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Bone tissue features a complex microarchitecture and biomolecular composition, which determine biomechanical properties. In addition to state-of-the-art technologies, innovative optical approaches allowing the characterization of the bone in native, label-free conditions can provide new, multi-level insight into this inherently challenging tissue. Here, we exploited multimodal nonlinear optical (NLO) microscopy, including co-registered stimulated Raman scattering, two-photon excited fluorescence, and second-harmonic generation, to image entire vertebrae of murine spine sections. The quantitative nature of these nonlinear interactions allowed us to extract accurate biochemical, morphological, and topological information on the bone tissue and to highlight differences between normal and pathologic samples. Indeed, in a murine model showing bone loss, we observed increased collagen and lipid content as compared to the wild type, along with a decreased craniocaudal alignment of bone collagen fibres. We propose that NLO microscopy can be implemented in standard histopathological analysis of bone in preclinical studies, with the ambitious future perspective to introduce this technique in the clinical practice for the analysis of larger tissue sections.

We introduce label-free multimodal nonlinear optical microscopy, based on different coherent Raman and multi-photon ultrafast light-matter interactions, as a noninvasive, quantitative and chemically selective tool to assess chemotherapy-induced senescence in human cancer cells.

We introduce a broadband coherent anti-Stokes Raman scattering (CARS) microscope based on a 2-MHz repetition rate ytterbium laser generating 1035-nm high-energy (≈µJ level) femtosecond pulses. These features of the driving laser allow producing broadband red-shifted Stokes pulses, covering the whole fingerprint region (400–1800 cm−1), employing supercontinuum generation in a bulk crystal. Our system reaches state-of-the-art acquisition speed (

Stimulated Raman scattering (SRS) microscopy is a powerful technique for label-free identification of molecules based on their intrinsic vibrational spectrum. We present a novel approach to broadband SRS microscopy based on a recently developed balanced low-noise integrated-circuit multichannel lock-in amplifier with 10-μs integration time and 32 channels working in parallel, enabling multiplex SRS detection at speed faster than one hyperspectral frame per second. The system is powered by a narrowband Stokes pulse at 1040 nm and a broadband (approx. 500 cm^-1) pump pulse generated by a home-built low-noise optical parametric oscillator with up to 100-mW average power, covering the whole C-H stretching band. We measure stimulated Raman loss on the broadband pump pulse employing an in-line balanced detection approach to suppress the laser fluctuations and achieve close to shot-noise-limited sensitivity. We will show the system performances in high-resolution cell imaging.

We present innovative approaches to broadband coherent Raman scattering microscopy, both in the stimulated Raman scattering (SRS) and broadband coherent anti-Stokes Raman scattering (CARS) modalities. A convolutional neural network removes the unwanted non-resonant background from broadband CARS spectra. The deep-learning model processes experimental data in 100microseconds and correctly retrieves all the relevant vibrational peaks without any user intervention or independent background measurement. A multi-channel lock-in amplifier, in combination with in-line balanced detection and a broadband optical parametric oscillator, allows sensitive measurement of the SRS spectrum at 32 frequencies in parallel, with pixel dwell times as short as 40 microseconds.

The first key step in the detection and classification of most cancers is the microscopic assessment of thin tissue slices, the so-called “histopathology”. This procedure is still nowadays, similarly to 150 years ago, performed by staining the tissue with two or more dyes able to bind to specific biological structures, followed by visual inspection by the histopathologist under the bright-field optical microscope. This approach involves long manual procedures which can be accompanied by human errors, subjectivity, and lack of reproducibility. Vibrational microscopies are capable of directly providing chemical and biomolecular information on tissues, identifying them through their fingerprint vibrational spectra without the need of staining and, thus, constitute powerful tools for label-free and objective tumour identification. The two most established techniques, spontaneous Raman microscopy and infrared absorption microscopy, suffer, respectively, from long acquisition times and low spatial resolution. These limitations can be overcome by novel and more technically demanding approaches such coherent Raman scattering and photothermal infrared microscopy. Here we present an extended overview of the major advances in the field of vibrational imaging for cancer diagnosis. We start from a detailed description of the different technologies and then present examples of their applications to tissue imaging for cancer assessment. We critically compare the presented approaches, discussing the steps required to bring these powerful technologies from bench to bedside.

Coherent anti-Stokes Raman scattering is an extremely powerful non-linear optical (NLO) microscopy technique for label-free vibrational imaging allowing for a detailed study of biological samples in their native state. To overcome the long acquisition times associated with raster sample scanning required in NLO microscopy, which impair real-time investigation of fast biological dynamics, we employ here wide-field signal generation over a large field of view, covering tens of micrometers. To this aim, we exploit an innovative approach based on the use of an amplified femtosecond ytterbium laser source delivering high energy (≈μJ) pulses in the near infrared. This enables the generation of stable broadband Stokes pulses to measure the entire fingerprint region of the molecular vibrational spectrum, the richest in chemical information. Our results pave the way for future translational applications and clinical diagnostics with video-rate imaging capabilities. ©2022 The Authors

We introduce a novel approach based on deep learning to remove non-resonant background from coherent anti-Stokes Raman scattering spectra in real time. The model is trained on synthetic spectra and successfully applied to experimental data.

Two‐photon laser writing is used here to fabricate 3D proteinaceous microstructures with photothermal functionality in the near‐infrared spectral region and tunable elasticity. The photo‐cross‐linking is initiated in bovine serum albumin (BSA) by rose bengal or methylene blue and the photo‐thermal effect arises from gold non‐spherically symmetric nanoparticles dispersed in the ink. Massive energy transfer of the plasmonic resonances of the gold nanoparticles to methylene blue prevents effective photo‐crosslinking of BSA. However, stable microstructures with photo‐thermal functionality can be fabricated in the rose bengal proteinaceous inks. On these microstructures, with a gold atom concentration as low as 1% w/w, a highly localized temperature increase can be quickly (≅1 s) reached and maintained under continuous wave laser irradiation at 800 nm. The photothermal efficiency under continuous wave laser irradiation depends on the thickness of the microstructure and can reach 12.2 ± 0.4 °C W−1 These proteinaceous microstructures represent therefore a promising platform for future applications in the fields like physical stimulation of cells for regenerative nanomedicine.

Stimulated Raman scattering (SRS) allows chemical identification of substances based on their third-order nonlinear vibrational susceptibility χ(3)(ω). In its standard single-frequency implementation, SRS can only access the imaginary part of χ(3)(ω). Here we introduce interferometric SRS (iSRS), which has the capability to measure both the real and the imaginary parts of the nonlinear susceptibility. With respect to a standard SRS setup, iSRS simply requires the insertion of a few optical elements in the Stokes(pump) beam pathway to generate an intrinsically phase-coherent local oscillator. While preserving the acquisition speed and the simplicity of single-frequency SRS, iSRS considerably increases its information content by providing access to the vibrational phase, which allows one to distinguish overlapping species in congested spectra and is more robust with respect to noise.

We report a novel transient absorption microscope based on a tailor-made femtosecond fiber laser system operating at 250 kHz. The setup is applied to study PtOEP crystals embedded in a PBMA polymer matrix by analyzing the excited state dynamics in specific points of the sample as well as by spatially resolved excited state dynamics of the crystals. The results reveal the impact of the distortions of the crystal lattice, such as microcracks or amorphous regions caused by non-thermal melting on a lifetime of the excited triplet states of PtOEP crystals. Although transient absorption studies without any spatial resolution of PtOEP in solution and thin films were reported before, the study of spatially resolved excited state dynamics of micrometer-sized PtOEP crystals is performed for the first time to the best of our knowledge.

This article reviews the state of the art of ultrafast transient absorption microscopy, discusses current experimental concepts and highlights future challenges. The advantages of transient absorption microscopy over other micro-spectroscopic techniques are its high optical resolution combined with high temporal resolution as well as its ability to study non-fluorescent and weakly fluorescent molecular species and to probe excited-state processes. In conventional transient absorption spectroscopy the spectroscopic information usually presents a spatial average over the focal spot of the typically weakly focused probe beam. Transient absorption microscopy, however, enables investigations of the excited state dynamics in individual microscopic areas of a sample. Hence, the technique does not only yield detailed morphological information based on a label-free molecular contrast, but also gives insight into the ultrafast morphology-dependent photoinduced processes in heterogeneous samples. Different variations of transient absorption microscopy have found a number of applications ranging from material sciences to biology, which are discussed in this review together with different setup modifications and approaches towards transient absorption spectroscopy with spatial resolution below the diffraction limit.

Interstitial Photodynamic Therapy (IPDT) is a promising form of treatment of deep-seated and bulky malignant tumors, based on the lethal cell response to the photochemical reactions when drug is light activated at presence of oxygen. After intravenous administration, the drug is retained selectively by malignant cells, and then, the light is delivered to the target tissue through multiple optical fibers. In order to accomplish an effective internal illumination, laser sources are preferably used because of two important reasons: the laser beam is easily focused to optical fibers, and the monochromatic light can be confined to the narrow absorption band of the drug. In this work we present the design of an irradiation laser system, which involves a 635nm laser diode and a delivering fiber system, for 5-ALA mediated IPDT.

An in cellulo study of the ultrafast excited state processes in the paradigm molecular light switch [Ru(bpy)2dppz]2+ by localized pump-probe spectroscopy is reported for the first time. The localization of [Ru(bpy)2dppz]2+ in HepG2 cells is verified by emission microscopy and the characteristic photoinduced picosecond dynamics of the molecular light switch is observed in cellulo. The observation of the typical phosphorescence stemming from a 3MLCT state suggests that the [Ru(bpy)2dppz]2+ complex intercalates with the DNA in the nucleus. The results presented for this benchmark coordination compound reveal the necessity to study the photoinduced processes in coordination compounds for intracellular use, e.g. as sensors or as photodrugs, in the actual biological target environment in order to derive a detailed molecular mechanistic understanding of the excited-state properties of the systems in the actual biological target environment.

Coherent Raman scattering (CRS) is a powerful label-free spectroscopic technique that allows fingerprinting of molecules based on their intrinsic vibrational response. The vibrational transitions can be described using Lorentzian functions, whose superposition gives rise to a complex third-order resonant nonlinear susceptibility χ(3) R (ω). Its direct experimental access would allow a very rich spectroscopic information, especially in the presence of mixtures of molecular species. Unfortunately, standard CRS techniques do not allow to fully extract it: stimulated Raman scattering (SRS) only measures the imaginary part of the nonlinear susceptibility, while coherent anti-Stokes Raman scattering (CARS) retrieves a mixture of real and imaginary parts, as the signal is proportional to |χ(3) R (ω)+χ(3) NR (ω)|2, where χ(3) NR (ω) is a real, frequency-independent non-resonant term.

Broadband Coherent Anti-Stokes Raman Scattering (B-CARS) is a powerful label-free nonlinear spectroscopy technique allowing one to measure the full vibrational spectrum of molecules and solids. B-CARS spectra, however, suffer from the presence of a spurious signal, called non-resonant background (NRB), which interferes with the resonant vibrational one, distorting the line shapes and degrading the chemical information. While several numerical techniques are available to remove this unwanted contribution and extract the resonant vibrational signal of interest, they all require the user’s intervention and sensitively depend on the spectral shape of the NRB, which needs to be measured independently. In this work, we present a novel approach to remove NRB from B-CARS spectra based on deep learning. Thanks to the high generalization capability offered by the deep architecture of the designed neural network, trained through realistic simulated spectra, our fully automated model is able to process B-CARS spectra in real time and independently of the detailed shape of the NRB spectrum. This results in fast extraction of vibrational spectra without requiring user intervention or the measurement of reference spectra. We expect that this model will significantly simplify and speed-up the analysis of B-CARS spectra in spectroscopy and microscopy.