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IntroductionThe recent advances of large language models (LLMs) have opened a wide range of opportunities, but at the same time, they pose numerous challenges and questions that research needs to answer. One of the main challenges are the quality and correctness of the output of LLMs as well as the overreliance of students on the output without critically reflecting on it. This poses the question of the quality of the output of LLMs in educational tasks and what students and teachers need to consider when using LLMs for creating educational items. In this work, we focus on the quality and characteristics of conceptual items developed using ChatGPT without user-generated improvements.MethodsFor this purpose, we optimized prompts and created 30 conceptual items in kinematics, which is a standard topic in high-school level physics. The items were rated by two independent experts. Those 15 items that received the highest rating were included in a conceptual survey. The dimensions were designed to align with the ones in the most commonly used concept inventory, the Force Concept Inventory (FCI). We administered the designed items together with the FCI to 172 first-year university students. The results show that ChatGPT items have a medium difficulty and discriminatory index but they overall exhibit a slightly lower average values as the FCI. Moreover, a confirmatory factor analysis confirmed a three factor model that is closely aligned with a previously suggested expert model.Results and discussionIn this way, after careful prompt engineering, thorough analysis and selection of fully automatically generated items by ChatGPT, we were able to create concept items that had only a slightly lower quality than carefully human-generated concept items. The procedures to create and select such a high-quality set of items that is fully automatically generated require large efforts and point towards cognitive demands of teachers when using LLMs to create items. Moreover, the results demonstrate that human oversight or student interviews are necessary when creating one-dimensional assessments and distractors that are closely aligned with students' difficulties.

BackgroundDiscordance between coronary angiographic findings and invasive functional significance is well-established. Yet, the prevalence of this mismatch in an era increasingly utilizing invasive functional assessments, such as fractional flow reserve (FFR), remains unclear. This study examines the extent of such discrepancies in current clinical practice.MethodsThis single-center prospective registry included consecutive patients with chronic coronary syndrome (CCS) who underwent elective coronary angiography, with or without revascularization. Coronary angiograms deemed not requiring FFR due to clear anatomical distinctions, either anatomically severe indicating a need for revascularization or mild suggesting no need for intervention, were selected for evaluation. These were then subjected to post-hoc analysis by three independent operators who were blinded to the definitive treatment strategies. Importantly, the post-hoc analysis was conducted in two distinct phases: firstly, a re-evaluation of coronary stenosis, and secondly, a separate functional assessment, each carried out independently. Coronary stenosis severity was assessed visually, while functional relevance was determined by quantitative flow ratio (QFR), calculated using a computational fluid dynamics algorithm applied to angiographic images. Analysis focused on discrepancies between QFR-based functional indications and revascularization strategies actually performed.ResultsIn 191 patients, 488 vessels were analyzed. Average diameter stenosis (DS) was 37 ± 34%, and QFR was 0.87 ± 0.15, demonstrating a moderate correlation (r = −0.84; 95% CI: −0.86 to −0.81, p

Development of local technologies is crucial to the sustainable energy agenda in resource-limited countries and the world. Strengthening local green technologies and promoting local utilization will reduce carbon emissions that could be generated during transportation and delivery of green products from one country to another. In this paper we developed bio-oil/diesel blends using a low-tech pyrolysis system designed for smallholder farmers in developing countries and tested their appropriateness for diesel engines using standard ASTM methods. Corn stover retrieved from smallholder farmers in Gayaza, Uganda were pyrolyzed in a batch rocket stove reactor at 350 °C and liquid bio-oil harvested. Bio-oil chemical composition was analyzed by Gas Chromatography equipped with Flame Ionization Detector (GC-FID). Bio-oil/diesel emulsions in ternary concentrations 5%, 10% and 20% bio-oil weight were developed with 1% concentration of sorbitan monolaurate as an emulsifier. The bio-oil/diesel emulsions and distillates had property ranges: specific gravities at 15 °C 827.4–830.7 kg m−3, specific gravities at 20 °C 823.9–827.2 kg m −3, kinematic viscosities at 40 °C 3.01–3.22 mm2/s, initial boiling points 140–160 °C, final boiling points 354–368 °C, and calculated cetane indexes 56.80–57.63. These properties of the bio-oil/diesel blends and their distillates compare well with standard transportation diesel fuel. The emulsion distillates meet the standard requirements for automotive diesel in East Africa.

BackgroundMean pulmonary artery wedge pressure (PAWP) represents a right heart catheter (RHC) surrogate measure for mean left atrial (LA) pressure and is crucial for the clinical classification of pulmonary hypertension (PH). Hypothesizing that PAWP is related to acceleration of blood throughout the LA, we investigated whether an adequately introduced LA acceleration factor derived from magnetic resonance (MR) four-dimensional (4D) flow imaging could provide an estimate of PAWP in patients with known or suspected PH.MethodsLA 4D flow data of 62 patients with known or suspected PH who underwent RHC and near-term 1.5 T cardiac MR (ClinicalTrials.gov identifier: NCT00575692) were retrospectively analyzed. Early diastolic LA peak outflow velocity (vE) as well as systolic (vS) and early diastolic (vD) LA peak inflow velocities were determined with prototype software to calculate the LA acceleration factor (α) defined as α = vE/[(vS + vD)/2]. Correlation, regression and Bland-Altman analysis were employed to investigate the relationship between α and PAWP, α-based diagnosis of elevated PAWP (>15 mmHg) was analyzed by receiver operating characteristic curve analysis.Resultsα correlated very strongly with PAWP (r = 0.94). Standard deviation of differences between RHC-derived PAWP and PAWP estimated from linear regression model (α = 0.61 + 0.10·PAWP) was 2.0 mmHg. Employing the linear-regression-derived cut-off α = 2.10, the α-based diagnosis of elevated PAWP revealed the area under the curve 0.97 with sensitivity/specificity 93%/92%.ConclusionsThe very close relationship between the LA acceleration factor α and RHC-derived PAWP suggests α as potential non-invasive parameter for the estimation of PAWP and the distinction between pre- and post-capillary PH.

Purpose Accumulating evidence points towards a close relationship between cardiovascular, endocrine and metabolic diseases. The BioPersMed Study (Biomarkers of Personalised Medicine) is a single-centre prospective observational cohort study with repetitive examination of participants in 2-year intervals. The aim is to evaluate the predictive impact of various traditional and novel biomarkers of cardiovascular, endocrine and metabolic pathways in asymptomatic individuals at risk for cardiovascular and/or metabolic disease.Participants Between 2010 and 2016, we recruited 1022 regional individuals into the study. Subjects aged 45 years or older presenting with at least one traditional cardiovascular risk factor or manifest type 2 diabetes mellitus (T2DM) were enrolled. The mean age of the participants was 57±8 years, 55% were female, 18% had T2DM, 33% suffered from arterial hypertension, 15% were smokers, 42% had hyperlipidaemia, and only 26% were at low cardiovascular risk according to the Framingham ‘Systematic COronary Risk Evaluation’.Findings to date Study procedures during screening and follow-up visits included a physical examination and comprehensive cardiovascular, endocrine, metabolic, ocular and laboratory workup with biobanking of blood and urine samples. The variety of assessed biomarkers allows a full phenotyping of individuals at cardiovascular and metabolic risk. Preliminary data from the cohort and relevant biomarker analyses were already used as control population for genomic studies in local and international research cooperation.Future plans Participants will undergo comprehensive cardiovascular, endocrine and metabolic examinations for the next decades and clinical outcomes will be adjudicated prospectively.

Physical interactions with the real world have many degrees of freedom, which has led to the development of novel input devices with a multitude of sensors to capture increasingly high‐dimensional data. This high dimensionality makes the design of interactive systems more complex. Herein, the use of autoencoder‐based dimensionality reduction is explored to simplify the design process. For this purpose, a data glove equipped with accelerometers is used to record high‐dimensional hand movement data that are thereafter reduced to 2D embeddings using autoencoders. The exploration and evaluation of the resulting embeddings suggest that autoencoders can be used to create meaningful low‐dimensional representations of complex human movement. The characteristics generality, variability, connectivity, and distinguishability are established and a guideline is provided for assessing low‐dimensional embeddings. Referring to these characteristics, system engineers can evaluate different input modalities and gestures for their specific interaction task. Further, a framework is outlined for designing and evaluating gesture interaction in the low‐dimensional space. By demonstrating the exemplary design of the interaction with a virtual lever, this research gives system engineers a template for interaction design in the low‐dimensional space.

Sarcopenia is linked with an increased risk of falls, osteoporosis and mortality and is an increasing problem for healthcare systems. No satisfying biomarkers for sarcopenia diagnosis exist, connecting bone, fat and muscle. Matrix-GLA-protein (MGP) is an adipokine that regulates bone metabolism and is associated with decreased muscle strength. Associations of dp-ucMGP were analyzed in the BioPersMed cohort (58 ± 9 years), including 1022 asymptomatic subjects at moderate cardiovascular risk. Serum measurements of dp-ucMGP in 760 persons were performed with the InaKtif MGP Kit with the IDS-iSYS Multi-Discipline Automated System. DXA data (792 persons) measured with the Lunar iDXA system and physical performance data (786 persons) were available. Dp-ucMGP plasma levels correlate with sarcopenia parameters like gait speed (ρ = −0.192, p < 0.001), appendicular skeletal muscle mass (ρ = 0.102, p = 0.005) and appendicular skeletal muscle mass index (ρ = 0.112, p = 0.001). They are lower in persons with sarcopenia (p < 0.001) and higher in persons with reduced physical performance (p = 0.019). Persons in the lowest dp-ucMGP quartile have the highest risk for reduced muscle mass, decreasing with each quartile, whereas persons in the highest quartile have the highest risk of reduced muscle strength. Dp-ucMGP might be a good biomarker candidate in sarcopenia characterization.

Background: Right ventricular (RV) function predicts survival in numerous cardiac conditions, including left heart disease. The reference standard for non-invasive assessment of RV function is cardiac magnetic resonance imaging (CMR). The aim of this study was to investigate the association between pre-procedural CMR-derived RV functional parameters and mortality in patients undergoing transcatheter aortic valve implantation (TAVI).Methods: Patients scheduled for TAVI were recruited to undergo pre-procedural CMR. Volumetric function and global longitudinal and circumferential strain (GLS and GCS) of the RV and left ventricle (LV) were measured. The association with the primary endpoint (1-year all-cause mortality) was analyzed with Cox regression.Results: Of 133 patients undergoing CMR, 113 patients were included in the analysis. Mean age was 81.8 ± 5.8 years, and 65% were female. Median follow-up was 3.9 [IQR 2.3–4.7] years. All-cause and cardiovascular mortality was 14 and 12% at 1 year, and 28 and 20% at 3 years, respectively. One-year all-cause mortality was significantly predicted by RV GLS [HR = 1.109 (95% CI: 1.023–1.203); p = 0.012], RV ejection fraction [HR = 0.956 (95% CI: 0.929–0.985); p = 0.003], RV end-diastolic volume index [HR = 1.009 (95% CI: 1.001–1.018); p = 0.025], and RV end-systolic volume index [HR = 1.010 (95% CI: 1.003–1.017); p = 0.005]. In receiver operating characteristic (ROC) analysis for 1-year all-cause mortality, the area under the curve was 0.705 (RV GLS) and 0.673 (RV EF). Associations decreased in strength at longer follow-up. None of the LV parameters was associated with mortality.Conclusions: RV function predicts intermediate-term mortality in TAVI patients while LV parameters were not associated with outcomes. Inclusion of easily obtainable RV GLS may improve future risk scores.

Hereby, the supplemental data of the research article “Long-Term Prognostic Value of High-Sensitivity Troponin T added to N-Terminal Pro Brain Natriuretic Peptide Plasma Levels before Valve Replacement for Severe Aortic Stenosis” are presented [1]. It offers enhanced input on the predictive value of these biomarkers considering the influence of the presence of concomitant coronary artery disease (CAD) in various severities as well as an additional cox proportional hazard model on cardiovascular mortality. Furthermore, the receiver operating characteristic (ROC) curves are shown as figures. The material described increases therefore the understanding of the predictive value of these already routinely available biomarkers and reduces the risk of potential bias due to possible confounding factors. It also underlines the urge for a multi-factorial approach in diagnostics to detect the optimal point for referral to valve replacement other than just symptomatic status, an observed reduction in left ventricular ejection fraction or the presence of CAD with the necessity for coronary artery bypass grafting (CABG) [2]. The data of the 3595 patients were gathered retrospectively at a consortium of four university hospital centers in Austria and combined with prospectively collected data on cardiovascular and all-cause mortality. Keywords: High sensitivity troponin T, N-terminal pro brain natiuretic peptide, Severe aortic stenosis, Valve replacement, Survival, Risk stratification

Sarcopenia is linked with increased risk of falls, osteoporosis and mortality. No consensus exists about a gold standard “dual-energy X-ray absorptiometry (DXA) index for muscle mass determination” in sarcopenia diagnosis. Thus, many indices exist, but data on sarcopenia diagnosis agreement are scarce. Regarding sarcopenia diagnosis reliability, the impact of influencing factors on sarcopenia prevalence, diagnosis agreement and reliability are almost completely missing. For nine DXA-derived muscle mass indices, we aimed to evaluate sarcopenia prevalence, diagnosis agreement and diagnosis reliability, and investigate the effects of underlying parameters, presence or type of adjustment and cut-off values on all three outcomes. The indices were analysed in the BioPersMed cohort (58 ± 9 years), including 1022 asymptomatic subjects at moderate cardiovascular risk. DXA data from 792 baselines and 684 follow-up measurements (for diagnosis agreement and reliability determination) were available. Depending on the index and cut-off values, sarcopenia prevalence varied from 0.6 to 36.3%. Height-adjusted parameters, independent of underlying parameters, showed a relatively high level of diagnosis agreement, whereas unadjusted and adjusted indices showed low diagnosis agreement. The adjustment type defines which individuals are recognised as sarcopenic in terms of BMI and sex. The investigated indices showed comparable diagnosis reliability in follow-up examinations

Remote eye tracking has become an important tool for the online analysis of learning processes. Mobile eye trackers can even extend the range of opportunities (in comparison to stationary eye trackers) to real settings, such as classrooms or experimental lab courses. However, the complex and sometimes manual analysis of mobile eye-tracking data often hinders the realization of extensive studies, as this is a very time-consuming process and usually not feasible for real-world situations in which participants move or manipulate objects. In this work, we explore the opportunities to use object recognition models to assign mobile eye-tracking data for real objects during an authentic students’ lab course. In a comparison of three different Convolutional Neural Networks (CNN), a Faster Region-Based-CNN, you only look once (YOLO) v3, and YOLO v4, we found that YOLO v4, together with an optical flow estimation, provides the fastest results with the highest accuracy for object detection in this setting. The automatic assignment of the gaze data to real objects simplifies the time-consuming analysis of mobile eye-tracking data and offers an opportunity for real-time system responses to the user’s gaze. Additionally, we identify and discuss several problems in using object detection for mobile eye-tracking data that need to be considered.

The diagnosis of heart failure with preserved ejection fraction (HFPEF) remains on the basis of echocardiographic analyses at rest. However, some patients with HFPEF have symptoms such as dyspnea only during exercise. Accordingly, echocardiographic analyses at rest could be insufficiently sensitive to identify these patients. In line, recent studies demonstrated that in some patients with HFPEF left ventricular diastolic abnormalities occur only during exercise. This review discusses and analyzes the clinical relevance and evidence of using diastolic stress test echocardiography in patients with HFPEF.

Objective This study was performed to determine whether add-on oral ivabradine in patients treated with beta blockers 1 hour before coronary computed tomographic angiography (CCTA) is effective in lowering the heart rate and thus improving CCTA quality. Methods In this single-center cohort study, the data of 294 patients referred for ambulant CCTA were retrospectively screened. Patients with an initial heart rate of ≥75 bpm (n = 112) were pretreated with either a combination of bisoprolol and ivabradine or with bisoprolol alone. Results During the scan, there was no difference in heart rate between the two groups Likewise, there was no significant difference in additionally administered intravenous bradycardic agents, the number of motion artifacts, or the radiation dose. Both drug regimens were tolerated well. Conclusion Additive oral ivabradine 1 hour before CCTA does not result in a further reduction of the heart rate. Consequently, neither movement artifacts nor radiation dose can be reduced. Therefore, pretreatment with ivabradine does not seem reasonably appropriate in an outpatient clinical setting with short patient contact.

Chronic kidney disease (CKD) is associated with mineral and bone disorder (MBD), which is the main cause of the extensively increased cardiovascular mortality in the CKD population. We now aimed to establish a new murine experimental CKD-MBD model. Dilute brown non-Agouti (DBA/2) mice were fed with high-phosphate diet for 4 (HPD4) or 7 (HPD7) days, then with standard chow diet (SCD) and subsequently followed until day 84. They were compared to DBA/2 mice maintained on SCD during the whole study period. Both 4 and 7 days HPD-fed mice developed phosphate nephropathy with tubular atrophy, interstitial fibrosis, decreased glomerular filtration rate, and increased serum urea levels. The abdominal aorta of HPD-treated mice showed signs of media calcification. Histomorphometric analysis of HPD-treated mice showed decreased bone volume/tissue volume, low mineral apposition rate, and low bone formation rate as compared to SCD-fed mice, despite increased parathyroid hormone levels. Overall, the observed phenotype was more pronounced in the HPD7 group. In summary, we established a new, noninvasive, and therefore easy to perform reproducible CKD-MBD model, which showed media calcification, secondary hyperparathyroidism, and low-turnover bone disease.

Background: Role modeling is an important and valuable educational method. It is predominant throughout (under-)graduate medical education, and attributes of exemplary medical role models are manifold. Aim: This article describes the impact of poor role modeling on medical students’ professional and personal development on the basis of a singular incident at an associated teaching hospital. In addition, scientific literature studying the effect of and the reasons behind poor role modeling in undergraduate and graduate medical education is analyzed and discussed. Results: To maximize the educational potential of clinical role modeling, medical schools have to consider strategies both on the individual as well as on the institutional level. Several suggestions are offered on both levels. Discussion/conclusion: Based on a case report of significantly poor role modeling, this article outlines strategies through which academic medical institutions may maximize the educational potential of role modeling and lastingly enhance teaching proficiency of clinical faculty.

Cancer is often associated with cachexia, cardiovascular symptoms and autonomic dysregulation. We tested whether extracardiac cancer directly affects the innervation of left ventricular myocardium. Mice injected with Lewis lung carcinoma cells (tumor group, TG) or PBS (control group, CG) were analyzed after 21 days. Cardiac function (echocardiography), serum levels of TNF-α and Il-6 (ELISA), structural alterations of cardiomyocytes and their innervation (design-based stereology) and levels of innervation-related mRNA (quantitative RT-PCR) were analysed. The groups did not differ in various functional parameters. Serum levels of TNF-α and Il-6 were elevated in TG. The total length of axons in the left ventricle was reduced. The number of dense core vesicles per axon profile was reduced. Decreased myofibrillar volume, increased sarcoplasmic volume and increased volume of lipid droplets were indicative of metabolic alterations of TG cardiomyocytes. In the heart, the mRNA level of nerve growth factor was reduced whereas that of β1-adrenergic receptor was unchanged in TG. In the stellate ganglion of TG, mRNA levels of nerve growth factor and neuropeptide Y were decreased and that of tyrosine hydroxylase was increased. In summary, cancer induces a systemic pro-inflammatory state, a significant reduction in myocardial innervation and a catabolic phenotype of cardiomyocytes in the mouse. Reduced expression of nerve growth factor may account for the reduced myocardial innervation.