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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Balanced spin-lock preparation for B1 -insensitive and B0 -insensitive quantification of the rotating frame relaxation time T1ρ.

PURPOSE: Accurate and artifact-free T1ρ quantification is still a major challenge due to a susceptibility of the spin-locking module to B0 and/or B1 field inhomogeneities. In this study, we present a novel spin-lock preparation module (B-SL) that enables an almost full compensation of both types of inhomogeneities. METHODS: The new B-SL module contains a second 180° refocusing pulse to compensate each pulse in the preparation block by a corresponding pulse with opposite phase. For evaluation and validation of B-SL, extensive simulations as well as phantom measurements were performed. Furthermore, the new module was compared to three common established compensation methods. RESULTS: Both simulations and measurements demonstrate a much lower susceptibility to artifacts for the B-SL module, therefore providing an improved accuracy in T1ρ quantification. In the presence of field inhomogeneities, measurements revealed an increased banding compensation by 79% compared with the frequently used composite module. The goodness of the mono-exponential T1ρ fitting procedure was improved by 58%. CONCLUSION: The B-SL preparation enables the generation of accurate relaxation maps with significantly reduced artifacts, even in the case of large field imperfections. Therefore, the B-SL module is suggested to be highly beneficial for in vivo T1ρ quantification.

Simultaneous measurements of 3D wall shear stress and pulse wave velocity in the murine aortic arch.

PURPOSE: Wall shear stress (WSS) and pulse wave velocity (PWV) are important parameters to characterize blood flow in the vessel wall. Their quantification with flow-sensitive phase-contrast (PC) cardiovascular magnetic resonance (CMR), however, is time-consuming. Furthermore, the measurement of WSS requires high spatial resolution, whereas high temporal resolution is necessary for PWV measurements. For these reasons, PWV and WSS are challenging to measure in one CMR session, making it difficult to directly compare these parameters. By using a retrospective approach with a flexible reconstruction framework, we here aimed to simultaneously assess both PWV and WSS in the murine aortic arch from the same 4D flow measurement. METHODS: Flow was measured in the aortic arch of 18-week-old wildtype (n = 5) and ApoE-/- mice (n = 5) with a self-navigated radial 4D-PC-CMR sequence. Retrospective data analysis was used to reconstruct the same dataset either at low spatial and high temporal resolution (PWV analysis) or high spatial and low temporal resolution (WSS analysis). To assess WSS, the aortic lumen was labeled by semi-automatically segmenting the reconstruction with high spatial resolution. WSS was determined from the spatial velocity gradients at the lumen surface. For calculation of the PWV, segmentation data was interpolated along the temporal dimension. Subsequently, PWV was quantified from the through-plane flow data using the multiple-points transit-time method. Reconstructions with varying frame rates and spatial resolutions were performed to investigate the influence of spatiotemporal resolution on the PWV and WSS quantification. RESULTS: 4D flow measurements were conducted in an acquisition time of only 35 min. Increased peak flow and peak WSS values and lower errors in PWV estimation were observed in the reconstructions with high temporal resolution. Aortic PWV was significantly increased in ApoE-/- mice compared to the control group (1.7 ± 0.2 versus 2.6 ± 0.2 m/s, p < 0.001). Mean WSS magnitude values averaged over the aortic arch were (1.17 ± 0.07) N/m2 in wildtype mice and (1.27 ± 0.10) N/m2 in ApoE-/- mice. CONCLUSION: The post processing algorithm using the flexible reconstruction framework developed in this study permitted quantification of global PWV and 3D-WSS in a single acquisition. The possibility to assess both parameters in only 35 min will markedly improve the analyses and information content of in vivo measurements.

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.

Insect haptoelectrical stimulation of Venus flytrap triggers exocytosis in gland cells.

The Venus flytrap Dionaea muscipula captures insects and consumes their flesh. Prey contacting touch-sensitive hairs trigger traveling electrical waves. These action potentials (APs) cause rapid closure of the trap and activate secretory functions of glands, which cover its inner surface. Such prey-induced haptoelectric stimulation activates the touch hormone jasmonate (JA) signaling pathway, which initiates secretion of an acidic hydrolase mixture to decompose the victim and acquire the animal nutrients. Although postulated since Darwin's pioneering studies, these secretory events have not been recorded so far. Using advanced analytical and imaging techniques, such as vibrating ion-selective electrodes, carbon fiber amperometry, and magnetic resonance imaging, we monitored stimulus-coupled glandular secretion into the flytrap. Trigger-hair bending or direct application of JA caused a quantal release of oxidizable material from gland cells monitored as distinct amperometric spikes. Spikes reminiscent of exocytotic events in secretory animal cells progressively increased in frequency, reaching steady state 1 d after stimulation. Our data indicate that trigger-hair mechanical stimulation evokes APs. Gland cells translate APs into touch-inducible JA signaling that promotes the formation of secretory vesicles. Early vesicles loaded with H+ and Cl- fuse with the plasma membrane, hyperacidifying the "green stomach"-like digestive organ, whereas subsequent ones carry hydrolases and nutrient transporters, together with a glutathione redox moiety, which is likely to act as the major detected compound in amperometry. Hence, when glands perceive the haptoelectrical stimulation, secretory vesicles are tailored to be released in a sequence that optimizes digestion of the captured animal.

Caffeine induces gastric acid secretion via bitter taste signaling in gastric parietal cells.

Caffeine, generally known as a stimulant of gastric acid secretion (GAS), is a bitter-tasting compound that activates several taste type 2 bitter receptors (TAS2Rs). TAS2Rs are expressed in the mouth and in several extraoral sites, e.g., in the gastrointestinal tract, in which their functional role still needs to be clarified. We hypothesized that caffeine evokes effects on GAS by activation of oral and gastric TAS2Rs and demonstrate that caffeine, when administered encapsulated, stimulates GAS, whereas oral administration of a caffeine solution delays GAS in healthy human subjects. Correlation analysis of data obtained from ingestion of the caffeine solution revealed an association between the magnitude of the GAS response and the perceived bitterness, suggesting a functional role of oral TAS2Rs in GAS. Expression of TAS2Rs, including cognate TAS2Rs for caffeine, was shown in human gastric epithelial cells of the corpus/fundus and in HGT-1 cells, a model for the study of GAS. In HGT-1 cells, various bitter compounds as well as caffeine stimulated proton secretion, whereby the caffeine-evoked effect was (i) shown to depend on one of its cognate receptor, TAS2R43, and adenylyl cyclase; and (ii) reduced by homoeriodictyol (HED), a known inhibitor of caffeine's bitter taste. This inhibitory effect of HED on caffeine-induced GAS was verified in healthy human subjects. These findings (i) demonstrate that bitter taste receptors in the stomach and the oral cavity are involved in the regulation of GAS and (ii) suggest that bitter tastants and bitter-masking compounds could be potentially useful therapeutics to regulate gastric pH.

Real-time Triggered RAdial Single-Shot Inversion recovery for arrhythmia-insensitive myocardial T1 mapping: motion phantom validation and in vivo comparison.

PURPOSE: Cardiac T1 mapping has become an increasingly important imaging technique, contributing novel diagnostic options. However, currently utilized methods are often associated with accuracy problems because of heart rate variations and cardiac arrhythmia, limiting their value in clinical routine. This study aimed to introduce an improved arrhythmia-related robust T1 mapping sequence called RT-TRASSI (real-time Triggered RAdial Single-Shot Inversion recovery). METHODS: All measurements were performed on a 3.0T whole-body imaging system. A real-time feedback algorithm for arrhythmia detection was implemented into the previously described pulse sequence. A programmable motion phantom was constructed and measurements with different simulated arrhythmias arranged. T1 mapping accuracy and susceptibility to artifacts were analyzed. In addition, in vivo measurements and comparisons with 3 prevailing T1 mapping sequences (MOLLI, ShMOLLI, and SASHA) were carried out to investigate the occurrence of artifacts. RESULTS: In the motion phantom measurements, RT-TRASSI showed excellent agreement with predetermined reference T1 values. Percentage scattering of the T1 values ranged from -0.6% to +1.9% in sinus rhythm and -1.0% to +3.1% for high-grade arrhythmias. In vivo, RT-TRASSI showed diagnostic image quality with only 6% of the acquired T1 maps including image artifacts. In contrast, more than 40% of the T1 maps acquired with MOLLI, ShMOLLI, or SASHA included motion artifacts. CONCLUSION: Accuracy issues because of heart rate variability and arrhythmia are a prevailing problem in current cardiac T1 mapping techniques. With RT-TRASSI, artifacts can be minimized because of the short acquisition time and effective real-time feedback, avoiding potential data acquisition during systolic heart phase.

Simultaneous T1 and T2 measurements using inversion recovery TrueFISP with principle component-based reconstruction, off-resonance correction, and multicomponent analysis.

PURPOSE: To improve the reconstruction quality for quantitative T1 and T2 measurements using the inversion recovery (IR) TrueFISP sequence and to demonstrate the potential for multicomponent analysis. METHODS: The iterative reconstruction method takes advantage of the high redundancy in the smooth exponential signals using principle component analysis (PCA). Multicomponent information is preserved and allows voxel-by-voxel computation of relaxation time spectra with an inverse Laplace transform. Off-resonance effects are analytically and numerically investigated and a correction approach is presented. RESULTS: Single-shot IR TrueFISP in vivo measurements on healthy volunteers demonstrate the improved reconstruction performance compared to a view sharing (k-space weighted image contrast [KWIC]) reconstruction. Especially, tissue components with short apparent relaxation times T1 * are not filtered out and can be identified in the relaxation time spectra. These components include myelin in the human brain (T1 * ≈ 130 ms) and extra cranial subcutaneous fat. CONCLUSION: The PCA-based reconstruction method improves the temporal accuracy and preserves multicomponent information. Spatially resolved relaxation time spectra can be obtained and allow the identification of tissue types with short, apparent relaxation times.

Fast self-navigated wall shear stress measurements in the murine aortic arch using radial 4D-phase contrast cardiovascular magnetic resonance at 17.6 T.

PURPOSE: 4D flow cardiovascular magnetic resonance (CMR) and the assessment of wall shear stress (WSS) are non-invasive tools to study cardiovascular risks in vivo. Major limitations of conventional triggered methods are the long measurement times needed for high-resolution data sets and the necessity of stable electrocardiographic (ECG) triggering. In this work an ECG-free retrospectively synchronized method is presented that enables accelerated high-resolution measurements of 4D flow and WSS in the aortic arch of mice. METHODS: 4D flow and WSS were measured in the aortic arch of 12-week-old wildtype C57BL/6 J mice (n = 7) with a radial 4D-phase-contrast (PC)-CMR sequence, which was validated in a flow phantom. Cardiac and respiratory motion signals were extracted from the radial CMR signal and were used for the reconstruction of 4D-flow data. Rigid motion correction and a first order B0 correction was used to improve the robustness of magnitude and velocity data. The aortic lumen was segmented semi-automatically. Temporally averaged and time-resolved WSS and oscillatory shear index (OSI) were calculated from the spatial velocity gradients at the lumen surface at 14 locations along the aortic arch. Reproducibility was tested in 3 animals and the influence of subsampling was investigated. RESULTS: Volume flow, cross-sectional areas, WSS and the OSI were determined in a measurement time of only 32 min. Longitudinal and circumferential WSS and radial stress were assessed at 14 analysis planes along the aortic arch. The average longitudinal, circumferential and radial stress values were 1.52 ± 0.29 N/m2, 0.28 ± 0.24 N/m2 and - 0.21 ± 0.19 N/m2, respectively. Good reproducibility of WSS values was observed. CONCLUSION: This work presents a robust measurement of 4D flow and WSS in mice without the need of ECG trigger signals. The retrospective approach provides fast flow quantification within 35 min and a flexible reconstruction framework.

Improved compressed sensing reconstruction for [Formula: see text]F magnetic resonance imaging.

OBJECTIVE: In magnetic resonance imaging (MRI), compressed sensing (CS) enables the reconstruction of undersampled sparse data sets. Thus, partial acquisition of the underlying k-space data is sufficient, which significantly reduces measurement time. While 19F MRI data sets are spatially sparse, they often suffer from low SNR. This can lead to artifacts in CS reconstructions that reduce the image quality. We present a method to improve the image quality of undersampled, reconstructed CS data sets. MATERIALS AND METHODS: Two resampling strategies in combination with CS reconstructions are presented. Numerical simulations are performed for low-SNR spatially sparse data obtained from 19F chemical-shift imaging measurements. Different parameter settings for undersampling factors and SNR values are tested and the error is quantified in terms of the root-mean-square error. RESULTS: An improvement in overall image quality compared to conventional CS reconstructions was observed for both strategies. Specifically spike artifacts in the background were suppressed, while the changes in signal pixels remained small. DISCUSSION: The proposed methods improve the quality of CS reconstructions. Furthermore, because resampling is applied during post-processing, no additional measurement time is required. This allows easy incorporation into existing protocols and application to already measured data.