Our publications
Our international team of scientists collaborates across different scientific and medical fields to define new frontiers of innovation. Here you can find relevant scientific work published in peer-reviewed scientific journals.
Flora B. Nemeth, Niklas Leopold-Kerschbaumer, Diana Debreceni, Frank Fleischmann, Krisztian Borbely, David Mazurencu-Marinescu-Pele, Thomas Bocklitz, Mihaela Žigman, Kosmas V. Kepesidis
05/21/2025
Overcoming a key challenge in blood-based infrared spectroscopy
This paper presents a solution to the challenge of cross-device model generalization in blood-based infrared spectroscopy. As infrared spectroscopy becomes increasingly popular for analyzing human blood, ensuring that machine learning models trained on one device can be effectively transferred to others is essential. However, variations in device characteristics often reduce model performance when applied across different devices. To address this issue, we propose a straightforward domain adaptation method based on data augmentation incorporating device-specific differences. By expanding the training data to include a broader range of nuances, our approach enhances the model’s ability to adapt to the unique characteristics of various devices. We validate the effectiveness of our method through experimental testing on two Fourier-Transform Infrared (FTIR) spectroscopy devices from different research laboratories, demonstrating improved prediction accuracy and reliability.
published in ACS Analytical Chemistry
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Kosmas V. Kepesidis, Philip Jacob, Wolfgang Schweinberger, Marinus Huber, Nico Feiler, Frank Fleischmann, Michael Trubetskov, Liudmila Voronina, Jacqueline Aschauer, Tarek Eissa, Lea Gigou, Patrik Karandušovský, Ioachim Pupeza, Alexander Weigel, Abdallah Azzeer, Christian Stief, Michael Chaloupka, Niels Reinmuth, Jürgen Behr, Thomas Kolben, Nadia Harbeck, Maximilian Reiser, Ferenc Krausz, Mihaela Žigman
04/17/2025
Electric-Field Molecular Fingerprinting to Probe Cancer
Human biofluids are valuable indicators of physiological states, and recent advances in molecular profiling technologies offer significant promise for improving clinical diagnostics. In this study, we evaluate the potential of laser-based electric-field molecular fingerprinting as a novel tool for in vitro diagnostics.
In a proof-of-concept clinical study involving 2,533 participants, we conducted randomized measurement campaigns to spectroscopically profile bulk venous blood plasma across four cancer types: lung, prostate, breast, and bladder. Using machine learning, we identified infrared spectral signatures associated with therapy-naïve cancer states, distinguishing them from matched control individuals. For lung cancer, we achieved a cross-validated area under the receiver operating characteristic curve (ROC AUC) of 0.88, while ROC AUC values ranged from 0.68 to 0.69 for prostate, breast, and bladder cancers.
In an independent held-out test set—designed to reflect experimental conditions different from those used during model training—we achieved a ROC AUC of 0.81 for lung cancer detection.
These results demonstrate that electric-field molecular fingerprinting provides a robust and scalable framework for disease phenotyping, with potential for broad application in real-world diagnostic settings.
published in ACS Central Science
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Corinna Wegner, Zita I. Zarandy, Nico Feiler, Lea Gigou, Timo Halenke, Niklas Leopold-Kerschbaumer, Maik Krusche, Weronika Skibicka, Kosmas V. Kepesidis
04/10/2025
Toward Informative Representations of Blood-Based Infrared Spectra via Unsupervised Deep Learning
At the heart of the research is a denoising autoencoder — a type of neural network designed to extract meaningful patterns from complex data. Applied to Fourier Transform Infrared (FTIR) spectroscopy, the model employs a custom loss function and a bottleneck architecture to strip away noise while preserving critical molecular information. The result: a 2.6-percentage-point boost in lung cancer detection accuracy in a case-control study.
Beyond improved performance, the learned latent space also highlights spectral features linked to disease presence, paving the way for more insightful and interpretable diagnostic tools.
This work marks the first-ever application of modern AI techniques to infrared molecular fingerprints from blood samples collected in the framework of attoworld.
published in Journal of Biophotonics
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Kosmas V. Kepesidis, Mircea-Gabriel Stoleriu, Nico Feiler, Lea Gigou, Frank Fleischmann, Jacqueline Aschauer, Sabine Eiselen, Ina Koch, Niels Reinmuth, Amanda Tufman, Jürgen Behr, Mihaela Žigman
04/01/2025
Assessing lung cancer progression and survival with infrared spectroscopy of blood serum
About eight years ago, the Broadband Infrared Diagnostics (BIRD) research group and the clinical study team,Lasers4Life at attoworld set out to collaborate with Prof. Dr. Jürgen Behr and the medical professionals from the Asklepios Clinic in München-Gauting and the Department of Medicine V of LMU University Hospital in Munich. Together, they initiated an investigation into the intricacies of chemical footprints left by lung tumors in the blood and how these profiles change over time. The study tracked individuals from the time of their lung cancer diagnosis throughout their treatment. Given that lung cancer is unfortunately still diagnosed at an advanced stage only, there is a critical unmet need for minimally invasive diagnostic tests that enable earlier detection.
In the current study, the BIRD team applied Fourier-transform infrared (FTIR) spectroscopy as a molecular fingerprinting technique to profile blood samples from 160 lung cancer patients. Meanwhile, the CMF Data Science team analyzed the acquired molecular profiles and applied statistical and machine learning methods to assess patient survival. Their findings revealed that the infrared fingerprints correlated with lung cancer survival in a manner comparable to traditional tumor staging and blood biomarkers. Moreover, a larger case-control comparison of 501 individuals demonstrated an association between these infrared fingerprints and lung cancer progression.
published in BMC Medicine
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Syed A. Hussain, Christina Hofer, Maximilian Högner, Wolfgang Schweinberger, Theresa Buberl, Daniel Bausch, Marinus Huber, Ferenc Krausz, Ioachim Pupeza
09/06/2024
Sub-attosecond-precision optical-waveform stability measurements using electro-optic sampling
The generation of laser pulses with controlled optical waveforms, and their measurement, lie at the heart of both time-domain and frequency-domain precision metrology. Here, we obtain midinfrared waves via intra-pulse difference-frequency generation (IPDFG) driven by 16-femtosecond near-infrared pulses, and characterise the jitter of sub-cycle fractions of these waves relative to the gate pulses using electro-optic sampling (EOS). We demonstrate sub-attosecond temporal jitter at individual zero-crossings and sub-0.1%-level relative amplitude fluctuations in the 10-kHz–0.625- MHz band. Chirping the nearly-octave-spanning mid-infrared pulses uncovers wavelength-dependent attosecond-scale waveform jitter. Our study validates EOS as a broadband (both in the radiofrequency and the optical domains), highly sensitive measurement technique for the jitter dynamics of optical waveforms. This sensitivity reveals outstanding stability of the waveforms obtained via IPDFG and EOS, directly benefiting precision measurements including linear and nonlinear (infrared) fieldresolved spectroscopy. Furthermore, these results form the basis toward EOS-based active waveform stabilisation and sub-attosecond multi-oscillator synchronisation/delay tracking.
published in Scientific Reports
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Marinus Huber, Michael Trubetskov, Wolfgang Schweinberger, Philip Jacob, Mihaela Žigman, Ferenc Krausz, Ioachim Pupeza
07/29/2024
Standardized Electric-Field-Resolved Molecular Fingerprinting
Field-resolved infrared spectroscopy (FRS) of impulsively excited molecular vibrations can surpass the sensitivity of conventional time-integrating spectroscopies, owing to a temporal separation of the molecular signal from the noisy excitation. However, the resonant response carrying the molecular signal of interest depends on both the amplitude and phase of the excitation, which can vary over time and across different instruments. To date, this has compromised the accuracy with which FRS measurements could be compared, which is a crucial factor for practical applications. Here, we utilize a data processing procedure that overcomes this shortcoming while preserving the sensitivity of FRS. We validate the approach for aqueous solutions of molecules. The employed approach is compatible with established processing and evaluation methods for the analysis of infrared spectra and can be applied to existing spectra from databases, facilitating the spread of FRS to new molecular analytical applications.
published in Analytical Chemistry
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Tarek Eissa, Cristina Leonardo, Kosmas V. Kepesidis, Frank Fleischmann, Birgit Linkohr, Daniel Meyer, Viola Zoka, Marinus Huber, Liudmila Voronina, Lothar Richter, Annette Peters, Mihaela Žigman
07/05/2024
Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening
Infrared spectroscopy is a powerful technique for probing the molecular profiles of complex biofluids, offering a promising avenue for high-throughput in vitro diagnostics. Using a population-based cohort, here we analyze 5,184 blood plasma samples from 3,169 individuals using Fourier transform infrared (FTIR) spectroscopy. Applying a multi-task classification to distinguish between dyslipidemia, hypertension, prediabetes, type 2 diabetes, and healthy states, we find that the approach can accurately single out healthy individuals and characterize chronic multimorbid states. We further identify the capacity to forecast the development of metabolic syndrome years in advance of onset. This study provides the framework that establishes infrared molecular fingerprinting as an efficient modality for populational health diagnostics.
published in Cell Reports Medicine
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Alexander Weigel, Philip Jacob, Wolfgang Schweinberger, Marinus Huber, Michael Trubetskov, Patrik Karandušovský, Christina Hofer, Theresa Buberl, Tatiana Amotchkina, Maximilian Högner, Daniel Hahner, Philipp Sulzer, Alfred Leitenstorfer, Vladimir Pervak, Ferenc Krausz, Ioachim Pupeza
05/28/2024
Dual-oscillator infrared electro-optic sampling with attosecond precision
Electro-optic sampling of infrared electric fields has set sensitivity and dynamic-range records in broadband molecular vibrational spectroscopy. Yet, in these works, the 1-second-scale single-trace acquisition time leads to intra-scan noise accumulation and restricts the throughput in measurements of multiple samples and of dynamic processes. We present a dual-laser-oscillator approach capturing 2800 mid-infrared waveforms per second by scanning the relative delay between the sampled waveform and the gate pulses using a modulated repetition-frequency lock. The new technique of electro-optic delay tracking (EODT) provides delay calibration with down to few-attosecond precision and provides a general route to high-precision dual-oscillator spectroscopy with picosecond delay ranges. Our work has immediate applications in, e.g., precision electric-field metrology and high-speed biosensing.
published in Optica
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Maciej Kowalczyk, Arun Paudel, Aleksandar Sebesta, Philipp Steinleitner, Nathalie Nagl, Markus Poetzlberger, Vladimir Pervak, Ka Fai Mak, Alexander Weigel
06/21/2023
Ultra-CEP-stable single-cycle pulses at 2,2 µm
Single-cycle optical pulses with controllable carrier-envelope phase (CEP) form the basis to manipulate the nonlinear polarization of matter on a sub-femtosecond time scale. We report a highly stable source of 6.9-fs, single-cycle pulses at 2.2 µm, based on a directly diode-pumped Cr:ZnS oscillator with 22.9-MHz repetition rate. Excellent agreement with simulations provides a precise understanding of the underlying nonlinear pulse propagation.
published in Optica
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Tarek Eissa, Kosmas V. Kepesidis, Mihaela Žigman, Marinus Huber
04/12/2023
Limits and prospects of molecular fingerprinting for phenotyping biological systems revealed through in silico modeling
Molecular fingerprinting via vibrational spectroscopy characterizes the chemical composition of molecularly complex media, which enables the classification of phenotypes associated with biological systems. However, the interplay between factors such as biological variability, measurement noise, chemical complexity, and cohort size makes it challenging to investigate their impact on how the classification performs. Considering these factors, we developed an in silico model that generates realistic but configurable molecular fingerprints.
published in Analytical Chemistry
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Shizhen Qu, Arun Paudel, Aleksandar Sebesta, Philipp Steinleitner, Nathalie Nagl, Markus Poetzlberger, Vladimir Pervak, Ka Fai Mak, Alexander Weigel
11/22/2022
Directly diode-pumped femtosecond Cr:ZnS amplifier with ultra-low intensity noise
A diode-pumped Cr:ZnS amplifier is showcased, delivering 2.2 W of 35-fs pulses with low noise and high stability. This amplifier holds promise for generating ultrashort infrared pulses, particularly for ultrasensitive vibrational spectroscopy.
published in Optica
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Philipp Steinleitner, Nathalie Nagl, Maciej Kowalczyk, Jinwei Zhang, Vladimir Pervak, Christina Hofer, Arkadiusz Hudzikowski, Jarosław Sotor, Alexander Weigel, Ferenc Krausz, Ka Fai Mak
05/26/2022
Single-cycle infrared waveform control
This study extends electric-field waveform control of ultrashort light pulses from visible to mid-infrared, generating single-cycle infrared pulses with broad applications, including material manipulation and molecular fingerprinting in biological systems.
published in Nature
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Kosmas V. Kepesidis, Masa Bozic-Iven, Marinus Huber, Nashwa Abdel-Aziz, Sharif Kullab, Ahmed Abdelwarith, Abdulrahman Al Diab, Mohammed Al Ghamdi, Muath Abu Hilal, Mohun R. K. Bahadoor, Abhishake Sharma, Farida Dabouz, Maria Arafah, Abdallah M. Azzeer, Ferenc Krausz, Khalid Alsaleh, Mihaela Žigman, Jean-Marc Nabholtz
12/02/2021
Breast-cancer detection using blood-based infrared molecular fingerprints
Current breast cancer screening, primarily using mammography, has limitations such as false results, prompting the need for innovative methods to improve early detection. This study explores the potential of FTIR spectroscopy on blood plasma, a rapid, cost-effective technique, to enhance breast cancer detection through molecular analysis.
published in BMC Cancer
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Marinus Huber, Kosmas V. Kepesidis, Liudmila Voronina, Frank Fleischmann, Ernst Fill, Jacqueline Hermann, Ina Koch, Katrin Milger-Kneidinger, Thomas Kolben, Gerald B Schulz, Friedrich Jokisch, Jürgen Behr, Nadia Harbeck, Maximilian Reiser, Christian Stief, Ferenc Krausz, Mihaela Žigman
09/13/2021
Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer
Recent omics studies on human biofluids using FTIR spectroscopy highlight the capability of infrared molecular fingerprinting to detect breast, bladder, prostate, and lung cancer, with AUC values ranging from 0.78 to 0.89. These results uncover unique spectral patterns for each cancer type and lay the groundwork for cost-effective onco-IR-phenotyping in efficient disease identification.
published in eLife
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Cristina Leonardo, Johannes B. Mueller-Reif, Liudmila Voronina, Philipp E. Geyer, Marinus Huber, Michael Trubetskov, Kosmas V. Kepesidis, Jürgen Behr, Matthias Mann, Ferenc Krausz, Mihaela Žigman
04/21/2021
Molecular origin of blood-based infrared spectroscopic fingerprints
Using infrared spectroscopy on liquid biopsies, alongside biochemical fractionation and proteomic profiling, helps us understand the molecular reasons behind disease-related alterations in infrared fingerprints. This approach, which combines proteomics, spectral data, and machine learning, improves our comprehension of liquid biopsy infrared spectra and its potential for researching various diseases.
published in Angewandte Chemie
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Marinus Huber, Kosmas V. Kepesidis, Liudmila Voronina, Maša Božić, Michael Trubetskov, Nadia Harbeck, Ferenc Krausz, Mihaela Žigman
03/08/2021
Stability of person-specific blood-based infrared molecular fingerprints opens up prospects for health monitoring
Studying the stability of individual biochemical fingerprints in blood serum and plasma samples from healthy individuals using FTIR spectroscopy supports the idea that blood-based infrared spectral fingerprinting could be a dependable method for health monitoring. This approach provides unique spectral markers for identifying and monitoring changes in molecular characteristics over time.
published in Nature Communications
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Ioachim Pupeza, Marinus Huber, Michael Trubetskov, Wolfgang Schweinberger, Syed A. Hussain, Christina Hofer, Kilian Fritsch, Markus Poetzlberger, Lenard Vamos, Ernst Fill, Tatiana Amotchkina, Kosmas V. Kepesidis, Alexander Apolonski, Nicholas Karpowicz, Vladimir Pervak, Oleg Pronin, Frank Fleischmann, Abdallah Azzeer, Mihaela Žigman, Ferenc Krausz
01/20/2020
Field-resolved infrared spectroscopy of biological systems
Broadband optical coherence, which utilizes vibrationally excited molecules and electro-optic sampling, allows for the sensitive detection and spectroscopic analysis of complex molecular structures in living systems. This includes applications in human cells, plant leaves, and blood serum, promising improved sensitivity and broader utility in real-world biological and medical scenarios.
published in Nature
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