Directional spontaneous emission and lateral Casimir-Polder force on an atom close to a nanofiber

We study the spontaneous emission of an excited atom close to an optical nanofiber and the resulting scattering forces. For a suitably chosen orientation of the atomic dipole, the spontaneous emission pattern becomes asymmetric and a resonant Casimir--Polder force parallel to the fiber axis arises. For a simple model case, we show that the such a lateral force is due to the interaction of the circularly oscillating atomic dipole moment with its image inside the material. With the Casimir--Polder energy being constant in the lateral direction, the predicted lateral force does not derive from a potential in the usual way. Our results have implications for optical force measurements on a substrate as well as for laser cooling of atoms in nanophotonic traps

Psychosocial impact of prognostic genetic testing in the care of uveal melanoma patients: protocol of a controlled prospective clinical observational study

Background: Uveal melanoma patients with a poor prognosis can be detected through genetic analysis of the tumor, which has a very high sensitivity. A large number of patients with uveal melanoma decide to receive information about their individual risk and therefore routine prognostic genetic testing is being carried out on a growing number of patients. It is obvious that a positive prediction for recidivism in the future will emotionally burden the respective patients, but research on the psychosocial impact of this innovative method is lacking. The aim of the current study is therefore to investigate the psychosocial impact (psychological distress and quality of life) of prognostic genetic testing in patients with uveal melanoma. Design and methods: This study is a non-randomized controlled prospective clinical observational trial. Subjects are patients with uveal melanoma, in whom genetic testing is possible. Patients who consent to genetic testing are allocated to the intervention group and patients who refuse genetic testing form the observational group. Both groups receive cancer therapy and psycho-oncological intervention when needed. The psychosocial impact of prognostic testing is investigated with the following variables: resilience, social support, fear of tumor progression, depression, general distress, cancer-specific and general health-related quality of life, attitude towards genetic testing, estimation of the perceived risk of metastasis, utilization and satisfaction with psycho-oncological crisis intervention, and sociodemographic data. Data are assessed preoperatively (at initial admission in the clinic) and postoperatively (at discharge from hospital after surgery, 6–12 weeks, 6 and 12 months after initial admission). Genetic test results are communicated 6–12 weeks after initial admission to the clinic. Discussion: We created optimal conditions for investigation of the psychosocial impact of prognostic genetic testing. This study will provide information on the course of disease and psychosocial outcomes after prognostic genetic testing. We expect that empirical data from our study will give a scientific basis for medico-ethical considerations

Deep learning-enabled detection of hypoxic–ischemic encephalopathy after cardiac arrest in CT scans: a comparative study of 2D and 3D approaches

Objective: To establish a deep learning model for the detection of hypoxic–ischemic encephalopathy (HIE) features on CT scans and to compare various networks to determine the best input data format. Methods: 168 head CT scans of patients after cardiac arrest were retrospectively identified and classified into two categories: 88 (52.4%) with radiological evidence of severe HIE and 80 (47.6%) without signs of HIE. These images were randomly divided into a training and a test set, and five deep learning models based on based on Densely Connected Convolutional Networks (DenseNet121) were trained and validated using different image input formats (2D and 3D images). Results: All optimized stacked 2D and 3D networks could detect signs of HIE. The networks based on the data as 2D image data stacks provided the best results (S100: AUC: 94%, ACC: 79%, S50: AUC: 93%, ACC: 79%). We provide visual explainability data for the decision making of our AI model using Gradient-weighted Class Activation Mapping. Conclusion: Our proof-of-concept deep learning model can accurately identify signs of HIE on CT images. Comparing different 2D- and 3D-based approaches, most promising results were achieved by 2D image stack models. After further clinical validation, a deep learning model of HIE detection based on CT images could be implemented in clinical routine and thus aid clinicians in characterizing imaging data and predicting outcome

Experimental analysis of the TRC benchmark system

The Tribomechadynamics Research Challenge (TRC) was a blind prediction of the vibration behavior of a thin plate clamped on two sides using bolted joints. The first bending mode's natural frequency and damping ratio were requested as function of the amplitude, starting from the linear regime until high levels, where both frictional contact and nonlinear bending-stretching coupling become relevant. The predictions were confronted with experimental results in a companion paper; the present article addresses the experimental analysis of this benchmark system. Amplitude-dependent modal data was obtained from phase resonance and response controlled tests. An original variant of response controlled testing is proposed: Instead of a fixed frequency interval, a fixed phase interval is analyzed. This way, the high excitation levels required outside resonance, which could activate unwanted exciter nonlinearity, are avoided. Consistency of testing methods is carefully analyzed. Overall, these measures have permitted to gain high confidence in the acquired modal data. The different sources of the remaining uncertainty were further analyzed. A low reassembly-variability but a moderate time-variability were identified, where the latter is attributed to some thermal sensitivity of the system. Two nominally identical plates were analyzed, which both have an appreciable initial curvature, and a significant effect on the vibration behavior was found depending on whether the plate is aligned/misaligned with the support structure. Further, a 1:2 nonlinear modal interaction with the first torsion mode was observed, which only occurs in the aligned configurations

The TRChallenge – Experimental quantification of nonlinear modal parameters and confrontation with the predictions

In recent years, the prediction of the behavior of structures with high-level nonlinearities has been a challenging area of research. In 2021, the Tribomechadynamics Research Challenge was proposed to evaluate the current state of the art in modelling in the community of jointed structures: the task was a blind prediction of the nonlinear dynamic response of a system including a frictional and a geometric nonlinearity. Participants of the challenge were given only the technical drawings, including mate rial and surface specifications required to manufacture and assemble the system and were asked to predict the frequency and damping ratio of the lowest-frequency elastic mode as function of the amplitude. The behavior of the real system was exper imentally characterized during the Tribomechadynamics Research Camp 2022. This contribution presents the experimental work performed during the research camp. As the nature of the structure requires a base excitation, two recently developed nonlinear testing techniques have been explored to extract the modal parameters: the response-controlled testing method and the phase-resonant testing method. The results obtained with the different methods are compared and the blind predictions are confronted with the experimental results in order to assess their accuracy

The prognostic value of gray-white-matter ratio in cardiac arrest patients treated with hypothermia

BACKGROUND: Mild therapeutic hypothermia alters the validity of a number of parameters currently used to predict neurological outcome after cardiac arrest and resuscitation. Thus, additional parameters are needed to increase certainty of early prognosis in these patients. A promising new approach is the determination of the gray-white-matter ratio (GWR) in cranial computed tomography (CCT) obtained early after resuscitation. It is not known how GWR relates to established outcome parameters such as neuron specific enolase (NSE) or somatosensory evoked potentials (SSEP). METHODS: Cardiac arrest patients (n = 98) treated with hypothermia were retrospectively analyzed with respect to the prognostic value of GWR, NSE and SSEP. RESULTS: A GWR < 1.16 predicted poor outcome with 100% specificity and 38% sensitivity. In 62 patients NSE, SSEP and CCT were available. The sensitivity of poor outcome prediction by both NSE > 97 μg/L and bilateral absent SSEP was 43%. The sensitivity increased to 53% in a multi-parameter approach predicting poor outcome using at least two of the three parameters (GWR, NSE and SSEP). CONCLUSION: Our results suggest a strong association of a low GWR with poor outcome following cardiac arrest. Determination of the GWR increases the sensitivity in a multi-parameter approach for prediction of poor outcome after cardiac arrest

LigaSure Impact™ versus conventional dissection technique in pylorus-preserving pancreatoduodenectomy in clinical suspicion of cancerous tumours on the head of the pancreas: study protocol for a randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>The pp-Whipple procedure requires extensive preparation. The conventional preparation technique is done with scissors for dissection and ligatures, and with clips and sutures for hemostasis. This procedure is very time-consuming and requires numerous changes of instruments. The LigaSure™ device allows dissection and hemostasis for preparation with one instrument. Up to now there has been no comparison of the two techniques with regard to operating time and the patients' outcome. It is still unclear which technique has the optimal benefit/risk ratio for the patient.</p> <p>Methods/Design</p> <p>A single-center, randomized, single-blinded, controlled superiority trial to compare two different techniques for dissection in a pp-Whipple procedure. 102 patients will be included and randomized pre-operatively. All patients aged 18 years or older scheduled for primary elective pp-Whipple procedure who signed the informed consent will be included. The primary endpoint is the operating time of the randomized technique. Control Intervention: Conventional dissection technique; experimental intervention: LigaSureTM dissection technique. Duration of study: Approximately 15 months; follow up time: 3 years. The trial is registered at German ClinicalTrials Register (DRKS00000166).</p

Deep learning-enabled detection of hypoxic–ischemic encephalopathy after cardiac arrest in CT scans: a comparative study of 2D and 3D approaches

ObjectiveTo establish a deep learning model for the detection of hypoxic–ischemic encephalopathy (HIE) features on CT scans and to compare various networks to determine the best input data format.Methods168 head CT scans of patients after cardiac arrest were retrospectively identified and classified into two categories: 88 (52.4%) with radiological evidence of severe HIE and 80 (47.6%) without signs of HIE. These images were randomly divided into a training and a test set, and five deep learning models based on based on Densely Connected Convolutional Networks (DenseNet121) were trained and validated using different image input formats (2D and 3D images).ResultsAll optimized stacked 2D and 3D networks could detect signs of HIE. The networks based on the data as 2D image data stacks provided the best results (S100: AUC: 94%, ACC: 79%, S50: AUC: 93%, ACC: 79%). We provide visual explainability data for the decision making of our AI model using Gradient-weighted Class Activation Mapping.ConclusionOur proof-of-concept deep learning model can accurately identify signs of HIE on CT images. Comparing different 2D- and 3D-based approaches, most promising results were achieved by 2D image stack models. After further clinical validation, a deep learning model of HIE detection based on CT images could be implemented in clinical routine and thus aid clinicians in characterizing imaging data and predicting outcome

A substrate of the ABC transporter PEN3 stimulates bacterial flagellin (flg22)-induced callose deposition in Arabidopsis thaliana

Nonhost resistance of Arabidopsis thaliana against Phytophthora infestans, a filamentous eukaryotic microbe and the causal agent of potato late blight, is based on a multilayered defense system. Arabidopsis thaliana controls pathogen entry through the penetration-resistance genes PEN2 and PEN3, encoding an atypical myrosinase and an ABC transporter, respectively, required for synthesis and export of unknown indole compounds. To identify pathogen-elicited leaf surface metabolites and further unravel nonhost resistance in Arabidopsis, we performed untargeted metabolite profiling by incubating a P. infestans zoospore suspension on leaves of WT or pen3 mutant Arabidopsis plants. Among the plant-secreted metabolites, 4-methoxyindol-3- yl-methanol and S-(4-methoxy-indol-3-yl-methyl) cysteine were detected in spore suspensions recollected from WT plants, but at reduced levels from the pen3 mutant plants. In both whole-cell and microsome-based assays, 4-methoxyindol-3-yl- methanol was transported in a PEN3-dependent manner, suggesting that this compound is a PEN3 substrate. The syntheses of both compounds were dependent on functional PEN2 and phytochelatin synthase 1. None of these compounds inhibited mycelial growth of P. infestans in vitro. Of note, exogenous application of 4- methoxyindol-3-yl methanol slightly elevated cytosolic Ca2+ levels and enhanced callose deposition in hydathodes of seedlings treated with a bacterial pathogen- associated molecular pattern (PAMP), flagellin (flg22). Loss of flg22-induced callose deposition in leaves of pen3 seedlings was partially reverted by the addition of 4- methoxyindol-3-yl methanol. In conclusion, we have identified a specific indole compound that is a substrate for PEN3 and contributes to the plant defense response against microbial pathogens