Thorlabs (Germany)

Optical coherence tomography (OCT) has become increasingly important in fundamental research, medical diagnostics, material characterization, and industrial process monitoring. OCT measures the depth-dependent reflectivity of a sample with micrometer-scale resolution by analyzing the interference between light reflected from the sample and a reference arm. Despite its widespread application, OCT remains underrepresented in undergraduate curricula due to the complexity and cost of commercial systems. Our contribution presents educational implementations of the two most widely used OCT modalities: swept-source OCT and spectral-domain OCT. In our swept-source setup, a grating monochromator is used as a tunable light source, providing a clear and cost-effective realization of wavelength sweeping. For our spectral-domain setup, we developed a compact, self-built two-dimensional spectrometer enabling efficient spectral acquisition. Both systems are capable of producing three-dimensional representations of the internal sample structure. Designed with open architecture and minimal complexity, these setups prioritize visibility of core principles, making them well-suited for hands-on learning in undergraduate laboratory environments.

Introduction: Radical Antegrade Modular Pancreatosplenectomy (RAMPS) was developed to improve surgical radicality for left-sided pancreatic ductal adenocarcinoma (PDAC). Although widely accepted, the optimal surgical approach-open versus minimally invasive (MI)-is still being debated. Methods: We conducted a multicenter retrospective cohort study across three Austrian centers, including all patients undergoing RAMPS between 2016 and 2023 indicated for suspected (pre-)malignant pancreatic lesions. Patients were grouped based on the surgical approach (MI vs. open). The primary endpoints were resection margin status and lymph node yield following PDAC resection. Secondary outcomes included survival for PDAC patients and postoperative complications; non-PDAC resections were also taken into account. Results: A total of 57 patients were included, of whom 34 had PDAC. In PDAC patients, the rate of tumor-free margins and the median lymph node yield were equivalent between the MI and open approaches (R0 rate: MI 92.9% vs. open 85%, p = 0.484; median lymph node yield: MI 16 (IQR 10-23) vs. open 19 (IQR 15-25), p = 0.314). Two-year overall survival was also comparable (MI: 71.6% vs. open: 66.4%, p = 0.479). Postoperative outcomes at 90 days, like CR-POPF and major complications (Clavien-Dindo ≥ IIIa), did not differ between the two approaches. MI-RAMPS showed non-significant favorable trends in median length of stay (p = 0.093) and likelihood of receiving adjuvant chemotherapy (p = 0.075). Conclusions: In our experience, MI-RAMPS demonstrates oncologic equivalence and similar early postoperative outcomes to open RAMPS, with potential advantages such as shorter length of stay and likelihood of receiving adjuvant chemotherapy.

Osteoporosis is a skeletal pathology characterized by decreased bone mass and structural deterioration resulting from an imbalance in bone metabolic processes. Estrogen deficiency in postmenopausal women leads to an increased risk of osteoporosis, while women who have undergone complete oophorectomies display an even higher risk due to the sudden decrease in estrogen. Some evidence indicates that bone loss slows in the period beyond 15 years after surgery; however, there is substantial uncertainty in clinical data. To explore the effects of surgically induced menopausal transition, here we propose a mathematical model for the bone cell dynamical responses to sudden estrogen deficiency, which extends an existing model for osteoporosis due to aging and natural menopause. Using data on the key impacts observed in female mice and humans after bilateral oophorectomy, this new model considers the role of osteocytes embedded within the bone mineralized matrix in regulating osteoclastogenesis, which results in increased bone resorption after surgical menopause. The values of model parameters in natural and surgical menopause were estimated from aggregated human clinical data from existing longitudinal studies. The new model effectively captures the previously unmodeled increase in bone loss during the first 15 years post-surgical menopause and the rebound in bone mineral density in the long-term. With this model, effects of treatments on targeting osteocyte dynamics could be explored in the future.

Railway systems, particularly in Germany, require high levels of automation to address legacy infrastructure challenges and increase train traffic safely. A key component of automation is robust long-range perception, essential for early hazard detection, such as obstacles at level crossings or pedestrians on tracks. Unlike automotive systems with braking distances of 70 meters, trains require perception ranges exceeding 1 km. This paper presents an deep-learning-based approach for long-range 3D object detection tailored for autonomous trains. The method relies solely on monocular images, inspired by the Faraway-Frustum approach, and incorporates LiDAR data during training to improve depth estimation. The proposed pipeline consists of four key modules: (1) a modified YOLOv9 for 2.5D object detection, (2) a depth estimation network, and (3–4) dedicated short- and long-range 3D detection heads. Evaluations on the OSDaR23 dataset demonstrate the effectiveness of the approach in detecting objects up to 250 meters. Results highlight its potential for railway automation and outline areas for future improvement.

A successful drug needs to combine several properties including high potency and good pharmacokinetic (PK) properties to sustain efficacious plasma concentration over time. To estimate required doses for preclinical animal efficacy models or for the clinics, invivo PK studies need to be conducted. Although the prediction of ADME properties of compounds using machine learning (ML) models based on chemical structures is well established in drug discovery, the prediction of complete plasma concentration-time profiles has only recently gained attention. In this study, we systematically compare various approaches that integrate ML models with empiric or mechanistic PK models to predict PK profiles in rats after intravenous administration prior to synthesis. More specifically, we compare a standard noncompartmental analysis (NCA)-based approach (prediction of CL and Vss), a pure ML approach (non-mechanistic PK description), a compartmental modeling approach, and a physiologically based pharmacokinetic (PBPK) approach. Our study based on internal preclinical data shows that the latter three approaches yield PK profile predictions of comparable accuracy across a large data set (evaluated as geometric mean fold errors for each profile of over 1000 small molecules). In summary, we demonstrate the improved ability to prioritize drug candidates with desirable PK properties prior to synthesis with ML predictions.

We investigated the transmission properties of tapered fibres both experimentally with simulations in order to select the appropriate fibre for the high-resolution spectrograph EXOhSPEC. The work focuses on testing commercial produced graded-index (GI) and custom made graded-index (GI) multimode fibres and compares these with a 10 μm step-index (SI) conventional fibre. The performance of a spliced taper package (SP) is also investigated. All tests are performed with coherent light at 635 nm. The main focus of the investigation was to determine the factors that optimised the light transmission by matching the numerical aperture to the fibre and minimising misalignment. We characterised how the transmission through the fibre depends on the effective numerical aperture (NA_eff ) or input beam numerical aperture. The results suggest that under optimal coupling conditions, the transmission of a Custom GI taper is better than the 10 μm SI fibre and the commercial Thorlabs taper over the range of NA_eff from 0.02 to 0.25. In addition, we characterised a spliced taper package (SP) which contained a tapered fibre spliced to untapered fibre. Additionally a comparison of transmission via two coupling methods was investigated in the work. The results indicate splicing a large core GI fibre onto a tapered fibre is an appropriate technique for the fibre link of a fibre-fed spectrograph.

This paper provides a comprehensive analysis of modern techniques used in the assessment of cutaneous flaps in reconstructive surgery. It emphasizes the importance of preoperative planning and intra- and perioperative assessment of flap perfusion to ensure successful outcomes. Despite technological advancements, direct clinical assessment remains the gold standard. We categorized assessment techniques into non-invasive and invasive modalities, discussing their strengths and weaknesses. Non-invasive methods, such as Acoustic Doppler Sonography, Near-Infrared Spectroscopy, Hyperspectral Imaging Thermal Imaging, and remote-Photoplethysmography, offer accessibility and safety but may sacrifice specificity. Invasive techniques, including Contrast-Enhanced Ultrasound, Computed Tomography Angiography, Near-Infrared Fluorescence Angiography with Indocyanine Green, and Implantable Doppler Probe, provide high accuracy but introduce additional risks. We emphasize the need for a tailored decision-making process based on specific clinical scenarios, patient characteristics, procedural requirements, and surgeon expertise. It also discusses potential future advancements in flap assessment, including the integration of artificial intelligence and emerging technologies.