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Objective: Management of follow-up protocols after endovascular aortic repair (EVAR) varies significantly between centers and is not standardized according to sac regression. By designing an international expert-based Delphi consensus, the study aimed to create recommendations on follow-up after EVAR according to sac evolution. Methods: Eight facilitators created appropriate statements regarding the study topic that were voted, using a 4-point Likert scale, by a selected panel of international experts using a three-round modified Delphi consensus process. Based on the experts' responses, only those statements reaching a grade A (full agreement ≥75%) or B (overall agreement ≥80% and full disagreement <5%) were included in the final document. Results: One-hundred and seventy-four participants were included in the final analysis, and each voted the initial 29 statements related to the definition of sac regression (Q1-Q9), EVAR follow-up (Q10-Q14), and the assessment and role of sac regression during follow-up (Q15-Q29). At the end of the process, 2 statements (6.9%) were rejected, 9 statements (31%) received a grade B consensus strength, and 18 (62.1%) reached a grade A consensus strength. Of 27 final statements, 15 (55.6%) were classified as grade I, whereas 12 (44.4%) were classified as grade II. Experts agreed that sac regression should be considered an important indicator of EVAR success and always be assessed during follow-up after EVAR. Conclusions: Based on the elevated strength and high consistency of this international expert-based Delphi consensus, most of the statements might guide the current clinical management of follow-up after EVAR according to the sac regression. Future studies are needed to clarify debated issues.

BackgroundGraduate medical education (GME) program leaders struggle to incorporate quality measures in the ambulatory care setting, leading to knowledge gaps on how to provide feedback to residents and programs. While nationally collected quality of care data are available, their reliability for individual resident learning and for GME program improvement is understudied.ObjectiveTo examine the reliability of the Healthcare Effectiveness Data and Information Set (HEDIS) clinical performance measures in family medicine and internal medicine GME programs and to determine whether HEDIS measures can inform residents and their programs with their quality of care.MethodsFrom 2014 to 2017, we collected HEDIS measures from 566 residents in 8 family medicine and internal medicine programs under one sponsoring institution. Intraclass correlation was performed to establish patient sample sizes required for 0.70 and 0.80 reliability levels at the resident and program levels. Differences between the patient sample sizes required for reliable measurement and the actual patients cared for by residents were calculated.ResultsThe highest reliability levels for residents (0.88) and programs (0.98) were found for the most frequently available HEDIS measure, colorectal cancer screening. At the GME program level, 87.5% of HEDIS measures had sufficient sample sizes for reliable measurement at alpha 0.7 and 75.0% at alpha 0.8. Most resident level measurements were found to be less reliable.ConclusionsGME programs may reliably evaluate HEDIS performance pooled at the program level, but less so at the resident level due to patient volume.

This programme covers basic concepts such as modelling to discovery of new metal-carbide systems with high hardness values. It additionally covered applied aspects about glass science, ceramics science and their manufacturing to develop life-changing innovations and products. This webinar is focused on the use of machine learning in the area of ceramics and glasses and therefore will have an impact on academics working in the area and on industry. Three important take away benefits for participants: Fundamental knowledge on the use of machine learning in the discovery and design of ceramics/glasses; Understanding digitalization in ceramic/glass industry; Knowledge about the development of machine learning the ceramic/glass field in UK., First-principles and machine learning modelling of ceramic materials: the case of AsTe3 thermoelectric material. Presented by Assil Bouzid, Researcher, CNRS. The search for high performing thermoelectric materials led recently to the development of a new crystalline compound with composition AsTe3, that exhibits a very low thermal conductivity and an interesting figure of merit (ZT) peak value of 0.3 at 405 K, indicative of its thermoelectric performance. Nevertheless, the atomic-scale structure of both crystalline and amorphous AsTe3 remain unknown which hinders further improvement of the properties of this compound. In this talk, Assil will show how first-principles molecular dynamics can be combined to machine-learning interatomic potentials to achieve an accurate determination of the atomic-scale structure of this ceramic material. A particular focus will be put on the use of machine learning to extend time- and size-scales beyond those achieved solely by resorting to state-of-the-art ab-initio modelling. Finally, they will show an example of high-throughput calculation used to determine the previously unknown structure of the crystalline phase of AsTe3., Formation Descriptors for High-Entropy High-Hardness Metal Carbides. Presented by Corey Oses, Postdoctoral Fellow, Duke University. Disorder is both intrinsic to all materials, and also a route to enhanced functionality. A combination of 1) high chemical disorder and 2) metal-nonmetal bonding offers a new direction for thermal protection materials, wear-resistant coatings, batteries, and catalysts. Engineering these materials for applications demands an understanding of the mechanisms governing synthesizability and other entropy-driven behaviour, a challenging task often resolved within a limited context or neglected altogether. A simple modeling paradigm is presented that has already led to the discovery of new metal-carbide systems achieving high hardness values as predicted. Additional factors within the framework are being considered to address the delicate balance between entropy maximization and induced enthalpic penalties that become important in other ceramic systems., Artificial Intelligence for materials design: advances and remaining challenges. Presented by Adama Tandia, Senior Research Associate, Corning Incorporated. Use of artificial intelligence with materials data sets has significantly improved the speed of discovery of new materials with improved attributes. In the field of glass and polymer design, combinations of different regression methods, such as genetic algorithm, Gaussian processes, and neural networks, and data generation methods, such as molecular dynamics and density functional theory, has led to robust design methods, and near defect free manufacturing processes. Yet, despite the many successes, many serious challenges for faster and more robust algorithms remain before the design and manufacture of materials with optimal characteristics., Machine-learning correlations between structure and dynamics in supercooled liquids and glasses. Presented by Dr Gerhard Jung, PostDoc, CNRS. One of the most fundamental problems in the field of glass physics is understanding the connection between amorphous, microscopic structure and structural relaxation. While for crystals it is well know that relaxation is induced by well-defined `defects' in the ordered structure, finding an analogous definition for `amorphous defects' in glasses remains to be a great challenge. Many physically-motivated structural descriptors have been suggested to predict dynamical properties from structure with good success but it could be shown in recent years that machine-learned descriptors have the potential to be far superior. In my talk, I will give a brief summary on different machine-learning technique that have recently been applied to study the physics of the glass transition. Based on this summary, I will discuss open challenges and potential machine-learning approaches which we are currently pursuing to work towards better characterizing structural relaxation in amorphous materials and quantifying its correlation to the microscopic structure., This programme covers basic concepts such as modelling to discovery of new metal-carbide systems with high hardness values. It additionally covered applied aspects about glass science, ceramics science and their manufacturing to develop life-changing innovations and products. This webinar is focused on the use of machine learning in the area of ceramics and glasses and therefore will have an impact on academics working in the area and on industry. Three important take away benefits for participants: Fundamental knowledge on the use of machine learning in the discovery and design of ceramics/glasses; Understanding digitalization in ceramic/glass industry; Knowledge about the development of machine learning the ceramic/glass field in UK., First-principles and machine learning modelling of ceramic materials: the case of AsTe3 thermoelectric material. Presented by Assil Bouzid, Researcher, CNRS. The search for high performing thermoelectric materials led recently to the development of a new crystalline compound with composition AsTe3, that exhibits a very low thermal conductivity and an interesting figure of merit (ZT) peak value of 0.3 at 405 K, indicative of its thermoelectric performance. Nevertheless, the atomic-scale structure of both crystalline and amorphous AsTe3 remain unknown which hinders further improvement of the properties of this compound. In this talk, Assil will show how first-principles molecular dynamics can be combined to machine-learning interatomic potentials to achieve an accurate determination of the atomic-scale structure of this ceramic material. A particular focus will be put on the use of machine learning to extend time- and size-scales beyond those achieved solely by resorting to state-of-the-art ab-initio modelling. Finally, they will show an example of high-throughput calculation used to determine the previously unknown structure of the crystalline phase of AsTe3., Formation Descriptors for High-Entropy High-Hardness Metal Carbides. Presented by Corey Oses, Postdoctoral Fellow, Duke University. Disorder is both intrinsic to all materials, and also a route to enhanced functionality. A combination of 1) high chemical disorder and 2) metal-nonmetal bonding offers a new direction for thermal protection materials, wear-resistant coatings, batteries, and catalysts. Engineering these materials for applications demands an understanding of the mechanisms governing synthesizability and other entropy-driven behaviour, a challenging task often resolved within a limited context or neglected altogether. A simple modeling paradigm is presented that has already led to the discovery of new metal-carbide systems achieving high hardness values as predicted. Additional factors within the framework are being considered to address the delicate balance between entropy maximization and induced enthalpic penalties that become important in other ceramic systems., Artificial Intelligence for materials design: advances and remaining challenges. Presented by Adama Tandia, Senior Research Associate, Corning Incorporated. Use of artificial intelligence with materials data sets has significantly improved the speed of discovery of new materials with improved attributes. In the field of glass and polymer design, combinations of different regression methods, such as genetic algorithm, Gaussian processes, and neural networks, and data generation methods, such as molecular dynamics and density functional theory, has led to robust design methods, and near defect free manufacturing processes. Yet, despite the many successes, many serious challenges for faster and more robust algorithms remain before the design and manufacture of materials with optimal characteristics., Machine-learning correlations between structure and dynamics in supercooled liquids and glasses. Presented by Dr Gerhard Jung, PostDoc, CNRS. One of the most fundamental problems in the field of glass physics is understanding the connection between amorphous, microscopic structure and structural relaxation. While for crystals it is well know that relaxation is induced by well-defined `defects' in the ordered structure, finding an analogous definition for `amorphous defects' in glasses remains to be a great challenge. Many physically-motivated structural descriptors have been suggested to predict dynamical properties from structure with good success but it could be shown in recent years that machine-learned descriptors have the potential to be far superior. In my talk, I will give a brief summary on different machine-learning technique that have recently been applied to study the physics of the glass transition. Based on this summary, I will discuss open challenges and potential machine-learning approaches which we are currently pursuing to work towards better characterizing structural relaxation in amorphous materials and quantifying its correlation to the microscopic structure.

The explosive demand for a wide range of data processing has sparked interest towards a new logic gate platform as the existing electronic logic gates face limitations in accurate and fast computing. Accordingly, optoelectronic logic gates (OELGs) using photodiodes are of significant interest due to their broad bandwidth and fast data transmission, but complex configuration, power consumption, and low reliability issues are still inherent in these systems. Herein, we present a novel all-in-one OELG based on the bipolar spectral photoresponse characteristics of a self-powered perovskite photodetector (SPPD) having a back-to-back p⁺-i-n-p-p⁺ diode structure. Five representative logic gates (“AND”, “OR”, “NAND”, “NOR”, and “NOT”) are demonstrated with only a single SPPD via the photocurrent polarity control. For practical applications, we propose a universal OELG platform of integrated 8 × 8 SPPD pixels, demonstrating the 100% accuracy in five logic gate operations irrelevant to current variation between pixels.

We provide a systematic study of the position-dependent correlation function in weak lensing convergence maps and its relation to the squeezed limit of the three-point correlation function (3PCF) using state-of-the-art numerical simulations. We relate the position-dependent correlation function to its harmonic counterpart, i.e., the position-dependent power spectrum or equivalently the integrated bispectrum. We use a recently proposed improved fitting function, BiHalofit, for the bispectrum to compute the theoretical predictions as a function of source redshifts. In addition to low redshift results ($z_s=1.0-2.0$), we also provide results for maps inferred from lensing of the cosmic microwave background, i.e., $z_s=1100$. We include a {\em Euclid}-type realistic survey mask and noise. In agreement with the recent studies on the position-dependent power spectrum, we find that the results from simulations are consistent with the theoretical expectations when appropriate corrections are included. Performing a rough estimate, we find that the (S/N) for the detection of the position-dependent correlation function from {\em Euclid}-type mask with $f_{sky}=0.35$, can range between $6-12$ depending on the value of the intrinsic ellipticity distribution parameter $\sigma_{\epsilon} = 0.3-1.0$. For reconstructed $\kappa$ maps using an ideal CMB survey the (S/N) $\approx 1.8$. We also found that a $10\%$ deviation in $\sigma_8$ can be detected using IB for the optimistic case of $\sigma_\epsilon=0.3$ with a (S/N) $\approx 5$. The (S/N) for such detection in case of $\Omega_M$ is lower., Comment: 7 pages, 7 figures (PRD in press)

We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and optimal modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following final results: (local)(NL) = -0.9 +/- 5.1 f NL local = - 0.9 +/- 5.1 ; f(NL)(equil) = -26 +/- 47 f NL equil = - 26 +/- 47 ; and f(NL)(ortho) = -38 +/- 24 f NL ortho = - 38 +/- 24 (68% CL, statistical). These results include low-multipole (4 <= l< 40) polarization data that are not included in our previous analysis. The results also pass an extensive battery of tests (with additional tests regarding foreground residuals compared to 2015), and they are stable with respect to our 2015 measurements (with small fluctuations, at the level of a fraction of a standard deviation, which is consistent with changes in data processing). Polarization-only bispectra display a significant improvement in robustness; they can now be used independently to set primordial NG constraints with a sensitivity comparable to WMAP temperature-based results and they give excellent agreement. In addition to the analysis of the standard local, equilateral, and orthogonal bispectrum shapes, we consider a large number of additional cases, such as scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is, however, detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5. Beyond estimates of individual shape amplitudes, we also present model-independent reconstructions and analyses of the Planck CMB bispectrum. Our final constraint on the local primordial trispectrum shape

We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and optimal modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following final results: (local)(NL) = -0.9 +/- 5.1 f NL local = - 0.9 +/- 5.1 ; f(NL)(equil) = -26 +/- 47 f NL equil = - 26 +/- 47 ; and f(NL)(ortho) = -38 +/- 24 f NL ortho = - 38 +/- 24 (68% CL, statistical). These results include low-multipole (4 <= l< 40) polarization data that are not included in our previous analysis. The results also pass an extensive battery of tests (with additional tests regarding foreground residuals compared to 2015), and they are stable with respect to our 2015 measurements (with small fluctuations, at the level of a fraction of a standard deviation, which is consistent with changes in data processing). Polarization-only bispectra display a significant improvement in robustness; they can now be used independently to set primordial NG constraints with a sensitivity comparable to WMAP temperature-based results and they give excellent agreement. In addition to the analysis of the standard local, equilateral, and orthogonal bispectrum shapes, we consider a large number of additional cases, such as scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is, however, detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5. Beyond estimates of individual shape amplitudes, we also present model-independent reconstructions and analyses of the Planck CMB bispectrum. Our final constraint on the local primordial

We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and optimal modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following final results: (local)(NL) = -0.9 +/- 5.1 f NL local = - 0.9 +/- 5.1 ; f(NL)(equil) = -26 +/- 47 f NL equil = - 26 +/- 47 ; and f(NL)(ortho) = -38 +/- 24 f NL ortho = - 38 +/- 24 (68% CL, statistical). These results include low-multipole (4 <= l< 40) polarization data that are not included in our previous analysis. The results also pass an extensive battery of tests (with additional tests regarding foreground residuals compared to 2015), and they are stable with respect to our 2015 measurements (with small fluctuations, at the level of a fraction of a standard deviation, which is consistent with changes in data processing). Polarization-only bispectra display a significant improvement in robustness; they can now be used independently to set primordial NG constraints with a sensitivity comparable to WMAP temperature-based results and they give excellent agreement. In addition to the analysis of the standard local, equilateral, and orthogonal bispectrum shapes, we consider a large number of additional cases, such as scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is, however, detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5. Beyond estimates of individual shape amplitudes, we also present model-independent reconstructions and analyses of the Planck CMB bispectrum. Our final constraint on the local primordial trispectrum shape

We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and optimal modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following final results: (local)(NL) = -0.9 +/- 5.1 f NL local = - 0.9 +/- 5.1 ; f(NL)(equil) = -26 +/- 47 f NL equil = - 26 +/- 47 ; and f(NL)(ortho) = -38 +/- 24 f NL ortho = - 38 +/- 24 (68% CL, statistical). These results include low-multipole (4 <= l< 40) polarization data that are not included in our previous analysis. The results also pass an extensive battery of tests (with additional tests regarding foreground residuals compared to 2015), and they are stable with respect to our 2015 measurements (with small fluctuations, at the level of a fraction of a standard deviation, which is consistent with changes in data processing). Polarization-only bispectra display a significant improvement in robustness; they can now be used independently to set primordial NG constraints with a sensitivity comparable to WMAP temperature-based results and they give excellent agreement. In addition to the analysis of the standard local, equilateral, and orthogonal bispectrum shapes, we consider a large number of additional cases, such as scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is, however, detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5. Beyond estimates of individual shape amplitudes, we also present model-independent reconstructions and analyses of the Planck CMB bispectrum. Our final constraint on the local primordial trispectrum shape

IntroductionCompetence in using an electronic health record (EHR) is considered a critical skill for physicians practicing in patient-centered medical homes (PCMHs), but few studies have examined the impact of EHR training for residents preparing to practice in PCMHs. This study explored the educational outcomes associated with comprehensive EHR training for family medicine residents.MethodsThe PCMH EHR training consisted of case-based routine clinic visits delivered to 3 resident cohorts (N = 18). Participants completed an EHR competency self-assessment between 2011 and 2016 (N = 127), examining 6 EHR/PCMH core skills. We compared baseline characteristics for residents by low vs high exposure to EHR training. Multivariate regression estimated whether self-reported competencies improved over time and whether high PCMH EHR training exposure was associated with incremental improvement in self-reported competencies over time.ResultsResidents completed an average of 8.2 sessions: low-exposure residents averaged 5.3 sessions (standard deviation = 1.5), and high-exposure residents averaged 9.0 sessions (standard deviation = 0.9). High-exposed residents had higher posttest scores at training completion (84.4 vs 70.7). Over time, adjusted mean scores (confidence interval) for both groups improved (p < 0.001) from 12.2 (9.6-14.8), with low-exposed residents having greater score improvement (p < 0.001) because of their much lower baseline scores.ConclusionComprehensive training designed to improve EHR competencies among residents practicing in a PCMH resulted in improved assessment scores. Our findings indicate EHR training as part of resident exposure to the PCMH measurably improves self-assessed competencies, even among residents less engaged in EHR training.

Contains fulltext : 208519pub.pdf (publisher's version ) (Closed access), INTRODUCTION: Serrated polyposis syndrome (SPS) is accompanied by a substantially increased colorectal cancer (CRC) risk. To prevent or treat CRC in patients with a very high polyp burden, (sub)total colectomy with ileorectal or ileosigmoidal anastomosis is regularly performed. The CRC risk after (sub)total colectomy might be decreased, but evidence is lacking. We aimed to assess the yield of endoscopic surveillance in patients with SPS who underwent (sub)total colectomy. METHODS: For this post hoc analysis, we used prospectively collected data from a large international prospective cohort study. We included patients diagnosed with SPS (World Health Organization type I and/or III) who underwent (sub)total colectomy. Primary endpoint was the cumulative 5-year incidence of CRC and advanced neoplasia (AN). RESULTS: Forty-eight patients (mean age 61 [+/-7.8]; 52% men) were included and followed up for a median of 4.7 years (interquartile range 4.7-5.1). None of the patients developed CRC during follow-up. Five patients developed AN, corresponding to a cumulative 5-year AN incidence of 13% (95% confidence interval 1.2-23). In 4 patients, AN was diagnosed at the first surveillance endoscopy after study inclusion, and in 1 patient, AN was detected during subsequent rounds of surveillance. The risk of AN was similar for patients with ileorectal and ileosigmoidal anastomosis (logrank P = 0.83). DISCUSSION: (Sub)total colectomy mitigates much of the excess risk of CRC in patients with SPS. Advanced neoplasms are mainly detected at the first endoscopy after (sub)total colectomy. Based on these results, after the first surveillance, intervals might be extended beyond the currently recommended 1-2 years.

We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following results: f_NL^local = -0.9 +\- 5.1; f_NL^equil = -26 +\- 47; and f_NL^ortho = - 38 +\- 24 (68%CL, statistical). These results include the low-multipole (4 <= l < 40) polarization data, not included in our previous analysis, pass an extensive battery of tests, and are stable with respect to our 2015 measurements. Polarization bispectra display a significant improvement in robustness; they can now be used independently to set NG constraints. We consider a large number of additional cases, e.g. scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5 sigma. We present model-independent reconstructions and analyses of the CMB bispectrum. Our final constraint on the local trispectrum shape is g_NLl^local = (-5.8 +\-6.5) x 10^4 (68%CL, statistical), while constraints for other trispectra are also determined. We constrain the parameter space of different early-Universe scenarios, including general single-field models of inflation, multi-field and axion field parity-breaking models. Our results provide a high-precision test for structure-formation scenarios, in complete agreement with the basic picture of the LambdaCDM cosmology regarding the statistics of the initial conditions (abridged)., Comment: 50 pages, 20 figures

Contains fulltext : 208519pub.pdf (publisher's version ) (Closed access), INTRODUCTION: Serrated polyposis syndrome (SPS) is accompanied by a substantially increased colorectal cancer (CRC) risk. To prevent or treat CRC in patients with a very high polyp burden, (sub)total colectomy with ileorectal or ileosigmoidal anastomosis is regularly performed. The CRC risk after (sub)total colectomy might be decreased, but evidence is lacking. We aimed to assess the yield of endoscopic surveillance in patients with SPS who underwent (sub)total colectomy. METHODS: For this post hoc analysis, we used prospectively collected data from a large international prospective cohort study. We included patients diagnosed with SPS (World Health Organization type I and/or III) who underwent (sub)total colectomy. Primary endpoint was the cumulative 5-year incidence of CRC and advanced neoplasia (AN). RESULTS: Forty-eight patients (mean age 61 [+/-7.8]; 52% men) were included and followed up for a median of 4.7 years (interquartile range 4.7-5.1). None of the patients developed CRC during follow-up. Five patients developed AN, corresponding to a cumulative 5-year AN incidence of 13% (95% confidence interval 1.2-23). In 4 patients, AN was diagnosed at the first surveillance endoscopy after study inclusion, and in 1 patient, AN was detected during subsequent rounds of surveillance. The risk of AN was similar for patients with ileorectal and ileosigmoidal anastomosis (logrank P = 0.83). DISCUSSION: (Sub)total colectomy mitigates much of the excess risk of CRC in patients with SPS. Advanced neoplasms are mainly detected at the first endoscopy after (sub)total colectomy. Based on these results, after the first surveillance, intervals might be extended beyond the currently recommended 1-2 years.

Contains fulltext : 208519pub.pdf (publisher's version ) (Closed access), INTRODUCTION: Serrated polyposis syndrome (SPS) is accompanied by a substantially increased colorectal cancer (CRC) risk. To prevent or treat CRC in patients with a very high polyp burden, (sub)total colectomy with ileorectal or ileosigmoidal anastomosis is regularly performed. The CRC risk after (sub)total colectomy might be decreased, but evidence is lacking. We aimed to assess the yield of endoscopic surveillance in patients with SPS who underwent (sub)total colectomy. METHODS: For this post hoc analysis, we used prospectively collected data from a large international prospective cohort study. We included patients diagnosed with SPS (World Health Organization type I and/or III) who underwent (sub)total colectomy. Primary endpoint was the cumulative 5-year incidence of CRC and advanced neoplasia (AN). RESULTS: Forty-eight patients (mean age 61 [+/-7.8]; 52% men) were included and followed up for a median of 4.7 years (interquartile range 4.7-5.1). None of the patients developed CRC during follow-up. Five patients developed AN, corresponding to a cumulative 5-year AN incidence of 13% (95% confidence interval 1.2-23). In 4 patients, AN was diagnosed at the first surveillance endoscopy after study inclusion, and in 1 patient, AN was detected during subsequent rounds of surveillance. The risk of AN was similar for patients with ileorectal and ileosigmoidal anastomosis (logrank P = 0.83). DISCUSSION: (Sub)total colectomy mitigates much of the excess risk of CRC in patients with SPS. Advanced neoplasms are mainly detected at the first endoscopy after (sub)total colectomy. Based on these results, after the first surveillance, intervals might be extended beyond the currently recommended 1-2 years.

We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following results: f_NL^local = -0.9 +\- 5.1; f_NL^equil = -26 +\- 47; and f_NL^ortho = - 38 +\- 24 (68%CL, statistical). These results include the low-multipole (4 <= l < 40) polarization data, not included in our previous analysis, pass an extensive battery of tests, and are stable with respect to our 2015 measurements. Polarization bispectra display a significant improvement in robustness; they can now be used independently to set NG constraints. We consider a large number of additional cases, e.g. scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5 sigma. We present model-independent reconstructions and analyses of the CMB bispectrum. Our final constraint on the local trispectrum shape is g_NLl^local = (-5.8 +\-6.5) x 10^4 (68%CL, statistical), while constraints for other trispectra are also determined. We constrain the parameter space of different early-Universe scenarios, including general single-field models of inflation, multi-field and axion field parity-breaking models. Our results provide a high-precision test for structure-formation scenarios, in complete agreement with the basic picture of the LambdaCDM cosmology regarding the statistics of the initial conditions (abridged)., Comment: 50 pages, 20 figures

Clinical translation of chimeric antigen receptor (CAR) T cell therapy in myeloid malignancies is progressing slowly compared to its success in treatment of B cell malignancies. Clinical experiences with CAR T cell therapies against the currently investigated tumor-associated antigens (TAA) (e.g. CD33, CD123 and FMS-like tyrosine kinase 3 (FLT3)) were discouraging and severe side effects occurred (cytokine release syndrome, neurotoxicity and myeloid aplasia) (Hoffmann et al. Journal of Clinical Medicine 2019). Probably targeting a single TAA is insufficient to treat high risk myeloid malignancies with CAR T cell therapies. Therefore, combined targeting of two or even more TAAs seems to be a promising approach. In order to implement such a multiple tumor targeting strategy, we developed a modular CAR T cell system termed UniCAR. The system consists of a universal CAR (UniCAR) directed against the La peptide epitope E5B9 combined with single-chain variable fragment (scFv) -based target modules (TM). In contrast to conventional CARs, anti-tumor activity of UniCAR T cells is only turned on in the presence of the TMs. Thus, this approach will allow UniCAR T cell control due to the short half-life of the TM and therefore has a favorable safety profile. Furthermore, different TMs against several TAAs can be administered both sequentially or in parallel to increase the anti-tumor efficacy or face disease relapse due to antigen escape mechanisms. In the field of myeloid malignancies our group developed retargeting strategies against the TAAs CD33 and CD123 (Cartellieri et al. Blood Cancer Journal 2016). In addition, we have developed a new TM for the UniCAR system that is directed against the TAA FLT3. FLT3 is highly expressed on acute myeloid leukemia (AML) cells and also present on CD123low AML samples (Riccioni et al. British Journal of Haematology 2011). The novel FLT3 TM was constructed by fusion of the variable domain of the heavy and the light chain of the murine anti

We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following results: f_NL^local = -0.9 +\- 5.1; f_NL^equil = -26 +\- 47; and f_NL^ortho = - 38 +\- 24 (68%CL, statistical). These results include the low-multipole (4 <= l < 40) polarization data, not included in our previous analysis, pass an extensive battery of tests, and are stable with respect to our 2015 measurements. Polarization bispectra display a significant improvement in robustness; they can now be used independently to set NG constraints. We consider a large number of additional cases, e.g. scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5 sigma. We present model-independent reconstructions and analyses of the CMB bispectrum. Our final constraint on the local trispectrum shape is g_NLl^local = (-5.8 +\-6.5) x 10^4 (68%CL, statistical), while constraints for other trispectra are also determined. We constrain the parameter space of different early-Universe scenarios, including general single-field models of inflation, multi-field and axion field parity-breaking models. Our results provide a high-precision test for structure-formation scenarios, in complete agreement with the basic picture of the LambdaCDM cosmology regarding the statistics of the initial conditions (abridged)., Comment: 50 pages, 20 figures

An effective inventory management requires timely and accurate forecasting of demand for parts or items. In many realworld scenarios, however, the demand for rare, high-cost spare parts are scarce and erratic, making it highly challenging to perform a reliable forecast for intermittent demand. Studies in the past offered two approaches to such intermittent demand forecasting: a traditional approach to estimating demand parametrically, and a non-parametric approach that estimates the distribution of demands. The bootstrap method is considered to be one of the key non-parametric methods available. Despite its usefulness, however, application of conventional bootstrap methods in intermittent demand forecasting does not take into account any existing dependent structures in lead time demand, leading to inaccurate forecasting. In this paper, we suggest a new bootstrap method that takes into consideration the unique characteristics of intermittent demand to improve forecasting performance. We conclude by demonstrating the applicability of suggested new method through the results of a simple case experiment

An effective inventory management requires timely and accurate forecasting of demand for parts or items. In many realworld scenarios, however, the demand for rare, high-cost spare parts are scarce and erratic, making it highly challenging to perform a reliable forecast for intermittent demand. Studies in the past offered two approaches to such intermittent demand forecasting: a traditional approach to estimating demand parametrically, and a non-parametric approach that estimates the distribution of demands. The bootstrap method is considered to be one of the key non-parametric methods available. Despite its usefulness, however, application of conventional bootstrap methods in intermittent demand forecasting does not take into account any existing dependent structures in lead time demand, leading to inaccurate forecasting. In this paper, we suggest a new bootstrap method that takes into consideration the unique characteristics of intermittent demand to improve forecasting performance. We conclude by demonstrating the applicability of suggested new method through the results of a simple case experiment

An effective inventory management requires timely and accurate forecasting of demand for parts or items. In many realworld scenarios, however, the demand for rare, high-cost spare parts are scarce and erratic, making it highly challenging to perform a reliable forecast for intermittent demand. Studies in the past offered two approaches to such intermittent demand forecasting: a traditional approach to estimating demand parametrically, and a non-parametric approach that estimates the distribution of demands. The bootstrap method is considered to be one of the key non-parametric methods available. Despite its usefulness, however, application of conventional bootstrap methods in intermittent demand forecasting does not take into account any existing dependent structures in lead time demand, leading to inaccurate forecasting. In this paper, we suggest a new bootstrap method that takes into consideration the unique characteristics of intermittent demand to improve forecasting performance. We conclude by demonstrating the applicability of suggested new method through the results of a simple case experiment

Background There is a paucity of treatments that are capable of reliably and robustly improving cognitive function in adults with mood disorders. Glucagon-like peptide-1 is synthesized centrally and its receptors are abundantly expressed in neural circuits subserving cognitive function. We aimed to determine the effects of liraglutide, a GLP-1 receptor (GLP-1 R) agonist, on objective measures of cognition in adults with a depressive or bipolar disorder. Methods In this 4-week, pilot, open-label, domain-based study (e.g. cognition), we recruited 19 individuals with major depressive disorder (MDD) or bipolar disorder (BD) and an impairment in executive function, defined as a below-average performance in the Trail Making Test-B (TMTB). Liraglutide 1.8 mg/day was added as an adjunct to existing pharmacotherapy. Results Participants had significant increases from baseline to week 4 in the TMTB standard score (age and education corrected) (Cohen's d=0.64, p=0.009) and in a composite Z-score comprising multiple cognitive tests (i.e. Digit Symbol Substitution Test, Rey Auditory Verbal Learning Test, Stroop test) (Cohen's d=0.77, p<0.001). Neither changes in mood rating scales nor metabolic parameters were associated with changes in cognitive performance (all p>0.05); however baseline insulin resistance (IR) and body mass index (BMI) moderated the changes in the composite Z-score (p=0.021 and p=0.046, respectively), indicating larger responses in individuals with higher IR and BMI at baseline. There was a significant increase in lipase (p<0.001), but individual values were above the upper limit of normality. Limitations Small sample size, open-label design, lack of a placebo group. Conclusions Liraglutide was safe and well tolerated by a sample of non-diabetic individuals with mood disorders and had beneficial effects on objective measures of cognitive function. Larger studies with controlled trial designs are necessary to confirm and expand the results described

Cognitive deficits are a core feature across psychiatric disorders. Emerging evidence indicates that metabolic pathways are highly relevant for the substrates and phenomenology of the cognitive domain. Herein, we aimed to determine the effects of liraglutide, a GLP-1R agonist, on brain structural/volumetric parameters in adults with a mood disorder. This is the secondary analysis of a 4-week, pilot, proof-of-concept, open-label study. Participants (N=19) exhibiting impairments in executive function with either major depressive disorder (MDD) or bipolar disorder (BD) were recruited. Liraglutide 1.8mg/day was added as an adjunct to existing pharmacotherapy. Structural magnetic resonance imaging (MRI) scanning was obtained at baseline and endpoint. Results showed that at endpoint there was significant weight loss (mean: 3.15%; p<0.001). Changes in frontal and striatal volumes were significantly correlated with changes in body mass index (BMI), indicating the weight loss was associated with volume increase in most regions (e.g. r=-0.561, p=0.042 in the left superior frontal area). After adjusting for intracranial volume, age, gender, and BMI, we observed significant changes from baseline to endpoint in multiple regions (e.g. RR: 1.011, p=0.049 in the left rostral middle frontal area). Changes in regional volumes were associated with improvement in executive function (e.g. r=0.698, p=0.003 for the right superior frontal area). Adjunctive liraglutide results in clinically significant weight loss, with corresponding improvement in cognitive function; changes in cognitive function were partially moderated by changes in brain morphometry, underscoring the interrelationship between weight and brain structure/function.

(extract) Overall, this study reveals high conservation of the PopP2 effector in Korean R. solanacearum strains isolated from commercially cultivated tomato and pepper genotypes. Importantly, our data also indicate that the PopP2 conserved repressor motif could contribute to the effector accumulation in plant cells.

Magnetic properties of compacted Sm0.27Ca0.73MnO3 nanoparticles with average particle size ranging from 20 to 80 nm have been investigated in wide temperature and magnetic field range. It has been found that charge ordering transition gradually shifts to lower temperatures with decreasing particle size and almost disappears for 20 nm particles. At the same time, the relative volume of the ferromagnetic phase increases monotonously. Field-induced transition from antiferromagnetic to ferromagnetic state in 80 nmparticles appears at the same magnetic field as in the bulk. In small 20 nm particles, the transition is strongly suppressed by increasing surface spins disorder. Magnetic hysteresis loops show size-dependent exchange bias effect with exchange field, remanence asymmetry, and magnetic coercivity that depend on cooling magnetic field and temperature. Magnetic training effect has been observed in 20 nm particles and analyzed using a spin relaxation model. The thermoremanence and isothermoremanence curves have provided fingerprints of irreversible magnetization originating from the glassy component. Analysis of remanence curves has showed that the inner core of small 20 nm particles behaves as a two-dimensional diluted antiferromagnet.

This report outlines the development and testing of a prototype compact automated impact hammer designed to be surface mounted on a structure to provide an impulse-based structural excitation source for vibration testing. The automated device was designed to be integrated with a distributed fibre optic sensing system which measures the in-plane dynamic strain of the structure at a spatially dense grid of sensing points. The hammer was tested on a composite plate with induced damage and the excitation and response data were used to generate complex curvature shapes for the plate. These data were in turn used with a structural health monitoring tool known as iSIDER that detects anomalies in complex operating curvature shapes to locate damage and other areas with structural sti ness variations. The impactor was shown to replicate the functionality of a modally tuned impact hammer that had been used previously. The analysed data correctly identified the impact damage location using a fully automated routine.

Magnetic properties of interacting La0.2Ca0.8MnO3 nanoparticles have been investigated. The field-induced transition from antiferromagnetic (AFM) to ferromagnetic (FM) state in the La0.2Ca0.8MnO3 bulk has been observed at exceptionally high magnetic fields. For large particles, the field-induced transition widens while magnetization progressively decreases. In small particles the transition is almost fully suppressed. The thermoremanence and isothermoremanence curves constitute fingerprints of irreversible magnetization originating from nanoparticle shells. We have ascribed the magnetic behaviour of nanoparticles to a core–shell scenario with two main magnetic contributions; one attributed to the formation of a collective state formed by FM clusters in frustrated coordination at the surfaces of interacting AFM nanoparticles and the other associated with inner core behaviour as a two-dimensional diluted antiferromagnet.

We designed a bifunctional protein, capable of capturing circulating endothelial progenitor cells to collagen-rich vascular lesions. The protein consists of the soluble platelet collagen receptor glycoprotein VI and an antibody to CD133. This construct substantially mediates EPC homing to vascular lesions. Furthermore, it augments reendothelialization of vascular lesions and reduces the extent of myocardial infarction. Therefore, this bifunctional protein could be a potential new therapeutic option in regenerative vascular medicine.

We designed a bifunctional protein, capable of capturing circulating endothelial progenitor cells to collagen-rich vascular lesions. The protein consists of the soluble platelet collagen receptor glycoprotein VI and an antibody to CD133. This construct substantially mediates EPC homing to vascular lesions. Furthermore, it augments reendothelialization of vascular lesions and reduces the extent of myocardial infarction. Therefore, this bifunctional protein could be a potential new therapeutic option in regenerative vascular medicine.

Magnetic and transport properties of 100 nm thick La(0.9)MnO(3-delta) manganite films have been studied in the temperature range 5 - 300 K. The films exhibit a paramagnetic to ferromagnetic transition at T(C) approximate to 194 K. The temperature dependence of the resistivity shows a metal-insulator transition at 204 K and a strong resistivity increase at temperatures T < 160 K. Variations of resistivity with magnetic field and current are non-hysteretic, while the temperature dependence of the resistivity exhibits unusual inverse thermal hysteresis. The magnetic field independent inverse thermal hysteresis depends significantly on the thermal history of the sample. The data suggests that nonlinear transport characteristics are attributed to inelastic tunneling through intrinsic tunnel juctions formed by phase separated ferromagnetic metallic domains and insulating antiferromagnetic matrics., QC 20120124

Magnetic and transport properties of 100 nm thick La0.9MnO3-delta self-doped manganite films have been investigated in the temperature range 5-300 K. The films exhibit a paramagnetic to ferromagnetic transition at T-C = 194 K. The temperature dependence of the resistivity shows a metal-insulator transition at 204 K and a strong resistivity increase below 160 K. The magnetoresistance was always negative and slightly bias dependent. Variations in resistivity with magnetic field and current are nonhysteretic, while the temperature dependence of the resistivity exhibits unusual inverse thermal hysteresis. The magnetic field independent inverse thermal hysteresis is strongly influenced by a thermal history of the sample. The data suggest that nonlinear low temperature transport is dominated by inelastic tunneling through intrinsic tunnel junctions formed by phase-separated ferromagnetic metallic domains and insulating anti ferromagnetic matrix., QC 20100525

Contains fulltext : 70946.pdf (publisher's version ) (Closed access), Cells in the body are exposed simultaneously to a multitude of various signals. Inside a cell, molecular signalling networks integrate this information into a physiologically meaningful response. Interestingly, in the cellular testing of drug candidates, this complexity is largely ignored. Compounds are tested for cells that are challenged with one stimulus only. The activation of T lymphocytes through engagement of the T cell receptor (TCR)-CD3 complex and CD28 coreceptor is a prominent example for a cellular response that depends on the integration of signals. We investigated the cellular response characteristics of this network at different strengths of receptor and coreceptor activation. A novel cellular microarray-based approach, in which various combinations of antibodies directed against the CD3 complex and CD28 were spotted, was employed for analysing the stimulus dependence of activation of the transcription factor NFAT and actin reorganisation. For both responses, quantitative differences in inhibitor activity were observed. Remarkably, for IL-2 expression, which was detected by standard ELISA, low doses of the Src-family kinase inhibitor PP2 strongly potentiated IL-2 expression at high-level, but not at low-level, CD28 co-engagement. Therefore, for a physiologically highly relevant signalling network, the cellular response might vary qualitatively with only quantitative variations of a stimulus. This level of complexity should be considered in early cellular drug testing.

The purpose of this phase III clinical trial was to compare two different extracellular contrast agents, 1.0 M gadobutrol and 0.5 M gadopentate dimeglumine, for magnetic resonance imaging (MRI) in patients with known or suspected focal renal lesions. Using a multicenter, single-blind, interindividual, randomized study design, both contrast agents were compared in a total of 471 patients regarding their diagnostic accuracy, sensitivity, and specificity to correctly classify focal lesions of the kidney. To test for noninferiority the diagnostic accuracy rates for both contrast agents were compared with CT results based on a blinded reading. The average diagnostic accuracy across the three blinded readers ('average reader') was 83.7% for gadobutrol and 87.3% for gadopentate dimeglumine. The increase in accuracy from precontrast to combined precontrast and postcontrast MRI was 8.0% for gadobutrol and 6.9% for gadopentate dimeglumine. Sensitivity of the average reader was 85.2% for gadobutrol and 88.7% for gadopentate dimeglumine. Specificity of the average reader was 82.1% for gadobutrol and 86.1% for gadopentate dimeglumine. In conclusion, this study documents evidence for the noninferiority of a single i.v. bolus injection of 1.0 M gadobutrol compared with 0.5 M gadopentate dimeglumine in the diagnostic assessment of renal lesions with CE-MRI.

Contains fulltext : 70946.pdf (publisher's version ) (Closed access), Cells in the body are exposed simultaneously to a multitude of various signals. Inside a cell, molecular signalling networks integrate this information into a physiologically meaningful response. Interestingly, in the cellular testing of drug candidates, this complexity is largely ignored. Compounds are tested for cells that are challenged with one stimulus only. The activation of T lymphocytes through engagement of the T cell receptor (TCR)-CD3 complex and CD28 coreceptor is a prominent example for a cellular response that depends on the integration of signals. We investigated the cellular response characteristics of this network at different strengths of receptor and coreceptor activation. A novel cellular microarray-based approach, in which various combinations of antibodies directed against the CD3 complex and CD28 were spotted, was employed for analysing the stimulus dependence of activation of the transcription factor NFAT and actin reorganisation. For both responses, quantitative differences in inhibitor activity were observed. Remarkably, for IL-2 expression, which was detected by standard ELISA, low doses of the Src-family kinase inhibitor PP2 strongly potentiated IL-2 expression at high-level, but not at low-level, CD28 co-engagement. Therefore, for a physiologically highly relevant signalling network, the cellular response might vary qualitatively with only quantitative variations of a stimulus. This level of complexity should be considered in early cellular drug testing.

Contains fulltext : 70946.pdf (publisher's version ) (Closed access), Cells in the body are exposed simultaneously to a multitude of various signals. Inside a cell, molecular signalling networks integrate this information into a physiologically meaningful response. Interestingly, in the cellular testing of drug candidates, this complexity is largely ignored. Compounds are tested for cells that are challenged with one stimulus only. The activation of T lymphocytes through engagement of the T cell receptor (TCR)-CD3 complex and CD28 coreceptor is a prominent example for a cellular response that depends on the integration of signals. We investigated the cellular response characteristics of this network at different strengths of receptor and coreceptor activation. A novel cellular microarray-based approach, in which various combinations of antibodies directed against the CD3 complex and CD28 were spotted, was employed for analysing the stimulus dependence of activation of the transcription factor NFAT and actin reorganisation. For both responses, quantitative differences in inhibitor activity were observed. Remarkably, for IL-2 expression, which was detected by standard ELISA, low doses of the Src-family kinase inhibitor PP2 strongly potentiated IL-2 expression at high-level, but not at low-level, CD28 co-engagement. Therefore, for a physiologically highly relevant signalling network, the cellular response might vary qualitatively with only quantitative variations of a stimulus. This level of complexity should be considered in early cellular drug testing.

The purpose of this phase III clinical trial was to compare two different extracellular contrast agents, 1.0 M gadobutrol and 0.5 M gadopentate dimeglumine, for magnetic resonance imaging (MRI) in patients with known or suspected focal renal lesions. Using a multicenter, single-blind, interindividual, randomized study design, both contrast agents were compared in a total of 471 patients regarding their diagnostic accuracy, sensitivity, and specificity to correctly classify focal lesions of the kidney. To test for noninferiority the diagnostic accuracy rates for both contrast agents were compared with CT results based on a blinded reading. The average diagnostic accuracy across the three blinded readers ('average reader') was 83.7% for gadobutrol and 87.3% for gadopentate dimeglumine. The increase in accuracy from precontrast to combined precontrast and postcontrast MRI was 8.0% for gadobutrol and 6.9% for gadopentate dimeglumine. Sensitivity of the average reader was 85.2% for gadobutrol and 88.7% for gadopentate dimeglumine. Specificity of the average reader was 82.1% for gadobutrol and 86.1% for gadopentate dimeglumine. In conclusion, this study documents evidence for the noninferiority of a single i.v. bolus injection of 1.0 M gadobutrol compared with 0.5 M gadopentate dimeglumine in the diagnostic assessment of renal lesions with CE-MRI.

Item does not contain fulltext, Lipoproteins activate cells of the innate immune system via heteromers of Toll-like receptor (TLR) 2 with either TLR1 or TLR6. In spite of progress in understanding TLR-dependent signal transduction and the pathophysiological relevance of TLR2, the molecular basis of ligand recognition by this receptor is poorly defined. Here, we show that the bioactivity of lipopeptides (LP) critically depends on the dilution protocol and especially the presence of proteins or detergents acting as solubilizers. Fluorescence correlation spectroscopy of fluorescently labeled analogs of synthetic LP revealed that the LP form aggregates in solution. Dilution into protein- and serum-free buffers led to a complete loss of activity due to formation of large and highly heterogeneous aggregates. When dimethylsulfoxide stock solutions were diluted into BSA or serum-containing buffers particles of strongly reduced size were obtained. For some LP, an intermediary dilution step either with tert.-butyl alcohol/H2O (4:1) or with octyl-beta-D-glucopyranoside further increased activity. For a panel of LP exhibiting very different activities when diluted directly into protein-containing solutions, introduction of this dilution step resulted in comparable bioactivities. These results demonstrate the significance of solubilizing agents for the bioactivity of LP and are highly relevant for analyzing structure-activity relationships of LP-dependent TLR2 activation.

Item does not contain fulltext, For the detection of bioanalytes, there is an ongoing search for synthetic sensors to replace enzyme-based assays which are sensitive to contaminants or suboptimal storage conditions. Lipopolysaccharide (LPS), a bacteria-borne endotoxin that may lead to life-threatening conditions such as septic shock, is one such case. Fluorescently labeled analogues of two peptide variants derived from the putative ligand-binding domain of the LPS-binding protein CD14 were developed that detect and discriminate LPS and lipids down to the submicromolar concentration range. Peptides are terminally labeled with carboxyfluorescein and tetramethylrhodamine. For one given peptide, sensitivity and specificity for the detection of LPS and discrimination from other lipids are achieved by spectral signatures that combine changes in the fluorescence resonance energy transfer (FRET) between both dyes and the total emission of tetramethylrhodamine. Alternatively, specificity is obtained by combining the FRET efficiencies of both peptide variants. In comparison to published synthetic LPS sensors, the CD14-derived sensors yield an increase in sensitivity by about 3 orders of magnitude and exhibit specificity for analytes for which the design of synthetic recognition elements is a challenging task. Moreover, one of the sensors enabled the detection of LPS in the presence of up to 50% fetal calf serum, thereby demonstrating the feasibility of this peptide-based approach for clinically relevant samples.