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Working memory (WM) involves short-term maintenance and manipulation of goal-relevant information, with cognitive control playing a crucial role in these processes due to WM’s limited capacity. Pupillometry studies show distinct pupillary changes for WM stages, reflecting cognitive effort and load. Motivational incentives enhance WM performance by potentially improving encoding, maintenance, or retrieval, though the specific components influenced by reward remain unclear. This study specifically tested whether reward modulates cognitive control processes during WM maintenance using pupillometry. Participants performed a delayed-estimation orientation WM task with reward cues indicating reward levels at the beginning of trials. The results revealed that motivational incentives significantly improved WM performance and increased pupillary dilation during maintenance. These findings provide evidence for the modulation of WM maintenance by reward through enhanced top-down cognitive control processes.

This review addresses the 100-year-old Hill equation (published in January 22, 1910), the first formula relating the result of a reversible association (e.g., concentration of a complex, magnitude of an effect) to the variable concentration of one of the associating substances (the other being present in a constant and relatively low concentration). In addition, the Hill equation was the first (and is the simplest) quantitative receptor model in pharmacology. Although the Hill equation is an empirical receptor model (its parameters have only physico-chemical meaning for a simple ligand binding reaction), it requires only minor a priori knowledge about the mechanism of action for the investigated agonist to reliably fit concentration-response curve data and to yield useful results (in contrast to most of the advanced receptor models). Thus, the Hill equation has remained an important tool for physiological and pharmacological investigations including drug discovery, moreover it serves as a theoretical basis for the development of new pharmacological models.

Extensive research with musicians has shown that instrumental musical training can have a profound impact on how acoustic features are processed in the brain. However, less is known about the influence of singing training on neural activity during voice perception, particularly in response to salient acoustic features, such as the vocal vibrato in operatic singing. To address this gap, the present study employed functional magnetic resonance imaging (fMRI) to measure brain responses in trained opera singers and musically untrained controls listening to recordings of opera singers performing in two distinct styles: a full operatic voice with vibrato, and a straight voice without vibrato. Results indicated that for opera singers, perception of operatic voice led to differential fMRI activations in bilateral auditory cortical regions and the default mode network. In contrast, musically untrained controls exhibited differences only in bilateral auditory cortex. These results suggest that operatic singing training triggers experience-dependent neural changes in the brain that activate self-referential networks, possibly through embodiment of acoustic features associated with one's own singing style.

Background Albeit smoking cessation has unequivocal health benefits, attempts to quit are not unanimous, even in patient populations at high risk for smoking-related diseases cessation. Allelic variations of enzymes involved in dopamine metabolism are being considered as candidates for nicotine addiction. We set out to assess whether rs4680 G/A and rs2235186 G/A polymorphisms of COMT and MAO-A, respectively are associated with the ability to quit smoking in chronic inflammatory pulmonary disease patients. Methods Patients managed for chronic inflammatory pulmonary disease by the Department of Pulmonology (University of Debrecen, Hungary), with a current or past smoking habit were included in the current analysis. The study was designed in line with the STROBE statement for cross-sectional studies and was approved by the National Center for Public Health, Hungary. Genomic DNA was extracted from peripheral blood specimens. SNPs were genotyped using TaqMan SNP genotyping assays. Results rs4680 COMT polymorphism showed significant effect for successful smoking cessation in patients with pulmonary disease. Accordingly, A/A subjects had lower odds for successful smoking cessation (odds ratio 0.37; 95% confidence interval 0.20–0.69, p  = 0.002 (additive model). On the other hand, patients homozygous for the minor allele (A) at rs2235186 of MAO-A showed a non-significant trend toward increased odds for successful smoking cessation. Conclusions The presence of the minor allele for rs4680 COMT was shown to decrease the odds for successful smoking cessation, a finding that may be interpreted in view of the altered balance between tonic and phasic dopamine release.

The receptorial responsiveness method (RRM) enables the estimation of a change in concentration of an (even degradable) agonist, near its receptor, via curve fitting to (at least) two concentration-effect (E/c) curves of a stable agonist. One curve should be generated before this change, and the other afterwards, in the same system. It follows that RRM yields a surrogate parameter (“c x ”) as the concentration of the stable agonist being equieffective with the change in concentration of the other agonist. However, regression can be conducted several ways, which can affect the accuracy, precision and ease-of-use. This study utilized data of previous ex vivo investigations. Known concentrations of stable agonists were estimated with RRM by performing individual (local) or global fitting, this latter with one or two model(s), using a logarithmic (logc x ) or a nonlogarithmic (c x ) parameter (the latter in a complex or in a simplified equation), with ordinary least-squares or robust regression, and with an “all-at-once” or “pairwise” fitting manner. We found that the simplified model containing logc x was superior to all alternative models. The most complicated individual regression was the most accurate, followed closely by the moderately complicated two-model global regression and then by the easy-to-perform one-model global regression. The two-model global fitting was the most precise, followed by the individual fitting (closely) and by the one-model global fitting (from afar). Pairwise fitting (two E/c curves at once) improved the estimation. Thus, the two-model global fitting, performed pairwise, and the individual fitting are recommended for RRM, using the simplified model containing logc x .

The Signal Amplification, Binding affinity, and Receptor-activation Efficacy (SABRE) model is the most recent general and quantitative model of receptor function, which enables the determination of K d (the equilibrium dissociation constant of the agonist-receptor complex) and q (the fraction of the operable receptors after a partial irreversible receptor inactivation) from purely functional data. The practical aim of the present study was to test the capabilities of this new model using concentration-effect (E/c) data from a previous investigation conducted in our laboratory. We have found that the SABRE model is at least as useful as two widely accepted older methods thought to have similar capabilities, the operational model of agonism and Furchgott’s method, even if the quality of the data to be evaluated is somewhat challenging. Nevertheless, the SABRE model seems to require a large amount of high-quality and, regarding the experimental design, diverse data. In addition, it is important to find the most suitable fitting strategy for the particular sort of data in order to obtain reliable results. However, owing to its unique feature of distinguishing between receptor activation and activation of postreceptorial signaling, the SABRE model appears to be superior to previous quantitative receptor function models in simulating E/c curves and thereby clarifying, explaining or simply illustrating theoretical issues.

In recent years, convolutional neural networks (CNNs) have emerged as highly efficient architectures for image and audio classification tasks, gaining widespread adoption in state-of-the-art methodologies. While CNNs excel in machine learning scenarios where the data representation exhibits a grid structure, they face challenges in generalizing to other data types. For instance, they struggle with data structured on 3D meshes (e.g., measurements from a network of meteorological stations) or data represented by graph structures (e.g., molecular graphs). To address such challenges, the scientific literature proposes novel graph-based convolutional network architectures, extending the classical convolution concept to data structures defined by graphs. In this paper, we use such a deep learning architecture to examine graphs defined using the ICD-10 codes appearing in the medical data of patients who suffered hemorrhagic stroke in Hungary in the period 2006–2012. The purpose of the analysis is to predict the risk of stroke by examining a patient’s ICD graph. Finally, we also compare the effectiveness of this method with classical machine learning classification methods. The results demonstrate that the graph-based method can predict the risk of stroke with an accuracy of over 73%, which is more than 10% higher than the classical methods.

In this study, we investigated the influence of AB-680, a highly potent CD73 inhibitor, on the effect of NBTI, a nucleoside transport blocker, exerted on concentration-effect (E/c) curves generated with CPA, a relatively stable, selective A adenosine receptor full agonist, in isolated, paced guinea pig left atria. Transformations of the CPA E/c curves, constructed in the absence and presence of AB-680 and NBTI (in all combinations), were used to assess the changes in the interstitial adenosine concentration. These changes were quantified with the receptorial responsiveness method (RRM), a unique procedure providing the CPA concentration (as c ), which is equieffective with the increase in the interstitial adenosine concentration caused by NBTI. AB-680 and NBTI were dissolved in DMSO (recommended for use) as well as in a buffer (recommended for use), and the results were compared. We found that AB-680, when added alone, did not affect the response to CPA. In turn, AB-680, when administered together with NBTI, was able to partially reverse the elevating effect of NBTI on the interstitial adenosine level. Nevertheless, the inhibitory action of AB-680 on the effect of NBTI appeared to be smaller than that of PSB-12379, another CD73 inhibitor investigated earlier in the same experimental model. We also found that DMSO interfered with our measurements to a lesser extent than the buffer recommended for studies. In addition, AB-680, when co-administered with NBTI (both dissolved in DMSO), reduced c (i.e. probably also the surplus interstitial adenosine) by at least half.

Cannabidiol (CBD), the most extensively studied non-intoxicating phytocannabinoid, has been attracting a lot of interest worldwide owing to its numerous beneficial effects. The aim of this study was to explore the effect that CBD exerts on the adenosinergic system of paced left atria isolated from obese type Zucker Diabetic Fatty (ZDF) rats, maintained on diabetogenic rat chow, received 60 mg/kg/day CBD or vehicle via gavage for 4 weeks. We found that N6-cyclopentyladenosine (CPA), a relatively stable and poorly transported A1 adenosine receptor agonist, elicited a significantly weaker response in the CBD-treated group than in the vehicle-treated one. In contrast, adenosine, a quickly metabolized and transported adenosine receptor agonist, evoked a significantly stronger response in the CBD-treated group than in the vehicle-treated counterpart (excepting its highest concentrations). These results can be explained only with the adenosine transport inhibitory property of CBD (and not with its adenosine receptor agonist activity). If all the effects of CBD are attributed to the interstitial adenosine accumulation caused by CBD in the myocardium, then a significantly increased adenosinergic activation can be assumed during the long-term oral CBD treatment, suggesting a considerably enhanced adenosinergic protection in the heart. Considering that our results may have been influenced by A1 adenosine receptor downregulation due to the chronic interstitial adenosine accumulation, an adenosinergic activation smaller than it seemed cannot be excluded, but it was above the CBD-naïve level in every case. Additionally, this is the first study offering functional evidence about the adenosine transport inhibitory action of CBD in the myocardium.

Study objectives Obstructive sleep apnea hypopnea syndrome (OSAHS) is a sleep-related breathing disorder, characterized by excessive daytime sleepiness (EDS), paralleled by intermittent collapse of the upper airway. EDS may be the symptom of OSAHS per se but may also be due to the alteration of central circadian regulation. Irisin is a putative myokine and has been shown to induce BDNF expression in several sites of the brain. BDNF is a key factor regulating photic entrainment and consequent circadian alignment and adaptation to the environment. Therefore, we hypothesized that EDS accompanying OSAHS is reflected by alteration of irisin/BDNF axis. Methods Case history, routine laboratory parameters, serum irisin and BDNF levels, polysomnographic measures and Epworth Sleepiness Scale questionnaire (ESS) were performed in a cohort of OSAHS patients ( n  = 69). Simple and then multiple linear regression was used to evaluate data. Results We found that EDS reflected by the ESS is associated with higher serum irisin and BDNF levels; β: 1.53; CI: 0.35, 6.15; p  = 0.012 and β: 0.014; CI: 0.0.005, 0.023; p  = 0.02, respectively. Furthermore, influence of irisin and BDNF was significant even if the model accounted for their interaction ( p  = 0.006 for the terms serum irisin, serum BDNF and their interaction). Furthermore, a concentration-dependent effect of both serum irisin and BDNF was evidenced with respect to their influence on the ESS. Conclusions These results suggest that the irisin-BDNF axis influences subjective daytime sleepiness in OSAS patients reflected by the ESS. These results further imply the possible disruption of the circadian regulation in OSAHS. Future interventional studies are needed to confirm this observation.