ACS Photonics

Temperature is a fundamental parameter governing all molecular processes, including those that define life. Fluorescence microscopy is a powerful tool to observe molecular processes in living systems in real time. Precise control and measurement of temperature during fluorescence microscopy is therefore essential. We present here a robust temperature measurement based on the excited-state lifetime of the widely available and relatively inexpensive fluorescent dye pentamethine cyanine (Cy5). The excited-state lifetime of Cy5 shows a monotonic decline in the measurement range of 0 {degrees}C - 80 {degrees}C. The measured dependency is linear until 39 {degrees}C and monoexponential above. The dependance of excited-state lifetime upon temperature is used to measure temperature up to a precision of 0.5 {degrees}C or less, a temporal resolution down to <1 millisecond and to resolve temperature gradients with spatial resolutions that are only diffraction-limited. The far-red excitation and emission of Cy5 leaves bandwidth to simultaneously measure at least 3 additional spectral channels in standard fluorescent microscopes simultaneously. We demonstrate determination of temperature during 4-color live-cell fluorescence microscopy for a temperature-controlled experiment. We also show its applicability in measuring temperature gradients and laser-induced sample heating such as during STED nanoscopy.

Light-sheet fluorescence microscopy (LSFM) has revolutionized biological imaging by enabling high spatial and temporal resolution with minimal photodamage. However, conventional LSFM techniques often suffer from striping artifacts in the resulting images due to light scattering and absorption within samples, leading to uneven illumination that negatively impacts the accuracy of subsequent image analyses. To address this limitation, we introduce dodecagon light-sheet fluorescence microscopy (dodecaLSFM), a novel approach that maximizes angular diversity to achieve homogeneous illumination and suppress striping artifacts. dodecaLSFM employs diffraction optics and cylindrical lenses to generate twelve light sheets, providing 360 degree omnidirectional illumination that significantly enhances illumination uniformity compared to traditional mSPIM, mDSLM, and ultramicroscopy systems, which use only one or two illumination planes. We demonstrate the effectiveness of dodecaLSFM by achieving high-resolution imaging of whole mouse brain vasculature following tissue clearing, allowing precise morphometric analysis of vascular networks without striping artifacts. Furthermore, we show that combining dodecaLSFM with expansion microscopy (ExM) enables whole-organ 3D imaging at cellular resolution. This novel approach provides an advanced, scalable solution for large-volume imaging, facilitating detailed structural and functional studies across diverse biological applications.

Fluorescence lifetime imaging microscopy (FLIM) provides molecular contrast that is largely independent of fluorophore concentration, yet it remains constrained by a persistent trade-off among acquisition speed, photon dose, and detector complexity. To address this challenge, we developed image-projection fluorescence lifetime imaging microscopy (IP-FLIM), an integrated optical and computational platform that enables high-resolution, component-resolved lifetime imaging using only a linear single-photon avalanche diode array. We validate IP-FLIM using fluorescent microbeads and bovine pulmonary artery endothelial cells, demonstrating up to 22.3x improvement in contrast-to-noise ratio and 72.3% reduction in background noise over conventional filtered back-projection reconstruction. By combining wide-field projection acquisition with computational k-space reconstruction, IP-FLIM provides a scalable route to fast, high-resolution multiplex lifetime imaging.

Spectroscopic single-molecule localization microscopy (sSMLM) enables multiplexed super-resolution imaging by simultaneously acquiring the spatial position and spectral information of individual fluorophores. Dual-wedge prism (DWP)-based implementations provide a compact, alignment-stable approach to spectral dispersion, but trade-offs between localization precision, spectral precision, and experimental complexity remain. We systematically compare five DWP-based sSMLM configurations, including two-dimensional (2D) and three-dimensional (3D) implementations using single DWP (DWP-sSMLM) and symmetrically-dispersed DWP (SDDWP-sSMLM). We evaluate lateral precision, spectral precision, and ease of use. SDDWP configurations acquire spectral images in both channels and utilize both for spatial localization, yielding the highest lateral and spectral precision. However, for applications that do not require axial information, 2D-DWP provides a simple, plug-and-play solution with robust performance. This work offers a guideline for selecting DWP configurations based on experimental needs.

Optogenetics enables experiments in out-of-equilibrium conditions to clarify biological mechanisms and quantify biophysical parameters. However, modelling and control techniques to study mammalian cell biology under optogenetic perturbation remain underutilised. Here, we benchmark these methods within mammalian cells by steering nucleocytoplasmic transport via the optogenetic LEXY protein in outcome-driven microscopy. First, we employ system identification to obtain models that predict transport dynamics by minimising the prediction error. We quantify this prediction accuracy for one biophysical model and two black-box models. Second, we evaluate closed-loop control efficacy by steering transport along a predefined trajectory using model-free Proportional Integral (PI) control, model-based Linear Quadratic Regulation (LQR) and Model Predictive Control (MPC). Both the predictive models and the applied control techniques demonstrate robust performance against cell-to-cell variation. This biological variation is quantified by the parameter distributions obtained from model identification with single-cell trajectories. While we show that model-free techniques such as PI and gain-scheduled PI achieve steering without explict model knowledge, predictive architectures offer better performance under this cell-to-cell variation and time-varying setpoints. Moreover, black-box predictive accuracy suggests that this model-based control is possible, even when explicit mechanistic understanding is missing. Ultimately, we demonstrate that predictive modelling and optogenetics enable quantitative characterisation and precise manipulation of mammalian cells, while offering practical guidelines for the implementation of these techniques.

The lifetime of fluorescent molecules provides an orthogonal readout to fluorescence intensity, opening experimental possibilities of measuring changes in local molecular environments, mechanical tension, and metabolism, among other factors. These changes are best studied live and in vivo; however, limitations of slow imaging speeds, high phototoxicity, and increased data size and complexity have significantly impeded progress on this front. Here, we present a complete and transferable pipeline consisting of a light sheet FLIM microscope and an accompanying machine learning model for data processing that renders long-term and/or high-speed volumetric FLIM (vFLIM) tractable in living systems. We benchmark this pipeline across several biological use cases, model systems, lifetime ranges, and spatiotemporal scales, showcasing a suite of possibilities that our workflow enables. This comprehensive pipeline from imaging to analysis is a crucial step forward towards disseminating the power of live vFLIM to the broader bioimaging community.

Cellular metabolic activities can be studied using label-free vibrational spectroscopic imaging to leverage the endogenous contrast of biomolecules. However, fast live-cell imaging over large fields-of-view remains challenging due to the need for raster scanning and despite advances in wide-field modalities, imaging rapid cellular activities across large cell populations remains challenging. Here, we introduce a mid-infrared optothermal microscopy method termed Instantaneous Phase-Shifting Optothermal Microscopy (IPSOM). IPSOM circumvents conventional mechanical phase-shifting methods, achieved single-frame imaging speed 588-fold increase compared to the sequential approach, under field-of-view of 300x350 {micro}m. For multi-wavelength hyperspectral imaging, IPSOM achieves an 8-fold speed improvement. IPSOM is used here to monitor lipid remodelling in adipocytes during lipolysis, demonstrating its potential for studying rapid cellular metabolism.

This study reports a brand-new continuous-wave-excited (CW-excited) two-photon fluorescence emission mechanism in indocyanine green (ICG), an organic fluorescent dye widely used in clinical practice. This mechanism is based on the excited state absorption (ESA) process of the first singlet excited state. Intramolecular electrons sequentially absorb two photons to reach a high-energy singlet excited state, followed by direct radiative transition to the ground state to generate fluorescence. The entire process is exclusively mediated by singlet states. We further summarize the essential requirements for organic dyes to realize this luminescence mechanism. First, the dye must possess at least two well-separated singlet excited states with distinct energies, corresponding to two absorption peaks at different wavelengths in the absorption spectrum. The wavelength of the high-energy singlet excited state is about half that of the first singlet excited state. Second, the peak in the absorption spectrum corresponding to the transition from the ground state to the first singlet excited state has a sufficiently large molar extinction coefficient. Third, the first singlet excited state exhibits the capability of ESA. Fourth, electrons at the high-energy singlet excited state can directly transit to the ground state and emit fluorescence. We validated this mechanism in a variety of organic dyes satisfying the above conditions, confirming its universality. Using CW laser as the excitation source, we achieved two-photon fluorescence imaging of mouse cerebral blood vessels at a depth of 400 m, which clearly resolves three-dimensional vascular networks with high resolution. We also performed two-photon fluorescence imaging on human gastric cancer tissue samples at a depth of around 150 m, which provides a low-cost strategy for clinicians to rapidly acquire high-contrast tumor tissue images.

Three-photon microscopy enables deep-tissue imaging but is highly sensitive to excitation pulse quality, since three-photon excitation efficiency scales with the cube of instantaneous intensity. Group-delay dispersion (GDD) and third-order dispersion (TOD) accumulated through the laser and microscope optics can substantially reduce peak intensity at the focal plane, yet these quantities are rarely measured where imaging occurs. Here, we use third-harmonic generation (THG) interferometric autocorrelation, together with Dispersion Look-Up-Table Estimation (D-LUTE) and a joint two-measurement fitting procedure validated on synthetic data, to estimate baseline GDD and TOD directly at the objective focal plane, requiring only a compact autocorrelator module added to the microscope beam path. Applying this method at 1300 nm and 1600 nm excitation across two microscope systems equipped with different units of the same laser model, we find pulse durations 1.4- to 1.7-fold longer than the transform limit at every condition, driven predominantly by TOD, which varied by roughly 2.7-fold between the two systems. Using the endogenous THG signal from myelinated fibers, we further demonstrate in vivo pulse characterization in the mouse brain, finding no measurable broadening between the tissue surface and a depth of nearly a millimeter. This low-cost, easily implemented approach enables routine, in situ pulse monitoring across multiphoton microscopy platforms.

Coherent structured illumination microscopy (c-SIM) is a synthetic aperture optical technique for sub-diffraction limit imaging that extends the utility of traditional SIM to non-fluorescent samples. Here, we present a complementary 5-beam implementation of c-SIM that provides enhanced optical sectioning compared to conventional quadrupolar illumination. Since our approach detects intensity images due to coherent light scattering, it avoids the complications associated with detecting complex fields. Through comparative measurements on calibration samples and live microalgae, we show that 5-beam c-SIM effectively suppresses coherent defocus effects, improving image quality while simultaneously providing a 2-fold lateral resolution improvement.

High-speed three-dimensional imaging in scattering tissues remains challenging because volumetric microscopy generally requires scanning, whereas snapshot light-field approaches divide limited detector pixels among multiple views. This constraint is particularly severe in the second near-infrared window (NIR-II), where commonly used InGaAs cameras typically have relatively small sensor formats and high detector noise. Here we introduce NIR-II squeezed light-field microscopy (NIR-II SLIM), which optically rotates and compresses multiple perspective views before detection, allowing efficient use of camera pixels while retaining complementary spatial information for three-dimensional reconstruction. NIR-II SLIM acquires volumes at up to 600 volumes s-1 with a reconstructed lateral sampling grid of 512 x 512 pixels. We use the method for label-free four-dimensional imaging of cardiac dynamics in pigmented late-larval zebrafish, resolving chamber deformation and millisecond-scale atrioventricular-valve motion, and for NIR-II fluorescence imaging of vascular and lymphatic transport in mice. NIR-II SLIM provides a detector-efficient approach for high-speed volumetric imaging of rapid biological dynamics in scattering tissues.

Optical fluorescence microscopy enables visualization of biological structures and dynamics. However, the intrinsic diffraction limit, especially axially, and depth-related scattering noise compromise the image resolution and fidelity. Computational 3D deconvolution is a promising approach for mitigating these issues, yet its execution is hindered by inaccurate and cumbersome theoretical modeling or experimental measurement of 3D point spread function (PSF), as well as ineffective 3D noise regularization. Furthermore, in the 3D super-resolution regime, there remains a lack of standardized tools for evaluating 3D super-resolution fidelity. Here, we present the 3D adaptive deconvolution and evaluation (3D-ADE) toolkit, which comprises 3D-Ada deconvolution with physics-oriented automatic 3D-PSF calibration, and 3D-SQUIRREL for 3D super-resolution quality assessment. It effectively resolves noise instability, eliminates the need for 3D-PSF calibration, and reliably assesses the fidelity of 3D resolution extension via deconvolution, physical, and deep-learning-based methods. Accessible via multiple software platforms, 3D-ADE enhances the versatility of 3D deconvolution and fills the gap in 3D super-resolution evaluation tools, and thereby advances volumetric fluorescence imaging applications.

Point-spread-function engineering by depth-encoding phase masks enables volumetric super-resolution imaging by 3D single-molecule localization microscopy (SMLM) but usually requires cumbersome relay optics. We demonstrate simple 3D SMLM implementation by phase mask insertion directly into the infinity space of a commercial microscope, along with appropriate computational compensation for field-dependence. The entire inserted component, including the phase mask, is 3D printing-based.

Visual neuroscience requires precise spatiotemporal projection of optical stimulation onto the retina, especially in experimental mouse models. However, in vivo patterned stimulation in mice is profoundly hindered by the extreme optical power and severe anatomical aberrations of the eye. Consequently, visual stimulation relies mainly on unverifiable, open-loop approximations that often lack spatial precision. Here, we introduce a closed-loop, spatially modulated stimulation platform that overcomes these barriers. By integrating a digital micromirror device (DMD) with electronically tunable lenses (ETLs) and a real-time, fundus camera-guided focus optimization module, we directly verify the location of patterned stimuli on the retina while dynamically correcting for chromatic and geometric defocus. This platform delivers quantitatively verified static and dynamic patterned stimuli to the living retina with lateral resolutions as fine as 6.7 {micro}m. Guided by ray-tracing optical analysis, our work establishes a technological foundation that enables highly reproducible, cellular-scale interrogations of the visual pathway.

Deep learning has enabled single-molecule localization microscopy (SMLM) at high emitter densities, but only for single channel systems. Here we present DECODE-Plex, a deep-learning-based framework to localize dense single molecules with overlapping point spread functions simultaneously in multiple channels. We showcase DECODE-Plex on experimental ultra-high density dual-color and 3D live-cell data. Packaged for ease of use, it will enable many groups to improve imaging speed and quality of multi-channel SMLM.

Surface phenotyping underpins plant science, preclinical animal research and entomology, yet across all three the measurement is almost always a photograph, which records a projection and not the surface itself. Here we present the Gentschinator3000, an open structured-light platform that brings high-end metric surface measurement within reach of laboratories with no optics expertise, combining documented open hardware, open reconstruction software and analysis workflows for under 4000 Euro in components. It resolves a planar reference to 45 m local flatness, registers full rotations to a loop closure of 156 m, and performs stably across acquisition ranges that we define. Applying one workflow to a leaf before and after desiccation, to murine anatomy and to a spread lepidopteran, we find that projection underestimates surface area by 11 to 41 %. That error grows with the condition under study, with the evaluation scale and with the direction of view, so it can confound phenotype comparisons dramatically. In murine limbs a 15-degree change of viewing direction shifts a projected inter-segment angle by up to 23.2 degrees, while the three-dimensional angle does not move. Projection geometry can therefore contribute as much to a measured phenotype as the biology it is meant to quantify.

Label-free optical redox imaging utilizes endogenous NAD(P)H and FAD autofluorescence to evaluate metabolism in living specimens. The conventional optical redox ratio collapses these two channels into a single value; however, it does not indicate whether a pixel has sufficient photon support or the cellular context necessary for quantitative aggregation. To address this limitation, we introduce FPhaS, a fixed-calibration phase- autofluorescence framework that integrates quantitative phase imaging (QPI) with simultaneous label-free autofluorescence multi-harmonic microscopy (SLAM), using fluorescence lifetime imaging (FLIM) solely for validation. Because QPI and SLAM are acquired with the same objective, a unified non-biological calibration aligns phase-derived structural data with the autofluorescence frame, yielding a residual error of 0.39 pixels. This calibration is maintained across all biological specimens. This shared geometric reference enables local evaluation of structural and metabolic information, rather than comparing approximately aligned images. FPhaS decomposes the data into cell presence, ratio credibility, and confidence-supported pooling. We validated FPhaS on A549 cells under high and low-photon conditions; the framework is designed to generalize to other cell and tissue types. Confidence-weighted intensity redox estimates were compared with lifetime-derived measurements within mask-locked cellular regions. Concordance improved exclusively when both the denominator photon support and an independent structural criterion were satisfied. The same reference layer generated cell-level descriptors of metabolic content, metabolic-structural organization, and measurement reliability, while also constraining the CombinedWLS reconstruction under diminished fluorescence acquisition. FPhaS redefines label-free metabolic imaging from producing comprehensive ratio maps to identifying regions where optical evidence substantiates quantitative inference.

Temperature regulation in the brain is essential for maintaining neuronal function and preventing thermally induced damage. Here, we report the development and in vivo application of quantum dots (QDs) to high-resolution thermometry in the mouse brain using two-photon excitation microscopy. These QDs, via the red-to-green photoluminescence (PL) intensity ratios, enabled stable temperature measurements in both normal and chronically hypo-perfused cerebral tissue. Our findings show that localized neuronal activity leads to transient heat generation, which is rapidly dissipated by cerebrovascular responses. In a chronic hypoperfusion model, impaired vascular function resulted in exaggerated and prolonged brain temperature elevations. This thermometry system provides unprecedented insight into the mechanisms of cerebral thermoregulation and highlights the importance of vascular cooling in protecting the brain from heat-induced stress, particularly in pathological conditions such as stroke.

Multispectral imaging is a cornerstone of chemical imaging, with bioluminescence, fluorescence, and phosphorescence imaging underpin much of preclinical and analytical chemical measurements. However, conventional implementations are typically proprietary, costly, and resolve spectral content from the reflectance of a broadband source, without control over the excitation spectrum. This architecture cannot isolate excitation-dependent photophysical processes. Spectral discrimination through sequentially resolved narrowband excitation, detected on a single broadband-sensitive camera, instead enables excitation-dependent fluorescence, phosphorescence, and reflectance measurements not available to such broadband approaches. We describe AURORA-MSI, an open-source multispectral platform that inverts this arrangement with fourteen narrowband LEDs spanning 367-940 nm, a 120-element annular illumination ring with eight independently addressable azimuthal sectors, and a thermoelectrically cooled monochrome CMOS camera. Radiometric calibration, spatial uniformity mapping, and camera noise characterization establish the quantitative measurement foundation. In bioluminescence imaging, AURORA-MSI localized sources in a calibrated tissue-mimicking mouse phantom comparably to a commercial Revvity IVIS Spectrum, detected luciferase-expressing HSJD-GBM1-001 glioblastoma cells across a dilution series, with reduced replicate consistency at the lowest densities, and mapped substrate-free fungal-pathway emission in an intact bioluminescent Petunia hybrida, none requiring photon-counting instrumentation. Time-resolved phosphorescence decay imaging of six inorganic phosphors over 33 minutes found tri-exponential models adequate at early times, while distributed-lifetime models were preferred at extended timescales. Multispectral image-texture features extracted across all fourteen excitation bands discriminated ten pharmaceutical and household powders spanning distinct chemical compositions and, in two cases, distinct formulations of the same compound. Generality beyond these regimes was established through dual-excitation fluorescence fingerprinting of fifteen mineral specimens and wavelength-selective plant-tissue imaging exploiting UV and NIR penetration-depth differences. Excitation-side spectral encoding enables photophysical measurements that detection-side systems with uncontrolled broadband illumination cannot isolate, and the cooled-camera architecture supports weak-signal modalities without photon-counting instrumentation.

The sea anemone Aiptasia is a model system for understanding cnidarian loss of symbiotic algae under heat stress (bleaching). While Aiptasia polyps have been widely used to study this process, accurate symbiosis phenotyping grapples with discordant length scales: fine spatial resolution (~100 um) is needed across a whole organism (~5 mm). To address this, we consider small (~100 um), optically transparent Aiptasia larvae as a bleaching model suitable for whole-organism phenotyping by fluorescence microscopy with larvae classified as symbiotic when algae are localized within gastrodermal cells. To expedite phenotyping, we introduce a machine-learning (ML) image-analysis pipeline (SYMPHONY) designed for single-larva resolution analysis of intact larvae. SYMPHONY efficiently identifies the cellular location of internalized algae (accuracy: 79%, precision: 82%, recall: 79%, F1 score: 79%; training dataset composed of 1611 total objects). Additionally, SYMPHONY reports statistically significant larval bleaching under heat stress and corroborates manual phenotyping results, while significantly reducing operator labor from hours to minutes. The combination of the Aiptasia larvae model and the SYMPHONY pipeline aims to accelerate our understanding of symbiosis breakdown.