Autofluorescence lifetime augmented reality as a means for real-time robotic surgery guidance in human patients

Due to loss of tactile feedback the assessment of tumor margins during robotic surgery is based only on visual inspection, which is neither significantly sensitive nor specific. Here we demonstrate time-resolved fluorescence spectroscopy (TRFS) as a novel technique to complement the visual inspection of oral cancers during transoral robotic surgery (TORS) in real-time and without the need for exogenous contrast agents. TRFS enables identification of cancerous tissue by its distinct autofluorescence signature that is associated with the alteration of tissue structure and biochemical profile. A prototype TRFS instrument was integrated synergistically with the da Vinci Surgical robot and the combined system was validated in swine and human patients. Label-free and real-time assessment and visualization of tissue biochemical features during robotic surgery procedure, as demonstrated here, not only has the potential to improve the intraoperative decision making during TORS but also other robotic procedures without modification of conventional clinical protocols

Stata Code for "An investigation of the causal effect of educational expectations on school performance. Behavioral consequences, time-stable confounding, or reciprocal causality?"

This project consists of Stata Code for our 2021 paper "An investigation of the causal effect of educational expectations on school performance. Behavioral consequences, time-stable confounding, or reciprocal causality?" by Neumeyer and Dochow. The full paper can be found here (OA): https://www.sciencedirect.com/science/article/pii/S0276562420301153 Abstract: Educational expectations are core concepts in the sociology of education. In this study, we are interested in the potential behavioral consequences of expectations on school performance in early secondary education. The existing literature leads to contradictory hypotheses regarding the causal effect of expectations on achievement. On the one hand, expectations could act as cognitions steering individual behavior towards the attainment of a certain educational degree via preparatory commitment and effort. Such behavioral consequences should affect achievement in school. On the other hand, expectations could merely reflect students’ perceptions of opportunities without exerting an effect on future achievement. This paper studies these claims by relying on German panel data of students in lower secondary education. In the first set of models, we find that after adjusting for student fixed effects, expectations are only marginally related to grades and competences. In further models, we assess the role of stable high and low aspirations in explaining educational achievement trajectories. After adjusting for past grades via inverse probability weighting, achievement at the end of lower secondary education is similar between students with stable high expectations and those with stable low expectations. Taking together the results of these different modelling approaches, our study suggests that expectations are not drivers of achievement-related behavior. The paper is part of the larger project "When immigrants are aiming high: Educational achievement and attainment in light of greater aspirations", funded by the German Research foundation, and led by Prof. Dr. Cornelia Kristen, Prof. Dr. Christoph Spörlein and Dr. Gisela Will

Classification of Raman spectra of single cells with autofluorescence suppression by wavelength modulated excitation

Wavelength modulated Raman spectroscopy has recently been shown to suppress the fluorescence background generated by the sample and the substrate. Here we apply this technique to collect wavelength modulated Raman spectra from 697 individual cells for a model system of circulating tumour cells that consists of leukocytes from patient's blood, acute myeloid leukaemia cells (OCI-AML3), and breast tumour cells BT-20 and MCF-7. We study the classification behaviour of wavelength modulated Raman spectra in comparison to a common background correction method in chemometrics. Classifications using a support vector machine with a radial based kernel function were compared for classical Raman spectra, average Raman spectra of each cell and wavelength modulated Raman spectra. The dataset was divided into 80% training spectra and 20% independent validation spectra. The stability of the classification was tested by performing training and validation 200 times with randomly selected datasets. The results are displayed in box whisker plots. Cell identification based on wavelength modulated Raman spectra gives similar classification rates than classical and averaged Raman spectra with a tendency of reduced accuracies and increased modelling variations. Possible explanations and strategies to further improve the wavelength modulated Raman spectroscopy are discussed.</p

Combined fiber probe for fluorescence lifetime and Raman spectroscopy

In this contribution we present a dual modality fiber optic probe combining fluorescence lifetime imaging (FLIm) and Raman spectroscopy for in vivo endoscopic applications. The presented multi-spectroscopy probe enables efficient excitation and collection of fluorescence lifetime signals for FLIm in the UV/visible wavelength region, as well as of Raman spectra in the near-IR for simultaneous Raman/FLIm imaging. The probe was characterized in terms of its lateral resolution and distance dependency of the Raman and FLIm signals. In addition, the feasibility of the probe for in vivo FLIm and Raman spectral characterization of tissue was demonstrated