Cause-effect Relationship Research Articles

Surprising Role for Immune Cells in Mood and Memory: Impact of Regulatory T Cells

Chronic stress manifests as depressive- and anxiety-like behavior while recurrent stress elicits disproportionate psychiatric responses linked to stress-induced immunological priming. Based on this evidence, we explored causative mechanisms of how dietary polyphenolics influence Regulatory T Cells and explored their role in preventing mood disorder and Alzheimer’s disease (AD) type cognitive deterioration and neuropathology. Using a conditional Treg depletion transgenic mouse model (Foxp3 cKO), we investigated the cause-effect relationship of Treg expression in mood disorder and AD phenotype preclinically. Interestingly depression and anxiety-like behavior coincide with cognitive decline and AD-type Aβ burden in Foxp3 cKO/5xTg-AD mice by transient depletion of FoxP3. Our studies tentatively support strategies to attenuate Treg immune responses as a potential preventative strategy in attenuating AD-type phenotype.

Learning Entangled Interactions of Complex Causality via Self-Paced Contrastive Learning

Learning causality from large-scale text corpora is an important task with numerous applications—for example, in finance, biology, medicine, and scientific discovery. Prior studies have focused mainly on simple causality, which only includes one cause-effect pair. However, causality is notoriously difficult to understand and analyze because of multiple cause spans and their entangled interactions. To detect complex causality, we propose a self-paced contrastive learning model, namely N2NCause, to learn entangled interactions between multiple spans. Specifically, N2NCause introduces data enhancement operations to convert implicit expressions into explicit expressions with the most rational causal connectives for the synthesis of positive samples and to invert the directed connection between a cause-effect pair for the synthesis of negative samples. To learn the semantic dependency and causal direction of positive and negative samples, self-paced contrastive learning is proposed to learn the entangled interactions among spans, including the interaction direction and interaction field. We evaluated the performance of N2NCause in three cause-effect detection tasks. The experimental results show that, with the least data annotation efforts, N2NCause demonstrates competitive performance in detecting simple cause-effect relations, and it is superior to existing solutions for the detection of complex causality.

Do foreign investors trading behaviors affect mutual fund performances or vice versa?

This paper is to examine the trading behavior, buy and sell, by foreign investors: institutional and retail investors, on the performance of the mutual funds (information contribution effect). The impact of mutual funds performances on the trading behavior (feedback effect) of foreign investors are also to be investigated. Since there have been increasing demand for much more secured and cheaper investment, such as mutual funds, the study on these funds is crucial. Granger causality, Spearman’s rho and Vector Autoregressive model analyses are applied on daily data of foreign institutional and retail buy, sell and net flows volume and Malaysia’s average mutual fund returns from 1st October 2009 to 31st December 2019. The findings reveal that only foreign retail investors have cause-effect relationships with the performance of the mutual funds. Thus, mutual funds companies, especially in the emerging countries, should be given more attention to foreign retail investors in attracting them to remain invest in our mutual funds for long-term. Having better anticipated returns would also discourage those foreign retail investors from selling the funds, indeed, would motivate them to contribute more into the funds. The findings would be able to guide the Mutual Fund companies in managing and promoting foreign investors and enhancing the mutual funds performances.

Navigating the Emotional Classroom: How experience shapes educators' anxiety and self-worth

Most of the teaching staff agrees that traits such as "personality" or "mental integrity", along with behavioral manifestations, show substantial significance in the context of the classroom; some of them might even argue that these character attributes have a higher relevance than competence in the specialized field or teaching skills themselves. When an educator experiences failures, they are often attributed to inadequacies of a personal nature, including but not limited to suboptimal empathy, excessive or insufficient enthusiasm, or, as appropriate, excessive authoritarianism, inflexibility, or, conversely, excessive permissiveness. The sphere of stress, tension and anxiety, respectively, within the teaching body is configured as a compartment of the personality and mental health of teachers, which has been almost neglected from a cause-effect relationship perspective. Many postgraduate protagonists went to great lengths to emphasize that dealing with and managing anxiety turned out to be experiences of exceptional significance in the context of their subsequent professional work. A substantial segment of this population showed a strong inclination towards careful consideration of anxiety as a central theme in the educational sphere. As a comprehensive entity, frequently accompanied by an implicit nuance or predispositional character (ie, acting as an internal cause of manifested behavior), anxiety lends itself to multiple operational definitions. The prevalence of various forms of emotional maladjustment, especially anxiety, among the teaching staff has been a subject of sustained research since the first decades of this century. Self-esteem is a trait dedicated to the individual characteristic affective evaluation of one's own person. It is assumed that the level of self-efficacy of the teaching staff is influenced by the degree of self-esteem they show. Thus, the hypothesis is drawn that self-esteem plays an essential role in the academic itinerary of the teachers. A positive self-evaluation intrinsically facilitates the individual's professional development, translated into visible and consistent performance over the relevant time period.

Posterior assessment of airborne non-carcinogenic health risk of the population of a large industrial center

Introduction. This article suggests an alternative solution to the task of quantifying and describing health harm under exposure to non-carcinogenic risk factors.
 Materials and methods. We have developed and tested a methodical approach that includes five subsequent steps; it is eligible for posterior quantification of non-carcinogenic health risks represented by additional diseases cases associated with poor ambient air quality. The approach relies on unified and validated methods for assessing exposure and health risks, mathematical parameterization of cause-effect relations within the "environment – public health" system, and calculation of additional incidence as well as combined assessment of all the obtained results.
 Results. According to calculated data, which were also verified by instrumental observations of ambient air quality, the existing hygienic standards are violated as per 27 chemicals in residential areas. Elevated hazard quotients are identified for 26 chemicals (up to 98.7HQac; up to 62.7HQch). Additive effects of the analyzed chemicals crated elevated hazard indices (HI) in residential areas that could be ranked as "alerting" (3<HI≤6) and "high" (HI>6) for respiratory organs, the cardiovascular and hematopoietic systems, liver, kidneys, eyes, development, the immune, reproductive, endocrine, and other systems. The identified levels of airborne exposure annually cause approximately 80.9 thousand additional diseases among the total population (71.0‰; 4.15% of the total incidence); 
 23 chemicals are considered priority risk factors (contributions vary between 0.25 and 65.0%). We have identified certain regularity for some disease classes: higher levels of additional incidence associated with ambient air quality are established in zones with higher airborne health risks. Thus, in zones where airborne risks for respiratory organs are HIch≤1, we identified no additional incidence as per such diseases; in zones with 1<HIch≤3 (with population being 800 people), additional incidence reaches 1.57‰ for the total population; 3<HIch≤6 (more than 100 thousand people), 3.25‰; HIch>6 (more than 1.09 million people), 5.0‰.
 Limitations. The suggested approaches have been obtained by calculation. Their results might differ from those obtained by targeted in-depth investigations aimed at creating an evidence base of health harm under adverse environmental conditions that do not conform to hygienic standards. The parameters of mathematical models within "the environment – public health" system have been obtained for a limited range of exposure to pollutants in ambient air and a limited list of airborne health risk factors.
 Conclusion. The suggested methodical approaches to posterior assessment of non-carcinogenic health risks allows quantifying these health risks as additional diseases associated with poor quality of the environment; they enlarge the results of health risk assessment and make them more precise, validate and support them with hygienic significance. They can be utilized within optimization of social and hygienic monitoring and assessment of effectiveness of implemented prevention activities.

The mediating role of dietary inflammatory index on the association between eating breakfast and depression: Based on NHANES 2007–2018

BackgroundDepression is a significant, pervasive, global public health problem, associated with many factors, such as diet, social factors, and lifestyle habits. We aimed to evaluate the association between eating breakfast, dietary inflammatory index (DII) and depression, and to verify the mediating role of DII on the effect of eating breakfast on depression. Methods21,865 participants from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018 were included in this study. Binary logistic regression and mediated effect analysis were conducted to analyze the associations between eating breakfast, DII and depression. Dietary inflammation was divided into pro-inflammatory diet and anti-inflammatory diet according to the DII. ResultsBoth pro-inflammatory diet and skipping breakfast were risk factors for depression. After adjusting for covariables, compared with participants reporting breakfast in both recalls, reporting breakfast in one recall had a higher OR 95%CI (1.54(1.20, 1.98)) of depression. These associations in stratified analysis and sensitivity analysis without cardiovascular diseases (CVD) and diabetes were robust. DII mediated the association between eating breakfast and depression, the proportion of participants who reported breakfast in one recall and no recall was 26.15 % and 26.67 %, respectively. LimitationsThis was a cross-sectional study that couldn't argue for the cause-effect relationship. Moreover, the confounding factor regarding medication use was not accounted for due to limited data. ConclusionsSkipping breakfast may increase the risk of depression by raising DII. And our study supported the essential role of regular breakfast and the anti-inflammatory diet in reducing the risk of depression.

Air quality and characterization of synoptic circulation weather patterns in a South American city from Argentina

The potential cause-effect relationship between synoptic meteorological conditions and levels of criteria air pollutants, including CO, NO2, O3, PM10, PM2.5 and SO2, in Bahia Blanca, Argentina, was assessed for the period of 2018–2019. Daily back-trajectories and global meteorological data fields were employed to characterize the primary transport paths of air masses reaching the study site, and to identify the synoptic meteorological patterns responsible for these atmospheric circulations. Time series of surface-level meteorological parameters and midday mixing layer height were collected to examine the impact of the synoptic meteorological patterns on local meteorology. Furthermore, the NAAPS global aerosol model was utilized to identify days when contributions from long-range transport processes, such as dust and/or biomass burning smoke, impacted air quality. By applying this methodology, it was determined that the air masses coming from the N, NW and W regions significantly contributed to increased mean concentrations of coarse particles in this area through long-range transport events involving dust and smoke. Indeed, the high average levels of PM10 recorded in 2018–2019 (annual mean values of 47 and 52 μg/m3, respectively) represent the main air quality concern in Bahía Blanca. Moreover, PM10, PM2.5 and NO2 emissions should be reduced in order to meet recommended air quality guidelines. On the other hand, the results from this study suggest that the sources and meteorological processes leading to the increase in the concentrations of CO and SO2 have a local-regional origin, although these air pollutants did not reach high values probably as a consequence of the strong wind speed registered in this region during any synoptic meteorological pattern.

Municipal solid waste management: Identification and analysis of technology selection criteria using Fuzzy Delphi and Fuzzy DEMATEL technique

Municipal solid waste management (MSWM) poses a considerable challenge to developing countries like Bangladesh because of the rising waste generation rates and lack of effective management practices such as illegal open dumping and informal waste collection. One of the crucial factors in the successful management of MSW is to select the appropriate technology which is a complex multi-criteria and laborious process. Despite the global emphasis on the importance of MSWM in the literature, there is a lack of studies conducted in developing countries that effectively identify and analyze the critical performance criteria for appropriate technology selection. This research aims to address this shortcoming by identifying, and prioritizing the selection criteria and finally investigating the inter-relationship between them and the degree to which they affect or are affected by one another. First, a thorough literature review and expert consultation were employed to determine a set of 21 key criteria using the Fuzzy Delphi method (FDM). Later, taking into account the imprecise and subjective nature of the DEMATEL method on human judgements, the Fuzzy DEMATEL technique was employed to investigate the cause-effect relationships among the identified criteria. The findings of the study demonstrated that 14 criteria were categorized as causal elements that have the most significant influence on the MSWM technology selection process and 7 criteria were categorized as effect. The selection of MSWM technology demands greater consideration of the top three ranked criteria, namely T4- Access to Technology (AT), T8- Feasibility (F), and the Ec6-Infrastructure requirements (IR). By identifying the pertinent criteria, structures and interrelationships, the outcome of the study can facilitate a better understanding of causal relationships among the criteria that require specific consideration from the decision-makers and allow them to select appropriate MSW management technology.

The Impact of Effective Leadership in the Digital Age on Organizational Effectiveness

Abstract The accelerated expansion of the global economic milieu, catalyzed by the inception of the Internet, has facilitated seamless communication across nations. This phenomenon has induced a transformation in the business landscapes of individual countries, escalating market competitiveness annually. The pervasive incorporation of contemporary technologies within organizations profoundly impacts the skill set, anticipations, cognizance, and overall structure and execution of work within the workforce. Modern leadership is often encapsulated under various nomenclatures such as digital leadership, e-leadership, and eHRM. These terminologies serve as comprehensive descriptors encompassing the realms of digitalization, Information Technology (IT), and Human Resource Management (HRM). Consequently, it becomes imperative to comprehend the disparities between traditional and virtual settings, acknowledge the significance of digital technology in leadership paradigms, identify potential challenges, and cultivate requisite leadership skills. The proposed research explores the correlation between leadership and organizational efficacy within multinational corporations. The focus is on discerning potential cause-effect relationships, aligning with the positivist paradigm. The investigation will employ a deductive approach, congruent with positivist hypotheses, deemed suitable for probing this query.

Exploring the endogenous effects among car dependency, work arrangement choice, and daily travel using the 2017 NHTS data

The paper presents an effort in investigating the cause-effect relationships among telecommuting, car dependency, and trip making behavior. Data from the 2017 National Household Travel Survey (NHTS) was used to develop a structural equations model (with latent constructs) to examine the endogenous effects between the decision to telework, the degree of car dependency, and the number of daily trips. Using confirmatory factor analysis, car dependency was measured by vehicle ownership, annual mileage, and car use frequency. The model provided interesting insights. Car dependency had a negative (both direct and total) impact on telework, an inference that confirms the role of car dependency as a resistant factor against alternative work arrangements and potentially any other new tech-based policies. In the opposite direction and surprisingly, telework encouraged car dependency, which might indicate that teleworkers tended to utilize the relaxed temporal-spatial constraints for non-work trips, and they were unlikely to give up private vehicle ownership simply because of their option to telecommute. Second, number of daily trips tended to increase the probability to telework, confirming the positive endogenous role of daily activity patterns on work arrangement decisions in a daily framework. Lastly, the significant negative impact of telework on daily trips was positively mediated through car dependency, leading to a smaller negative total impact on daily trips. Our study confirms that the association between telework and trip generation is quite a complex and multi-faceted relationship, leaving the argument regarding whether or not telework increases the number of daily trips as a debatable topic that calls for further exploration.

DOMINO: Visual Causal Reasoning With Time-Dependent Phenomena.

Current work on using visual analytics to determine causal relations among variables has mostly been based on the concept of counterfactuals. As such the derived static causal networks do not take into account the effect of time as an indicator. However, knowing the time delay of a causal relation can be crucial as it instructs how and when actions should be taken. Yet, similar to static causality, deriving causal relations from observational time-series data, as opposed to designed experiments, is not a straightforward process. It can greatly benefit from human insight to break ties and resolve errors. We hence propose a set of visual analytics methods that allow humans to participate in the discovery of causal relations associated with windows of time delay. Specifically, we leverage a well-established method, logic-based causality, to enable analysts to test the significance of potential causes and measure their influences toward a certain effect. Furthermore, since an effect can be a cause of other effects, we allow users to aggregate different temporal cause-effect relations found with our method into a visual flow diagram to enable the discovery of temporal causal networks. To demonstrate the effectiveness of our methods we constructed a prototype system named DOMINO and showcase it via a number of case studies using real-world datasets. Finally, we also used DOMINO to conduct several evaluations with human analysts from different science domains in order to gain feedback on the utility of our system in practical scenarios.

Fault diagnosis-based SDG transfer for zero-sample fault symptom

The traditional fault diagnosis models cannot achieve good fault diagnosis accuracy when a new unseen fault class appears in the test set, but there is no training sample of this fault in the training set. Therefore, studying the unseen cause-effect problem of fault symptoms is extremely challenging. As various faults often occur in a chemical plant, it is necessary to perform fault causal-effect diagnosis to find the root cause of the fault. However, only some fault causal-effect data are always available to construct a reliable causal-effect diagnosis model. Another worst thing is that measurement noise often contaminates the collected data. The above problems are very common in industrial operations. However, past-developed data-driven approaches rarely include causal-effect relationships between variables, particularly in the zero-shot of causal-effect relationships. This would cause incorrect inference of seen faults and make it impossible to predict unseen faults. This study effectively combines zero-shot learning, conditional variational autoencoders (CVAE), and the signed directed graph (SDG) to solve the above problems. Specifically, the learning approach that determines the cause-effect of all the faults using SDG with physics knowledge to obtain the fault description. SDG is used to determine the attributes of the seen and unseen faults. Instead of the seen fault label space, attributes can easily create an unseen fault space from a seen fault space. After having the corresponding attribute spaces of the failure cause, some failure causes are learned in advance by a CVAE model from the available fault data. The advantage of the CVAE is that process variables are mapped into the latent space for dimension reduction and measurement noise deduction; the latent data can more accurately represent the actual behavior of the process. Then, with the extended space spanned by unseen attributes, the migration capabilities can predict the unseen causes of failure and infer the causes of the unseen failures. Finally, the feasibility of the proposed method is verified by the data collected from chemical reaction processes.

Association Vs Causation: Epidemiologic Clues As to the Autoimmune Pathogenesis of MDS

Multiple clinical associations of MDS and autoimmunity have been described, but the pathogenesis and cause-effect relationship are likely diverse and possibly intertwining. Telomeropathies, while increasing risk of bone marrow failure, can be also associated with liver or lung fibrosis and therapies for Wegener's granulomatosis can predispose to MDS. Moreover, clonal hematopoiesis (CH) seems to be more prevalent in some autoimmune diseases 1 (AD) perpetuating a process that may ultimately lead to increased risk of MDS. Reverse scenarios are also possible and AD can be a result of MDS as a form of paraneoplastic syndrome. The recently established relationship of somatic UBA1 mutations and MDS with autoimmune manifestations exemplifies such a scenario e.g., VEXAS syndrome 2. This remarkable configuration prompted us to systematically investigate the relationships between autoimmune symptomatology and MDS including genomic features such as UBA1 mutations, pathomorphological phenotypes, and demographics. We have investigated 1,903 MDS patients for the presence and the anamnestic evidence of AD. A total of 197 patients (about 10%) had a concurrent well-defined AD (5.3%) or positive inflammatory/autoimmune markers (4.9%; fibromyalgia and chronic fatigue syndrome invoked 0.3% of MDS cases and were not counted). Of those, polymyalgia rheumatica, systemic lupus erythematosus and rheumatoid arthritis were most common accounting for 13%, 5.5% and 19% of MDS cases with autoimmunity. The remaining 60% involved the presence of serological markers such as ANA, anti-RNP and anti-SSA among others (45%, 4%, 2%, respectively) without fulfilling the criteria for specific autoimmune entities. The gender distribution of cases with MDS/autoimmune features was similar to the general MDS demographics and cases without autoimmune conditions. A similar distribution was seen among males and females in both groups, with males representing 84% of each subgroup and females accounting for 16%. When stratified by risk criteria, 58% of patients with MDS/AD were found to have low risk disease (<5% of blasts) compared to patients without AD (46%; p= .74), while intermediate to high risk (HR) categories were seen in 42% and 52% (p= .74), respectively. While trisomy 8 and complex karyotype were underrepresented in MDS with AD (15% vs 22%, 4.5% vs 10%), del(11q), del(12q) and del(20q) were more common among patients with AD (10% vs 5.8%). When we screened the genomic landscape of AD/MDS, we found more mutations in TET2 (24 vs 13%, p= .004), SF3B1 (14 vs 8%, p= .026), BCORL1 (5 vs 1.5%, p= .026), DNMT3A (13 vs 6%, p= .003), IDH1 (3 vs 0.8%, p= .01), and CEBPA (3 vs 0.8%, p= .04) compared to patients without AD ( Fig.1) With a median follow up of 19 months, female patients with AD showed better 1-year survival rate of 89% vs 65% in cases without AD, (p= .044). A similar trend was seen for transformation to AML. However, such differences were not found among males. Next, we determined the etiologic fraction of the MDS/AD clinical dyad explained by the presence of VEXAS by screening UBA1 mutation in our cohort. We found mutations in 0.5% of MDS/AD vs 0.05% of the total cohort (p=0.1). To further expand on MDS association with AD, we investigated other potential autoimmune syndromes and found 0.5% of MDS with co-associated LGL with 1/3 of them presenting with RA. Notably, in the hypocellular MDS subgroup (n=175), 9.7% had concomitant AD (p= .89). Similarly, 0.3% of evaluable patients had Sweet syndrome, of which 16% associated with autoimmune conditions. Finally, since AD appear to be frequent in MDS, we queried whether in our internal cohort of CHIP patients (n=115), their prevalence could be analogous. Indeed, AD were present in a fraction similar to that of manifest MDS (around 5%). Moreover, in all of these patients, similar to those with MDS, the autoimmune diagnosis preceded that of CHIP with the caveat that, unlike MDS, CHIP may have evolved much sooner than the original diagnosis but was not screened. Our study provides valuable insights into the intricate relationship between MDS and AD. Our findings demonstrate that MDS and autoimmunity are linked through diverse mechanisms, with potential cause-effect relationships existing in both directions. Figure 1. Frequency of mutations Graph shows frequency of mutations among patients with autoimmune diseases (AD) in MDS versus those without AD.* p<0.05, **p<0.001.

Managing open loop water resource value chain through IoT focused decision and information integration (DII) modelling using fuzzy MCDM approach

Water is a limited and invaluable resource that is essential for human survival. Negligence and unregulated water use have brought about a global water crisis. Proper management with a relevant decision and information integration approach can aid water to continue as a renewable resource. The water and wastewater industry must shift from outmoded, inefficient techniques to more sustainable, data-driven solutions to address water concerns and improve public health. The Internet of Things (IoT) has emerged as an innovative strategy for decision and information integration to drive an open-loop Water Value Chain (WVC) efficiently. The IoT-driven network allows objects to connect and communicate, gather data in real-time, analyze data and develop reasonable decision – making insights instantaneously. This study aims to find the enablers of IoT for an open-loop WVC. It examines 25 factors for IoT implementation in the open-loop WVC. The 25 factors are clustered into seven enablers using Principal Component Analysis (PCA). These principal components are analyzed by employing a Multi-Criteria Decision Making (MCDM) approach, i.e., the Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), which helps to find the cause-effect relationship to prioritize the enablers. The fuzzy set theory is used to address the uncertainty and vagueness in experts' opinions and data deficiency problems. The study reveals that the Ecosystem of an IoT network, IoT network configuration and adaptation and data mobility in an IoT network are the most prominent enablers to consider for the implementation of IoT in an open loop WVC. The study may be helpful for regulatory agencies and enterprises in water distribution and processing for identifying and prioritizing the potential enablers of IoT in an open-loop WVC.

Returns and Asymmetric Volatility Interdependencies between Sustainable and Conventional Stock Indices: Evidence from Developed and Emerging Countries

The study investigates the co-integration and asymmetric volatility interdependence between the sustainable and conventional stock indices of emerging and developed countries. Daily closing values are used from 1st January 2015 to 15th July 2022. The study employs ARDL and VAR-Granger causality model to examine long-run association and cause-effect relation, respectively. Moreover, the Bivariate EGARCH model is also used to analyse return and asymmetric volatility spillover between two indices. The analysis reveals no evidence of co-integration between sustainable and conventional indices. However, bidirectional causality exists in all countries except the United Kingdom (UK) and United Arab Emirates (UAE). The return spillover result exhibits that return of the conventional index of Japan and Brazil are negatively affected by changes in its sustainable index. The EGARCH results reveal the bidirectional volatility spillover in all the markets. The volatility shocks from the sustainable index of the United States of America (USA) and China have an asymmetric effect on the conventional indices of these countries. Further, positive asymmetric spillover was observed between the sustainable and conventional indices of Brazil and UK. The knowledge of linkage and asymmetric volatility spillover will assist the investors in portfolio management and formulating hedging strategies during financial and economic adversities.

Evaluation of the peculiarity of the combined action of a number of chemicals based on the analysis of parameterized cause-effect relationships of marketers of exposure and negative effects and quantitative evaluation of additional health risk

Introduction. Assessing the type of combined action of chemicals is a complex and pressing problem of hygiene and preventive medicine.
 
 The purpose of the work is to expand methodological approaches to assessing the characteristics of the combined interaction of a number of chemical substances based on the analysis of parameterized cause-and-effect relationships of exposure and negative effects and quantitative assessment of additional health risks.
 
 Materials and methods. There was applied basic multiple logistic regression model, which is an assessment of the probability of developing a negative effect simultaneously with the isolated and combined effects of substances. The model was implemented for three components, the exposure of which was confirmed by exposure to biomarkers. Expert assessment of the type of combined action, carried out taking into account the regression coefficients of the adopted models. Quantitative assessment of the additional risk of negative effects from isolated and combined exposure to substances is carried out according to the parameters of cause-and-effect relationships of exposure to biomarkers and effects. Approbation of the methodological method provided for conditions of exposure to short-term aerogenic exposure to benzo(a)pyrene, significantly exceeding the reference concentrations (15.4 Rfc), with combustion oxide and hydrofluoride at the level of reference indicators (0.2–0.8 Rfc). The results of a study of cause-and-effect relationships based on previously conducted (in 2021–2022) medical examinations of four hundred fifty four exposed and unexposed 4-7 years children were used as biomarker effects.
 
 Results. Depending on the binary combination of three chemical substances and the choice of biomarker of the negative effect (8 indicators), various options for the combined action were identified (24 options in total). For 10 of them, an increase in the adverse effect was established. The predominant nature of the action is the synergistic nature, which causes, in addition to the isolated one, the risk of developing negative effects on the part of the immune, bone and nervous systems, exceeding up to 56.8 times the acceptable level.
 
 Limitations. During the combination effect, there was measured the substance in a binary combination of substances, taking into account the adverse effect and the direction of biomarkers.
 
 Conclusion. In the practice of hygienic assessments, it is necessary to take into account the additional risk of developing negative effects with more complex types of combined action (synergism, antagonism) than simple summation, which will increase the objectivity of the hygienic assessment of the risk to the health of the exposed population.
 
 Compliance with ethical standards. The study was approved by the local ethical committee of the Federal Scientific Center for Medical and Reservative Technologies for Risk Management of the Population of the Rospotrebnadzor (meeting protocol No. 2 dated 11.02.2021), and the Gelsinki Helsinki Declaration of the World Medical Association (as amended 2013) was carried out.

Allergic rhinitis in schoolchildren under combined exposure to various environmental risk factors

Introduction. Growing prevalence of allergic rhinitis (AR) and significant socioeconomic losses related to implementing medical and prevention activities indicate the necessity to examine what role exogenous factors play in the disease onset and development. The aim of this study was to establish pathogenetic peculiarities of AR onset and development in schoolchildren under combined exposure to various environmental risk factors. 
 Materials and methods. We analyzed results of clinical and laboratory examinations of schoolchildren’s health and data obtained by questioning and taken from diaries of daily rations provided at school for four hundred thirty nine AR children. They attended either an ordinary secondary school or a school with profound studies of some subjects. Influence of risk factors on clinical and laboratory indicators was evaluated by using one-factor logistic regression models that described “adverse exposure – likelihood of a response (effect)” relationships. Leading risk factors and pathogenetic peculiarities of AR onset and development were identified based on analyzing established cause-effect relations “risk factor – laboratory indicator – likelihood of diagnosing AR». 
 Results. More significant violations of hygienic standards were established in schools with profound studies of some subjects; we identified improper management of educational activities, non-rational diets, and too intensive use of electronic devices. Likelihood of AR is 4.2 times higher for schoolchildren in such schools than for their counterparts from ordinary schools (OR=4.2) under combined exposure to adverse factors related to the educational process, diets, the environment (blood contamination with nickel, chromium, manganese, zinc, benzene, and toluene) and low physical activity. We established cause-effect relations between the disease development and the examined factors as well as their contributions to likelihood of risk-associated AR (12–60 %). We identified adverse laboratory effects in AR children who attended schools with profound studies of some subjects and established their association with affecting environmental factors. Pathogenetic peculiarities of the disease onset and development were posited based on modelling associations between laboratory indicators of disrupted homeostasis and AR development. 
 Limitations. The examination was performed with 439 schoolchildren participating in it. Participants were not divided into sex-specific groups when describing peculiarities of allergic rhinitis development.
 Conclusion. The established key pathogenetic components in development of risk-associated AR are relevant targets for hygienic activities as regards the educational process and quality of the environment

Is There any Correlation Between Nutrient Intake and Mental Health in Patients with Chronic Kidney Disease? A Cross-Sectional Study

Background: The prevalence of stress, anxiety, and depression seems to be high in patients with chronic kidney disease (CKD), which may influence their quality of life. Due to limiting some food groups, these patients suffer from a deficiency of some nutrients, which may be related to mood disorders. Objectives: This study aimed to investigate the correlation between nutrient intake, stress, anxiety, and depression in patients with CKD. Methods: The present cross-sectional study was conducted on 90 patients with CKD. To assess the diet of the patients, the researchers completed three days of the 24-hour food recall. The short self-report Iranian version of the Depression, Anxiety, and Stress Scale 21 (DASS-21) was also used to investigate the participants' mental health. Results: Of the 90 patients examined, 64 were men and 26 were women. There was a significant inverse correlation between depression and the dietary intake of polyunsaturated fatty acids (PUFAs) (β = -0.214, P = 0.039) and α-tocopherol (β = -0.225, P = 0.025). A significant inverse correlation was also found between anxiety and the dietary intake of iron (β = -0.319, P = 0.003), copper (β = -0.25, P = 0.031), vitamin B1 (β = -0.314, P = 0.004), vitamin B5 (β = -0.262, P = 0.016), vitamin B6 (β = -0.292, P = 0.007), vitamin B9 (β = -0.241, P = 0.026), fiber (β = -0.224, P = 0.04), and vitamin K (β = -0.26, P = 0.015). Conclusions: The dietary intake of nutrients such as PUFAs, α-tocopherol, B vitamins, vitamin K, iron, copper, and fiber might be associated with depression and anxiety. However, further studies with longitudinal designs are needed to reveal cause-effect relationships in this regard.

Urinary Bisphenol A and Bis(2-Ethylhexyl) Phthalate Metabolite Concentrations in Children with Obesity: A Case-Control Study

Introduction: Obesity is a worldwide public health problem. Experimental animal and in vitro studies suggest that the exposure to BPA and phthalates are associated to a higher risk of obesity. Objective: The objective of the study was to determine urinary excretion of bisphenol A and phthalates in obese and normal weight children. Methods: A case-control study was conducted in 122 children. Sixty-six obese children, 36 girls (mean age 8.41 ± 1.27 years), and 30 boys (mean age 8.51 ± 1.33 years) and 56 normal weight children, 27 girls (mean age 7.64 ± 1.49 years), and 29 boys (mean age 7.77 ± 1.56 years) were studied. Urinary BPA and bis(2-ethylhexyl) phthalate (DEHP) metabolites (MEHP, MEHHP, and MEOHP) were measured, respectively, by gas chromatography and high-performance liquid chromatography. Individual determinants of exposure were evaluated through “ad hoc” questionnaires. Results: BPA and DEHP metabolites were detectable in obese and normal weight children. Obese girls showed significantly higher BPA concentrations in comparison with normal weight girls (means 10.77, 95% CI = 7.02–16.53 vs. 5.50, 95% CI = 3.93–7.71 μg/g creatinine, respectively, p < 0.02). The first step of DEHP metabolic rate was significantly higher in obese girls compared with controls (p < 0.05). DEHP metabolites correlated significantly with leptin concentrations in obese girls (p < 0.03). A higher risk of obesity was found in children with BPA levels above the median values with the habit to eat food packaged (OR = 11.09, 95% CI = 1.28–95.78). Conclusions: These findings show that a higher exposure to BPA is associated with the risk of obesity in girls. Further studies are needed to unveil the cause-effect relationship.

Pengaruh Citra Destinasi Dan Atribut Destinasi Terhadap Minat Berkunjung Ulang Wisatawan Ke Destinasi Wisata Alahan Panjang

This research was motivated by the intention phenomenon to revisit the Alahan Panjang destination. The length is influenced by the tourist destination image and the attributes of the tourist destination in Alahan Panjang. Several tourist reviews state that the tourist destination Alahan Panjang is not Recommended for those who re-visit and haven't experienced the attraction yet impressive for tourists. This research aims to analyze the tourist destination image and attributes of the Alahan Panjang tourist destination. In this research using quantitative methods, the research type used in this research is causal associative or cause-effect relationships. Data was obtained from survey results by distributing questionnaires to respondents which is the object of research. The average for the tourist destination image variable is 4.112 with criteria Good. The tourist destination attribute variable has an average of 3.996 with Good criteria. Then The tourist destination attribute variable has an average of 4.016 with Good criteria. So therefore There is a positive and significant influence between the image of a tourist destination and interest in visiting repeated the tourist. There is also an influence between tourist destination attributes and interest in visiting repeated the tourist. Destination image variables and tourist destination attributes have an impact on variable interest in revisiting, then H1, H2 and H3 are accepted.