Search

Your search keyword '"Hein L."' showing total 1,188 results
Start Over Author "Hein L."
1,188 results on '"Hein L."'

1. Coloration principles of the Great purple emperor butterfly (Sasakia charonda)

Author

Doekele G. Stavenga, Hein L. Leertouwer, and Kentaro Arikawa

Subjects
Wing scales, Iridescence, Thin films, Structural coloration, Spectrophotometry, Scatterometry, Zoology, QL1-991
Abstract

Abstract The dorsal wings of male Sasakia charonda butterflies display a striking blue iridescent coloration, which is accentuated by white, orange-yellow and red spots, as well as by brown margins. The ventral wings also have a variegated, but more subdued, pattern. We investigated the optical basis of the various colors of intact wings as well as isolated wing scales by applying light and electron microscopy, imaging scatterometry and (micro)spectrophotometry. The prominent blue iridescence is due to scales with tightly packed, multilayered ridges that contain melanin pigment. The scales in the brown wing margins also contain melanin. Pigments extracted from the orange-yellow and red spots indicate the presence of 3-OH-kynurenine and ommochrome pigment. The scales in the white spots also have multilayered ridges but lack pigment. The lower lamina of the scales plays a so-far undervalued but often crucial role. Its thin-film properties color the majority of the ventral wing scales, which are unpigmented and have large windows. The lower lamina acting as a thin-film reflector generally contributes to the reflectance of the various scale types.

Published
2020
Full Text
View/download PDF

2. Coloration of Flowers by Flavonoids and Consequences of pH Dependent Absorption

Author

Doekele G. Stavenga, Hein L. Leertouwer, Bettina Dudek, and Casper J. van der Kooi

Subjects
flavonol, anthocyanin, nudicaulin, carotenoid, pollination, Papaver, Plant culture, SB1-1110
Abstract

Flavonoid pigments are key determinants of flower colors. As absorption spectra of flavonoids are known to be severely pH-dependent, cellular pH will play a crucial role in flower coloration. The flavonoids are concentrated in the vacuoles of the flowers’ epidermal cells, and thus the pigments’ absorption spectra are modulated by the vacuolar pH. Here we study the pH dependence of flavonoid absorption spectra in extracts from flowers of two poppy species Papaver dubium (red) and Meconopsis cambrica (orange), and a white and red Mandevilla sanderi variety. In the red poppy and Mandevilla flowers, absorption spectra of the cyanidin- and pelargonidin-based anthocyanins peak in the blue-green-wavelength range at low pH, but exhibit a distinct bathochromic shift at higher pH. This shift to longer wavelengths is not found for the blue-absorbing nudicaulin derivatives of M. cambrica, which have a similar absorption spectrum at low and high pH. The pH-dependent absorption changes of the white M. sanderi’s flavonoid remained restricted to the UV. An analysis of the spectra with logistic functions suggests that the pH-dependent characteristics of the basic states of flavonols and anthocyanins are related. The implications of tuning of pH and pigment absorption spectra for studies on flower color evolution are discussed.

Published
2021
Full Text
View/download PDF

4. Classical lepidopteran wing scale colouration in the giant butterfly-moth Paysandisia archon

Author

Doekele G. Stavenga, Hein L. Leertouwer, Andrej Meglič, Kazimir Drašlar, Martin F. Wehling, Primož Pirih, and Gregor Belušič

Subjects
Pigments, Spectrophotometry, Ommochrome, Thin films, Melanin, Medicine, Biology (General), QH301-705.5
Abstract

The palm borer moth Paysandisia archon (Castniidae; giant butterfly-moths) has brown dorsal forewings and strikingly orange-coloured dorsal hindwings with white spots surrounded by black margins. Here, we have studied the structure and pigments of the wing scales in the various coloured wing areas, applying light and electron microscopy and (micro)spectrophotometry, and we analysed the spatial reflection properties with imaging scatterometry. The scales in the white spots are unpigmented, those in the black and brown wing areas contain various amounts of melanin, and the orange wing scales contain a blue-absorbing ommochrome pigment. In all scale types, the upper lamina acts as a diffuser and the lower lamina as a thin film interference reflector, with thickness of about 200 nm. Scale stacking plays an important role in creating the strong visual signals: the colour of the white eyespots is created by stacks of unpigmented blue scales, while the orange wing colour is strongly intensified by stacking the orange scales.

Published
2018
Full Text
View/download PDF

11. Optimization of anastomotic technique and gastric conduit perfusion with hyperspectral imaging and machine learning in an experimental model for minimally invasive esophagectomy

Author

Nickel, F., Studier-Fischer, A., Özdemir, B., Odenthal, J., Müller, L.R., Knoedler, S., Kowalewski, K.F., Camplisson, I., Allers, M.M., Dietrich, M., Schmidt, K., Salg, G.A., Kenngott, H.G., Billeter, A.T., Gockel, I., Sagiv, C., Hadar, O.E., Gildenblat, J., Ayala, L., Seidlitz, S., Maier-Hein, L., and Müller-Stich, B.P.

Published
2023
Full Text
View/download PDF

13. Uncertainty-Aware Organ Classification for Surgical Data Science Applications in Laparoscopy

Author

Moccia, S., Wirkert, S. J., Kenngott, H., Vemuri, A. S., Apitz, M., Mayer, B., De Momi, E., Mattos, L. S., and Maier-Hein, L.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Objective: Surgical data science is evolving into a research field that aims to observe everything occurring within and around the treatment process to provide situation-aware data-driven assistance. In the context of endoscopic video analysis, the accurate classification of organs in the field of view of the camera proffers a technical challenge. Herein, we propose a new approach to anatomical structure classification and image tagging that features an intrinsic measure of confidence to estimate its own performance with high reliability and which can be applied to both RGB and multispectral imaging (MI) data. Methods: Organ recognition is performed using a superpixel classification strategy based on textural and reflectance information. Classification confidence is estimated by analyzing the dispersion of class probabilities. Assessment of the proposed technology is performed through a comprehensive in vivo study with seven pigs. Results: When applied to image tagging, mean accuracy in our experiments increased from 65% (RGB) and 80% (MI) to 90% (RGB) and 96% (MI) with the confidence measure. Conclusion: Results showed that the confidence measure had a significant influence on the classification accuracy, and MI data are better suited for anatomical structure labeling than RGB data. Significance: This work significantly enhances the state of art in automatic labeling of endoscopic videos by introducing the use of the confidence metric, and by being the first study to use MI data for in vivo laparoscopic tissue classification. The data of our experiments will be released as the first in vivo MI dataset upon publication of this paper., Comment: 7 pages, 6 images, 2 tables

Published
2017
Full Text
View/download PDF

14. Beyond Survival: A Scoping Review on the Sexual Health of Sexual and Gender Minority Women Following Curative Cancer Treatment.

Author

Miles, Heather S., Wickersham, Karen E., and Hein, L. C.

Subjects
TUMOR treatment, SEXUAL orientation, WOMEN, GENDER identity, CINAHL database, LGBTQ+ people, CANCER patients, DESCRIPTIVE statistics, BODY image, EXPERIENCE, SYSTEMATIC reviews, MEDLINE, LITERATURE reviews, SEXUAL minorities, ONLINE information services, INTERPERSONAL relations, SEXUAL health, PSYCHOLOGY information storage & retrieval systems, FRIENDSHIP
Abstract

Introduction: To explore the existing research on sexual health experiences of sexual and gender minority women (SGMW) post-curative cancer treatment. Methodology: This scoping review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. Four articles that focused on sexual health experiences of SGMW post-curative cancer treatment were included. Results: Four themes were identified: (a) sexual function; (b) sexual orientation and gender identity, including disclosure and health care provider reactions; (c) relationship dynamics, such as relationship status and the quality of romantic relationships; and (d) body image. Discussions: The findings underscore substantial challenges faced by SGMW cancer survivors in achieving optimal sexual well-being, impacting their access to post-treatment care. This study advocates for more expansive research efforts involving diverse participant cohorts, extending beyond breast cancer, to gain deeper insights into these critical issues. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

17. Domestication of Euterpe oleracea (Arecaceae) to provide food from peatlands

Author

Tata, H.L., Rachmanadi, D., Suwarno, A., van der Meer, P., Hein, L., Tata, H.L., Rachmanadi, D., Suwarno, A., van der Meer, P., and Hein, L.

Abstract

Euterpe oleracea (Arecaceae), which is known as Acai, is a palm tree originating from swampy forest of Suriname.Acai is naturally distributed in swampy, sandy soil, river edges and seasonally flooded habitats; hence it is considered as paludiculture species.Acai's domestication study in Indonesia is limited, therefore our study aimed to assess morphology and germination of Acai's seeds in the nursery, and early growth performance in the field.Acai's seed diameter was ranging from 0.88±0.01 cm; seed wet weight was 1.19±0.31 g.Acai seeds germinated for up to 5-7 months.Soaked seeds in warm water overnight had 8.33% germination rate, while soaked seeds in tap water overnight had lesser germination rates (1.75%).After one year transplanted to a peat swamp forest ecosystem of Tumbang Nusa, Central Kalimantan, Acai's seedlings had 100% survival rate.The relative growth rate of height and diameter of Acai seedlings were 4.21 cm month-1 and 0.08 cm month-1, respectively.Acai seedlings survived floodings that occurred in November 2021 to March 2022.The water level was around-35.6 to 17.7 cm.Despite of some challenging, açai is a promising species to be domesticated on degraded peatlands.

Published
2024

18. Metrics reloaded: recommendations for image analysis validation

Author

Maier-Hein, L., Reinke, A., Godau, P., Tizabi, M.D., Buettner, F., Christodoulou, E., Glocker, B., Isensee, F., Kleesiek, J., Kozubek, M., Reyes, M., Riegler, M.A., Wiesenfarth, M., Kavur, A.E., Sudre, C.H., Baumgartner, M., Eisenmann, M., Heckmann-Notzel, D., Radsch, T., Acion, L., Antonelli, M., Arbel, T., Bakas, S., Benis, A., Blaschko, M.B., Cardoso, M.J., Cheplygina, V., Cimini, B.A., Collins, G.S., Farahani, K., Ferrer, L., Galdran, A., Ginneken, B. van, Haase, R., Hashimoto, D.A., Hoffman, M.M., Huisman, M., Jannin, P., Kahn, C.E., Kainmueller, D., Kainz, B., Karargyris, A., Karthikesalingam, A., Kofler, F., Kopp-Schneider, A., Kreshuk, A., Kurc, T., Landman, B.A., Litjens, G.J., Madani, A., Maier-Hein, K., Martel, A.L., Mattson, P., Meijering, E., Menze, B., Moons, K.G., Muller, H., Nichyporuk, B., Nickel, F., Petersen, J., Rajpoot, N., Rieke, N., Saez-Rodriguez, J., Sanchez, C.I., Shetty, S., Smeden, M. van, Summers, R.M., Taha, A.A., Tiulpin, A., Tsaftaris, S.A., Calster, B. van, Varoquaux, G., Jager, P.F., Maier-Hein, L., Reinke, A., Godau, P., Tizabi, M.D., Buettner, F., Christodoulou, E., Glocker, B., Isensee, F., Kleesiek, J., Kozubek, M., Reyes, M., Riegler, M.A., Wiesenfarth, M., Kavur, A.E., Sudre, C.H., Baumgartner, M., Eisenmann, M., Heckmann-Notzel, D., Radsch, T., Acion, L., Antonelli, M., Arbel, T., Bakas, S., Benis, A., Blaschko, M.B., Cardoso, M.J., Cheplygina, V., Cimini, B.A., Collins, G.S., Farahani, K., Ferrer, L., Galdran, A., Ginneken, B. van, Haase, R., Hashimoto, D.A., Hoffman, M.M., Huisman, M., Jannin, P., Kahn, C.E., Kainmueller, D., Kainz, B., Karargyris, A., Karthikesalingam, A., Kofler, F., Kopp-Schneider, A., Kreshuk, A., Kurc, T., Landman, B.A., Litjens, G.J., Madani, A., Maier-Hein, K., Martel, A.L., Mattson, P., Meijering, E., Menze, B., Moons, K.G., Muller, H., Nichyporuk, B., Nickel, F., Petersen, J., Rajpoot, N., Rieke, N., Saez-Rodriguez, J., Sanchez, C.I., Shetty, S., Smeden, M. van, Summers, R.M., Taha, A.A., Tiulpin, A., Tsaftaris, S.A., Calster, B. van, Varoquaux, G., and Jager, P.F.

Abstract

Contains fulltext : 305368.pdf (Publisher’s version ) (Closed access), Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Developed by a large international consortium in a multistage Delphi process, it is based on the novel concept of a problem fingerprint-a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), dataset and algorithm output. On the basis of the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as classification tasks at image, object or pixel level, namely image-level classification, object detection, semantic segmentation and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases.

Published
2024

19. Understanding metric-related pitfalls in image analysis validation

Author

Reinke, A., Tizabi, M.D., Baumgartner, M., Eisenmann, M., Heckmann-Notzel, D., Kavur, A.E., Radsch, T., Sudre, C.H., Acion, L., Antonelli, M., Arbel, T., Bakas, S., Benis, A., Buettner, F., Cardoso, M.J., Cheplygina, V., Chen, J., Christodoulou, E., Cimini, B.A., Farahani, K., Ferrer, L., Galdran, A., Ginneken, B. van, Glocker, B., Godau, P., Hashimoto, D.A., Hoffman, M.M., Huisman, M., Isensee, F., Jannin, P., Kahn, C.E., Kainmueller, D., Kainz, B., Karargyris, A., Kleesiek, J., Kofler, F., Kooi, T., Kopp-Schneider, A., Kozubek, M., Kreshuk, A., Kurc, T., Landman, B.A., Litjens, G.J., Madani, A., Maier-Hein, K., Martel, A.L., Meijering, E., Menze, B., Moons, K.G., Muller, H., Nichyporuk, B., Nickel, F., Petersen, J., Rafelski, S.M., Rajpoot, N., Reyes, M., Riegler, M.A., Rieke, N., Saez-Rodriguez, J., Sanchez, C.I., Shetty, S., Summers, R.M., Taha, A.A., Tiulpin, A., Tsaftaris, S.A., Calster, B. van, Varoquaux, G., Yaniv, Z.R., Jager, P.F., Maier-Hein, L., Reinke, A., Tizabi, M.D., Baumgartner, M., Eisenmann, M., Heckmann-Notzel, D., Kavur, A.E., Radsch, T., Sudre, C.H., Acion, L., Antonelli, M., Arbel, T., Bakas, S., Benis, A., Buettner, F., Cardoso, M.J., Cheplygina, V., Chen, J., Christodoulou, E., Cimini, B.A., Farahani, K., Ferrer, L., Galdran, A., Ginneken, B. van, Glocker, B., Godau, P., Hashimoto, D.A., Hoffman, M.M., Huisman, M., Isensee, F., Jannin, P., Kahn, C.E., Kainmueller, D., Kainz, B., Karargyris, A., Kleesiek, J., Kofler, F., Kooi, T., Kopp-Schneider, A., Kozubek, M., Kreshuk, A., Kurc, T., Landman, B.A., Litjens, G.J., Madani, A., Maier-Hein, K., Martel, A.L., Meijering, E., Menze, B., Moons, K.G., Muller, H., Nichyporuk, B., Nickel, F., Petersen, J., Rafelski, S.M., Rajpoot, N., Reyes, M., Riegler, M.A., Rieke, N., Saez-Rodriguez, J., Sanchez, C.I., Shetty, S., Summers, R.M., Taha, A.A., Tiulpin, A., Tsaftaris, S.A., Calster, B. van, Varoquaux, G., Yaniv, Z.R., Jager, P.F., and Maier-Hein, L.

Abstract

Contains fulltext : 305370.pdf (Publisher’s version ) (Closed access), Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although taking into account the individual strengths, weaknesses and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multistage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides a reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Although focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation.

Published
2024

20. Spectral characterization of intraoperative renal perfusion using hyperspectral imaging and artificial intelligence.

Author

Studier-Fischer, A., Bressan, M., Qasim, A.bin, Özdemir, B., Sellner, J., Seidlitz, S., Haney, C. M., Egen, L., Michel, M., Dietrich, M., Salg, G. A., Billmann, F., Nienhüser, H., Hackert, T., Müller, B. P., Maier-Hein, L., Nickel, F., and Kowalewski, K. F.

Subjects
ARTIFICIAL intelligence, PERFUSION, ISOLATION perfusion, KIDNEY surgery, SPECTRAL reflectance, HYPEREMIA, SPECTRAL imaging
Abstract

Accurate intraoperative assessment of organ perfusion is a pivotal determinant in preserving organ function e.g. during kidney surgery including partial nephrectomy or kidney transplantation. Hyperspectral imaging (HSI) has great potential to objectively describe and quantify this perfusion as opposed to conventional surrogate techniques such as ultrasound flowmeter, indocyanine green or the subjective eye of the surgeon. An established live porcine model under general anesthesia received median laparotomy and renal mobilization. Different scenarios that were measured using HSI were (1) complete, (2) gradual and (3) partial malperfusion. The differences in spectral reflectance as well as HSI oxygenation (StO2) between different perfusion states were compelling and as high as 56.9% with 70.3% (± 11.0%) for "physiological" vs. 13.4% (± 3.1%) for "venous congestion". A machine learning (ML) algorithm was able to distinguish between these perfusion states with a balanced prediction accuracy of 97.8%. Data from this porcine study including 1300 recordings across 57 individuals was compared to a human dataset of 104 recordings across 17 individuals suggesting clinical transferability. Therefore, HSI is a highly promising tool for intraoperative microvascular evaluation of perfusion states with great advantages over existing surrogate techniques. Clinical trials are required to prove patient benefit. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

22. Why is the Winner the Best?

Author

Eisenmann, M., primary, Reinke, A., additional, Weru, V., additional, Tizabi, M. D., additional, Isensee, F., additional, Adler, T. J., additional, Ali, S., additional, Andrearczyk, V., additional, Aubreville, M., additional, Baid, U., additional, Bakas, S., additional, Balu, N., additional, Bano, S., additional, Bernal, J., additional, Bodenstedt, S., additional, Casella, A., additional, Cheplygina, V., additional, Daum, M., additional, De Bruijne, M., additional, Depeursinge, A., additional, Dorent, R., additional, Egger, J., additional, Ellis, D. G., additional, Engelhardt, S., additional, Ganz, M., additional, Ghatwary, N., additional, Girard, G., additional, Godau, P., additional, Gupta, A., additional, Hansen, L., additional, Harada, K., additional, Heinrich, M., additional, Heller, N., additional, Hering, A., additional, Huaulmé, A., additional, Jannin, P., additional, Kavur, A. E., additional, Kodym, O., additional, Kozubek, M., additional, Li, J., additional, Li, H., additional, Ma, J., additional, Martín-Isla, C., additional, Menze, B., additional, Noble, A., additional, Oreiller, V., additional, Padoy, N., additional, Pati, S., additional, Payette, K., additional, Rädsch, T., additional, Rafael-Patiño, J., additional, Bawa, V. Singh, additional, Speidel, S., additional, Sudre, C. H., additional, Van Wijnen, K., additional, Wagner, M., additional, Wei, D., additional, Yamlahi, A., additional, Yap, M. H., additional, Yuan, C., additional, Zenk, M., additional, Zia, A., additional, Zimmerer, D., additional, Aydogan, D., additional, Bhattarai, B., additional, Bloch, L., additional, Brüngel, R., additional, Cho, J., additional, Choi, C., additional, Dou, Q., additional, Ezhov, I., additional, Friedrich, C. M., additional, Fuller, C., additional, Gaire, R. R., additional, Galdran, A., additional, Faura, Á. García, additional, Grammatikopoulou, M., additional, Hong, S., additional, Jahanifar, M., additional, Jang, I., additional, Kadkhodamohammadi, A., additional, Kang, I., additional, Kofler, F., additional, Kondo, S., additional, Kuijf, H., additional, Li, M., additional, Luu, M., additional, Martinčič, T., additional, Morais, P., additional, Naser, M. A., additional, Oliveira, B., additional, Owen, D., additional, Pang, S., additional, Park, J., additional, Park, S., additional, Płotka, S., additional, Puybareau, E., additional, Rajpoot, N., additional, Ryu, K., additional, Saeed, N., additional, Shephard, A., additional, Shi, P., additional, Štepec, D., additional, Subedi, R., additional, Tochon, G., additional, Torres, H. R., additional, Urien, H., additional, Vilaça, J. L., additional, Wahid, K. A., additional, Wang, H., additional, Wang, J., additional, Wang, L., additional, Wang, X., additional, Wiestler, B., additional, Wodzinski, M., additional, Xia, F., additional, Xie, J., additional, Xiong, Z., additional, Yang, S., additional, Yang, Y., additional, Zhao, Z., additional, Maier-Hein, K., additional, Jäger, P. F., additional, Kopp-Schneider, A., additional, and Maier-Hein, L., additional

Published
2023
Full Text
View/download PDF

23. Crowd-Algorithm Collaboration for Large-Scale Endoscopic Image Annotation with Confidence

Author

Maier-Hein, L., Ross, T., Gröhl, J., Glocker, B., Bodenstedt, S., Stock, C., Heim, E., Götz, M., Wirkert, S., Kenngott, H., Speidel, S., Maier-Hein, K., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Ourselin, Sebastien, editor, Joskowicz, Leo, editor, Sabuncu, Mert R., editor, Unal, Gozde, editor, and Wells, William, editor

Published
2016
Full Text
View/download PDF

26. Correlation between breeding values for milk fatty acids and Nordic Total Merit index traits for Danish Holstein and Danish Jersey

Author

Buitenhuis, A J, Hein, L, Sørensen, L P, and Kargo, M

Abstract

Milk fatty acid composition is gaining interest in the Danish dairy industry both to develop new dairy products and as a management tool. To be able to implement milk fatty acid (FA) composition in the breeding program, it is important to know the correlations with the traits in the breeding goal. To estimate these correlations, we measured milk fat composition in Danish Holstein (DH) and Danish Jersey (DJ) cattle breeds using mid-infrared spectroscopy. Breeding values were estimated for specific FA and for groups of FA. Correlations with the estimated breeding values (EBV) underlying the Nordic Total Merit index (NTM) were calculated within breed. For both DH and DJ, we showed that FA EBV had moderate correlations with the NTM and production traits. For both DH and DJ, the correlation of FA EBV and NTM were in the same direction, except for C16:0 (0 in DH, 0.23 in DJ). A few correlations differed between DH and DJ. The correlation between claw health index and C18:0 was negative in DH (−0.09) but positive in DJ (0.12). In addition, some correlations were not significant in DH but were significant in DJ. The correlations between udder health index and long-chain FA, trans FA, C16:0, and C18:0 were not significant in DH (−0.05 to 0.02), but were significant in DJ (−0.17, −0.15, 0.14, and −0.16, respectively). For both DH and DJ, the correlations between FA EBV and nonproduction traits were low. This implies that it is possible to breed for a different fat composition in the milk without affecting the nonproduction traits in the breeding goal. Milk fatty acid composition is gaining interest in the Danish dairy industry both to develop new dairy products and as a management tool. To be able to implement milk fatty acid (FA) composition in the breeding program, it is important to know the correlations with the traits in the breeding goal. To estimate these correlations, we measured milk fat composition in Danish Holstein (DH) and Danish Jersey (DJ) cattle breeds using mid-infrared spectroscopy. Breeding values were estimated for specific FA and for groups of FA. Correlations with the estimated breeding values (EBV) underlying the Nordic Total Merit index (NTM) were calculated within breed. For both DH and DJ, we showed that FA EBV had moderate correlations with the NTM and production traits. For both DH and DJ, the correlation of FA EBV and NTM were in the same direction, except for C16:0 (0 in DH, 0.23 in DJ). A few correlations differed between DH and DJ. The correlation between claw health index and C18:0 was negative in DH (-0.09) but positive in DJ (0.12). In addition, some correlations were not significant in DH but were significant in DJ. The correlations between udder health index and long-chain FA, trans FA, C16:0, and C18:0 were not significant in DH (-0.05 to 0.02), but were significant in DJ (-0.17, -0.15, 0.14, and -0.16, respectively). For both DH and DJ, the correlations between FA EBV and nonproduction traits were low. This implies that it is possible to breed for a different fat composition in the milk without affecting the nonproduction traits in the breeding goal.

Published
2023

29. Why is the Winner the Best?

Author

Beeldverwerking ISI, Brain, Cancer, Circulatory Health, Structure and Connections, Eisenmann, M., Reinke, A., Weru, V., Tizabi, M. D., Isensee, F., Adler, T. J., Ali, S., Andrearczyk, V., Aubreville, M., Baid, U., Bakas, S., Balu, N., Bano, S., Bernal, J., Bodenstedt, S., Casella, A., Cheplygina, V., Daum, M., De Bruijne, M., Depeursinge, A., Dorent, R., Egger, J., Ellis, D. G., Engelhardt, S., Ganz, M., Ghatwary, N., Girard, G., Godau, P., Gupta, A., Hansen, L., Harada, K., Heinrich, M., Heller, N., Hering, A., Huaulmé, A., Jannin, P., Kavur, A. E., Kodym, O., Kozubek, M., Li, J., Li, H., Ma, J., Martín-Isla, C., Menze, B., Noble, A., Oreiller, V., Padoy, N., Pati, S., Payette, K., Rädsch, T., Rafael-Patiño, J., Bawa, V. Singh, Speidel, S., Sudre, C. H., Van Wijnen, K., Wagner, M., Wei, D., Yamlahi, A., Yap, M. H., Yuan, C., Zenk, M., Zia, A., Zimmerer, D., Aydogan, D., Bhattarai, B., Bloch, L., Brüngel, R., Cho, J., Choi, C., Dou, Q., Ezhov, I., Friedrich, C. M., Fuller, C., Gaire, R. R., Galdran, A., García Faura, A., Grammatikopoulou, M., Hong, S., Jahanifar, M., Jang, I., Kadkhodamohammadi, A., Kang, I., Kofler, F., Kondo, S., Kuijf, H., Li, M., Luu, M., Martinčič, T., Morais, P., Naser, M. A., Oliveira, B., Owen, D., Pang, S., Park, J., Park, S., Płotka, S., Puybareau, E., Rajpoot, N., Ryu, K., Saeed, N., Shephard, A., Shi, P., Štepec, D., Subedi, R., Tochon, G., Torres, H. R., Urien, H., Vilaça, J. L., Wahid, K. A., Wang, H., Wang, J., Wang, L., Wang, X., Wiestler, B., Wodzinski, M., Xia, F., Xie, J., Xiong, Z., Yang, S., Yang, Y., Zhao, Z., Maier-Hein, K., Jäger, P. F., Kopp-Schneider, A., Maier-Hein, L., Beeldverwerking ISI, Brain, Cancer, Circulatory Health, Structure and Connections, Eisenmann, M., Reinke, A., Weru, V., Tizabi, M. D., Isensee, F., Adler, T. J., Ali, S., Andrearczyk, V., Aubreville, M., Baid, U., Bakas, S., Balu, N., Bano, S., Bernal, J., Bodenstedt, S., Casella, A., Cheplygina, V., Daum, M., De Bruijne, M., Depeursinge, A., Dorent, R., Egger, J., Ellis, D. G., Engelhardt, S., Ganz, M., Ghatwary, N., Girard, G., Godau, P., Gupta, A., Hansen, L., Harada, K., Heinrich, M., Heller, N., Hering, A., Huaulmé, A., Jannin, P., Kavur, A. E., Kodym, O., Kozubek, M., Li, J., Li, H., Ma, J., Martín-Isla, C., Menze, B., Noble, A., Oreiller, V., Padoy, N., Pati, S., Payette, K., Rädsch, T., Rafael-Patiño, J., Bawa, V. Singh, Speidel, S., Sudre, C. H., Van Wijnen, K., Wagner, M., Wei, D., Yamlahi, A., Yap, M. H., Yuan, C., Zenk, M., Zia, A., Zimmerer, D., Aydogan, D., Bhattarai, B., Bloch, L., Brüngel, R., Cho, J., Choi, C., Dou, Q., Ezhov, I., Friedrich, C. M., Fuller, C., Gaire, R. R., Galdran, A., García Faura, A., Grammatikopoulou, M., Hong, S., Jahanifar, M., Jang, I., Kadkhodamohammadi, A., Kang, I., Kofler, F., Kondo, S., Kuijf, H., Li, M., Luu, M., Martinčič, T., Morais, P., Naser, M. A., Oliveira, B., Owen, D., Pang, S., Park, J., Park, S., Płotka, S., Puybareau, E., Rajpoot, N., Ryu, K., Saeed, N., Shephard, A., Shi, P., Štepec, D., Subedi, R., Tochon, G., Torres, H. R., Urien, H., Vilaça, J. L., Wahid, K. A., Wang, H., Wang, J., Wang, L., Wang, X., Wiestler, B., Wodzinski, M., Xia, F., Xie, J., Xiong, Z., Yang, S., Yang, Y., Zhao, Z., Maier-Hein, K., Jäger, P. F., Kopp-Schneider, A., and Maier-Hein, L.

Published
2023

32. Markerlose Navigation für perkutane Nadelinsertionen

Author

Seitel, A., Servatius, M., Franz, A. M., Kilgus, T., Bellemann, N., Radeleff, B. R., Fuchs, S., Meinzer, H.-P., Maier-Hein, L., Tolxdorff, Thomas, editor, Deserno, Thomas Martin, editor, Handels, Heinz, editor, and Meinzer, Hans-Peter, editor

Published
2012
Full Text
View/download PDF

36. Polarized iridescence of the tropical carpenter bee, Xylocopa latipes

Author

Doekele G. Stavenga, Kim Kats, and Hein L. Leertouwer

Subjects
Behavioral Neuroscience, Physiology, Animal Science and Zoology, Ecology, Evolution, Behavior and Systematics
Abstract

The tropical carpenter bee, Xylocopa latipes, has metallic-reflecting, iridescent wings. The wing reflectance spectra for TE- and TM-polarized light depend on the angle of light incidence in a way characteristic for dielectric multilayers. Anatomy indicates the presence of melanin multilayers in the wing’s chitinous matrix. A simple optical model of melanin multilayers explains the angle dependence of the wing reflectance spectra. The wing reflections that occur upon oblique illumination exhibit colourful and strongly polarized light patterns, which may mediate intraspecific signaling and mutual recognition by conspecifics.

Published
2022

38. Digital transformation of surgical services with a focus on patient wearables

Author

Collins, J.W., primary, Khetrapal, P., additional, Sridhar, A., additional, Hung, A., additional, Ghazi, A., additional, Slack, M., additional, Bishop, S., additional, Wang, Y., additional, Maier-Hein, L., additional, Anvari, M., additional, Nakawala, H., additional, Garcia, P., additional, Jarc, A., additional, Bano, S., additional, Nathan, A., additional, Percy, E., additional, Burke, J., additional, Stoyanov, D., additional, and Kelly, J., additional

Published
2022
Full Text
View/download PDF

39. Accounting for Anisotropic Noise in Fine Registration of Time-of-Flight Range Data with High-Resolution Surface Data

Author

Maier-Hein, L., Schmidt, M., Franz, A. M., dos Santos, T. R., Seitel, A., Jähne, B., Fitzpatrick, J. M., Meinzer, H. P., Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Pandu Rangan, C., Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Jiang, Tianzi, editor, Navab, Nassir, editor, Pluim, Josien P. W., editor, and Viergever, Max A., editor

Published
2010
Full Text
View/download PDF

42. Sequential defects in cardiac lineage commitment and maturation cause hypoplastic left heart syndrome

Author

Krane, M, Dressen, M, Santamaria, G, My, I, Schneider, C, Dorn, T, Laue, S, Mastantuono, E, Berutti, R, Rawat, H, Gilsbach, R, Schneider, P, Lahm, H, Schwarz, S, Doppler, S, Paige, S, Puluca, N, Doll, S, Neb, I, Brade, T, Zhang, Z, Abou-Ajram, C, Northoff, B, Holdt, L, Sudhop, S, Sahara, M, Goedel, A, Dendorfer, A, Tjong, F, Rijlaarsdam, M, Cleuziou, J, Lang, N, Kupatt, C, Bezzina, C, Lange, R, Bowles, N, Mann, M, Gelb, B, Crotti, L, Hein, L, Meitinger, T, Wu, S, Sinnecker, D, Gruber, P, Laugwitz, K, Moretti, A, Krane M., Dressen M., Santamaria G., My I., Schneider C. M., Dorn T., Laue S., Mastantuono E., Berutti R., Rawat H., Gilsbach R., Schneider P., Lahm H., Schwarz S., Doppler S. A., Paige S., Puluca N., Doll S., Neb I., Brade T., Zhang Z., Abou-Ajram C., Northoff B., Holdt L. M., Sudhop S., Sahara M., Goedel A., Dendorfer A., Tjong F. V. Y., Rijlaarsdam M. E., Cleuziou J., Lang N., Kupatt C., Bezzina C., Lange R., Bowles N. E., Mann M., Gelb B. D., Crotti L., Hein L., Meitinger T., Wu S., Sinnecker D., Gruber P. J., Laugwitz K. -L., Moretti A., Krane, M, Dressen, M, Santamaria, G, My, I, Schneider, C, Dorn, T, Laue, S, Mastantuono, E, Berutti, R, Rawat, H, Gilsbach, R, Schneider, P, Lahm, H, Schwarz, S, Doppler, S, Paige, S, Puluca, N, Doll, S, Neb, I, Brade, T, Zhang, Z, Abou-Ajram, C, Northoff, B, Holdt, L, Sudhop, S, Sahara, M, Goedel, A, Dendorfer, A, Tjong, F, Rijlaarsdam, M, Cleuziou, J, Lang, N, Kupatt, C, Bezzina, C, Lange, R, Bowles, N, Mann, M, Gelb, B, Crotti, L, Hein, L, Meitinger, T, Wu, S, Sinnecker, D, Gruber, P, Laugwitz, K, Moretti, A, Krane M., Dressen M., Santamaria G., My I., Schneider C. M., Dorn T., Laue S., Mastantuono E., Berutti R., Rawat H., Gilsbach R., Schneider P., Lahm H., Schwarz S., Doppler S. A., Paige S., Puluca N., Doll S., Neb I., Brade T., Zhang Z., Abou-Ajram C., Northoff B., Holdt L. M., Sudhop S., Sahara M., Goedel A., Dendorfer A., Tjong F. V. Y., Rijlaarsdam M. E., Cleuziou J., Lang N., Kupatt C., Bezzina C., Lange R., Bowles N. E., Mann M., Gelb B. D., Crotti L., Hein L., Meitinger T., Wu S., Sinnecker D., Gruber P. J., Laugwitz K. -L., and Moretti A.

Abstract

BACKGROUND: Complex molecular programs in specific cell lineages govern human heart development. Hypoplastic left heart syndrome (HLHS) is the most common and severe manifestation within the spectrum of left ventricular outflow tract obstruction defects occurring in association with ventricular hypoplasia. The pathogenesis of HLHS is unknown, but hemodynamic disturbances are assumed to play a prominent role. METHODS: To identify perturbations in gene programs controlling ventricular muscle lineage development in HLHS, we performed whole-exome sequencing of 87 HLHS parent-offspring trios, nuclear transcriptomics of cardiomyocytes from ventricles of 4 patients with HLHS and 15 controls at different stages of heart development, single cell RNA sequencing, and 3D modeling in induced pluripotent stem cells from 3 patients with HLHS and 3 controls. RESULTS: Gene set enrichment and protein network analyses of damaging de novo mutations and dysregulated genes from ventricles of patients with HLHS suggested alterations in specific gene programs and cellular processes critical during fetal ventricular cardiogenesis, including cell cycle and cardiomyocyte maturation. Single-cell and 3D modeling with induced pluripotent stem cells demonstrated intrinsic defects in the cell cycle/unfolded protein response/autophagy hub resulting in disrupted differentiation of early cardiac progenitor lineages leading to defective cardiomyocyte subtype differentiation/ maturation in HLHS. Premature cell cycle exit of ventricular cardiomyocytes from patients with HLHS prevented normal tissue responses to developmental signals for growth, leading to multinucleation/polyploidy, accumulation of DNA damage, and exacerbated apoptosis, all potential drivers of left ventricular hypoplasia in absence of hemodynamic cues. CONCLUSIONS: Our results highlight that despite genetic heterogeneity in HLHS, many mutations converge on sequential cellular processes primarily driving cardiac myogenesis, suggesting n

Published
2021

43. In-Vivo Targeting of Liver Lesions with a Navigation System Based on Fiducial Needles

Author

Maier-Hein, L., Tekbas, A., Seitel, A., Pianka, F., Müller, S. A., Schawo, S., Radeleff, B., Tetzlaff, R., Franz, A., Rau, A. -M., Wolf, I., Kauczor, H. -U., Schmied, B. M., Meinzer, H. -P., Brauer, W., editor, Tolxdorff, Thomas, editor, Braun, Jürgen, editor, Deserno, Thomas M., editor, Horsch, Alexander, editor, Handels, Heinz, editor, and Meinzer, Hans-Peter, editor

Published
2008
Full Text
View/download PDF

44. Precision Targeting of Liver Lesions with a Needle-Based Soft Tissue Navigation System

Author

Maier-Hein, L., Pianka, F., Seitel, A., Müller, S. A., Tekbas, A., Seitel, M., Wolf, I., Schmied, B. M., Meinzer, H. -P., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ayache, Nicholas, editor, Ourselin, Sébastien, editor, and Maeder, Anthony, editor

Published
2007
Full Text
View/download PDF

48. Adrenergic System

Author

Engelhardt, S., Hein, L., Starke, K., editor, Offermanns, Stefan, editor, and Hein, Lutz, editor

Published
2004
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results