Conference Agenda

High-precision biosensors for single or few molecules detection play a central role in numerous key fields, such as environmental monitoring and healthcare for early-stage disease diagnosis. In the last decade, laser biosensors have been investigated as proofs of concept, and several technologies have been proposed. Here we propose a demonstration of polymeric whispering gallery microlasers as biosensors for detecting proteins at low concentrations. Free space microlasers have the great advantage of working without any need for waveguiding for input excitation or output signal detection. The photonic microsensors can be easily patterned on microscope slides and operate in air and solution. We could detect down to 400 pg of protein without specific binding, and few tens of pg/mL with specific binding.

New photonic techniques need to be developed to improve personalised medicine methods in tissue engineering. In the case of severe bone injuries, difficulties arise when creating platforms where cells required to be efficiently adhered. Femtosecond laser ablation appears as a versatile technique for modifying the surface of materials with high precision and neat outcomes. Thus, a strategy combining 3D printing of biopolymeric scaffolds and femtosecond laser ablation is proposed to design a device with enhanced material properties in terms of cell growth for bone tissue regeneration. Three different patterns were proposed, and it was proven that cell adhesion improvements rely on the pattern profile, assessing that grooved scaffold successfully increased cell adhesion and proliferation in comparison with micropitted samples.

Assessing HER2 expression in breast cancer cells holds significant diagnostic and prognostic importance. Traditional methods like immunohistochemistry and in situ hybridization suffer from low sensitivity and misclassification rates. In this frame, techniques such as vibrational microscopies can ensure, together with low costs and analytical speed, both high accuracy and precision. Herein, we propose a combined Raman and SERS approach for characterizing 4 breast cancer cell lines and normal cells with varying HER2 expression levels. We show that Raman spectroscopy offers a promising alternative, providing unique molecular fingerprints for cell types based on their biochemical signatures. Its non-invasive nature and ability to detect subtle changes in cellular metabolism make it ideal for cancer cell analysis. Coupled with machine learning techniques like PCA and LDA, Raman spectroscopy can classify different breast cancer subcategories accurately. Surface Enhanced Raman Scattering (SERS) further enhances sensitivity, allowing the detection of single molecules like HER2 receptors. Overall, our results enable fast screening of cancer subpopulation in terms of HER2 concentration and macromolecule cell content. Integration of Raman spectroscopy with SERS offers precise identification and opens avenues for personalized therapies

With continuously improving resolution of today’s (super-resolution) microscopes, a major technical limitation of light microscopy based image analysis is linkage error – a visualization error that is measured by the distance between the cellular target to be detected and the fluorescence emitter used for detection. The linkage error of standard labelled antibodies is caused by the size of the antibody and the random distribution of fluorescent emitters on the antibody surface. In this study, we describe a class of staining reagents that effectively reduce the linkage error by more than five-fold when compared to conventional staining techniques. These reagents, called Fluo-N-Fabs, consist of an antigen binding fragment that is selectively conjugated at the N-terminal amino group with fluorescent organic molecules, thereby reducing the distance between the fluorescent emitter and the protein target of the analysis. Fluo-N-Fabs also exhibit the capability to penetrate tissues and highly crowded cell compartments, thus allowing for the efficient detection of cellular epitopes in a wide range of fixed samples. We believe this class of reagents realize an unmet need in cell biological super resolution imaging studies where the precise localization of the target of interest is crucial for the understanding of complex biological phenomena.

The manufacturing rate of laser-chemical machining (LCM) is limited to avoid disruptive boiling bubbles in the process fluid. Adjustments to e.g. the laser beam or the fluid properties can increase the removal rate. However, the existing understanding of the surface removal mechanisms is insufficient to ensure the removal quality under these conditions. Thus, near-process measurements of the surface geometry and the surface temperature are required for an improved process modeling. Due to the complex process environment, no suitable in-process measurement technique for the geometry or surface temperature exists so far. This contribution presents an indirect geometry measurement approach based on scanning confocal fluorescence microscopy that is integrated into the LCM plant. As a result, it is shown that the approx. 200 μm deep micro-geometry of laser-chemically processed surfaces can be indirectly measured in-situ, i.e. inside the LCM system. The realized setup is designed in such a way that in future it will be additionally possible to measure the temperature by means of the fluorescence life-time.