Conversion and Obsessive-Phobic Symptoms Predict IL-33 and IL-28A Levels in Individuals Diagnosed with COVID-19

The first epidemiological wave of the incidence of COVID-19 in Bulgaria was registered in June 2020. After the wave peak, we conducted a study in persons diagnosed with COVID-19 (N = 52). They were assessed with the anxiety-depressive scale (ADS), including basic (BS), vegetative (VS), conversion (CS), obsessive-phobic (OPS), and depressive (DS) symptoms. ADS assessment of individuals diagnosed with SARS-CoV-2 indicated a correlation between OPS and IL-33 values. IL-10 levels were higher than reference ranges in all patients. Multiple linear regression analyses demonstrated that combination of CS and OPS explained 28% of IL-33 levels, while combination of symptoms from all ADS dimensions explained 24% of IL-33 levels. It was also found that 21% of IL-28A levels was explained from the combination by all ADS dimensions, whereas OPS was the predictor for lower concentrations. The obtained results revealed meaningful correlations between psycho neuro-immunological factors in pathogenesis of illness from the coronavirus infection.

Retrospective Analysis of the Psychological Predictors of Public Health Support in Bulgarians at the Beginning of the Coronavirus Pandemic

The earliest critical context of the pandemic, preceding the first real epidemiological wave of contagion in Bulgaria, was examined using a socio-affective perspective. A retrospective and agnostic analytical approach was adopted. Our goal was to identify traits and trends that explain public health support (PHS) of Bulgarians during the first two months of the declared state of emergency. We investigated a set of variables with a unified method within an international scientific network named the International Collaboration on Social & Moral Psychology of COVID-19 (ICSMP) in April and May 2020. A total of 733 Bulgarians participated in the study (67.3% females), with an average age of 31.8 years (SD = 11.66). Conspiracy Theories Beliefs were a significant predictor of lower PHS. Psychological Well-Being was significantly associated with Physical Contact and Anti-Corona Policy Support. Physical Contact was significantly predicted by fewer Conspiracy Theories Beliefs, higher Collective Narcissism, Open-mindedness, higher Trait Self-Control, Moral Identity, Risk Perception and Psychological Well-Being. Physical Hygiene compliance was predicted by fewer Conspiracy Theories Beliefs, Collective Narcissism, Morality-as-Cooperation, Moral Identity and Psychological Well-Being. The results revealed two polar trends of support and non-support of public health policies. The contribution of this study is in providing evidence for the affective polarization and phenomenology of (non)precarity during the outbreak of the pandemic.

Differences in subjective well-being between individuals with distinct Joint Personality (temperament-character) networks in a Bulgarian sample

Background

Personality is the major predictor of people's subjective well-being (i.e., positive affect, negative affect, and life satisfaction). Recent research in countries with high-income and strong self-transcendent values shows that well-being depends on multidimensional configurations of temperament and character traits (i.e., Joint Personality Networks) that regulate the way people learn to adapt their habits to be in accord with their goals and values, rather than individual traits. To evaluate the prevalence and the associations of different Joint Personality (temperament-character) Networks with well-being in a low-income country with weak self-transcendent values, we tested their association in Bulgarian adults, a population known to have strong secular-rationalist values but weak self-transcendent values.

Method

The sample consisted of 443 individuals from Bulgaria (68.70% females) with a mean age of 34 years (SD = 15.05). Participants self-reported personality (Temperament and Character Inventory), affect (Positive Affect Negative Affect Schedule), and life satisfaction (Satisfaction with Life Scale). The personality scores were used for profiling through latent profile analysis and latent class analysis based on temperament configurations (i.e., Temperament Profiles) of high/low scores of Novelty Seeking (N/n), Harm Avoidance (H/h), Reward Dependence (R/r), and Persistence (P/s); and character configurations (i.e., Character Profiles) of high/low scores of Self-Directedness (S/s), Cooperativeness (C/c), and Self-Transcendence (T/t).

Results

We found two Temperament Profiles and two Character Profiles that clustered into two distinctive Joint Personality Networks. All individuals in Joint Personality Network 1 had a Reliable (nhRP) Temperament Profile in combination with an Organized (SCt) Character Profile (i.e., a stable temperament and a healthy character configuration). About 71.9% in Joint Personality Network 2 had an Apathetic (sct) Character Profile in combination with Methodical (nHrp) or Reliable (nhRP) Temperament Profiles, while 28.1% had a Methodical (nHrp) Temperament Profile in combination with an Organized (SCt) Character Profile. Few people with high self-expressive values (i.e., high in all three character traits; SCT) were found. Individuals with a Joint Personality Network 1 with strong secular-rationalist values reported higher levels of positive affect and life satisfaction (p < .001), while individuals with a Joint Personality Network 2 reported higher levels of negative affect (p < .001).

Conclusions

Although a stable temperament and a healthy character were separately important for well-being, it was clear that it was the interaction between such temperament and character configuration that yielded greater levels of subjective well-being. Nevertheless, future research needs to investigate this interaction further to evaluate other cultures with variable configurations of personality traits and values.

Lowered Quality of Life in Long COVID Is Predicted by Affective Symptoms, Chronic Fatigue Syndrome, Inflammation and Neuroimmunotoxic Pathways

The physio-affective phenome of Long COVID-19 is predicted by (a) immune-inflammatory biomarkers of the acute infectious phase, including peak body temperature (PBT) and oxygen saturation (SpO2), and (b) the subsequent activation of immune and oxidative stress pathways during Long COVID. The purpose of this study was to delineate the effects of PBT and SpO2 during acute infection, as well as the increased neurotoxicity on the physical, psychological, social and environmental domains of health-related quality of life (HR-QoL) in people with Long COVID. We recruited 86 participants with Long COVID and 39 normal controls, assessed the WHO-QoL-BREF (World Health Organization Quality of Life Instrument-Abridged Version, Geneva, Switzerland) and the physio-affective phenome of Long COVID (comprising depression, anxiety and fibromyalgia-fatigue rating scales) and measured PBT and SpO2 during acute infection, and neurotoxicity (NT, comprising serum interleukin (IL)-1β, IL-18 and caspase-1, advanced oxidation protein products and myeloperoxidase, calcium and insulin resistance) in Long COVID. We found that 70.3% of the variance in HR-QoL was explained by the regression on the physio-affective phenome, lowered calcium and increased NT, whilst 61.5% of the variance in the physio-affective phenome was explained by calcium, NT, increased PBT, lowered SpO2, female sex and vaccination with AstraZeneca and Pfizer. The effects of PBT and SpO2 on lowered HR-QoL were mediated by increased NT and lowered calcium yielding increased severity of the physio-affective phenome which largely affects HR-QoL. In conclusion, lowered HR-Qol in Long COVID is largely predicted by the severity of neuro-immune and neuro-oxidative pathways during acute and Long COVID.

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution-individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.

Differential aberrant connectivity of precuneus and anterior insula may underpin the diagnosis of schizophrenia and mood disorders

BACKGROUND

Over the past decade, resting-state functional magnetic resonance imaging (rs-fMRI) has concentrated on brain networks such as the default mode network (DMN), the salience network (SN), and the central executive network (CEN), allowing for a better understanding of cognitive deficits observed in mental disorders, as well as other characteristic psychopathological phenomena such as thought and behavior disorganization.

AIM

To investigate differential patterns of effective connectivity across distributed brain networks involved in schizophrenia (SCH) and mood disorders.

METHODS

The sample comprised 58 patients with either paranoid syndrome in the context of SCH (n = 26) or depressive syndrome (Ds) (n = 32), in the context of major depressive disorder or bipolar disorder. The methods used include rs-fMRI and subsequent dynamic causal modeling to determine the direction and strength of connections to and from various nodes in the DMN, SN and CEN.

RESULTS

A significant excitatory connection from the dorsal anterior cingulate cortex to the anterior insula (aI) was observed in the SCH patient group, whereas inhibitory connections from the precuneus to the ventrolateral prefrontal cortex and from the aI to the precuneus were observed in the Ds group.

CONCLUSION

The results delineate specific patterns associated with SCH and Ds and offer a better explanation of the underlying mechanisms of these disorders, and inform differential diagnosis and precise treatment targeting.

Sense of Coherence and Burnout in Healthcare Professionals in the COVID-19 Era

Emotional exhaustion in the context of vulnerability to burnout is a part of the universal narrative of high stress and systematically reported in healthcare professionals. The sense of coherence (SOC) is a salutogenic construct, operationalized by A. Antonovsky as a generalized resistance resource (GRR) to stress in three dimensions: meaningfulness (Me), the desire of a person to be motivated to cope; comprehensibility (C), the belief that the challenge is understood; and manageability (Ma), the belief that coping resources are available. The relation between SOC and the dimensions of burnout-Emotional Exhaustion (EE), Depersonalization (D), and Personal Accomplishment (PA)-is a part of salutogenic functioning, which reveals the inner motivation and self-organization of the psycho-emotional energetic resource. This study traces the salutogenic functioning of Bulgarian healthcare professionals during the pandemic. A general psychological background of coherence and exhaustion has been identified. All components of the SOC were positively correlated to Personal Accomplishment. Emotional Exhaustion and Depersonalization correlated negatively with coherence. SOC was validated as a possible determinant to predict the reduction of exhaustion and depersonalization as well as high levels of professional performance. The dimension of Meaningfulness in the coherence phenomenon was demonstrated to have the highest predictive value for professional burnout.

The reification of the clinical diagnosis of myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS) as an immune and oxidative stress disorder: construction of a data-driven nomothethic network and exposure of ME/CFS subgroups

The approach towards myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS) remains in a permanent state of crisis with fierce competition between the psychosocial school, which attributes ME/CFS to the perception of effort, and the medical approach (Maes and Twisk, BMC Med, 2010,8,35). The aim of this paper is to review how to construct a nomothetic model of ME/CFS using Partial Least Squares (PLS) path analysis and ensembling causome (bacterial translocation as assessed with IgM/IgA responses to LPS), protectome (lowered coenzyme Q10), adverse outcome pathways (AOP) including increased lysozyme, CD38+ T cell activation, cell-mediated immune activation (CMI), and IgM responses to oxidative specific epitopes and NO-adducts (IgM OSENO). Using PLS, we trained, tested and validated this knowledge- and data-driven causal ME/CFS model, which showed adequate convergence, construct and replicability validity. This bottom-up explicit data model of ME/CFS objectivates the descriptive narratives of the ME/CFS phenome, using causome-protectome-AOP data, whereby the abstract concept ME/CFS is translated into pathways, thereby securing the reification of the ME/CFS phenome. We found that 31.6% of the variance in the physiosomatic symptom dimension of ME/CFS was explained by the cumulative effects of CMI and CD38+ activation, IgM OSENO, IgA LPS, lysozyme (all positive) and coenzyme Q10 (inversely). Cluster analysis performed on the PLS-generated latent vector scores of all feature sets exposed three distinct immune groups of ME/CFS, namely one with increased lysozyme, one with increased CMI + CD38 activation + depressive symptoms, and another with increased bacterial translocation + autoimmune responses to OSENO.

Interview with professor C. Robert Cloninger

On March 26, 2019, at the 12th Geneva Conference on Personality-centered Medicine, I had the opportunity to interview Professor Cloninger – a contemporary theoretician of the personality, creator of the psychobiological theory of personal structure, Professor of Psychiatry, Psychology and Genetics at Wallace Renard, Director of the Center for Social Care at the University of Washington and beyond his many contributions, he is a very warm, positive and spiritual person.

Неорайхиански прочит на бърн аут – разговор с мадлен алгафари

Интервюто е проведено на 15 май 2018 г. с идеята за поглед към бърн аут и емоционалната интелигентност в перспективата на Неорайхианската психоаналитична школа.

Comparison of different methods for uranium determination in water

Photometry, laser photometry, liquid scintillation (LSC), gamma spectrometry and alpha spectrometry were used for estimating waterborne uranium concentration. The chemical procedures applied were pre-concentration, liquid extraction, chromatographic resin extraction and precipitation. Our results show that laser photometry is an easy and accurate method capable of estimating low uranium concentrations, parts of micrograms per litre. It is not applicable for higher concentrations, difficult water matrixes and isotope determination. The classical photometry is complementary, resolving the problem related to high concentrations, practically up to 10 mg/l. Alpha and gamma spectrometry resolve the problem of precise isotope determination, but with the disadvantage of hard chemical preparation and long measurement times. An intermediate method is LSC, with the problem of isotope estimation, due to poor energy resolution.