the knowledge, attitudes, and behaviors of providers and (2) elicit feedback on intervention prototypes developed to align with and support the use of the VA/DoD guidelines. Our aim was to use this information to design a local quality improvement intervention focused on statin prescribing that was tailored to the needs of primary care providers at our facility. Cabana’s Clinical Practice Guidelines Framework for Improvement and Nielsen’s Usability Heuristics were used to guide the analysis of data obtained in the intervention development process. RESULTS Semistructured qualitative interviews were conducted with 15 primary care Patient Aligned Care Team professionals (13 physicians and 2 clinical pharmacists) at a single VA medical center. Findings highlight that providers were generally comfortable with the paradigm shift to risk-based guidelines but less clear on the need for the VA/DoD guidelines in specific. Providers preferred a clinical decision support tool that helped them calculate patient risk and guide their care without limiting autonomy. They were less comfortable with risk communication and performance measurement systems that do not account for shared decision making. When possible, we incorporated their recommendations into the intervention. CONCLUSIONS By combining qualitative methods and user-centered design principles, we could inform the design of a multicomponent guideline implementation intervention to better address the needs and preferences of providers, including clear and direct language, logical decision prompts with an option to dismiss a clinical decision support tool, and logical ordering of feedback information. Additionally, this process allowed us to identify future design considerations for quality improvement interventions.

Lean burn diesel engines operate at a high air-to-fuel ratio to improve fuel efficiency and reduce the emissions of hydrocarbons (HC) and CO. The higher amounts of NOx (NO and NO2) produced under lean-burn conditions require a complex catalytic treatment system where an initial diesel oxidation catalyst eliminates HC and CO and an ammonia-mediated selective catalytic reduction (SCR) system converts NOx to N2. Excess ammonia is then oxidized to N2 and H2O through an ammonia oxidation catalyst.1,2 To enable the real-time tuning of the SCR system, sensors are required which can simultaneously quantify NH3 and NOxunder exhaust gas conditions. We have designed three-electrode mixed-potential sensors for real-time detection of NOx and NH3. The sensors were manufactured by ESL ElectroScience on an insulator-yttria-stabilized zirconia (YSZ)-insulator substrate. Dense electrodes of La0.8Sr0.2CrO3 (LSCO), Au0.5Pd0.5 (Au/Pd), and Pt and a porous layer of YSZ electrolyte have been deposited by screen printing. The Au/Pd+Pt pair is sensitive to NH3 under open circuit conditions, while under a negative current bias, the sensitivity of the LSCO+Pt pair to NOx is enhanced and the sensitivity to NH3 is suppressed. The tunable sensitivity allows us to quantify the concentration of NOx and NH3 separately. These mixed potential sensors are also expected to have fast response times, sufficient robustness in the exhaust gas conditions, and are manufactured in processes that are readily scaled up for mass production. We take advantage of the ability of artificial neural networks (ANNs) to learn continuous functional relationships without human intervention to decode the sensor signals in the presence of cross interference. ANNs have also been successfully used in a broad range of mobile applications which makes them an attractive tool for developing portable analyzers and on-board vehicle diagnostic systems. We have previously demonstrated this technique can quantify mixtures of NOx, C3H8, and CO.3 The ANN model used for NOx/NH3 in Figure 1(a) consists of a three-layer feed-forward structure with 6 input neurons, 16 hidden layer neurons, and 2 output neurons. A peak test error in Figure 1(b) of less than 5% was achieved for decoding the signals from NOx/NH3 mixtures in the 50-200 ppm range. For practical use in automotive systems, stability on the order of 103 hours must be studied. Long term signal drift and changes in impedance response were monitored under repeated exposure to 50-200 ppm of NOx, C3H8, and NH3 in alternating biased and unbiased conditions at 530oC over a period of over 100 days. References [1] G. Busca, L. Lietti, G. Ramis, F. Berti, Appl. Catal. B Environ., 18, 1–36 (1998). [2] M. Koebel, M. Elsener, M. Kleemann, Catal. Today, 59, 335–345 (2000). [3] L. Tsui, A.D. Benavidez, P. Palanisamy, L. Evans, F.H. Garzon, ECS Trans., 75, 9–22 (2016). Figure 1. (a) Artificial neural network model used to decode the signals from a three-electrode sensor operated in open circuit and unbiased mode. (b) Test error for the ANN shows a peak at 2.5% and 90% of the data points are confined to less than 15% error. Figure 1

The additive manufacturing of electro-ceramics is a major technological challenge with many possible applications. The technology can prototype and produce in small volume production, custom dielectric, piezoelectric and solid state ionic devices. Sandia National Laboratories was the birthplace of modern, 3-D ceramic additive manufacturing. The newly developed manufacturing methods are considered to be the foundation of 3-D printing via particulate slurries and our spin off company Robocasting Enterprises, is commercially producing dense ceramic and composite parts. These parts are used in various applications including complex geometry catalyst supports and casting filters. This technique is based on the layer-by-layer deposition of highly loaded colloidal slurries that are extruded through a small nozzle. The rheology of the slurry is crucial in order to maintain the structural integrity of the part being built, as Robocasting does not rely on polymerization reactions or solidification to retain shape after extrusion. Since this process is essentially binderless, a dense ceramic part can typically be freeformed, dried, and sintered in less than 24 hours. Although Robocasting is a highly useful technique, it has been optimized for ceramic and composite materials. More recently there has been some work on expanding this technology for use in printing electrode materials. Printing conductors and other structures for electrochemical and electronics using direct write technology gives the potential to reduce production time and reduce waste of expensive material. We have demonstrated that this direct write manufacturing technique can produce Multi-Chip Modules (MCM) by depositing silver and gold on Low Temperature Co-fired Ceramics (LTCC). We have also applied this additive manufacturing technique to our unique design of electrochemical gas sensors. These multi-component mixed potential sensors consist of solid electrodes and a porous electrolyte. In order to expand the versatility of this manufacturing method to be used in solid state ionic devices, slurries of solid electrolytes and electrode materials with specific rheological properties were developed. Another challenge was controlling the residual stress and shrinkage through the material properties of various components. These devices are capable of detecting NOx, hydrocarbons, and NH3 at concentrations on the order of parts per million. The additive manufacturing technique allows for the rapid prototyping of these devices and low volume production of custom devices optimized for specific applications. Figure 1

The platinum electrode/yttria-stabilized zirconia metal/solid electrolyte interface is used in a wide variety of sensing applications including lambda oxygen sensors, wide range oxygen sensors, HC and NOx sensors.1–3 In many cases the electrode is protected by a porous ceramic layer to shield the device from exhaust particle impingement,1 or in the case of some types of mixed potential sensors, the electrolyte itself is porous.4The electrochemically active surface area and porosity are important factors that may control the performance of all types of zirconia-based sensors. While measuring AC impedance behavior in the gas phase is possible, the high diffusivity of gases through the porous layer makes extracting diffusion parameters difficult. Mixed potential electrochemical sensors being electro-kinetic devices, are particularly sensitive to these parameters, but few techniques have been developed to measure active surface areas and characterize transport through porous layers. We have developed sensors consisting of a yttria-stabilized zirconia (YSZ) substrate coated with an insulating ceramic onto which dense electrodes of Pt, La0.8Sr0.2CrO3, or Au0.5Pd0.5alloy are screen printed. Finally, a porous YSZ electrolyte is deposited on top of the electrodes. Measuring the effective diffusivity through the porous layer and the electrochemically active surface area of the underlying electrodes is useful in optimizing the performance of the devices. The electrochemically active surface area of the Pt electrodes beneath the porous electrolyte layer was determined by immersing the sensor in aqueous H2SO4 solution and measuring the double layer capacitance or adsorption of a monolayer of H. The oxidation and reduction of [Fe(CN)6]-4/-3 observed by cyclic voltammetry (CV) acts as a probe for the effective diffusion constant through the porous layer as the kinetics of this reaction are fast and the reaction is easily reversible. The effective diffusion coefficient is obtained by fitting to the Randles-Secvik equation for the peak CV current as a function of scan rate. Figure 1 shows the CVs obtained on (a) a Pt disk and (b) the Pt sensor electrode beneath a porous YSZ electrolyte. The effective diffusion coefficient is on the order of 10-6 cm2/s for the Pt disk and is consistent with values reported in the literature.4 The diffusion coefficient is 10-10 cm2/s for the transport through the porous layer on sensor indicating significant hindrance by the YSZ. Measuring these characteristics for both sensors produced by screen printing (ESL ElectroScience) and sensors produced by additive manufacturing in our lab will guide the optimization of sensor performance characteristics. The measurements are correlated to the device sensing and AC impedance response. References 1. J. Riegel, H. Neumann, and H.-M. Wiedenmann, Solid State Ionics, 152–153, 783–800 (2002). 2. F. H. Garzon, R. Mukundan, and E. L. Brosha, Solid State Ionics, 136–137, 633–638 (2000). 3. E. Ivers-Tiffée, K. H. Härdtl, W. Menesklou, and J. Riegel, Electrochim. Acta, 47, 807–814 (2001). 4. P. K. Sekhar, E. L. Brosha, R. Mukundan, W. Li, M. A. Nelson, P. Palanisamy, F. H. Garzon, Sensors Actuators, B Chem., 144, 112–119 (2010). 5. S. J. Konopka and B. McDuffie, Anal. Chem., 42, 1741–1746 (1970). Figure 1. Cyclic voltammetry of [Fe(CN)6]-4/-3 oxidation and reduction on (a) Pt disk electrode and (b) Pt sensor electrode beneath a porous YSZ electrolyte. Current densities are normalized to electrochemically active surface area. Figure 1