Search

Background: Natriuretic peptide (NP) levels have been proposed for characterization and risk stratification of heart failure (HF) among patients with cardiovascular disease (CVD). However, their role in patients with diabetes mellitus type 2 (T2DM) has not been well studied and understood. The aim of this study was to assess phenotypical, functional characteristics and imaging parameters in relation to N-terminal pro b-type natriuretic peptide (NT-proBNP) values in T2DM patients without known CVD that may predispose to overt HF. Methods: This was a cross-sectional study of 100 consecutive T2DM patients (mean overall age of 67 ± 9 years, 40% women and 60% men) who were enrolled from the outpatient diabetic clinic. Patients underwent a cardiopulmonary exercise test (CPET), and echocardiographic and cardiac magnetic resonance imaging (CMR); serum NT-proBNP was also measured. Results: The mean (standard deviation) NT-proBNP was 149 (±186) pg/mL. Patients in the highest tertile of NT-proBNP values (>107 pg/mL) had lower values of predicted maximum oxygen consumption compared to the lowest quartile (<55 pg/mL) (84% vs. 92%, p = 0.018) in the CPET and higher ratio of early diastolic mitral inflow velocity to early diastolic mitral annulus velocity (E/e′) (9.0 vs. 7.2, p = 0.05) in echocardiography. Finally, there was a negative correlation between right ventricle end diastolic volume in CMR and predicted maximum oxygen consumption (b = −0.225 ± 0.11, p = 0.046). Conclusions: NT-proBNP levels seemed to be a useful marker in people with T2DM, as elevated levels reflected ongoing appearance of HF with preserved ejection fraction and were related to CPET and echocardiographic indices of impaired left ventricular diastolic and right ventricular systolic function. [ABSTRACT FROM AUTHOR]

Background: Elderly patients, particularly those over 75 years old, have been disproportionately affected by COVID-19, exhibiting higher rates of severe outcomes, such as ICU admissions and mortality. This study aimed to evaluate and compare the effectiveness of various clinical scoring systems—qSOFA, PRIEST, PAINT, and ISARIC4C—in predicting ICU admission, the need for mechanical ventilation, and mortality among elderly COVID-19 patients. Methods: In this retrospective cohort study conducted at two tertiary care hospitals, 131 elderly patients (aged ≥ 75) and 226 younger controls (aged < 65) with confirmed COVID-19 were included. Clinical scores were computed at admission and five days after symptom onset. Kaplan–Meier survival analysis and Receiver Operating Characteristic (ROC) curve analysis were performed to assess the predictive performance of the scores regarding severe outcomes. Results: Kaplan–Meier analysis indicated significantly lower survival probabilities for elderly patients with high scores at admission. Those with an ISARIC4C score above 11.8 had a survival probability of 25% compared to 74% for those below this threshold (p < 0.001). Similarly, elderly patients with a qSOFA score above 2.1 had a survival probability of 36% compared to 72% for those with lower scores (p < 0.001). The PRIEST and PAINT scores also demonstrated predictive validity; patients with a PRIEST score above 6.3 and a PAINT score above 6.5 at admission showed comparable decreases in survival probabilities. ROC analysis at five days post-symptom onset revealed that the ISARIC4C score had the highest area under the curve (AUC) of 0.772, suggesting excellent predictive validity for severe outcomes, including mortality. The optimal cutoffs identified were 11.2 for ISARIC4C, 6.3 for PRIEST, and 6.5 for PAINT, each displaying high sensitivity and specificity. Conclusions: The ISARIC4C, qSOFA, PRIEST, and PAINT scores are robust predictors of severe outcomes in elderly COVID-19 patients over 75 years old, as confirmed by Kaplan–Meier and ROC analyses. These tools can be crucial for early identification of patients at high risk of adverse outcomes, guiding clinical decision making, and optimizing resource allocation. The use of these scoring systems should be encouraged in clinical settings to enhance the management of elderly COVID-19 patients. Further research is necessary to validate these findings across different populations and settings. [ABSTRACT FROM AUTHOR]

Social cognitive deficits and social behavior impairments are common in major depressive disorder (MDD) and affect the quality of life and recovery of patients. This review summarizes the impact of standard and novel treatments on social functioning in MDD and highlights the potential of combining different approaches to enhance their effectiveness. Standard treatments, such as antidepressants, psychotherapies, and brain stimulation, have shown mixed results in improving social functioning, with some limitations and side effects. Newer treatments, such as intranasal oxytocin, mindfulness-based cognitive therapy, and psychedelic-assisted psychotherapy, have demonstrated positive effects on social cognition and behavior by modulating self-referential processing, empathy, and emotion regulation and through enhancement of neuroplasticity. Animal models have provided insights into the neurobiological mechanisms underlying these treatments, such as the role of neuroplasticity. Future research should explore the synergistic effects of combining different treatments and investigate the long-term outcomes and individual differences in response to these promising interventions. [ABSTRACT FROM AUTHOR]

Background and Objectives: Depression is associated with problems in social interaction and communication. Most of the research conducted in this field uses non-interactive tasks. The theory of economic games as a branch of behavioral economics can provide a new tool for investigating interactions and social decisions in interactive and dynamic conditions and help to better understand neuropsychiatric disorders. In this research, the decision making of depressed people in interactive situations is investigated with a systematic review of economic game theory articles. Methods: By systematic review method, 45 related articles from 2010 to 2023 were extracted from Scopus and Web of Science databases. After removing the duplicate articles and checking the exclusion criteria, finally, 23 articles that analyzed the decision-making process of patients with depression symptoms in economic games were analyzed. Results: The findings showed that the performance of depression sufferers in economic games is different from the healthy group. These differences can be discussed in two groups of cognitive and social components. The cognitive component was classified into the subcomponents of theory of mind, negative cognitive schema, bias in perception, and limited cognitive processing, and the social component was classified into the subcomponents of social avoidance, social comparison and competition, and interpersonal trust. Conclusion: Economic games may help identify suboptimal and maladaptive choices associated with depressive disorder and thus provide a powerful tool for discovering candidate cognitive and social markers of depressive disorder. [ABSTRACT FROM AUTHOR]

Various scoring systems are available for COVID-19 risk stratification. This study aimed to validate their performance in predicting severe COVID-19 course in a large, heterogeneous Swiss cohort. Scores like the National Early Warning Score (NEWS), CURB-65, 4C mortality score (4C), Spanish Society of Infectious Diseases and Clinical Microbiology score (COVID-SEIMC), and COVID Intubation Risk Score (COVID-IRS) were assessed in patients hospitalized for COVID-19 in 2020 and 2021. Predictive accuracy for severe course (defined as all-cause in-hospital death or invasive mechanical ventilation (IMV)) was evaluated using receiver operating characteristic curves and the area under the curve (AUC). The new 'COVID-COMBI' score, combining parameters from the top two scores, was also validated. This study included 1,051 patients (mean age 65 years, 60% male), with 162 (15%) experiencing severe course. Among the established scores, 4C had the best accuracy for predicting severe course (AUC 0.76), followed by COVID-IRS (AUC 0.72). COVID-COMBI showed significantly higher accuracy than all established scores (AUC 0.79, p = 0.001). For predicting in-hospital death, 4C performed best (AUC 0.83), and, for IMV, COVID-IRS performed best (AUC 0.78). The 4C and COVID-IRS scores were robust predictors of severe COVID-19 course, while the new COVID-COMBI showed significantly improved accuracy but requires further validation. [ABSTRACT FROM AUTHOR]

Process optimization is an important area of research in the mining and metal industries. The application of mathematical models and optimization techniques has led to significant improvements in process efficiency, reduced operating costs, and improved product quality. The use of simulation tools has also allowed for the development of virtual plants that can be used to test different process scenarios and optimize plant performance. To completely reap the rewards of process optimisation, there are still several issues that need to be resolved. The integration of sustainability and environmental impact assessments into the optimisation process is one of the major issues. This necessitates the creation of models that can take the environmental impact of various process factors into consideration and enable process optimisation using environmental standards. The creation of more complicated mathematical models that can capture the intricate interconnections between various process factors presents another difficulty. Advanced machine learning and data analytics methods like neural networks and genetic algorithms must be used for this. Despite these challenges, the future of process optimization looks promising. Emerging technologies, such as the Internet of Things and big data analytics, are opening up new opportunities for process optimization. The use of sensors and real-time data analytics can provide plant operators with the information they need to make realtime decisions and optimize plant performance. Process optimization is a critical area of research for the mining and metal industries. The use of mathematical models, optimization techniques, and simulation tools has led to significant improvements in process efficiency and product quality. [ABSTRACT FROM AUTHOR]

Entomophthoralean fungi have long been recognized as promising candidates for biological insect pest control. However, due to technical challenges, no preparation based on these fungi has been established for practical use so far. Low water availability is a key limiting factor of conidial discharge and germination. In the present study, sporulation of psyllid-pathogenic entomophthoralean fungus Pandora cacopsyllae Eilenberg, Keller and Humber (Entomophthorales Entomophthoraceae) was not observable under reduced water activity (aW ≤ 0.97). To support sporulation of encapsulated P. cacopsyllae hyphae from submerged culture under low humidity conditions in above-ground applications in field, we developed a novel paste-type formulation containing biobased superabsorbents, which retained water for a prolonged time period. In co-application with the superabsorbent formulation, the otherwise fast-drying capsules were kept sufficiently moist for sporulation for at least six days in laboratory trials at low humidity below 40%. Using the new formulation, we measured conidial discharge by P. cacopsyllae from the capsules under dry semi-field conditions in summertime by trapping conidia at a vertical distance of up to 40 cm from the sporulation source. By considering the cardinal directions, fewer conidia were discharged on the sun-facing side in the east than on the sun-averted side in the west. The developed formulation improved the sporulation efficacy significantly. Since water availability is a limiting factor for many fungal biocontrol agents, the developed formulation has the potential to also improve their efficacy. [ABSTRACT FROM AUTHOR]

Performance of electrocatalytic reactions depends on not only the composition and structure of the active sites, but also their local environment, including the surrounding electrolyte. In this work, we demonstrate that BF2(OH)2− anion is the key fluoroborate species formed in the mixed KBi/KF (KBi=potassium borate) electrolyte to enhance the rate of the oxygen evolution reaction (OER) at near‐neutral pH. Through a combination of electrokinetic and in situ spectroscopic studies, we show that the mixed KBi/KF electrolyte promotes the OER via two pathways: 1) stabilizing the interfacial pH during the proton‐producing reaction with its high buffering capacity; and 2) activating the interfacial water via strong hydrogen bonds with F‐containing species. With the KBi/KF electrolyte, electrodeposited Co(OH)2 is able to achieve 100 mA/cm2 at 1.74 V, which is among the highest reported activities with earth‐abundant electrocatalysts at near neutral conditions. These findings highlight the potential of leveraging electrolyte‐engineering for improving the electrochemical performance of the OER. [ABSTRACT FROM AUTHOR]

Understanding the adsorption behavior of base probes in aluminosilicates and its relationship to the intrinsic acidity of Brønsted acid sites (BAS) is essential for the catalytic applications of these materials. In this study, we investigated the adsorption properties of base probe molecules with varying proton affinities (acetonitrile, acetone, formamide, and ammonia) within six different aluminosilicate frameworks (FAU, CHA, IFR, MOR, FER, and TON). An important objective was to propose a robust criterion for evaluating the intrinsic BAS acidity (i.e., state of BAS deprotonation). Based on the bond order conservation principle, the changes in the covalent bond between the aluminum and oxygen carrying the proton provide a good description of the BAS deprotonation state. The ammonia and formamide adsorption cause BAS deprotonation and cannot be used to assess intrinsic BAS acidity. The transition from ion-pair formation, specifically conjugated acid/base interaction, in formamide to strong hydrogen bonding in acetone occurs within a narrow range of base proton affinities (812–822 kJ mol−1). The adsorption of acetonitrile results in the formation of hydrogen-bonded complexes, which exhibit a deprotonation state that follows a similar trend to the deprotonation induced by acetone. This allows for a semi-quantitative comparison of the acidity strengths of BAS within and between the different aluminosilicate frameworks. [ABSTRACT FROM AUTHOR]

Social cognition guides social behavior. Subjects with proper social cognition should be able to: (1) have reasonable social motivation, (2) recognize other people and infer their intentions, and (3) weigh social hierarchies and other values. The choice of appropriate behavioral paradigms enables the use of rodents to study social behavior disorders in humans, thus enabling research to go deeper into neural mechanisms. This paper reviews commonly used rodent behavioral paradigms in studies of social behavior disorders. We focused specifically on sorting out ways to transfer the study of human social behavior to rodents through behavioral paradigms. [ABSTRACT FROM AUTHOR]

Acid forms of zeolites have been used in industry for several decades but scaling the strength of their acid centers is still an unresolved and intensely debated issue. In this paper, the Brønsted acidity strength in aluminosilicates measured by their deprotonation energy (DPE) was investigated for FAU, CHA, IFR, MOR, FER, MFI, and TON zeolites by means of periodic and cluster calculations at the density functional theory (DFT) level. The main drawback of the periodic DFT is that it does not provide reliable absolute values due to spurious errors associated with the background charge introduced in anion energy calculations. To alleviate this problem, we employed a novel approach to cluster generation to obtain accurate values of DPE. The cluster models up to 150 T atoms for the most stable Brønsted acid sites were constructed on spheres of increasing diameter as an extension of Harrison's approach to calculating Madelung constants. The averaging of DPE for clusters generated this way provides a robust estimate of DPE for investigated zeolites despite slow convergence with the cluster size. The accuracy of the cluster approach was further improved by a scaled electrostatic embedding scheme proposed in this work. The electrostatic embedding model yields the most reliable values with the average deprotonation energy of about 1245 ± 9 kJ·mol−1 for investigated acidic zeolites. The cluster calculations strongly indicate a correlation between the deprotonation energy and the zeolite framework density. The DPE results obtained with our electrostatic embedding model are highly consistent with the previously reported QM/MM and periodic calculations. [ABSTRACT FROM AUTHOR]

Performance of electrocatalytic reactions depends on not only the composition and structure of the active sites, but also their local environment, including the surrounding electrolyte. In this work, we demonstrate that BF 2 (OH) 2 - anion is the key fluoroborate species formed in the mixed KBi/KF (KBi=potassium borate) electrolyte to enhance the rate of the oxygen evolution reaction (OER) at near-neutral pH. Through a combination of electrokinetic and in situ spectroscopic studies, we show that the mixed KBi/KF electrolyte promotes the OER via two pathways: 1) stabilizing the interfacial pH during the proton-producing reaction with its high buffering capacity; and 2) activating the interfacial water via strong hydrogen bonds with F-containing species. With the KBi/KF electrolyte, electrodeposited Co(OH) 2 is able to achieve 100 mA/cm 2 at 1.74 V, which is among the highest reported activities with earth-abundant electrocatalysts at near neutral conditions. These findings highlight the potential of leveraging electrolyte-engineering for improving the electrochemical performance of the OER., (© 2023 Wiley-VCH GmbH.)

In the context of the Bologna reform, the Environmental Sciences programme at ETH Zurich was transformed from a Diploma to a Master's degree programme. In a comparative secondary analysis of graduate surveys of the last homogeneous cohort of Diploma graduates (N = 85) and two Master's cohorts after the reform (N = 108), this study investigated the qualifications required by graduates in their professional activities and matched them with the level of qualification acquired at university. It concluded that graduates' general skills meet professional requirements better after the reform. However, for two out of five domain-specific skills (knowledge of legal aspects, interdisciplinary knowledge) ratings of skill acquisition declined significantly. Nonetheless, Master's graduates showed a slight or substantial knowledge and skills advantage for seven of the eight skills of the programme's qualification profile that were addressed in the survey. The basic quality of the sustainability oriented programme has thus been maintained. [ABSTRACT FROM AUTHOR]

This article highlights the evolutionary biological epistemology in Freud psychoanalytic theory. The concepts of aggressive and sexual drives are cornerstones of the psychoanalytic epistemological system, concerning the motivational/emotional roots of mental functioning. These biological roots of mental functioning, especially with regard to aggressive drive, have gradually faded away from psychoanalytic epistemology, as we show in this article. Currently, however, Neurosciences, and in particular Affective Neuroscience (Panksepp, 1998), can help us to have a better understanding of the biological roots of human mental functioning. The motivational/emotional systems studied by Affective Neuroscience can give a new epistemological foundation to the aggressive drive concept in psychoanalytic theory. Over the course of human evolution, motivational/emotional systems have played a role in social relationships and also in mental functioning. In this regard, among the various types of aggression (ANGER in Panksepp taxonomy 1998) that we consider in our article, inter-male aggression, also named Dominance motivational/emotional system , is that which regulates social interactions between sexually matured adults. This type of aggression acts in complementary connection with FEAR motivational/emotional system that regulate submissive behavior and social defeat, and the latter one is of the more important stressors. The interaction between aggression and FEAR motivational/emotional systems gives rise to agonistic behavior or dominance/submission motivational/emotional system, as we propose in our article. There is now a large literature that identifies in the dynamic of Competitive behavior , which is one of the main factors of mental illness. When social interactions activate the competitive behavior, the subject can perceive himself as "destined to victory" or "destined to defeat," activating either behaviors or emotions connected to the Involuntary Defeat Strategy or Involuntary Dominant Strategy (Sloman, 2002), which we can find in many types of mental disorders, for example, mood disorders or anxiety disorders. [ABSTRACT FROM AUTHOR]

Probing the adsorption of tetralin on zeolite is of prime scientific and industrial importance with the aim to upgrade the industrial process of tetralin cracking. In this work, the effect of Si/Al ratio ranging from 12 to 39 on tetralin adsorption property on Y zeolite is studied by DFT calculations. Tetralin adsorption on Y zeolite corresponds to aπ-stacking adsorption mechanism between double bonds of aromatic ring and Brønsted acid sites. Therefore, the number of Brønsted acid sites influences the adsorption properties. Lower Si/Al ratio with more Brønsted acid sites interacting with the aromatic ring of tetralin leads to a higher adsorption energy. Furthermore, the charge and frontier molecular orbital analysis are also performed to understand the influence of Si/Al ratio on adsorption performance. Y zeolite with lower Si/Al ratio shows larger charge difference values and lower HOMO–LUMO gap, which directly manifests the stronger adsorption ability of tetralin and indicates bigger possibility of reacting. [ABSTRACT FROM AUTHOR]

Barley ( Hordeum vulgare) is cultivated on 49.1 million hectares worldwide with 50.2% of the area located in Europe. Powdery mildew, caused by Blumeria graminis f. sp. hordei ( Bgh), occurs wherever barley is grown. Cultivar resistance plays an important role in global barley production, especially in parts of Europe where high concentrations of both spring and winter types are grown. The aim of this report was to postulate specific resistance genes in barleys from nine European countries registered in the Czech Republic from 2011 to 2015. Thirty-five spring cultivars and 27 winter barleys were tested with 56 diverse Bgh isolates. Twenty-five known resistance genes were postulated, and unknown genes were detected in Sandra, Saturn and Zeppelin. Unidentified specific resistance genes were also present in winter hybrids Hobbit and Wootan. Spring cultivars Arthur and Francin consisted of three and two genotypes, respectively. Resistance gene mlo was present in 26 spring cultivars, and the proportion of cultivars with this gene increased from 62.9% in 2006-2010 to 75.7% in 2011-2015. The gene Mlp1 was identified for the first time in German winter cultivar Saturn. Five spring cultivars registered in Slovakia were included in the tests. All the cultivars that were tested contained one or more specific resistance genes to powdery mildew. Adaptability of the pathogen and possibilities for breeding winter barleys are discussed. [ABSTRACT FROM AUTHOR]

Copyright of Zeitschrift für Psychiatrie, Psychologie und Psychotherapie is the property of Hogrefe AG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A density functional theory study has been employed to investigate the effect of next-nearest-neighbours aluminium (NNN Al) atom on the acid strength of Brönsted acid site in Y zeolite. Additionally, the distribution of NNN Al atom was also studied. The obtained results show that thermodynamically, the favourable sites for location of NNN Al atom are the diagonal sites of the four-membered ring and meta-position of hexagon I. Furthermore, the increase of NNN Al atoms causes the nonlinear reduction of the strength of Brönsted acid sites. When the number of NNN Al atoms is greater than two, the increasing extent of acid strength is not obvious with the reduction in the number of NNN Al atoms. But the acid strength will increase linearly with the further reduce of the number of NNN Al atoms. Compared with deprotonation energy (ED), ammonia adsorption energy (Eads) could give a more reasonable measuring result for the acid strength. [ABSTRACT FROM PUBLISHER]

Powdery mildew is the most common disease of barley in the Czech Republic and winter barley plays a crucial role in the winter survival and reproduction of the pathogen. This study was aimed at identifying resistance genes in winter barley cultivars grown in the Czech Republic from 1971 to 2005 by using the method of postulation. Forty-one cultivars and a parental line were tested at the seedling stage for their reaction to 32 selected isolates of Blumeria graminis f. sp. hordei. In total, 26 resistance spectra were detected and the following 18 resistance genes were found: Mla6, Mla7, Mla8, Mla13, Mla14, MlaMu2, MlaNo3, MlaRu4, Mlg, Mlh, MlLa, Mlra, Ml( Bw), Ml( Ch), Ml( Dr2), Ml( Dt5), Ml( IM9) and Ml( St). Two cultivars (‘Kiruna’ and ‘Sorna’) exhibited heterogeneity for mildew resistance. Another source of Mla13 and a possible centre of origin of Ml( Bw) are discussed. [ABSTRACT FROM AUTHOR]

With the rapid development of machine learning techniques, data-mining for processes in chemistry, materials, and engineering has been widely reported in recent years. In this discussion, we summarize some typical applications for process optimization, design, and evaluation of chemistry, materials, and engineering. Although the research and application targets are various, many important common points still exist in their data-mining. We then propose a generalized strategy based on the philosophy of data-mining, which should be applicable for the design and optimization targets for processes in various fields with both scientific and industrial purposes. [ABSTRACT FROM AUTHOR]