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IMPORTANCE: Appropriately established pediatric reference intervals are critical to the clinical decision-making process and should reflect the physiologic changes that occur during healthy child development. Reference intervals used in pediatric care today remain highly inconsistent across a broad range of common clinical biomarkers. OBSERVATIONS: This narrative review assesses biomarker-specific pediatric reference intervals and their clinical utility with respect to the underlying biological changes occurring during development. Pediatric reference intervals from PubMed-indexed articles published from January 2015 to April 2021, commercial laboratory websites, study cohorts, and pediatric reference interval books were all examined. Although large numbers of pediatric reference intervals are published for some biomarkers, very few are used by clinical and commercial laboratories. The patterns, extent, and timing of biomarker changes are highly variable, particularly during developmental stages with rapid physiologic changes. However, many pediatric reference intervals do not capture these changes and thus do not accurately reflect the underlying biochemistry of development, resulting in significant inconsistencies between reference intervals. CONCLUSIONS AND RELEVANCE: There is a need to correctly describe the biochemistry of child development as well as to identify strategies to develop accurate and consistent pediatric reference intervals for improved pediatric care.

ABSTRACTIntroductionHepatocellular carcinoma (HCC) remains a leading cause of liver-related mortality. Cirrhosis of any etiology is the major risk factor although HCC can develop in its absence in patients with hepatitis B and increasingly in those with nonalcoholic fatty liver disease. When detected at an early stage, curative options include surgical resection, liver transplantation, and/or ablative therapies. Unfortunately, most cases of HCC are recognized at an advanced stage when options are limited and noncurative. However, new systemic therapies with tyrosine kinase inhibitors and immunotherapy have expanded therapeutic options in advanced HCC. Advances in systemic therapy have given patients with advanced HCC hope and prolonged their survival.Areas coveredWe discuss recent data and ongoing research efforts to improve the treatment of hepatocellular carcinoma with discussion of current and upcoming systemic therapies combining agents of different classes.Expert opinionSystemic therapy for HCC is in evolution. The inclusion of immunotherapy to systemic therapy has revolutionized the field of HCC treatment. Identification of the appropriate combination and sequence of systemic therapy coupled with discovery of reliable HCC biomarkers will lead to improved survival and individualized HCC therapy.

ObjectiveAlcohol-related liver disease (ALD) ranges from never-decompensated ALD (ndALD) to the life-threatening decompensated phenotype, known as alcohol-related hepatitis (AH). A multidimensional study of the clinical, histological and molecular features of these subtypes is lacking.DesignTwo large cohorts of patients were recruited in an international, observational multicentre study: a retrospective cohort of patients with ndALD (n=110) and a prospective cohort of patients with AH (n=225). Clinical, analytical, immunohistochemistry and hepatic RNA microarray analysis of both disease phenotypes were performed.ResultsAge and mean alcohol intake were similar in both groups. AH patients had greater aspartate amino transferase/alanine amino transferase ratio and lower gamma-glutamyl transferase levels than in ndALD patients. Patients with AH demonstrated profound liver failure and increased mortality. One-year mortality was 10% in ndALD and 50% in AH. Histologically, steatosis grade, ballooning and pericellular fibrosis were similar in both groups, while advanced fibrosis, Mallory-Denk bodies, bilirubinostasis, severe neutrophil infiltration and ductular reaction were more frequent among AH patients. Transcriptome analysis revealed a profound gene dysregulation within both phenotypes when compare to controls. While ndALD was characterised by deregulated expression of genes involved in matrisome and immune response, the development of AH resulted in a marked deregulation of genes involved in hepatocyte reprogramming and bile acid metabolism.ConclusionsDespite comparable alcohol intake, AH patients presented with worse liver function compared with ndALD patients. Bilirubinostasis, severe fibrosis and ductular reaction were prominent features of AH. AH patients exhibited a more profound deregulation of gene expression compared with ndALD patients.

Urban settlements and urbanised populations continue to grow rapidly and much of this transition is occurring in less developed countries. Remote sensing techniques are now often applied to monitor urbanisation and changes in settlement patterns. In particular, increasing availability of very high resolution imagery (<1 m spatial resolution) and computing power is enabling complete sets of settlement data in the form of building footprints to be extracted from imagery. These settlement data provide information on the changes occurring in cities, particularly in countries which may lack other data on urbanisation. While spatially detailed, extracted building footprints typically lack other information that identify building types or can be used to differentiate intra-urban land uses or neighbourhood types. This work demonstrates an approach to classifying settlement types through multi-scale spatial patterns of urban morphology visible in building footprint data extracted from very high resolution imagery. The work uses a Gaussian mixture modelling approach to select and hierarchically merge components into clusters. The results are maps classifying settlement types on a high spatial resolution (100 m) grid. The approach is applied in Kaduna, Nigeria; Kinshasa, Democratic Republic of the Congo; and Maputo, Mozambique and demonstrates the potential of computational methods to take advantage of large spatial datasets and extract meaningful information to support monitoring of urban areas. The model-based approach produces a hierarchy of potential clustering solutions, and we suggest that this can be used in partnership with local knowledge of the context when creating settlement typologies.

This study examines to what extent mixed groups of computers and humans are able to produce conformity effects in human interaction partners. Previous studies reveal that nonhuman groups can induce conformity under certain circumstances, but it is unknown to what extent mixed groups of human and nonhuman agents are able to produce similar effects. It is also unknown how varying the number of human agents per group can affect conformity. Participants were assigned to one of five groups varying in their proportion of human to nonhuman agent composition and were asked to complete a social and analytical task with the assigned group. These task types were chosen to represent tasks which humans (i.e., social task) or computers (i.e., analytical task) may be perceived as having greater expertise in, as well as roughly approximating real-world tasks humans may complete. A mixed analysis of variance (ANOVA) revealed higher rates of conformity (i.e., percentage of time participants answered in line with their group on critical trials) with the group opinion for the analytical versus the social task. In addition, there was an impact of the ratio of human to nonhuman agents per group on conformity on the social task, with higher conformity with the group opinion as the number of humans in the group increased. No such effect was observed for the analytical task. The findings suggest that mixed groups produce different levels of conformity depending on group composition and task type. Designers of systems should be aware that group composition and task type may influence compliance and should design systems accordingly.

Because one of the largest influences on trust in automation is the familiarity with the system, we sought to examine the effects of familiarity on driver interventions while using the autoparking feature of a Tesla Model X. Participants were either told or shown how the autoparking feature worked. Results showed a significantly higher initial driver intervention rate when the participants were only told how to employ the autoparking feature, than when shown. However, the intervention rate quickly leveled off, and differences between conditions disappeared. The number of interventions and the distances from the parking anchoring point (a trashcan) were used to create a new measure of distrust in autonomy. Eyetracking measures revealed that participants disengaged from monitoring the center display as the experiment progressed, which could be a further indication of a lowering of distrust in the system. Combined, these results have important implications for development and design of explainable artificial intelligence and autonomous systems. Finally, we detail the substantial hurdles encountered while trying to evaluate “autonomy in the wild.” Our research highlights the need to re-evaluate trust concepts in high-risk, high-consequence environments.

Research suggests that humans and autonomous agents can be more effective when working together as a combined unit rather than as individual entities. However, most research has focused on autonomous agent design characteristics while ignoring the importance of social interactions and team dynamics. Two experiments examined how the perception of teamwork among human–human and human–autonomous agents and the application of team building interventions could enhance teamwork outcomes. Participants collaborated with either a human or an autonomous agent. In the first experiment, it was revealed that manipulating team structure by considering your human and autonomous partner as a teammate rather than a tool can increase affect and behavior, but does not benefit performance. In the second experiment, participants completed goal setting and role clarification (team building) with their teammate prior to task performance. Team building interventions led to significant improvements for all teamwork outcomes, including performance. Across both studies, participants communicated more substantially with human partners than they did with autonomous partners. Taken together, these findings suggest that social interactions between humans and autonomous teammates should be an important design consideration and that particular attention should be given to team building interventions to improve affect, behavior, and performance.

A common assumption across many industries is that inserting advanced autonomy can often replace humans for low-level tasks, with cost reduction benefits. However, humans are often only partially replaced and moved into a supervisory capacity with reduced training. It is not clear how this shift from human to automation control and subsequent training reduction influences human performance, errors, and a tendency toward automation bias. To this end, a study was conducted to determine whether adding autonomy and skipping skill-based training could influence performance in a supervisory control task. In the human-in-the-loop experiment, operators performed unmanned aerial vehicle (UAV) search tasks with varying degrees of autonomy and training. At the lowest level of autonomy, operators searched images and, at the highest level, an automated target recognition algorithm presented its best estimate of a possible target, occasionally incorrectly. Results were mixed, with search time not affected by skill-based training. However, novices with skill-based training and automated target search misclassified more targets, suggesting a propensity toward automation bias. More experienced operators had significantly fewer misclassifications when the autonomy erred. A descriptive machine learning model in the form of a hidden Markov model also provided new insights for improved training protocols and interventional technologies.

We describe efforts to make humans more transparent to machines by focusing on uncertainty, a concept with roots in neuronal populations that scales through social interactions. To be effective team partners, machines will need to learn why uncertainty happens, how it happens, how long it will last, and possible mitigations the machine can supply. Electroencephalography-derived measures of team neurodynamic organization were used to identify times of uncertainty in military, health care, and high school problem-solving teams. A set of neurodynamic sequences was assembled that differed in the magnitudes and durations of uncertainty with the goal of training machines to detect the onset of prolonged periods of high level uncertainty, that is, when a team might require support. Variations in uncertainty onset were identified by classifying the first 70 s of the exemplars using self-organizing maps (SOM), a machine architecture that develops a topology during training that separates closely related from desperate data. Clusters developed during training that distinguished patterns of no uncertainty, low-level and quickly resolved uncertainty, and prolonged high-level uncertainty, creating opportunities for neurodynamic-based systems that can interpret the ebbs and flows in team uncertainty and provide recommendations to the trainer or team in near real time when needed.

This paper presents a three-phase computational methodology for making informed design decisions when determining the allocation of work and the interaction modes for human-robot teams. The methodology highlights the necessity to consider constraints and dependencies in the work and the work environment as a basis for team design, particularly those dependencies that arise within the dynamics of the team’s collective activities. These constraints and dependencies form natural clusters in the team’s work, which drive the team’s performance and behavior. The proposed methodology employs network visualization and computational simulation of work models to identify dependencies resulting from the interplay of taskwork distributed between teammates, teamwork, and the work environment. Results from these analyses provide insight into not only team efficiency and performance, but also quantified measures of required teamwork, communication, and physical interaction. The paper describes each phase of the methodology in detail and demonstrates each phase with a case study examining the allocation of work in a human-robot team for space operations.

Function allocation refers to strategies for distributing system functions and tasks across people and technology. We review approaches to function allocation in the context of human machine teaming with technology that exhibits high levels of autonomy (e.g., unmanned aerial systems). Although most function allocation projects documented in the literature have employed a single method, we advocate for an integrated approach that leverages four key activities: (1) analyzing operational demands and work requirements; (2) exploring alternative distribution of work across person and machine agents that make up a human machine team (HMT); (3) examining interdependencies between human and autonomous technologies required for effective HMT performance under routine and off-nominal (unexpected) conditions; and (4) exploring the trade-space of alternative HMT options. Our literature review identified methods to support each of these activities. In combination, they enable system designers to uncover, explore, and weigh a range of critical design considerations beyond those emphasized by the MABA–MABA (“Men are better at, Machines are better at”) and Levels of Automation function allocation traditions. Example applications are used to illustrate the value of these methods to design of HMT that includes autonomous machine agents.

CD49d is emerging as a powerful adverse prognostic marker in chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). However, flow cytometric testing for CD49d has not yet been widely adopted in the United States, in part due to the lack of establishment of its performance characteristics in the clinical setting, especially in comparison with the more common CLL/SLL prognostic markers CD38 and ZAP‐70. CD49d expression levels in 124 CLL/SLL cases were assessed among peripheral blood (PB), bone marrow (BM), and lymph node (LN) specimens and correlated with available CD38 and ZAP‐70 expression and cytogenetic findings. For 10 PB/BM specimens, the stability of CD49d, CD38, and ZAP‐70 expression was assessed at <24 hours, 48 hours, 72 hours, and 96 hours. 39% (28 of 71) PB, 56% (18 of 32) BM, and 71% (15 of 21) LN involved by CLL/SLL were CD49d+, using a ≥30% threshold. The mean for the CD49d+ cases was 2.8 standard deviations (SD) above the cutoff for positivity, compared with 1.7 SD for CD38 and 1.1 SD for ZAP‐70. CD49d demonstrated the lowest mean SD (0.91) and coefficient of variation (CV) (8.0%) compared with CD38 (SD = 2.1, CV = 10.4%) and ZAP‐70 (SD = 9.8, CV = 40.5%) in stability studies over a 96‐hours time period. CD49d+ CLL/SLL correlated with trisomy 12 (P =0.025) and lack of isolated deletion (13q) (P =0.005). CD38+ CLL/SLL correlated with deletion (11q) (P =0.025). ZAP‐70 did not correlate with any underlying cytogenetic abnormality. CD49d is a robust adverse prognostic marker in CLL/SLL with superior performance characteristics. © 2016 International Clinical Cytometry Society

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A growing population of adolescents/young adults with eosinophilic esophagitis (EoE) and eosinophilic gastroenteritis (EGE) will need to transition from pediatric to adult health providers. Measuring health care transition (HCT) readiness is critical, but no studies have evaluated this process in EoE/EGE. We determined the scope and predictors of HCT knowledge in patients and parents with EoE/EGE and measured HCT readiness in adolescents/young adults. We conducted an online survey of patients 13 years or older and parents of patients with EoE/EGE who were diagnosed when 25 years or younger. Parents answered questions regarding their children and their own knowledge of HCT. HCT readiness was assessed in adolescents/young adults aged 13 to 25 years with the Self-Management and Transition to Adulthood with Rx Questionnaire (a 6-domain self-report tool) with a score range of 0 to 90. Four hundred fifty participants completed the survey: 205 patients and 245 parents. Included in the analysis (those diagnosed with EoE/EGE at age 25 years or younger) were 75 of 205 patients and children of 245 parent respondents. Overall, 78% (n = 52) of the patients and 76% (n = 187) of parents had no HCT knowledge. Mean HCT readiness score in adolescents/young adults (n = 50) was 30.4 ± 11.3 with higher scores in domains of provider communication and engagement during appointments. Mean parent-reported (n = 123) score was 35.6 ± 9.7 with higher scores in medication management and disease knowledge. There was a significant deficit in HCT knowledge, and HCT readiness scores were lower than other chronic health conditions. HCT preparation and readiness assessments should become a priority for adolescents/young adults with EoE/EGE and their parents.

The poem "Closing the Cabin for the Winter" by Patricia Wellingham-Jones. First line: Pine shadows stripe the blacktop; Last line: lake black in the coming cold, voices silent.

This article presents research conducted within the Vessel Traffic Service (VTS) domain. VTS is a service that is provided close to ports and geographically challenging areas to support merchant vessels in their navigation. Although VTS is legally an advice and assistance service, applying concepts from Cognitive Systems Engineering and Resilience Engineering can highlight how the joint human-machine system works to promote safe and efficient traffic movements. The VTS is a Joint Cognitive System that maintains control through a mixture of opportunistic and tactical control. Strategic control is only partially supported by the higher levels of system aggregation that provide the basis for defining daily operations within the settings of the VTS. To increase the VTS system’s ability to anticipate, respond, monitor, and learn, and therefore the ability to be resilient, there is a need to promote more strategic and tactical control within daily operations.

Design cognition research aims to investigate the cognitive mechanisms and thought processes of human designers. In previous research, the cognitive activity of experienced and inexperienced designers has been compared in order to identify design strategies leading to design creativity. However, it is still unknown whether the design strategies applied are effective and whether the design processes are efficiently improved. In this paper, cognitive efficiency, describing how designers optimize mental resources to achieve creativity in conceptual design processes, was directly measured by the mental effort of designers and the creativity level of design outcomes. The results showed that the experienced designers generated more design concepts with higher quality and variety than did the inexperienced designers. The cognitive efficiency measures indicated that design expertise contributed to improving cognitive efficiency scores of quality. In addition, the systematic design method used by some designers was found to be related to high cognitive efficiency. It can be seen that the evaluation of cognitive efficiency has practical applications for designer training, design methodology evaluation, and design process improvement.

In early 2014, a number of large-scale adverse weather events in the United States (and elsewhere) have renewed discussions of event response and resilience. Unlike events causedby human error or malicious intent, adverse natural events can be seen as uncontrolled and unpreventable; the measure of response success is the mitigation of adverse and disastrous effects. However, significant cognitive limitations interfere with human decision makers’ ability to effectively estimate likelihood, magnitude, and effective response of large-scale events in the face of multiple forms of uncertainty and system dependencies. Some authors highlight stability and maintenance of original design capability as the fundamental goal of robust and resilient response. Long-standing traditions from systems dynamics, population ecology, and process control suggest that improved understanding of system response ranges and dynamic equilibria provide a better description of effective event response. Challenges due to cognitive framing and deep uncertainty influence critical interplays of event characteristics, decision maker expertise, and resource availability. The concept of resilience boundary framingis introduced as a desirable, but difficult to achieve, goal for decision makers to respond gracefully to large-scale natural events. Examples from January and February 2014 are used to highlight these issues.

The decision sciences are increasingly challenged to advance methods for modeling analysts, accounting for both analytic strengths and weaknesses, to improve inferences taken from increasingly large and complex sources of data. We examine whether psychometric measures—personality, cognitive style, motivated cognition—predict analytic performance and whether psychometric measures are competitive with aptitude measures (i.e., SAT scores) as analyst sample selection criteria. A heterogeneous, national sample of 927 participants completed an extensive battery of psychometric measures and aptitude tests and was asked 129 geopolitical forecasting questions over the course of 1 year. Factor analysis reveals four dimensions among psychometric measures; dimensions characterized by differently motivated “top-down” cognitive styles predicted distinctive patterns in aptitude and forecasting behavior. These dimensions were not better predictors of forecasting accuracy than aptitude measures. However, multiple regression and mediation analysis reveals that these dimensions influenced forecasting accuracy primarily through bias in forecasting confidence. We also found that these facets were competitive with aptitude tests as forecast sampling criteria designed to mitigate biases in forecasting confidence while maximizing accuracy. These findings inform the understanding of individual difference dimensions at the intersection of analytic aptitude and demonstrate that they wield predictive power in applied, analytic domains.

Knowledge-sharing behavior seems to be important for team functioning and performance. A theoretical model explaining antecedents that impact knowledge-sharing behavior and its interplay with shared knowledge within teams was investigated. In the present study, we examined the effect of the individual’s intention and five organizational antecedents (team communication, perceived appraisal, organizational communication, organizational support, and social ties) on knowledge-sharing behavior. Five production and five maintenance teams (123 participants altogether) working in a steel mill took part in the study to investigate the assumed relationships. The results indicate that knowledge-sharing behavior is positively affected by intention, organizational communication, and social ties. in turn, knowledge-sharing behavior had a significant impact on the shared knowledge corresponding to the four types of shared mental models (task, equipment, interaction, team), and as a trend, teams with a higher knowledge-sharing behavior seem to have greater shared mental model similarity. The implications of the findings are discussed in terms of further research in production settings and with regard to developing a knowledge-sharing intervention.

AbstractEosinophilic esophagitis is a chronic immune-mediated disease characterized by infiltration of the esophageal mucosa with eosinophils and concomitant esophageal dysfunction. Though there are well-described associations between certain chronic inflammatory conditions and venous thromboembolism, there have been no reports of venous thromboembolism occurring in eosinophilic esophagitis. We report the case of a 33-year-old man with severe eosinophilic esophagitis resulting in recurrent esophageal strictures who was unresponsive to oral viscous budesonide therapy, and who developed an isolated pulmonary embolism in the absence of risk factors for venous thromboembolism. We then discuss potential mechanisms for venous thromboembolism in eosinophilic esophagitis, such as inflammation-mediated hypercoagulability, hypereosinophilia, and immunoglobulin E-mediated platelet activation.Copyright © 2013 S. Karger AG, Basel

Students with hearing loss attending general education classrooms have been reported to experience difficulties in social skills and relationships. This 5-year longitudinal study examined the social skills and problem behaviors of students who were deaf or hard of hearing, and who attended general education classrooms. Data were obtained from classroom teachers and students themselves. The mean Social Skills and Problem Behavior scores (Social Skills Rating Scales; Gresham & Elliott, 1990) were within the average range and normally distributed each year. The average change over 5 years in social skills and problem behavior was not significant. The most consistent predictors of social outcomes were the students' classroom communication participation and participation in extracurricular activities. Implications for placement, intervention, and further research are discussed.

In response to the global shortage of nursing faculty, Loma Linda University School of Nursing offered an off-campus master’s degree program to prepare nurse educators who would commit to remain in their home countries following graduation. The program was approved by the Western Association of Schools and Colleges to be offered in both English and Spanish. Students and faculty met for 1 month each year for 4 years at one of two international sites: Thailand or Argentina. Forty-five of 49 students completed the program. The cultural diversity in both cohorts enriched classroom discussions, social interaction, and student-faculty conversations. The program was a life-changing experience for all involved and helped to meet the global need for nursing faculty. The faculty reported that it broadened their world view and opened their minds to the potential for innovation to transform nursing education.

Human factors is a critical discipline for human spaceflight. Nearly every human factors research area is relevant to space exploration-from the ergonomics of hand tools used by astronauts, to the displays and controls of a spacecraft cockpit or mission control workstation, to levels of automation designed into rovers on Mars, to organizational issues of communication between crew and ground. This chapter focuses more on the ways in which the space environment (especially altered gravity and the isolated and confined nature of longduration spaceflight) affects crew performance and thus has specific novel implications for human factors research and practice. We focus on four aspects of human performance: neurovestibular integration, motor control and musculoskeletal effects, cognitive effects, and behavioral health. We also provide a sampler of recent human factors studies from the National Aeronautics and Space Administration.