julilili42/papers huggingface dataset:
Perspectives on physician-assisted suicide in mental healthcare: results of a survey of physicians and medical students
2024-08-07

Background Physician-assisted suicide (PAS) is typically associated with serious physical illnesses that are prevalent in palliative care. However, individuals with mental illnesses may also experience such severity that life becomes intolerable. In February 2020, the previous German law prohibiting PAS was repealed. Patients with severe mental illnesses are increasingly likely to approach physicians with requests for PAS. Aims To explore the ethical and moral perspectives of medical students and physicians when making individual decisions regarding PAS. Method An anonymised digital survey was conducted among medical students and physicians in Germany. Participants were presented with a case vignette of a chronically depressed patient requesting PAS. Participants decided on PAS provision and assessed theoretical arguments. We employed generalised ordinal regression and qualitative analysis for data interpretation. Results A total of N = 1478 participants completed the survey. Of these, n = 470 (32%) stated that they would refuse the request, whereas n = 582 (39%) would probably refuse, n = 375 (25%) would probably agree and n = 57 (4%) would definitely agree. Patient-centred arguments such as the right to self-determination increased the likelihood of consent. Concerns that PAS for chronically depressed patients might erode trust in the medical profession resulted in a decreased willingness to provide PAS. Conclusions Participants displayed relatively low willingness to consider PAS in the case of a chronically depressed patient. This study highlights the substantial influence of theoretical medical-ethical arguments and the broader public discourse, underscoring the necessity of an ethical discussion on PAS for mental illnesses.
A new class of receptors: Lipids regulate mammalian Gsα-stimulated adenylyl cyclase activities via their membrane anchors
2024-08-07

The biosynthesis of cAMP by mammalian membrane-bound adenylyl cyclases (mACs) is predominantly regulated by G-protein-coupled-receptors (GPCRs). Up to now the two hexahelical transmembrane domains of mACs were considered to fix the enzyme to membranes. Here we show that the transmembrane domains serve in addition as signal receptors and transmitters of lipid signals that control Gsα-stimulated mAC activities. We identify aliphatic fatty acids and anandamide as receptor ligands of mAC isoforms 1 to 7 and 9. The ligands enhance (mAC isoforms 2, 3, 7, and 9) or attenuate (isoforms 1, 4, 5, and 6) Gsα-stimulated mAC activities in vitro and in vivo . Substitution of the stimulatory membrane receptor of mAC3 by the inhibitory receptor of mAC5 results in a ligand inhibited mAC5-mAC3 chimera. Thus, we discovered a new class of membrane receptors in which two signaling modalities are at a crossing, direct tonic lipid and indirect phasic GPCR-Gsα signaling regulating the biosynthesis of cAMP.
Functional organization of the primate prefrontal cortex reflects individual mnemonic strategies
2024-08-07

Abstract Modular organization, the division of the cerebral cortex into functionally distinct subregions, is well established in the primate sensorimotor cortex, but debated in the cognitive association cortex, including the prefrontal cortex (PFC). Here, we obtained microelectrode recordings with broad spatial coverage from the lateral PFC of two rhesus monkeys performing a working memory task with distractors. We found that neighboring electrodes shared task-related oscillatory neural dynamics that were stable across recording sessions and formed spatially continuous, mesoscale clusters that also segregated by local and long-range frontoparietal connectivity, spiking activity, involvement in working memory processing stages and influence on behavioral accuracy. Remarkably, the degree of parcellation reflected the animals’ individual mnemonic abilities and strategies. Our findings support functional organization of the PFC by cognitive control operations rather than by the type of processed information, indicating that modularity may be a fundamental architectural principle across the primate cortex.
Preparing for Artificial General Intelligence (AGI) in Health Professions Education: AMEE Guide No. 172
2024-08-08

Generative Artificial Intelligence (GenAI) caught Health Professions Education (HPE) institutions off-guard, and they are currently adjusting to a changed educational environment. On the horizon, however, is Artificial <i>General</i> Intelligence (AGI) which promises to be an even greater leap and challenge. This Guide begins by explaining the context and nature of AGI, including its characteristics of multi-modality, generality, adaptability, autonomy, and learning ability. It then explores the implications of AGI on students (including personalised learning and electronic tutors) and HPE institutions, and considers some of the context provided by AGI in healthcare. It then raises the problems to address, including the impact on employment, social risks, student adaptability, costs, quality, and others. After considering a possible timeline, the Guide then ends by indicating some first steps that HPE institutions and educators can take to prepare for AGI.
A Meta-Analysis on Teachers’ Growth Mindset
2024-08-08

Abstract The concept of growth mindset—an individual’s beliefs that basic characteristics such as intelligence are malleable—has gained immense popularity in research, the media, and educational practice. Even though it is assumed that teachers need a growth mindset and that both teachers and their students benefit when teachers adopt a growth mindset, systematic syntheses of the potential advantages of a growth mindset in teachers are lacking. Therefore, in this article, we present the first meta-analysis on teachers’ growth mindset and its relationships with multiple outcomes (50 studies, 81 effect sizes; N = 19,555). Multilevel analyses showed a small effect across outcomes. Statistically significant small-to-typical positive associations between teachers’ growth mindset and their motivation in terms of self-efficacy and mastery goals were observed in subgroup analyses. No statistically significant relationships were found with teachers’ performance-approach goals, teachers’ performance-avoidance goals, teachers’ performance on achievement tests, or student achievement. Teachers’ growth mindset was related to instructional practices in terms of mastery goal structures but unrelated to performance goal structures. Moderator analyses indicated that the dimensionality of the mindset measure (recoded from a fixed mindset to a growth mindset measure vs. assessed as a growth mindset), item referent and content of the mindset measure, publication status (published vs. unpublished), world region, educational level, and study quality influenced the strengths of some of the relationships. Overall, our findings extend knowledge about teachers’ mindset and add to the evidence base on teacher characteristics and their links to relevant outcomes.
The calculating brain
2024-08-08

The human brain possesses neural networks and mechanisms enabling the representation of numbers, basic arithmetic operations, and mathematical reasoning. Without the ability to represent numerical quantity and perform calculations, our scientifically and technically advanced culture would not exist. However, the origins of numerical abilities are grounded in an intuitive understanding of quantity deeply rooted in biology. Nevertheless, more advanced symbolic arithmetic skills require a cultural background with formal mathematical education. In the past two decades, cognitive neuroscience has seen significant progress in understanding the workings of the calculating brain through various methods and model systems. This review begins by exploring the mental and neuronal representations of nonsymbolic numerical quantity and then progresses to symbolic representations acquired in childhood. During arithmetic operations (addition, subtraction, multiplication, and division), these representations are processed and transformed according to arithmetic rules and principles, leveraging different mental strategies and types of arithmetic knowledge that can be dissociated in the brain. Although it was once believed that number processing and calculation originated from the language faculty, it is now evident that mathematical and linguistic abilities are primarily processed independently in the brain. Understanding how the healthy brain processes numerical information is crucial for gaining insights into debilitating numerical disorders, including acquired conditions like acalculia and learning-related calculation disorders such as developmental dyscalculia.
Novel Small-Molecule Atypical Chemokine Receptor 3 Agonists: Design, Synthesis, and Pharmacological Evaluation for Antiplatelet Therapy
2024-08-08

ACKR3, an atypical chemokine receptor, has been associated with prothrombotic events and the development of cardiovascular events. We designed, synthesized, and evaluated a series of novel small molecule ACKR3 agonists. Extensive structure-activity relationship studies resulted in several promising agonists with potencies ranging from the low micromolar to nanomolar range, for example, <b>23</b> (EC<sub>50</sub> = 111 nM, <i>E</i><sub><i>max</i></sub> = 95%) and <b>27</b> (EC<sub>50</sub> = 69 nM, <i>E</i><sub><i>max</i></sub> = 82%) in the β-arrestin-recruitment assay. These compounds are selective for ACKR3 versus ACKR2, CXCR3, and CXCR4. Several agonists were subjected to investigations of their P-selectin expression reduction in the flow cytometry experiments. In particular, compounds <b>23</b> and <b>27</b> showed the highest potency for platelet aggregation inhibition, up to 80% and 97%, respectively. The most promising compounds, especially <b>27</b>, exhibited good solubility, metabolic stability, and no cytotoxicity, suggesting a potential tool compound for the treatment of platelet-mediated thrombosis.
Isolation and characterization of novel acetogenic Moorella strains for employment as potential thermophilic biocatalysts
2024-08-08

Abstract Thermophilic acetogenic bacteria have attracted attention as promising candidates for biotechnological applications such as syngas fermentation, microbial electrosynthesis, and methanol conversion. Here, we aimed to isolate and characterize novel thermophilic acetogens from diverse environments. Enrichment of heterotrophic and autotrophic acetogens was monitored by 16S rRNA gene-based bacterial community analysis. Seven novel Moorella strains were isolated and characterized by genomic and physiological analyses. Two Moorella humiferrea isolates showed considerable differences during autotrophic growth. The M. humiferrea LNE isolate (DSM 117358) fermented carbon monoxide (CO) to acetate, while the M. humiferrea OCP isolate (DSM 117359) transformed CO to hydrogen and carbon dioxide (H2 + CO2), employing the water–gas shift reaction. Another carboxydotrophic hydrogenogenic Moorella strain was isolated from the covering soil of an active charcoal burning pile and proposed as the type strain (ACPsT) of the novel species Moorella carbonis (DSM 116161T and CCOS 2103T). The remaining four novel strains were affiliated with Moorella thermoacetica and showed, together with the type strain DSM 2955T, the production of small amounts of ethanol from H2 + CO2 in addition to acetate. The physiological analyses of the novel Moorella strains revealed isolate-specific differences that considerably increase the knowledge base on thermophilic acetogens for future applications.
Intelligent tutoring systems need real teachers
2024-08-08

The development and distribution of digital learning software, such as intelligent tutoring systems (ITSs), have evolved into a billion-dollar industry, impacting a vast number of students worldwide. While ITSs have significant potential to effectively transform learning and support teachers, the extent to which ITSs rely on teacher support to maintain students’ engagement with the ITS is less well understood. This study evaluates exceptionally rich data from an ITS for learning mathematics used in Germany and the Netherlands (~139,000,000 problems; n ~ 194,000 students) between 2016 and 2023. We compared whether students’ engagement varied based on how they used the ITS: with teacher support (i.e., teachers assigned mathematics problems to students) versus without teacher support (i.e., students self-assigned problems). Our results indicated that students in Germany and the Netherlands consistently (i) dropped out later, (ii) were active for significantly more weeks, and (iii) worked through more mathematics problems each week with teacher support as compared to without teacher support. We observed these results robustly across academic school years within the examined period. Overall, our study challenges the usefulness of digital learning software as stand-alone tools and emphasizes the need for embedding such software in real-life learning scenarios involving teachers.
Evaluation and Optimization of an X-ray Fluorescence Analyzer for Rapid Analysis of Chemical Elements in Solid Biofuels
2024-08-08

To optimize wood-fired heat (and power) plants, it is essential to rapidly determine the chemical composition of solid biofuels on-site shortly before combustion. However, the standard procedures for chemical analysis [inductively coupled plasma-optical emission spectrometry (ICP-OES), inductively coupled plasma-mass spectrometry] are time-consuming, expensive and require highly trained personnel. Thus, they are unsuitable for online fuel analysis. Newly developed, rapid, on-site analysis methods might enhance analysis at the plant. Thereby, X-ray fluorescence (XRF) analysis is one of the most promising methods. So far, XRF has been evaluated in various fields like geology, coal, ash analysis, as well as biomass in general, but this method is still insufficiently investigated for the sector of solid biofuels. The aim of this work is to evaluate and optimize an XRF analyzer for the rapid determination of chemical elements in wood fuels. The XRF analyzer was calibrated using several wood chip samples. Measurements before and after calibration were compared with the reference method (ICP-OES). Results show that XRF can be recommended for analyzing the elements Mg, P, K, Ca, Si, Al, Cr, Mn, Fe, Zn and Pb, while S, Cl, Ti and Ni can potentially be determined with element-specific calibrations. Cu, As, and Cd could not be measured satisfactorily, as many measurements were below the limit of detection. Still, XRF might be used for threshold value monitoring (e.g., in the scope of the German Waste Wood Ordinance).
Ion concentration polarization causes a nearly pore-length-independent conductance of nanopores
2024-08-08

The conductance and selectivity of low-aspect-ratio nanopores are almost independent of the length due to polarization effects controlled by the geometric and electrochemical properties of the whole (pore + reservoir) system.
Nonlinear latent representations of high-dimensional task-fMRI data: Unveiling cognitive and behavioral insights in heterogeneous spatial maps
2024-08-08

Finding an interpretable and compact representation of complex neuroimaging data is extremely useful for understanding brain behavioral mapping and hence for explaining the biological underpinnings of mental disorders. However, hand-crafted representations, as well as linear transformations, may inadequately capture the considerable variability across individuals. Here, we implemented a data-driven approach using a three-dimensional autoencoder on two large-scale datasets. This approach provides a latent representation of high-dimensional task-fMRI data which can account for demographic characteristics whilst also being readily interpretable both in the latent space learned by the autoencoder and in the original voxel space. This was achieved by addressing a joint optimization problem that simultaneously reconstructs the data and predicts clinical or demographic variables. We then applied normative modeling to the latent variables to define summary statistics (‘latent indices’) and establish a multivariate mapping to non-imaging measures. Our model, trained with multi-task fMRI data from the Human Connectome Project (HCP) and UK biobank task-fMRI data, demonstrated high performance in age and sex predictions and successfully captured complex behavioral characteristics while preserving individual variability through a latent representation. Our model also performed competitively with respect to various baseline models including several variants of principal components analysis, independent components analysis and classical regions of interest, both in terms of reconstruction accuracy and strength of association with behavioral variables.
Deciphering the SAM- and metal-dependent mechanism of O-methyltransferases in cystargolide and belactosin biosynthesis: A structure–activity relationship study
2024-08-08

Cystargolides and belactosins are natural products with a distinct dipeptide structure and an electrophilic β-lactone warhead. They are known to inhibit proteases such as the proteasome or caseinolytic protease P, highlighting their potential in treating cancers and neurodegenerative diseases. Recent genetic analyses have shown homology between the biosynthetic pathways of the two inhibitors. Here, we characterize the O-methyltransferases BelI and CysG, which catalyze the initial step of β-lactone formation. Employing techniques such as crystallography, computational analysis, mutagenesis, and activity assays, we identified a His-His-Asp (HHD) motif in the active sites of the two enzymes, which is crucial for binding a catalytically active calcium ion. Our findings thus elucidate a conserved divalent metal-dependent mechanism in both biosynthetic pathways that distinguish BelI and CysG from previously characterized O-methyltransferases.
Do prompts and strategy instruction contribute to pre-service teachers’ peer-feedback on technology-integration?
2024-08-08

Abstract Peer feedback is regarded as playing a vital role in fostering preservice teachers’ noticing and reasoning skills during technology integration. However, novices in particular (e.g., pre-service teachers) tend to provide rather superficial feedback, which does not necessarily contribute to professional development. Against this background, we developed an online video-annotation tool, LiveFeedback + , which allows for providing peer feedback on the quality of technology integration during microteachings in a fine-grained manner. Applying a design-based research approach (2 design cycles, N = 42 pre-service teachers, quasi-experimental interrupted time-series design), we investigated whether the addition of prompts (Cycle 1) and strategy instruction combined with prompts (Cycle 2) contributed to the quality of peer feedback. Contrary to our predictions, piecewise regressions demonstrated that pre-service teachers provided more feedback comments with superficial praise and fewer feedback comments with substantial problem identification and solutions when prompts were available. However, when pre-service teachers were explicitly instructed in strategy use, the reasoning during peer feedback could be enhanced to some extent, as pre-service teachers provided less praise and more problem diagnosis in feedback comments when strategy instruction was available. These findings suggest that the addition of strategy instruction that explicitly models adequate feedback strategies based on prompts can help overcome mediation deficits during peer feedback in technology-based settings.
Oxytocin does not acutely improve glucose tolerance in men with type 2 diabetes
2024-08-08

Abstract Aim To assess oxytocin's acute glucoregulatory impact in men with type 2 diabetes in the context of our previous findings that oxytocin improves β‐cell responsivity in healthy men. Methods In a double‐blind, crossover comparison, intranasal oxytocin (24 IU) and placebo, respectively, were administered to 25 fasted men with non‐insulin–treated type 2 diabetes (age ± standard error of the mean, 63.40 ± 1.36 years; body mass index, 27.77 ± 0.66 kg/m 2 ; HbA1c, 6.86% ± 0.08%; Homeostatic Model Assessment of Insulin Resistance (HOMA‐IR, 3.44 ± 0.39) 60 minutes before an oral glucose tolerance test (oGTT). Key outcomes were compared with previous results in men with normal weight or obesity. Results Oxytocin compared with placebo increased plasma oxytocin concentrations and reduced the heart rate, but did not alter glucose metabolism in the 3 hours after oGTT onset (area under the curve, glucose, 2240 ± 80.5 vs. 2190 ± 69.5 mmol/L × min; insulin, 45 663 ± 4538 vs. 44 343 ± 4269 pmol/L × min; C‐peptide, 235 ± 5.1 vs. 231 ± 15.9 nmol/L × min). Conclusions This outcome contrasts with the oxytocin‐induced attenuation of early postprandial glucose excursions in normal‐weight individuals, but is in line with the absence of respective effects in men with obesity. We conclude that insulin resistance in type 2 diabetes is associated with decreased sensitivity to the acute glucoregulatory effect of oxytocin in male individuals.
High-Resolution Tandem Mass Spectrometry-Based Analysis of Model Lignin–Iron Complexes: Novel Pipeline and Complex Structures
2024-08-08

Understanding the chemical nature of soil organic carbon (SOC) with great potential to bind iron (Fe) minerals is critical for predicting the stability of SOC. Organic ligands of Fe are among the top candidates for SOCs able to strongly sorb on Fe minerals, but most of them are still molecularly uncharacterized. To shed insights into the chemical nature of organic ligands in soil and their fate, this study developed a protocol for identifying organic ligands using ultrahigh-performance liquid chromatography-high-resolution tandem mass spectrometry (UHPLC-HRMS/MS) and metabolomic tools. The protocol was used for investigating the Fe complexes formed by model compounds of lignin-derived organic ligands, namely, caffeic acid (CA), p-coumaric acid (CMA), vanillin (VNL), and cinnamic acid (CNA). Isotopologue analysis of &lt;sup&gt;54/56&lt;/sup&gt;Fe was used to screen out the potential UHPLC-HRMS (m/z) features for complexes formed between organic ligands and Fe, with multiple features captured for CA, CMA, VNL, and CNA when &lt;sup&gt;35/37&lt;/sup&gt;Cl isotopologue analysis was used as supplementary evidence for the complexes with Cl. MS/MS spectra, fragment analysis, and structure prediction with SIRIUS were used to annotate the structures of mono/bidentate mono/biligand complexes. The analysis determined the structures of monodentate and bidentate complexes of FeL&lt;sub&gt;x&lt;/sub&gt;Cl&lt;sub&gt;y&lt;/sub&gt; (L: organic ligand, x = 1–4, y = 0–3) formed by model compounds. The protocol developed in this study can be used to identify unknown organic ligands occurring in complex environmental samples and shed light on the molecular-level processes governing the stability of the SOC.
Bayesian Priors in Active Avoidance
2024-08-08

Failing to make decisions that would actively avoid negative outcomes is central to helplessness. In a Bayesian framework, deciding whether to act is informed by beliefs about the world that can be characterised as priors. However, these priors have not been previously quantified. Here we administered two tasks in which participants decided whether to attempt active avoidance actions. The tasks differed in framing and valence, allowing us to test whether the prior generating biases in behaviour is problem-specific or task-independent and general. We performed extensive comparisons of models offering different structural explanations of the data, finding that a Bayesian model with a task-invariant prior for active avoidance provided the best fit to participants’ trial-by-trial behaviour. The parameters of this prior were reliable, and participants with an optimistic prior also reported higher levels of positive affect. These results show that individual differences in prior beliefs can explain decisions to engage in active avoidance of negative outcomes, providing evidence for a Bayesian conceptualization of helplessness.