Comprehensive metabolome characterization of leaves, internodes, and aerial roots of Vanilla planifolia by untargeted LC-MS and GC × GC-MS.

INTRODUCTION: Untargeted metabolomics is a powerful tool that provides strategies for gaining a systematic understanding of quantitative changes in the levels of metabolites, especially when combining different metabolomic platforms. Vanilla is one of the world's most popular flavors originating from cured pods of the orchid Vanilla planifolia. However, only a few studies have investigated the metabolome of V. planifolia, and no LC-MS or GC-MS metabolomics studies with respect to leaves have been performed. OBJECTIVE: The aim of the study was to comprehensively characterize the metabolome of different organs (leaves, internodes, and aerial roots) of V. planifolia. MATERIAL AND METHODS: Characterization of the metabolome was achieved using two complementary platforms (GC × GC-MS, LC-QToF-MS), and metabolite identification was based on a comparison with in-house databases or curated external spectral libraries. RESULTS: In total, 127 metabolites could be identified with high certainty (confidence level 1 or 2) including sugars, amino acids, fatty acids, organic acids, and amines/amides but also secondary metabolites such as vanillin-related metabolites, flavonoids, and terpenoids. Ninty-eight metabolites showed significantly different intensities between the plant organs. Most strikingly, aglycons of flavonoids and vanillin-related metabolites were elevated in aerial roots, whereas its O-glycoside forms tended to be higher in leaves and/or internodes. This suggests that the more bioactive aglycones may accumulate where preferably needed, e.g. for defense against pathogens. CONCLUSION: The results derived from the study substantially expand the knowledge regarding the vanilla metabolome forming a valuable basis for more targeted investigations in future studies, e.g. towards an optimization of vanilla plant cultivation.

Quantification of the rotating frame relaxation time T2ρ: Comparison of balanced spin-lock and continuous-wave Malcolm-Levitt preparations.

For the quantification of rotating frame relaxation times, the T2ρ relaxation pathway plays an essential role. Nevertheless, T2ρ imaging has been studied only to a small extent compared with T1ρ, and preparation techniques for T2ρ have so far been adapted from T1ρ methods. In this work, two different preparation concepts are compared specifically for the use of T2ρ mapping. The first approach involves transferring the balanced spin-locking (B-SL) concept of T1ρ imaging. The second and newly proposed approach is a continuous-wave Malcolm-Levitt (CW-MLEV) pulse train with zero echo times and was motivated from T2 preparation strategies. The modules are tested in Bloch simulations for their intrinsic sensitivity to field inhomogeneities and validated in phantom experiments. In addition, myocardial T2ρ mapping was performed in mice as an exemplary application. Our results demonstrate that the CW-MLEV approach provides superior robustness and thus suggest that established methods of T1ρ imaging are not best suited for T2ρ experiments. In the presence of field inhomogeneities, the simulations indicated an increased banding compensation by a factor of 4.1 compared with B-SL. Quantification of left ventricular T2ρ time in mice yielded more consistent results, and values in the range of 59.2-61.1 ms (R2 = 0.986-0.992) were observed at 7 T.

Rotary excitation of non-sinusoidal pulsed magnetic fields: Towards non-invasive direct detection of cardiac conduction.

PURPOSE: There is a need for high resolution non-invasive imaging methods of physiologic magnetic fields. The purpose of this work is to develop a MRI detection approach for non-sinusoidal magnetic fields based on the rotary excitation (REX) mechanism which was previously successfully applied for the detection of oscillating magnetic fields in the sub-nT range. METHODS: The new detection concept was examined by means of Bloch simulations, evaluating the interaction effect of spin-locked magnetization and low-frequency pulsed magnetic fields. The REX detection approach was validated under controlled conditions in phantom experiments at 3 T. Gaussian and sinc-shaped stimuli were investigated. In addition, the detection of artificial fields resembling a cardiac QRS complex, which is the most prominent peak visible on a magnetocardiogram, was tested. RESULTS: Bloch simulations demonstrated that the REX method has a high sensitivity to pulsed fields in the resonance case, which is met when the spin-lock frequency coincides with a non-zero Fourier component of the stimulus field. In the experiments, we found that magnetic stimuli of different durations and waveforms can be distinguished by their characteristic REX response spectrum. The detected REX amplitude was proportional to the stimulus peak amplitude (R2 > 0.98) and the lowest field detection was 1 nT. Furthermore, the detection of QRS-like fields with varying QRS durations yielded significant results in a phantom setup (p < 0.001). CONCLUSION: REX detection can be transferred to non-sinusoidal pulsed magnetic fields and could provide a non-invasive, quantitative tool for spatially resolved assessment of cardiac biomagnetism. Potential applications include the direct detection and characterization of cardiac conduction.

Enhancing quality and speed in database-free neural network reconstructions of undersampled MRI with SCAMPI.

PURPOSE: We present SCAMPI (Sparsity Constrained Application of deep Magnetic resonance Priors for Image reconstruction), an untrained deep Neural Network for MRI reconstruction without previous training on datasets. It expands the Deep Image Prior approach with a multidomain, sparsity-enforcing loss function to achieve higher image quality at a faster convergence speed than previously reported methods. METHODS: Two-dimensional MRI data from the FastMRI dataset with Cartesian undersampling in phase-encoding direction were reconstructed for different acceleration rates for single coil and multicoil data. RESULTS: The performance of our architecture was compared to state-of-the-art Compressed Sensing methods and ConvDecoder, another untrained Neural Network for two-dimensional MRI reconstruction. SCAMPI outperforms these by better reducing undersampling artifacts and yielding lower error metrics in multicoil imaging. In comparison to ConvDecoder, the U-Net architecture combined with an elaborated loss-function allows for much faster convergence at higher image quality. SCAMPI can reconstruct multicoil data without explicit knowledge of coil sensitivity profiles. Moreover, it is a novel tool for reconstructing undersampled single coil k-space data. CONCLUSION: Our approach avoids overfitting to dataset features, that can occur in Neural Networks trained on databases, because the network parameters are tuned only on the reconstruction data. It allows better results and faster reconstruction than the baseline untrained Neural Network approach.

Seeing plants as never before.

Imaging has long supported our ability to understand the inner life of plants, their development, and response to a dynamic environment. While optical microscopy remains the core tool for imaging, a suite of novel technologies is now beginning to make a significant contribution to visualize plant metabolism. The purpose of this review was to provide the scientific community with an overview of current imaging methods, which rely variously on either nuclear magnetic resonance (NMR), mass spectrometry (MS) or infrared (IR) spectroscopy, and to present some examples of their application in order to illustrate their utility. In addition to providing a description of the basic principles underlying these technologies, the review discusses their various advantages and limitations, reveals the current state of the art, and suggests their potential application to experimental practice. Finally, a view is presented as to how the technologies will likely develop, how these developments may encourage the formulation of novel experimental strategies, and how the enormous potential of these technologies can contribute to progress in plant science.

Non-destructive classification of unlabeled cells: Combining an automated benchtop magnetic resonance scanner and artificial intelligence.

In order to treat degenerative diseases, the importance of advanced therapy medicinal products has increased in recent years. The newly developed treatment strategies require a rethinking of the appropriate analytical methods. Current standards are missing the complete and sterile analysis of the product of interest to make the drug manufacturing effort worthwhile. They only consider partial areas of the sample or product while also irreversibly damaging the investigated specimen. Two-dimensional T1 / T2 MR relaxometry meets these requirements and is therefore a promising in-process control during the manufacturing and classification process of cell-based treatments. In this study a tabletop MR scanner was used to perform two-dimensional MR relaxometry. Throughput was increased by developing an automation platform based on a low-cost robotic arm, resulting in the acquisition of a large dataset of cell-based measurements. Two-dimensional inverse Laplace transformation was used for post-processing, followed by data classification performed with support vector machines (SVM) as well as optimized artificial neural networks (ANN). The trained networks were able to distinguish non-differentiated from differentiated MSCs with a prediction accuracy of 85%. To increase versatility, an ANN was trained on 354 independent, biological replicates distributed across ten different cell lines, resulting in a prediction accuracy of up to 98% depending on data composition. The present study provides a proof of principle for the application of T1 / T2 relaxometry as a non-destructive cell classification method. It does not require labeling of cells and can perform whole mount analysis of each sample. Since all measurements can be performed under sterile conditions, it can be used as an in-process control for cellular differentiation. This distinguishes it from other characterization techniques, as most are destructive or require some type of cell labeling. These advantages highlight the technique's potential for preclinical screening of patient-specific cell-based transplants and drugs.

Iterative training of robust k-space interpolation networks for improved image reconstruction with limited scan specific training samples.

PURPOSE: To evaluate an iterative learning approach for enhanced performance of robust artificial-neural-networks for k-space interpolation (RAKI), when only a limited amount of training data (auto-calibration signals [ACS]) are available for accelerated standard 2D imaging. METHODS: In a first step, the RAKI model was tailored for the case of limited training data amount. In the iterative learning approach (termed iterative RAKI [iRAKI]), the tailored RAKI model is initially trained using original and augmented ACS obtained from a linear parallel imaging reconstruction. Subsequently, the RAKI convolution filters are refined iteratively using original and augmented ACS extracted from the previous RAKI reconstruction. Evaluation was carried out on 200 retrospectively undersampled in vivo datasets from the fastMRI neuro database with different contrast settings. RESULTS: For limited training data (18 and 22 ACS lines for R = 4 and R = 5, respectively), iRAKI outperforms standard RAKI by reducing residual artifacts and yields better noise suppression when compared to standard parallel imaging, underlined by quantitative reconstruction quality metrics. Additionally, iRAKI shows better performance than both GRAPPA and standard RAKI in case of pre-scan calibration with varying contrast between training- and undersampled data. CONCLUSION: RAKI benefits from the iterative learning approach, which preserves the noise suppression feature, but requires less original training data for the accurate reconstruction of standard 2D images thereby improving net acceleration.

Post-COVID-19-associated morbidity in children, adolescents, and adults: A matched cohort study including more than 157,000 individuals with COVID-19 in Germany.

BACKGROUND: Long-term health sequelae of the Coronavirus Disease 2019 (COVID-19) are a major public health concern. However, evidence on post-acute COVID-19 syndrome (post-COVID-19) is still limited, particularly for children and adolescents. Utilizing comprehensive healthcare data on approximately 46% of the German population, we investigated post-COVID-19-associated morbidity in children/adolescents and adults. METHODS AND FINDINGS: We used routine data from German statutory health insurance organizations covering the period between January 1, 2019 and December 31, 2020. The base population included all individuals insured for at least 1 day in 2020. Based on documented diagnoses, we identified individuals with polymerase chain reaction (PCR)-confirmed COVID-19 through June 30, 2020. A control cohort was assigned using 1:5 exact matching on age and sex, and propensity score matching on preexisting medical conditions. The date of COVID-19 diagnosis was used as index date for both cohorts, which were followed for incident morbidity outcomes documented in the second quarter after index date or later.Overall, 96 prespecified outcomes were aggregated into 13 diagnosis/symptom complexes and 3 domains (physical health, mental health, and physical/mental overlap domain). We used Poisson regression to estimate incidence rate ratios (IRRs) with 95% confidence intervals (95% CIs). The study population included 11,950 children/adolescents (48.1% female, 67.2% aged between 0 and 11 years) and 145,184 adults (60.2% female, 51.1% aged between 18 and 49 years). The mean follow-up time was 236 days (standard deviation (SD) = 44 days, range = 121 to 339 days) in children/adolescents and 254 days (SD = 36 days, range = 93 to 340 days) in adults. COVID-19 and control cohort were well balanced regarding covariates. The specific outcomes with the highest IRR and an incidence rate (IR) of at least 1/100 person-years in the COVID-19 cohort in children and adolescents were malaise/fatigue/exhaustion (IRR: 2.28, 95% CI: 1.71 to 3.06, p < 0.01, IR COVID-19: 12.58, IR Control: 5.51), cough (IRR: 1.74, 95% CI: 1.48 to 2.04, p < 0.01, IR COVID-19: 36.56, IR Control: 21.06), and throat/chest pain (IRR: 1.72, 95% CI: 1.39 to 2.12, p < 0.01, IR COVID-19: 20.01, IR Control: 11.66). In adults, these included disturbances of smell and taste (IRR: 6.69, 95% CI: 5.88 to 7.60, p < 0.01, IR COVID-19: 12.42, IR Control: 1.86), fever (IRR: 3.33, 95% CI: 3.01 to 3.68, p < 0.01, IR COVID-19: 11.53, IR Control: 3.46), and dyspnea (IRR: 2.88, 95% CI: 2.74 to 3.02, p < 0.01, IR COVID-19: 43.91, IR Control: 15.27). For all health outcomes combined, IRs per 1,000 person-years in the COVID-19 cohort were significantly higher than those in the control cohort in both children/adolescents (IRR: 1.30, 95% CI: 1.25 to 1.35, p < 0.01, IR COVID-19: 436.91, IR Control: 335.98) and adults (IRR: 1.33, 95% CI: 1.31 to 1.34, p < 0.01, IR COVID-19: 615.82, IR Control: 464.15). The relative magnitude of increased documented morbidity was similar for the physical, mental, and physical/mental overlap domain. In the COVID-19 cohort, IRs were significantly higher in all 13 diagnosis/symptom complexes in adults and in 10 diagnosis/symptom complexes in children/adolescents. IRR estimates were similar for age groups 0 to 11 and 12 to 17. IRs in children/adolescents were consistently lower than those in adults. Limitations of our study include potentially unmeasured confounding and detection bias. CONCLUSIONS: In this retrospective matched cohort study, we observed significant new onset morbidity in children, adolescents, and adults across 13 prespecified diagnosis/symptom complexes, following COVID-19 infection. These findings expand the existing available evidence on post-COVID-19 conditions in younger age groups and confirm previous findings in adults. TRIAL REGISTRATION: ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT05074953.

An enzymatic tandem reaction to produce odor-active fatty aldehydes.

Aldehydes represent a versatile and favored class of flavoring substances. A biocatalytic access to odor-active aldehydes was developed by conversion of fatty acids with two enzymes of the α-dioxygenase pathway. The recombinant enzymes α-dioxygenase (α-DOX) originating from Crocosphaera subtropica and fatty aldehyde dehydrogenase (FALDH) from Vibrio harveyi were heterologously expressed in E. coli, purified, and applied in a coupled (tandem) repetitive reaction. The concept was optimized in terms of number of reaction cycles and production yields. Up to five cycles and aldehyde yields of up to 26% were achieved. Afterward, the approach was applied to sea buckthorn pulp oil as raw material for the enzyme catalyzed production of flavoring/fragrance ingredients based on complex aldehyde mixtures. The most abundant fatty acids in sea buckthorn pulp oil, namely palmitic, palmitoleic, oleic, and linoleic acid, were used as substrates for further biotransformation experiments. Various aldehydes were identified, semi-quantified, and sensorially characterized by means of headspace-solid phase microextraction-gas chromatography-mass spectrometry-olfactometry (HS-SPME-GC-MS-O). Structural validation of unsaturated aldehydes in terms of double-bond positions was performed by multidimensional high-resolution mass spectrometry experiments of their Paternò-Büchi (PB) photoproducts. Retention indices and odor impressions of inter alia (Z,Z)-5,8-tetradecadienal (Z,Z)-6,9-pentadecadienal, (Z)-8-pentadecenal, (Z)-4-tridecenal, (Z)-6-pentadecenal, and (Z)-8-heptadecenal were determined for the first time. KEY POINTS: • Coupled reaction of Csα-DOX and VhFALDH yields chain-shortened fatty aldehydes. • Odors of several Z-unsaturated fatty aldehydes are described for the first time. • Potential for industrial production of aldehyde-based odorants from natural sources.

Quantification correction for free-breathing myocardial T1ρ mapping in mice using a recursively derived description of a T1ρ* relaxation pathway.

BACKGROUND: Fast and accurate T1ρ mapping in myocardium is still a major challenge, particularly in small animal models. The complex sequence design owing to electrocardiogram and respiratory gating leads to quantification errors in in vivo experiments, due to variations of the T1ρ relaxation pathway. In this study, we present an improved quantification method for T1ρ using a newly derived formalism of a T1ρ* relaxation pathway. METHODS: The new signal equation was derived by solving a recursion problem for spin-lock prepared fast gradient echo readouts. Based on Bloch simulations, we compared quantification errors using the common monoexponential model and our corrected model. The method was validated in phantom experiments and tested in vivo for myocardial T1ρ mapping in mice. Here, the impact of the breath dependent spin recovery time Trec on the quantification results was examined in detail. RESULTS: Simulations indicate that a correction is necessary, since systematically underestimated values are measured under in vivo conditions. In the phantom study, the mean quantification error could be reduced from - 7.4% to - 0.97%. In vivo, a correlation of uncorrected T1ρ with the respiratory cycle was observed. Using the newly derived correction method, this correlation was significantly reduced from r = 0.708 (p < 0.001) to r = 0.204 and the standard deviation of left ventricular T1ρ values in different animals was reduced by at least 39%. CONCLUSION: The suggested quantification formalism enables fast and precise myocardial T1ρ quantification for small animals during free breathing and can improve the comparability of study results. Our new technique offers a reasonable tool for assessing myocardial diseases, since pathologies that cause a change in heart or breathing rates do not lead to systematic misinterpretations. Besides, the derived signal equation can be used for sequence optimization or for subsequent correction of prior study results.

Quantitative monitoring of paramagnetic contrast agents and their allocation in plant tissues via DCE-MRI.

BACKGROUND: Studying dynamic processes in living organisms with MRI is one of the most promising research areas. The use of paramagnetic compounds as contrast agents (CA), has proven key to such studies, but so far, the lack of appropriate techniques limits the application of CA-technologies in experimental plant biology. The presented proof-of-principle aims to support method and knowledge transfer from medical research to plant science. RESULTS: In this study, we designed and tested a new approach for plant Dynamic Contrast Enhanced Magnetic Resonance Imaging (pDCE-MRI). The new approach has been applied in situ to a cereal crop (Hordeum vulgare). The pDCE-MRI allows non-invasive investigation of CA allocation within plant tissues. In our experiments, gadolinium-DTPA, the most commonly used contrast agent in medical MRI, was employed. By acquiring dynamic T1-maps, a new approach visualizes an alteration of a tissue-specific MRI parameter T1 (longitudinal relaxation time) in response to the CA. Both, the measurement of local CA concentration and the monitoring of translocation in low velocity ranges (cm/h) was possible using this CA-enhanced method. CONCLUSIONS: A novel pDCE-MRI method is presented for non-invasive investigation of paramagnetic CA allocation in living plants. The temporal resolution of the T1-mapping has been significantly improved to enable the dynamic in vivo analysis of transport processes at low-velocity ranges, which are common in plants. The newly developed procedure allows to identify vascular regions and to estimate their involvement in CA allocation. Therefore, the presented technique opens a perspective for further development of CA-aided MRI experiments in plant biology.

Reducing the Bitter Taste of Pharmaceuticals Using Cell-Based Identification of Bitter-Masking Compounds.

The palatability of a pharmaceutical preparation is a significant obstacle in developing a patient-friendly dosage form. Bitter taste is an important factor for patients in (i) selecting a certain drug from generic products available in the market and (ii) adhering to a therapeutic regimen. The various methods developed for identification of bitter tasting and bitter-taste modulating compounds present a number of limitations, ranging from limited sensitivity to lack of close correlations with sensory data. In this study, we demonstrate a fluorescence-based assay, analyzing the bitter receptor TAS2R-linked intracellular pH (pHi) of human gastric parietal (HGT-1) cells as a suitable tool for the identification of bitter tasting and bitter-taste modulating pharmaceutical compounds and preparations, which resembles bitter taste perception. Among the fluorometric protocols established to analyze pHi changes, one of the most commonly employed assays is based on the use of the pH-sensitive dye SNARF-1 AM. This methodology presents some limitations; over time, the assay shows a relatively low signal amplitude and sensitivity. Here, the SNARF-1 AM methodology was optimized. The identified bicarbonate extrusion mechanisms were partially inhibited, and measurements were carried out in a medium with lower intrinsic fluorescence, with no need for controlling external CO2 levels. We applied the assay for the screening of flavonoids as potential bitter-masking compounds for guaifenesin, a bitter-tasting antitussive drug. Our findings revealed that eriodictyol, hesperitin and phyllodulcin were the most potent suitable candidates for bitter-masking activity, verified in a human sensory trial.

Mattering and parental presence in systemic therapy using nonviolent resistance: The utilization of imaginary methods.

An empowered sense of "self" is crucial for emotional well-being and positive relationships. Certain family interaction patterns can disrupt the adult's sense of "mattering" to the child, eroding their perceived self-efficacy. Mattering can be understood as a felt sense of relational agency which is necessary for experiencing one's interactions as meaningful, effective, and self-determined. When parents generate more positive future narratives in co-creation with their therapist, their sense of relevance to a child can be restored. In this way, more constructive forms of interaction can emerge with their child which has hitherto eschewed their care. This article aims to provide a conceptual basis for addressing an absence of reciprocity, where children demonstrate harmful or self-destructive behavior and refuse to cooperate in therapy. In such instances, one-sided parental action, utilizing nonviolent resistance methods, can influence relational dynamics. Imaginary methods can then facilitate shifts to psychological states in which the parent internally experiences efficacy and mattering more often without requiring validation from the "physical child" in the here and now. We introduce examples of specific imaginary techniques, which in our clinical practice have shown to facilitate such shifts in parents. We discuss neuroscientific theories that may account for their powerful impact we witness in our clinical experience.

Una sensación fortalecida del yo es fundamental para el bienestar emocional y las relaciones positivas. Ciertos patrones de interacción familiar pueden alterar la sensación del adulto de importarle al niño, deteriorando su autoeficacia percibida. La sensación de importarles a los demás puede entenderse como una percepción sentida de voluntad relacional que es necesaria para vivir las interacciones propias como significativas, eficaces y autodeterminadas. Cuando los padres generan narrativas futuras más positivas junto con su terapeuta, se puede recuperar su sensación de importancia para un niño. De esa manera, pueden surgir formas más constructivas de interacción con su hijo que hasta el momento ha eludido su cuidado. Este artículo tiene como finalidad ofrecer una base conceptual para abordar una ausencia de reciprocidad, donde los niños demuestran una conducta perjudicial o autodestructiva y se niegan a cooperar en la terapia. En esos casos, la acción de uno de los padres mediante el uso de métodos de resistencia no violenta puede influir en la dinámica relacional. Los métodos imaginarios pueden entonces facilitar cambios a estados psicológicos en los cuales el padre siente internamente su eficacia y tiene la sensación de importarle al niño con más frecuencia sin necesitar confirmación del niño físico en el aquí y ahora. Presentamos ejemplos de técnicas imaginarias específicas que en nuestra práctica clínica han demostrado facilitar dichos cambios en los padres. Comentamos las teorías neurocientíficas que pueden explicar el enorme efecto que observamos en nuestra experiencia clínica.

Fast myocardial T1ρ mapping in mice using k-space weighted image contrast and a Bloch simulation-optimized radial sampling pattern.

PURPOSE: T1ρ dispersion quantification can potentially be used as a cardiac magnetic resonance index for sensitive detection of myocardial fibrosis without the need of contrast agents. However, dispersion quantification is still a major challenge, because T1ρ mapping for different spin lock amplitudes is a very time consuming process. This study aims to develop a fast and accurate T1ρ mapping sequence, which paves the way to cardiac T1ρ dispersion quantification within the limited measurement time of an in vivo study in small animals. METHODS: A radial spin lock sequence was developed using a Bloch simulation-optimized sampling pattern and a view-sharing method for image reconstruction. For validation, phantom measurements with a conventional sampling pattern and a gold standard sequence were compared to examine T1ρ quantification accuracy. The in vivo validation of T1ρ mapping was performed in N = 10 mice and in a reproduction study in a single animal, in which ten maps were acquired in direct succession. Finally, the feasibility of myocardial dispersion quantification was tested in one animal. RESULTS: The Bloch simulation-based sampling shows considerably higher image quality as well as improved T1ρ quantification accuracy (+ 56%) and precision (+ 49%) compared to conventional sampling. Compared to the gold standard sequence, a mean deviation of - 0.46 ± 1.84% was observed. The in vivo measurements proved high reproducibility of myocardial T1ρ mapping. The mean T1ρ in the left ventricle was 39.5 ± 1.2 ms for different animals and the maximum deviation was 2.1% in the successive measurements. The myocardial T1ρ dispersion slope, which was measured for the first time in one animal, could be determined to be 4.76 ± 0.23 ms/kHz. CONCLUSION: This new and fast T1ρ quantification technique enables high-resolution myocardial T1ρ mapping and even dispersion quantification within the limited time of an in vivo study and could, therefore, be a reliable tool for improved tissue characterization.

2D Projection Maps of WSS and OSI Reveal Distinct Spatiotemporal Changes in Hemodynamics in the Murine Aorta during Ageing and Atherosclerosis.

Growth, ageing and atherosclerotic plaque development alter the biomechanical forces acting on the vessel wall. However, monitoring the detailed local changes in wall shear stress (WSS) at distinct sites of the murine aortic arch over time has been challenging. Here, we studied the temporal and spatial changes in flow, WSS, oscillatory shear index (OSI) and elastic properties of healthy wildtype (WT, n = 5) and atherosclerotic apolipoprotein E-deficient (Apoe-/-, n = 6) mice during ageing and atherosclerosis using high-resolution 4D flow magnetic resonance imaging (MRI). Spatially resolved 2D projection maps of WSS and OSI of the complete aortic arch were generated, allowing the pixel-wise statistical analysis of inter- and intragroup hemodynamic changes over time and local correlations between WSS, pulse wave velocity (PWV), plaque and vessel wall characteristics. The study revealed converse differences of local hemodynamic profiles in healthy WT and atherosclerotic Apoe-/- mice, and we identified the circumferential WSS as potential marker of plaque size and composition in advanced atherosclerosis and the radial strain as a potential marker for vascular elasticity. Two-dimensional (2D) projection maps of WSS and OSI, including statistical analysis provide a powerful tool to monitor local aortic hemodynamics during ageing and atherosclerosis. The correlation of spatially resolved hemodynamics and plaque characteristics could significantly improve our understanding of the impact of hemodynamics on atherosclerosis, which may be key to understand plaque progression towards vulnerability.

Astringent Gallic Acid in Red Wine Regulates Mechanisms of Gastric Acid Secretion via Activation of Bitter Taste Sensing Receptor TAS2R4.

Red wine is rich in phenolic compounds, which chiefly determine its characteristic taste. One of its major phenolic acid constituents for which an astringency, yet no clear contribution to bitter taste has been reported, is gallic acid (GA). In previous studies, we have demonstrated bitter-tasting constituents to regulate cellular proton secretion (PS) as a key mechanism of gastric acid secretion via activation of bitter taste sensing receptors (TAS2Rs). Here, we hypothesized a contributing role of GA to the red wine-stimulated effect on PS in human gastric tumor cells (HGT-1 cells). Sensory analyses revealed that 10 µM GA as the lowest concentration tested more bitter than tap water, with increasing bitter ratings up to 1000 µM. In HGT-1 cells, the concentration of 10 µM GA evoked the most pronounced effect on PS secretion, either when added to cells as in-water solution or when spiked to a red wine matrix. GA-spiking of Zweigelt and Blaufränkisch red wine samples up to a concentration of 10 µM resulted in an equally stimulated PS, whereas the non-GA-spiked wine samples demonstrated contrary effects on PS, indicating a functional role of GA on PS. Involvement of TAS2R4 in the GA-induced PS was verified by means of an HGT-1 homozygote CRISPR-Cas9 TAS2R4 knockout approach. Moreover, gene expression analyses revealed GA to increase TAS2R4. These results demonstrate a functional role of TAS2R4 in GA-evoked PS as a key mechanism of gastric acid secretion aiding digestion. Moreover, our data provide mechanistic insights, which will help to produce stomach-friendly red wines.

Multi-Perspective Anomaly Detection.

Anomaly detection is a critical problem in the manufacturing industry. In many applications, images of objects to be analyzed are captured from multiple perspectives which can be exploited to improve the robustness of anomaly detection. In this work, we build upon the deep support vector data description algorithm and address multi-perspective anomaly detection using three different fusion techniques, i.e., early fusion, late fusion, and late fusion with multiple decoders. We employ different augmentation techniques with a denoising process to deal with scarce one-class data, which further improves the performance (ROC AUC =80%). Furthermore, we introduce the dices dataset, which consists of over 2000 grayscale images of falling dices from multiple perspectives, with 5% of the images containing rare anomalies (e.g., drill holes, sawing, or scratches). We evaluate our approach on the new dices dataset using images from two different perspectives and also benchmark on the standard MNIST dataset. Extensive experiments demonstrate that our proposed multi-perspective approach exceeds the state-of-the-art single-perspective anomaly detection on both the MNIST and dices datasets. To the best of our knowledge, this is the first work that focuses on addressing multi-perspective anomaly detection in images by jointly using different perspectives together with one single objective function for anomaly detection.

SARS-CoV-2 transmissions in students and teachers: seroprevalence follow-up study in a German secondary school in November and December 2020.

Objective: To quantify the number of undetected SARS-CoV-2 infections in educational settings. Design: Serial SARS-CoV-2 seroprevalence study before and during the second wave of the COVID-19 pandemic. Setting: Secondary school in Dresden, Germany. Participants: Grade 8-12 students and their teachers were invited to participate in serial blood sampling and SARS-CoV-2 IgG antibody assessment. Main outcome measure: Seroprevalence of SARS-CoV-2 antibodies in study population. Results: 247 students and 55 teachers participated in the initial study visit and 197 students and 40 teachers completed follow-up. Seroprevalence increased from 1.7% (0.3-3.3) to 6.8% (3.8-10.1) during the study period mirroring the increase of officially reported SARS-CoV-2 infections during this time. The ratio of undetected to detected SARS-CoV-2 infections ranged from 0.25 to 0.33. Conclusions: We could not find evidence of relevant silent, asymptomatic spread of SARS-CoV-2 in schools neither in a low prevalence setting nor during the second wave of the pandemic, making it unlikely that educational settings play a crucial role in driving the SARS-CoV-2 pandemic. Trial registration number: DRKS00022455.

Evaluation of Plaque Characteristics and Inflammation Using Magnetic Resonance Imaging.

Atherosclerosis is an inflammatory disease of large and medium-sized arteries, characterized by the growth of atherosclerotic lesions (plaques). These plaques often develop at inner curvatures of arteries, branchpoints, and bifurcations, where the endothelial wall shear stress is low and oscillatory. In conjunction with other processes such as lipid deposition, biomechanical factors lead to local vascular inflammation and plaque growth. There is also evidence that low and oscillatory shear stress contribute to arterial remodeling, entailing a loss in arterial elasticity and, therefore, an increased pulse-wave velocity. Although altered shear stress profiles, elasticity and inflammation are closely intertwined and critical for plaque growth, preclinical and clinical investigations for atherosclerosis mostly focus on the investigation of one of these parameters only due to the experimental limitations. However, cardiovascular magnetic resonance imaging (MRI) has been demonstrated to be a potent tool which can be used to provide insights into a large range of biological parameters in one experimental session. It enables the evaluation of the dynamic process of atherosclerotic lesion formation without the need for harmful radiation. Flow-sensitive MRI provides the assessment of hemodynamic parameters such as wall shear stress and pulse wave velocity which may replace invasive and radiation-based techniques for imaging of the vascular function and the characterization of early plaque development. In combination with inflammation imaging, the analyses and correlations of these parameters could not only significantly advance basic preclinical investigations of atherosclerotic lesion formation and progression, but also the diagnostic clinical evaluation for early identification of high-risk plaques, which are prone to rupture. In this review, we summarize the key applications of magnetic resonance imaging for the evaluation of plaque characteristics through flow sensitive and morphological measurements. The simultaneous measurements of functional and structural parameters will further preclinical research on atherosclerosis and has the potential to fundamentally improve the detection of inflammation and vulnerable plaques in patients.