Combined GFAP, NFL, Tau, and UCH-L1 panel increases prediction of outcomes in neonatal encephalopathy.

BACKGROUND: Neuroprognostication in neonates with neonatal encephalopathy (NE) may be enhanced by early serial measurement of a panel of four brain-specific biomarkers. METHODS: To evaluate serum biomarkers, 40 NE samples and 37 healthy neonates from a biorepository were analyzed. Blood samples were collected at 0-6, 12, 24, 48, and 96 h of life. MRI provided a short-term measure of injury. Long-term outcomes included death or a Bayley III score at 17-24 months of age. RESULTS: Glial fibrillary acidic protein (GFAP), ubiquitin c-terminal hydrolase-L1 (UCH-L1), and Tau peaked at 0-6 h of life, while neurofilament light chain (NFL) peaked at 96 h of life. These four marker concentrations at 96 h of life differentiated moderate/severe from none/mild brain injury by MRI, while GFAP and Tau showed early discrimination. For long-term outcomes, GFAP, NFL, Tau, and UCH-L1 could differentiate a poor outcome vs good outcome as early as 0-6 h of life, depending on the Bayley domain, and a combination of the four markers enhanced the sensitivity and specificity. Machine learning trajectory analyses identified upward trajectory patients with a high concordance to poor outcomes. CONCLUSION: GFAP, NFL, Tau, and UCH-L1 may be of neuroprognostic significance after NE. IMPACT: Serial measurements of GFAP, NFL, Tau, and UCH-L1 show promise in aiding the bedside clinician in making treatment decisions in neonatal encephalopathy. The panel of four neuroproteins increased the ability to predict neurodevelopmental outcomes. The study utilized a trajectory analysis that enabled predictive modeling. A panel approach provides the bedside clinician with objective data to individualize care. This study provides the foundation to develop a point of care device in the future.

Evaluation of a decision support system using Bayesian network modeling in an applied Multi-INT surveillance environment.

Sensemaking and decision-making are fundamental components of applied Intelligence, Surveillance, and Reconnaissance (ISR). Analysts acquire information from multiple sources over a period of hours, days, or even over the scale of months or years, that must be interpreted and integrated to predict future adversarial events. Sensemaking is essential for developing an appropriate mental model that will lead to accurate predictions sooner. Decision Support Systems (DSS) are one proposed solution to improve analyst decision-making outcomes by leveraging computers to conduct calculations that may be difficult for human operators and provide recommendations. In this study, we tested two simulated DSS that were informed by a Bayesian Network Model as a potential prediction-assistive tool. Participants completed a simulated multi-day, multi-source intelligence task and were asked to make predictions regarding five potential outcomes on each day. Participants in both DSS conditions were able to converge on the correct solution significantly faster than the control group, and between 36-44% more of the sample was able to reach the correct conclusion. Furthermore, we found that a DSS representing projected outcome probabilities as numerical, rather than using verbal ordinal labels, were better able to differentiate which outcomes were extremely unlikely than the control group or verbal-probability DSS.

Recent Development of Moisture-Enabled-Electric Nanogenerators.

Power generation by converting energy from the ambient environment has been considered a promising strategy for developing decentralized electrification systems to complement the electricity supply for daily use. Wet gases, such as water evaporation or moisture in the atmosphere, can be utilized as a tremendous source of electricity by emerging power generation devices, that is, moisture-enabled-electric nanogenerators (MEENGs). As a promising technology, MEENGs provided a novel manner to generate electricity by harvesting energy from moisture, originating from the interactions between water molecules and hydrophilic functional groups. Though the remarkable progress of MEENGs has been achieved, a systematic review in this specific area is urgently needed to summarize previous works and provide sharp points to further develop low-cost and high-performing MEENGs through overcoming current limitations. Herein, the working mechanisms of MEENGs reported so far are comprehensively compared. Subsequently, a systematic summary of the materials selection and fabrication methods for currently reported MEENG construction is presented. Then, the improvement strategies and development directions of MEENG are provided. At last, the demonstrations of the applications assembled with MEENGs are extracted. This work aims to pave the way for the further MEENGs to break through the performance limitations and promote the popularization of future micron electronic self-powered equipment.

Society for Vascular Surgery appropriate use criteria for management of intermittent claudication.

The Society for Vascular Surgery appropriate use criteria (AUC) for the management of intermittent claudication were created using the RAND appropriateness method, a validated and standardized method that combines the best available evidence from medical literature with expert opinion, using a modified Delphi process. These criteria serve as a framework on which individualized patient and clinician shared decision-making can grow. These criteria are not absolute. AUC should not be interpreted as a requirement to administer treatments rated as appropriate (benefit outweighs risk). Nor should AUC be interpreted as a prohibition of treatments rated as inappropriate (risk outweighs benefit). Clinical situations will occur in which moderating factors, not included in these AUC, will shift the appropriateness level of a treatment for an individual patient. Proper implementation of AUC requires a description of those moderating patient factors. For scenarios with an indeterminate rating, clinician judgement combined with the best available evidence should determine the treatment strategy. These scenarios require mechanisms to track the treatment decisions and outcomes. AUC should be revisited periodically to ensure that they remain relevant. The panelists rated 2280 unique scenarios for the treatment of intermittent claudication (IC) in the aortoiliac, common femoral, and femoropopliteal segments in the round 2 rating. Of these, only nine (0.4%) showed a disagreement using the interpercentile range adjusted for symmetry formula, indicating an exceptionally high degree of consensus among the panelists. Post hoc, the term "inappropriate" was replaced with the phrase "risk outweighs benefit." The term "appropriate" was also replaced with "benefit outweighs risk." The key principles for the management of IC reflected within these AUC are as follows. First, exercise therapy is the preferred initial management strategy for all patients with IC. Second, for patients who have not completed exercise therapy, invasive therapy might provide net a benefit for selected patients with IC who are nonsmokers, are taking optimal medical therapy, are considered to have a low physiologic and technical risk, and who are experiencing severe lifestyle limitations and/or a short walking distance. Third, considering the long-term durability of the currently available technology, invasive interventions for femoropopliteal disease should be reserved for patients with severe lifestyle limitations and a short walking distance. Fourth, in the common femoral segment, open common femoral endarterectomy will provide greater net benefit than endovascular intervention for the treatment of IC. Finally, in the infrapopliteal segment, invasive intervention for the treatment of IC is of unclear benefit and could be harmful.

Evaluation of Simulated Recognition Aids for Human Sensemaking in Applied Surveillance Scenarios.

OBJECTIVE: We determined whether the human capability for sensemaking, or for identifying essential elements of information (EEIs), could be enhanced by a simulated recognition aid that directed attention to people and vehicles in scenes or by a simulated recognition aid that directed attention to EEIs. BACKGROUND: For intelligence analysts, sensemaking is challenging because it frequently involves making inferences about uncertain data. One way to enhance sensemaking may involve collaboration from a machine recognition aid such as Project Maven, an established algorithm that directs analysts' attention to people and vehicles in scenes. We simulated the directed attention of Project Maven as well as a machine recognition aid that directed attention to EEIs. METHOD: We created full-motion videos of simulated compounds viewed by an overhead camera. Sensemaking was assessed by measuring participants' ability to predict events and identify signs. Participants' attention was directed by placing small globe symbols above either all people and vehicles, or all EEIs. Novices and intelligence analysts participated. RESULTS: Simulated recognition aids directing participants' attention to EEIs improved EEI identification but directing attention to people and vehicles (emulating Project Maven) did not. Participants' sensemaking was not enhanced by either type of simulated recognition aid. CONCLUSION: Guiding attention to features in a scene improves their identification whereas indiscriminate steering of attention to entities in the scene does not improve understanding of the holistic meaning of events, unless attention is drawn to relevant signs of those events. APPLICATION: Results contribute to our goal of determining which human-machine systems improve the sensemaking capability of intelligence analysts in the field.

Characterization of Calpain and Caspase-6-Generated Glial Fibrillary Acidic Protein Breakdown Products Following Traumatic Brain Injury and Astroglial Cell Injury.

Glial fibrillary acidic protein (GFAP) is the major intermediate filament III protein of astroglia cells which is upregulated in traumatic brain injury (TBI). Here we reported that GFAP is truncated at both the C- and N-terminals by cytosolic protease calpain to GFAP breakdown products (GBDP) of 46-40K then 38K following pro-necrotic (A23187) and pro-apoptotic (staurosporine) challenges to primary cultured astroglia or neuron-glia mixed cells. In addition, with another pro-apoptotic challenge (EDTA) where caspases are activated but not calpain, GFAP was fragmented internally, generating a C-terminal GBDP of 20 kDa. Following controlled cortical impact in mice, GBDP of 46-40K and 38K were formed from day 3 to 28 post-injury. Purified GFAP protein treated with calpain-1 and -2 generates (i) major N-terminal cleavage sites at A-56*A-61 and (ii) major C-terminal cleavage sites at T-383*Q-388, producing a limit fragment of 38K. Caspase-6 treated GFAP was cleaved at D-78/R-79 and D-225/A-226, where GFAP was relatively resistant to caspase-3. We also derived a GBDP-38K N-terminal-specific antibody which only labels injured astroglia cell body in both cultured astroglia and mouse cortex and hippocampus after TBI. As a clinical translation, we observed that CSF samples collected from severe human TBI have elevated levels of GBDP-38K as well as two C-terminally released GFAP peptides (DGEVIKES and DGEVIKE). Thus, in addition to intact GFAP, both the GBDP-38K as well as unique GFAP released C-terminal proteolytic peptides species might have the potential in tracking brain injury progression.

Inferring a complete genotype-phenotype map from a small number of measured phenotypes.

Understanding evolution requires detailed knowledge of genotype-phenotype maps; however, it can be a herculean task to measure every phenotype in a combinatorial map. We have developed a computational strategy to predict the missing phenotypes from an incomplete, combinatorial genotype-phenotype map. As a test case, we used an incomplete genotype-phenotype dataset previously generated for the malaria parasite's 'chloroquine resistance transporter' (PfCRT). Wild-type PfCRT (PfCRT3D7) lacks significant chloroquine (CQ) transport activity, but the introduction of the eight mutations present in the 'Dd2' isoform of PfCRT (PfCRTDd2) enables the protein to transport CQ away from its site of antimalarial action. This gain of a transport function imparts CQ resistance to the parasite. A combinatorial map between PfCRT3D7 and PfCRTDd2 consists of 256 genotypes, of which only 52 have had their CQ transport activities measured through expression in the Xenopus laevis oocyte. We trained a statistical model with these 52 measurements to infer the CQ transport activity for the remaining 204 combinatorial genotypes between PfCRT3D7 and PfCRTDd2. Our best-performing model incorporated a binary classifier, a nonlinear scale, and additive effects for each mutation. The addition of specific pairwise- and high-order-epistatic coefficients decreased the predictive power of the model. We evaluated our predictions by experimentally measuring the CQ transport activities of 24 additional PfCRT genotypes. The R2 value between our predicted and newly-measured phenotypes was 0.90. We then used the model to probe the accessibility of evolutionary trajectories through the map. Approximately 1% of the possible trajectories between PfCRT3D7 and PfCRTDd2 are accessible; however, none of the trajectories entailed eight successive increases in CQ transport activity. These results demonstrate that phenotypes can be inferred with known uncertainty from a partial genotype-phenotype dataset. We also validated our approach against a collection of previously published genotype-phenotype maps. The model therefore appears general and should be applicable to a large number of genotype-phenotype maps.

Gendered racial differences and similarities in subjective cognitive decline and life satisfaction: results from a population-based sample.

OBJECTIVE: The objectives of this study were to: 1) Determine the association between subjective cognitive decline (SCD) and life satisfaction; and 2) Assess the gendered racial/ethnic disparities in the association between SCD and life satisfaction. METHOD: Data were obtained from 3,795 participants from the Behavioral Risk Factor Surveillance System survey. SCD was operationalized by "During the past 12 months, have you experienced confusion or memory loss that is happening more often or is getting worse?" Life satisfaction was operationalized by the question "In general how satisfied are you with your life?" Interaction terms of SCD*sex, SCD*race/ethnicity, and SCD*sex*race/ethnicity were used to determine potential effect measure modification. Crude and adjusted linear regression models, controlling for age, education, income and employment, were used to assess the association between SCD and life satisfaction by sex, race, and by gendered racial/ethnic groups: Black women, White women, Hispanic women, Other women; and Black men, White men, Hispanic men and Other men. RESULTS: SCD was negatively associated with life satisfaction in the overall sample (ß: -0.55; 95% CI: -0.66, -0.43). However, the negative associations seen across gender, race/ethnicity, and gendered racial/ethnic groups were statistically similar (p for interaction terms > 0.05). The highest effect estimate was seen for Other men (ß: -1.22; 95% CI: -1.37, -1.09). CONCLUSION: Interventions geared towards improving cognition may improve life satisfaction for all groups, irrespective of gender and/or race/ethnicity. Future research may include longitudinal studies to determine the temporal sequence between SCD and life satisfaction.

Examination of the interaction between method of anesthesia and shunting with carotid endarterectomy.

BACKGROUND: Although the choice of anesthesia during carotid endarterectomy (CEA) does not seem to increase the risk of perioperative stroke, it might affect the outcomes of shunting during CEA. This study aims to evaluate whether the choice of anesthesia modifies the association between shunting and in-hospital stroke/death after CEA. METHODS: We retrospective reviewed all CEA cases performed between 2003 and 2017 in the Vascular Quality Initiative. Patients were divided into three groups: (1) no shunting during CEA (n = 29,227 [48.4%]), (2) routine shunting (n = 28,673 [47.5%]), and (3) selective shunting based on an intraoperative indication (n = 2499 [4.1%]). Multivariable logistic regression analysis was used to study the interaction between anesthesia (local anesthesia [LA]/regional anesthesia [RA] vs general anesthesia [GA]) and intraoperative shunting (no shunting vs routine and selective shunting) during CEA in predicting the risk of in-hospital stroke/death after CEA. RESULTS: The final cohort included 60,399 patients. The majority of CEA cases (90.2%) were performed under GA. Of the study cohort, 29,227 (48.4%) underwent CEA without shunting, 28,673 patients (47.5%) had routine shunting, and the remaining (n = 2499 [4.1%]) were selectively shunted. The interaction between intraoperative shunting and anesthesia in predicting in-hospital stroke/death was statistically significant (P < .05). When CEA is performed under LA/GA, routine shunting was associated with 3.5 times the adjusted odds of in-hospital stroke/death after CEA (odds ratio [OR], 3.5; 95% confidence interval [CI], 1.8-6.8; P < .001) compared with no shunting, whereas selective shunting was associated with 7.1 the odds (OR, 7.1; 95% CI, 3.5-14.7; P < .001). In contrast, under GA, there was no significant association between routine shunting and in-hospital stroke/death (OR, 1.2; 95% CI, 1.0-1.5; P = .12), whereas selective shunting was associated with 1.7 times the odds (OR, 1.7; 95% CI, 1.2-2.4; P < .01) compared with not performing shunting during CEA. CONCLUSIONS: The use of LA/RA is associated with increased odds of stroke/death compared with GA when intraoperative shunting is performed. The effect of anesthesia is more pronounced in patients who develop clamp-related ischemia and undergo selective shunting. More controlled studies are needed to explain these findings and validate them.

Multiscale modeling and cinematic visualization of photosynthetic energy conversion processes from electronic to cell scales.

Conversion of sunlight into chemical energy, namely photosynthesis, is the primary energy source of life on Earth. A visualization depicting this process, based on multiscale computational models from electronic to cell scales, is presented in the form of an excerpt from the fulldome show Birth of Planet Earth. This accessible visual narrative shows a lay audience, including children, how the energy of sunlight is captured, converted, and stored through a chain of proteins to power living cells. The visualization is the result of a multi-year collaboration among biophysicists, visualization scientists, and artists, which, in turn, is based on a decade-long experimental-computational collaboration on structural and functional modeling that produced an atomic detail description of a bacterial bioenergetic organelle, the chromatophore. Software advancements necessitated by this project have led to significant performance and feature advances, including hardware-accelerated cinematic ray tracing and instanced visualizations for efficient cell-scale modeling. The energy conversion steps depicted feature an integration of function from electronic to cell levels, spanning nearly 12 orders of magnitude in time scales. This atomic detail description uniquely enables a modern retelling of one of humanity's earliest stories-the interplay between light and life.

Ligand-mediated synthesis of colloidal Cs2SnI6 three-dimensional nanocrystals and two-dimensional nanoplatelets.

Cs2SnI6 is a variant on tin-iodide solution-processable materials and may lead to a lead-free material for use in next-generation photovoltaic cells and other optoelectronics. So far, only a few studies have been conducted where shape and geometry control of Cs2SnI6 nanocrystals is demonstrated. Here we report a general approach to directly synthesize Cs2SnI6 of two-dimensional (2D) layered nanoplatelets as well as three-dimensional (3D) nanocrystals. The shape of Cs2SnI6 nanocrystals could be engineered into 3D nanoparticles and different 2D nanoplatelets with well-defined morphology by choosing different organic acid and amine ligands via a hot injection process. Moreover, the thickness of layered 2D nanoplatelets could be adjusted by changing the amount of Cs-oleate present during the synthesis. The photoluminescence emission peaks changed from 643 to 742 nm based on nanomaterial shape. Our method provides a facile and versatile route to rationally control the shape of the Cs2SnI6 nanocrystals, which will create opportunities for applications in lead-free optoelectronics.

MgCl2 passivated ZnO electron transporting layer to improve PbS quantum dot solar cells.

The unique tunable bandgaps and straightforward synthesis of colloidal quantum dots make them promising low-cost materials for photovoltaics. High-performance colloidal quantum dot solar cells rely on good-quality electron transporting layers (ETLs) to make carrier selective contacts. Despite extensive use of n-type oxides as ETLs, a detailed understanding of their surface and interface states as well as mechanisms to improve their optical properties are still under development. Here, we report a simple procedure to produce MgCl2 passivated ZnO nanoparticles ETLs that show improved device performance. The MgCl2 treated ZnO electron transporting layers boost the PbS colloidal quantum dot cell efficiency from 6.3% to 8.2%. The cell exhibits reduced defects leading to significant improvements of both FF and J sc. This low-temperature MgCl2 treated ZnO electron transporting layer may be applied in solution processed tandem cells as a promising strategy to further increase cell efficiencies.

Computational Modeling of the Effects of Sleep Deprivation on the Vigilance Decrement.

OBJECTIVE: We developed a computational model of the effects of sleep deprivation on the vigilance decrement by employing the methods of system dynamics modeling. BACKGROUND: Situations that require sustained attention for a prolonged duration can cause a decline in cognitive performance, the so-called vigilance decrement. One factor that should influence the vigilance decrement is fatigue in the form of sleep deprivation. METHOD: We employed the methods of system dynamics modeling (numerical-integration techniques for modeling complex feedback systems) to create a computational model of the vigilance decrement. We then simulated the computational effects of sleep deprivation on the behavior of that model, using empirical data obtained from the literature for calibrating such effects. RESULTS: Sleep deprivation of 2 hr over a 14-day period should produce an additional decline of 9% in detection performance over that found with the typical vigilance decrement, whereas 4 hr of sleep deprivation over 14 days should produce an additional decline of 14% in detection performance. CONCLUSION: With respect to dual-process theory, it is through its deleterious effects on analytical cognition that sleep deprivation should impact the vigilance decrement. APPLICATION: Such computational modeling may be advantageous for human-machine teaming by theoretically allowing a future autonomous software agent to anticipate the decline of human performance and compensate accordingly.

Comparing the efficacy of shunting approaches and cerebral monitoring during carotid endarterectomy using a national database.

OBJECTIVE: Carotid endarterectomy practice patterns, including the use of shunts and cerebral monitoring techniques, are typically surgeon-dependent and differ greatly on a national level. Prior literature evaluating these techniques is often underpowered for detecting variations in low-frequency outcomes. The purpose of this study was to evaluate current carotid endarterectomy practice patterns and to allow comparison across surgical approaches using a large national database. METHODS: We divided carotid cases entered into the Vascular Quality Initiative database between October 2012 and April 2015 into routine shunting, selective shunting, and never shunting cohorts, excluding endarterectomies performed with concomitant procedures and those with incomplete information on the use of a shunt. The selective group was subdivided into cases with awake, electroencephalography, and stump pressure monitoring. We evaluated differences in practice patterns and compared rates of stroke, death, return to the operating room, reperfusion injury, and re-exploration after closure across these groups. Multivariate logistic regression models adjusting for risk factors were used to identify predictors of each outcome. RESULTS: Between October 2012 and April 2015, there were a total of 28,457 endarterectomies included in our analysis, of which 14,128 involved routine shunting, 1740 involved never shunting, and 12,489 involved selective shunting. Of the selective cases, 6144 involved electroencephalography monitoring, 2310 involved stump pressure monitoring, and 2052 involved awake monitoring. Unadjusted rates of in-hospital death and stroke were 0.30% (95% confidence interval [CI], 0.21-0.39) and 0.78% (95% CI, 0.64-0.93) for routine shunting and 0.22% (95% CI, 0.14-0.31) and 0.91% (95% CI, 0.75-1.08) for selective shunting, respectively. The unadjusted rate of in-hospital death was lower in the awake monitoring group than in the routine shunting group (0.05% vs 0.30%; P = .037). After adjustment for patient risk factors, the multivariate models showed no difference in rates of any primary outcomes among the groups, although there was a shorter postoperative length of stay for the awake monitoring group compared with the routine shunting group (1.55 days vs 2.00 days, respectively; P < .01). CONCLUSIONS: Analysis of the Vascular Quality Initiative registry shows equivalent unadjusted rates of in-hospital death and stroke across different approaches to shunting and cerebral monitoring with the exception of the awake monitoring group, which has lower unadjusted mortality compared with the routine shunting group. In the risk-adjusted analysis, however, there are no differences across any of the groups. Given the clinical equivalence of approaches to shunting and cerebral monitoring, further work should evaluate the relative cost of these techniques.

Short communication: Evaluation of the PREP10 energy-, protein-, and amino acid-allowable milk equations in comparison with the National Research Council model.

The objective of this work was to evaluate the precision and accuracy of the milk yield predictions made by the PREP10 model in comparison to those from the National Research Council (NRC) Nutrient Requirements of Dairy Cattle. The PREP10 model is a ration-balancing system that allows protein use efficiency to vary with production level. The model also has advanced AA supply and requirement calculations that enable estimation of AA-allowable milk (MilkAA) based on 10 essential AA. A literature data set of 374 treatment means was collected and used to quantitatively evaluate the estimates of protein-allowable milk (MilkMP) and energy-allowable milk yields from the NRC and PREP10 models. The PREP10 MilkAA prediction was also evaluated, as were both models' estimates of milk based on the most-limiting nutrient or the mean of the estimated milk yields. For most milk estimates compared, the PREP10 model had reduced root mean squared prediction error (RMSPE), improved concordance correlation coefficient, and reduced mean and slope bias in comparison to the NRC model. In particular, utilizing the variable protein use efficiency for milk production notably improved the estimate of MilkMP when compared with NRC. The PREP10 MilkMP estimate had an RMSPE of 18.2% (NRC = 25.7%), concordance correlation coefficient of 0.82% (NRC = 0.64), slope bias of -0.14 kg/kg of predicted milk (NRC = -0.34 kg/kg), and mean bias of -0.63 kg (NRC = -2.85 kg). The PREP10 estimate of MilkAA had slightly elevated RMSPE and mean and slope bias when compared with MilkMP. The PREP10 estimate of MilkAA was not advantageous when compared with MilkMP, likely because AA use efficiency for milk was constant whereas MP use was variable. Future work evaluating variable AA use efficiencies for milk production is likely to improve accuracy and precision of models of allowable milk.

Intuitive Cognition and Models of Human-Automation Interaction.

OBJECTIVE: The aim of this study was to provide an analysis of the implications of the dominance of intuitive cognition in human reasoning and decision making for conceptualizing models and taxonomies of human-automation interaction, focusing on the Parasuraman et al. model and taxonomy. BACKGROUND: Knowledge about how humans reason and make decisions, which has been shown to be largely intuitive, has implications for the design of future human-machine systems. METHOD: One hundred twenty articles and books cited in other works as well as those obtained from an Internet search were reviewed. Works were deemed eligible if they were published within the past 50 years and common to a given literature. RESULTS: Analysis shows that intuitive cognition dominates human reasoning and decision making in all situations examined. The implications of the dominance of intuitive cognition for the Parasuraman et al. model and taxonomy are discussed. A taxonomy of human-automation interaction that incorporates intuitive cognition is suggested. APPLICATION: Understanding the ways in which human reasoning and decision making is intuitive can provide insight for future models and taxonomies of human-automation interaction.