On formal limitations of causal ecological networks.

Causal multivariate time-series analysis, combined with network theory, provide a powerful tool for studying complex ecological interactions. However, these methods have limitations often underestimated when used in graphical modelling of ecological systems. In this opinion article, I examine the relationship between formal logic methods used to describe causal networks and their inherent statistical and epistemological limitations. I argue that while these methods offer valuable insights, they are restricted by axiomatic assumptions, statistical constraints and the incompleteness of our knowledge. To prove that, I first consider causal networks as formal systems, define causality and formalize their axioms in terms of modal logic and use ecological counterexamples to question the axioms. I also highlight the statistical limitations when using multivariate time-series analysis and Granger causality to develop ecological networks, including the potential for spurious correlations among other data characteristics. Finally, I draw upon Gödel's incompleteness theorems to highlight the inherent limits of fully understanding complex networks as formal systems and conclude that causal ecological networks are subject to initial rules and data characteristics and, as any formal system, will never fully capture the intricate complexities of the systems they represent. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

A comparison of 'not just right experiences' in obsessive-compulsive disorder, anxiety and depressive disorders and non-clinical controls in China.

OBJECTIVE: The aim of this study is to investigate the characteristics of 'not just right experiences' (NJREs) in patients with obsessive-compulsive disorder (OCD), anxiety disorders (ADs) or major depressive disorder (MDD), compared with those of healthy controls (HCs). METHOD: One hundred adults with OCD, 86 adults with ADs, 57 adults with MDD and 60 HCs were enrolled in the study. The Not Just Right Experiences Questionnaire Revised (NJRE-QR), Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) were used to evaluate clinical symptoms in patients with OCD, ADs or MDD. The Obsessive Belief Questionnaire-44 (OBQ-44) was used to evaluate OC beliefs in the OCD patients. The HCs only received assessment using the NJRE-QR. Analysis of variance (ANOVA) and covariance (ANCOVA) were performed to compare the NJREs scores across the groups, while Pearson correlation and partial correlation analyses were used to examine the association between NJREs and other clinical features. The contribution of NJREs to predict OC symptoms was determined by multiple stratified linear regression. RESULTS: Individuals with OCD had significantly higher scores for the number of NJREs than ADs, but not MDD. The severity of NJREs was also significantly higher in patients with OCD than those with MDD or ADs (F = 5.23 and F = 19.79, respectively, P < 0.01). All the clinical scores in the NJRE-QR were significantly higher than those in the HC group. The number and severity of NJREs correlated significantly with the Y-BOCS total score (r = 0.29 and r = 0.39, respectively, P < 0.01). NJREs showed an independent contribution to OC symptoms, which alone explained 8% of the variation (F = 16.49, ΔR2 = 0.08; P < 0.01). CONCLUSION: NJREs are related closely to OC symptoms, with their severity discriminating between OCD patients and those with ADs or MDD. NJREs were more specific for OCD in the Chinese population and are therefore worthy of further study in the future.

Estimating Vaccine Hesitancy in Colorado by Using Immunization Information System Data.

OBJECTIVES: Vaccine hesitancy is a complex issue that threatens global health. We used data from the Colorado Immunization Information System (CIIS) to quantify vaccine hesitancy. METHODS: We examined immunization records from CIIS for patients age 2 up to 9 months to estimate vaccine hesitancy by tabulating the number of doses received per visit and comparing it with the number of expected doses based on recommendations of the Advisory Committee on Immunization Practices. We calculated the percentage of patients in each vaccine hesitancy group who were up to date on the 7-antigen series by age 35 months. We examined the distribution of vaccine-hesitant populations among vaccination providers who report to CIIS to estimate the difference in vaccine-hesitant patient populations among vaccination providers in Colorado. RESULTS: Of 201 450 patients, 5147 (2.6%) consistently limited the number of shots received at each visit as compared with recommendations from the Advisory Committee on Immunization Practices; 166 927 (82.9%) patients did not limit the number of shots received; 5693 (2.8%) limited the number of shots received at >1 visit but not all visits; and 23 683 (11.8%) limited the number of shots received at only 1 visit. We found differences in vaccine hesitancy distributions among certain Colorado vaccination providers. CONCLUSIONS: Immunization information system data, although sometimes incomplete, offer an opportunity to investigate state-level vaccine hesitancy. Areas of future research include performing similar analyses over time and determining geographic and socioeconomic factors that contribute to vaccine hesitancy.

Erratum: System principles governing the organization, architecture, dynamics, and evolution of gene regulatory networks.

[This corrects the article DOI: 10.3389/fbioe.2022.888732.].

Incompleteness features in the descriptive discourse of Chinese elders with and without Alzheimer's disease.

Alzheimer's disease (AD) can manifest itself with prominent language dysfunction. Incompleteness in discourse refers to the lack of indispensable sentence-constructing elements that hinder communication fluency and accuracy. The current study investigates how the pattern of incompleteness is associated with the descriptive discourse produced by elders without AD and those with different stages of AD. The Chinese discourse samples were collected from the picture description of 40 elders with mild probable AD (Mini-Mental State Examination (MMSE) 21-26, Montreal Cognitive Assessment Scale-Basic (MoCA-B) 15-19), 40 elders with moderate probable AD (MMSE 11-20, MoCA-B 10-14), and 40 controls (MMSE 26-29, MoCA-B 24-29). The total production of incomplete sentences and six incompleteness features were examined. The Mild AD, Moderate AD, and Control groups differed in the total output of the incomplete sentence. Group differences also emerged in four incompleteness features: missing subject, missing predicate, missing object, and missing functional word. The Moderate AD group differed from the Mild AD group with respect to most significant features, while Mild AD and Control groups were very similar. The results suggested that AD impairs the sentence construction ability of Chinese elders, especially at the later stage. These statistically significant differences between the groups might provide some references when diagnosing the risk and possibility of cognitive impairment of Chinese elders, facilitating the design of clinical evaluation or screening for probable AD.

System Principles Governing the Organization, Architecture, Dynamics, and Evolution of Gene Regulatory Networks.

Synthetic biology aims to apply engineering principles for the rational, systematical design and construction of biological systems displaying functions that do not exist in nature or even building a cell from scratch. Understanding how molecular entities interconnect, work, and evolve in an organism is pivotal to this aim. Here, we summarize and discuss some historical organizing principles identified in bacterial gene regulatory networks. We propose a new layer, the concilion, which is the group of structural genes and their local regulators responsible for a single function that, organized hierarchically, coordinate a response in a way reminiscent of the deliberation and negotiation that take place in a council. We then highlight the importance that the network structure has, and discuss that the natural decomposition approach has unveiled the system-level elements shaping a common functional architecture governing bacterial regulatory networks. We discuss the incompleteness of gene regulatory networks and the need for network inference and benchmarking standardization. We point out the importance that using the network structural properties showed to improve network inference. We discuss the advances and controversies regarding the consistency between reconstructions of regulatory networks and expression data. We then discuss some perspectives on the necessity of studying regulatory networks, considering the interactions' strength distribution, the challenges to studying these interactions' strength, and the corresponding effects on network structure and dynamics. Finally, we explore the ability of evolutionary systems biology studies to provide insights into how evolution shapes functional architecture despite the high evolutionary plasticity of regulatory networks.

Key observations in terms of management of electronic health records from a mHealth perspective.

The article is a narrative review that briefly describes some of the recent advances in healthcare data management that will have positive effect on mHealth. The advances described in this article are in fact innovation introduced by the author to the field of data management with respect to electronic health records. The research delineated is transdisciplinary in nature and will potentially have positive impact on healthcare outcomes. Also, the article illustrates the necessity for an out of the box thinking approach to improve mHealth while discussing the current impending issues related to data incompleteness of electronic health records and the much-needed decision support systems for mHealth. It is to be noted that most of the electronic health records are now accessed by patients through mobile devices. These mobile devices will run as clients while much of the heavy computing is performed using servers. Here it is important to discuss some of the important technologies and methods used for decision making. The article attempts to present a discussion on how this myriad of intertwining technologies support this decision making with respect to electronic health records. More importantly it is these processes that assist in decision making and efficiency for both mHealth users and providers. In this respect, the article first provides insights on the complexities of decision making involved with electronic health records. This is followed by a discussion on the problem of data incompleteness of electronic health records. Finally, the author provides some insights into the gravity of the problem of data incompleteness in terms of revenue loss/gain for healthcare providers.

On the necessity of importing neurobiology into mathematics.

In Gödel's Incompleteness Theorems, for every mathematical system there are correct statements that cannot be proven to be correct within that system. We here extend this to address the question of axiomatic statements that are perceived (or known) to be correct but which mathematics, as presently constituted, cannot prove. We refer to these as perceptual axioms.

The World Is Not a Theorem.

The evolution of the biosphere unfolds as a luxuriant generative process of new living forms and functions. Organisms adapt to their environment, exploit novel opportunities that are created in this continuous blooming dynamics. Affordances play a fundamental role in the evolution of the biosphere, for organisms can exploit them for new morphological and behavioral adaptations achieved by heritable variations and selection. This way, the opportunities offered by affordances are then actualized as ever novel adaptations. In this paper, we maintain that affordances elude a formalization that relies on set theory: we argue that it is not possible to apply set theory to affordances; therefore, we cannot devise a set-based mathematical theory to deduce the diachronic evolution of the biosphere.

Endangering the integrity of science by misusing unvalidated models and untested assumptions as facts: General considerations and the mineral and phosphorus scarcity fallacy.

There is increasing demand for science to contribute to solving societal problems (solutionism). Thereby, scientists may become normative activists for solving certain problems (advocacy). When doing this, they may insufficiently differentiate between scientific and political modes of reasoning and validation (de-differentiationism), which is sometimes linked to questionable forms of utilizing the force of facts (German: Faktengewalt). Scientific findings are simplified and communicated in such a way that they acquire a status as unfalsifiable and absolutely true (truth to power). This becomes critical if the consistency and validation of the findings are questionable and scientific models underlying science activists' actions are doubtful, oversimplified, or incorrect. Herein, we exemplarily elaborate how the integrity of science is endangered by normative solutionist and sociopolitically driven transition management and present mineral scarcity claims that ignore that reserves or resources are dynamic geotechnological-socioeconomic entities. We present the main mineral scarcity models and their fallacious assumptions. We then discuss the phosphorus scarcity fallacy, which is of particular interest as phosphorus is non-substitutable and half of all current food production depends on fertilizers (and thus phosphorus). We show that phosphorus scarcity claims are based on integrating basic geoeconomic knowledge and discuss cognitive and epistemological barriers and motivational and sociopolitical drivers promoting the scarcity fallacy, which affects high-level public media. This may induce unsustainable environmental action. Scientists as honest knowledge brokers should communicate the strengths but also the constraints and limits of scientific modeling and of applying it in reality. Supplementary Information: The online version contains supplementary material available at 10.1007/s11625-021-01006-w.

Action inhibition in individuals with high obsessive-compulsive trait of incompleteness: An ERP study.

BACKGROUND: Missing action completion signals are assumed to trigger repetitive behavior and feelings of the action "not being right". This proposal is based mostly on individual's self-reports. Here, we investigated the influence of experimentally manipulated action completion experience and the obsessive-compulsive (OC) trait of incompleteness on behavioral and neurophysiological measures of action inhibition. METHODS: Action completion was manipulated in an adapted Go/NoGo task, and OC trait incompleteness was assessed in healthy participants. More commission errors and faster responses were expected after missing action completion, especially for individuals with high OC trait incompleteness. The inhibition-related event-related potentials (ERPs) N200 and P300 were also measured. RESULTS: High OC trait incompleteness led to more errors following omitted- and faster responses during commission errors following incongruent outcomes. Furthermore, lower N200 was associated with worse response inhibition, and high OC trait incompleteness was associated with reduced N200, but not reduced P300 amplitude. These findings provide evidence that trait-like feelings of incompleteness may underlie maladaptive action repetition and impaired inhibitory control as observed in OCD.

Incompleteness and Disgust Predict Treatment Outcome in Pediatric Obsessive-Compulsive Disorder.

Increasing evidence suggests that pediatric obsessive-compulsive disorder (OCD) is motivated not only by fear but also by feelings of incompleteness and disgust. However, it is currently unclear whether emotion involvement in OCD symptoms is associated with treatment response in youth with OCD. The present study examined whether treatment outcome for youth with OCD was predicted by the degree to which fear, disgust, and incompleteness were involved in baseline OCD symptoms. Children and adolescents with OCD entering treatment for this condition (N = 111) were administered standardized OCD symptom measures and an interview designed to assess the degree of fear, incompleteness, and disgust experienced during current OCD symptoms. Follow-up assessments occurred on average 13 months after baseline with each participant coded for outcome according to internationally acknowledged change criteria for pediatric OCD. Higher levels of incompleteness and disgust as part of baseline OCD symptoms predicted poorer outcome. The degree of fear during baseline OCD symptoms did not predict outcome. If replicated under controlled conditions, these results suggest that incompleteness and disgust may act as barriers to improvement in pediatric OCD and that treatment modifications that target these emotion-related motivators may improve outcome for a subset of youth.

Involvement of fear, incompleteness, and disgust during symptoms of pediatric obsessive-compulsive disorder.

Fear has been assigned a central role in models of obsessive-compulsive disorder (OCD), but empirical investigations into the emotions that underpin OCD symptoms are few, especially in pediatric samples. Using validated, clinician-led structured interviews, 124 youth with OCD reported on the presence and severity of symptoms across the main symptom dimensions of OCD (aggressive, symmetry, contamination) and the degree to which fear, incompleteness, and disgust accompanied these symptoms. For comparison purposes, the degree of fear, incompleteness, and disgust during symptoms was obtained also from youth with social anxiety disorder (SAD; n = 27) and generalized anxiety disorder (GAD; n = 28). Participants with OCD reported that all three emotions were involved in their symptoms; however, fear was most strongly linked to aggressive symptoms, incompleteness to symmetry symptoms, and disgust to contamination symptoms. Incompleteness differentiated youth with OCD from those with SAD and GAD. No differences for these emotions were found for youth with OCD with versus without the tic-disorder subtype or comorbid autism. A positive association between incompleteness and self-reported hoarding emerged among youth with OCD. Further studies of the emotional architecture of pediatric OCD, and its relationship to etiology and treatment, are warranted.

Core Motivations of Childhood Obsessive-Compulsive Disorder: The Role of Harm Avoidance and Incompleteness.

In an effort to improve patient conceptualization and targeted treatment, researchers have sought to accurately classify OCD subtypes. To date, the most common form of OCD classification has used the content of symptom topography as opposed to functional links between symptoms to categorize OCD. The aim of the current study was to explore the associations between these two forms of OCD classification. Participant topographical symptoms were self-reported using the Obsessive-Compulsive Inventory-Child Version (OCI-CV). Clinicians assessed whether participant symptoms were motivated by harm avoidance and/or incompleteness. Structural equation modeling was employed to explore the associations between harm avoidance and incompleteness and symptom dimensions in youth with OCD. Results showed that harm avoidance was significantly associated with doubting/checking, obsessing, and neutralizing symptoms, whereas incompleteness was associated with doubting/checking, ordering, and neutralizing symptoms. Findings are consistent with child and adult literature and highlight the importance of assessing the underlying function of OC behaviors.

On the Classification Between ψ -Ontic and ψ -Epistemic Ontological Models.

Harrigan and Spekkens (Found Phys 40:125-157, 2010) provided a categorization of quantum ontological models classifying them as ψ -ontic or ψ -epistemic if the quantum state ψ describes respectively either a physical reality or mere observers' knowledge. Moreover, they claimed that Einstein-who was a supporter of the statistical interpretation of quantum mechanics-endorsed an epistemic view of ψ . In this essay we critically assess such a classification and some of its consequences by proposing a twofold argumentation. Firstly, we show that Harrigan and Spekkens' categorization implicitly assumes that a complete description of a quantum system (its ontic state, λ ) only concerns single, individual systems instantiating absolute, intrinsic properties. Secondly, we argue that such assumptions conflict with some current interpretations of quantum mechanics, which employ different ontic states as a complete description of quantum systems. In particular, we will show that, since in the statistical interpretation ontic states describe ensembles rather than individuals, such a view cannot be considered ψ -epistemic. As a consequence, the authors misinterpreted Einstein's view concerning the nature of the quantum state. Next, we will focus on relational quantum mechanics and perspectival quantum mechanics, which in virtue of their relational and perspectival metaphysics employ ontic states λ dealing with relational properties. We conclude that Harrigan and Spekkens' categorization is too narrow and entails an inadequate classification of the mentioned interpretations of quantum theory. Hence, any satisfactory classification of quantum ontological models ought to take into account the variations of λ across different interpretations of quantum mechanics.

Taxon incompleteness and discrete time bins affect character change rates in simulated data.

Estimating how fast or slow morphology evolves through time (phenotypic change rate, PR) has become common in macroevolutionary studies and has been important for clarifying key evolutionary events. However, the inclusion of incompletely scored taxa (e.g. fossils) and variable lengths of discrete arbitrary time bins could affect PR estimates and potentially mask real PR patterns. Here, the impact of taxon incompleteness (unscored data) on PR estimates is assessed in simulated data. Three different time bin series were likewise evaluated: bins evenly spanning the tree length (i), a shorter middle bin and longer first and third bins (ii), and a longer middle bin and shorter first and third bins (iii). The results indicate that PR values decrease as taxon incompleteness increases. Statistically significant PR values, and the dispersion among PR values, depended on the time bins. These outcomes imply that taxon incompleteness can undermine our capacity to infer morphology evolutionary dynamics and that these estimates are also influenced by our choice of discrete time bins. More importantly, the present results stress the need for a better approach to deal with taxon incompleteness and arbitrary discrete time bins.

Inducing and manipulating sensations of incompleteness.

Incompleteness (INC) and Harm Avoidance (HA) are known core dimensions of obsessive-compulsive disorder (OCD). Emotional processing and inhibitory learning (IL) have both been proposed as viable mechanisms of exposure for the alleviation of HA, yet the relationship with INC remains unclear. This study evaluated differential manipulation responses to induced INC. The authors specifically tested whether targeting the key component of IL, expectancy violation generated by the discrepancy between an articulated prediction and the actual exposure experience, would lead to improved outcomes. A sample of undergraduates (N = 68) completed a series of behavioral tasks to induce INC, followed by manipulations (exposure with or without articulated predictions) to reduce INC reactions. Results show that modest changes were observed following reduction manipulations following INC induction. Furthermore, heightened HA predicted the changes of induced sensations. Mediation tests showed that articulation of predicted sensations mediated pre- to postreduction ratings. Clinical and research implications are discussed.

Preventive healthcare policies in the US: solutions for disease management using Big Data Analytics.

Data-driven healthcare policy discussions are gaining traction after the Covid-19 outbreak and ahead of the 2020 US presidential elections. The US has a hybrid healthcare structure; it is a system that does not provide universal coverage, albeit few years ago enacted a mandate (Affordable Care Act-ACA) that provides coverage for the majority of Americans. The US has the highest health expenditure per capita of all western and developed countries; however, most Americans don't tap into the benefits of preventive healthcare. It is estimated that only 8% of Americans undergo routine preventive screenings. On a national level, very few states (15 out of the 50) have above-average preventive healthcare metrics. In literature, many studies focus on the cure of diseases (research areas such as drug discovery and disease prediction); whilst a minority have examined data-driven preventive measures-a matter that Americans and policy makers ought to place at the forefront of national issues. In this work, we present solutions for preventive practices and policies through Machine Learning (ML) methods. ML is morally neutral, it depends on the data that train the models; in this work, we make the case that Big Data is an imperative paradigm for healthcare. We examine disparities in clinical data for US patients by developing correlation and imputation methods for data completeness. Non-conventional patterns are identified. The data lifecycle followed is methodical and deliberate; 1000+ clinical, demographical, and laboratory variables are collected from the Centers for Disease Control and Prevention (CDC). Multiple statistical models are deployed (Pearson correlations, Cramer's V, MICE, and ANOVA). Other unsupervised ML models are also examined (K-modes and K-prototypes for clustering). Through the results presented in the paper, pointers to preventive chronic disease tests are presented, and the models are tested and evaluated.

Explanatory completeness.

All explanations are incomplete, but reasoners think some explanations are more complete than others. To explain this behavior, we propose a novel theory of how people assess explanatory incompleteness. The account assumes that reasoners represent explanations as causal mental models - iconic representations of possible arrangements of causes and effects. A complete explanation refers to a single integrated model, whereas an incomplete explanation refers to multiple models. The theory predicts that if there exists an unspecified causal relation - a gap - anywhere within an explanation, reasoners must maintain multiple models to handle the gap. They should treat such explanations as less complete than those without a gap. Four experiments provided participants with causal descriptions, some of which yield one explanatory model, e.g., A causes B and B causes C, and some of which demand multiple models, e.g., A causes X and B causes C. Participants across the studies preferred one-model descriptions to multiple-model ones on tasks that implicitly and explicitly required them to assess explanatory completeness. The studies corroborate the theory. They are the first to reveal the mental processes that underlie the assessment of explanatory completeness. We conclude by reviewing the theory in light of extant accounts of causal reasoning.