High-resolution Structural Imaging Research Articles

Abstract 24: Iron deposition changes of ipsilateral ventral posterolateral nuclei correlate with central post-stroke pain after thalamic infarction

Objectives: To investigate the correlation between iron deposition changes in the lesioned thalamic nuclei and the presence and severity of central post-stroke pain (CPSP) after thalamic infarction using quantitative susceptibility mapping (QSM) technique. Methods: We consecutively enrolled patients with unilateral chronic thalamic infarction with radiological examination conformed . Detailed and multidimensional pain characteristics measured as follows: Douleur Neuropathique 4 (DN4) questionnaire for validation of neuropathic pain diagnosis, Short-Form McGill Pain Questionnaire (SF-MPQ) for comprehensive representation of pain experience, Present Pain Intensity index (PPI) for current pain severity upon examination, and Visual Analogue Scale (VAS) for overall pain feeling since symptom onset. Age- and sex-matched stoke-free healthy controls were recruited simultaneously. High resolution structural image 3D-T1 BRAVO and QSM sequences were obtained with 3.0T MRI. The voxel-lesion-symptom-mapping (VLSM) was used to determine lesioned thalamic nuclei at the high risk for CPSP. Then ipsilateral QSM values of the whole thalamus and subregions were compared with contralateral side and healthy controls. Partial correlation analysis were performed to explore the relationship between QSM value and pain severity. Results: Finally, 28 CPSP patients, 33 non-CPSP patients and 55 healthy controls were included in the study. Our results indicated no significant difference in overall QSM values of the whole thalamus among the groups. The VLSM results showed lesion involving ventral posterolateral nuclei (VPL) was highly orrelaed with occurance of CPSP ( p FWE =0.0092.). The QSM values of each subnuclei in the thalamus ipsilateral to infarction were lower compared with the contralateral side and healthy controls ( p <0.001). Nonetheless, the QSM values in ipsilateral VPL were higher in CPSP patients campared with non-CPSP patients( p =0.003). Notably, the QSM values in the ipsilateral VPL were significantly correlated to pain severity (all p <0.05). Conclusions: The study showed that altered iron deposition in the VPL nuclei is associated with the occurrence and severity of CPSP following thalamic infarction. Aberrant iron deposition after ischemic thalamus stroke may play an important role in the pathogenesis of CPSP. Key words: Thalamic infarction; Central post-stoke pain; Iron deposition; VLSM; Quantitative susceptibility mapping

Weighted multichannel singular spectrum analysis for diffraction amplitude preservation

Diffractions generated by the wavefield response of small-scale discontinuous geological bodies carry a wealth of information regarding complex geological structures, which can be used for high-resolution imaging. However, the weak amplitudes of diffractions make them vulnerable to strong reflections. Thus, separating diffractions from strong reflections is crucial in the high-resolution imaging of underground structures. The low-rank (LR) characteristics of seismic wavefields enable LR methods to be used for diffraction extraction. However, traditional low-rank algorithms tend to disrupt the dynamic characteristics of diffraction during the separation process, which is detrimental to the subsequent high-precision imaging of diffractions. To address these shortcomings of traditional methods, we propose a weighted multichannel singular spectrum analysis (MSSA) algorithm designed to preserve the dynamic characteristics of diffractions. This algorithm fully considers the distribution characteristics of diffractions and reflections energies within the singular spectrum and redefines the singular values using a weighted approach, ultimately achieving amplitude-preserving separation of diffracted waves. Through a combined qualitative and quantitative analysis of synthetic and field examples, we demonstrate the effectiveness of this method in separating diffractions and suppressing reflections with robustness and high stability. Compared with the traditional MSSA method, the proposed approach can provide better high-precision imaging results for small-scale geological structures.

White Matter Fiber Bundle Alterations Correlate with Gait and Cognitive Impairments in Parkinson's Disease based on HARDI Data.

The neuroanatomical basis of white matter fiber tracts in gait impairments in individuals suffering from Parkinson's Disease (PD) is unclear. Twenty-four individuals living with PD and 29 Healthy Controls (HCs) were included. For each participant, two-shell High Angular Resolution Diffusion Imaging (HARDI) and high-resolution 3D structural images were acquired using the 3T MRI. Diffusion-weighted data preprocessing was performed using the orientation distribution function to trace the main fiber tracts in PD individuals. Clinical characteristics between the two groups were compared, and the correlation between the FA value and behavioral data was analyzed. Quantitative gait and clinical parameters were recorded in PD at ON and OFF states, respectively. The mean tract-specific FA values of the right Cingulum Cingulate (rCC) were statistically different between the PD group and the HC group (p =0.047). The FA value of 34-58 equidistant nodes in rCC was positively correlated with Mini-Mental State Examination (MMSE) (r=0.527, p=0.024), Berg Balance Scale (BBS)-OFF (r=0.480, p =0.040), and BBS-ON (r=0.528, p =0.024) scores, while it was negatively correlated with the MDS-UPDRS-III-ON score (r=-0.502, p =0.030). Regarding the gait analysis, the FA value was significantly correlated with velocity, cadence, and stride time of the pace and rhythm domains in both 'ON' and 'OFF' states, respectively (p<0.05). This study served as an initial exploration to establish that HARDI sequences could be employed as a robust tool for analyzing microstructural alterations in white matter fiber bundles among PD patients, although the sample size was small. We confirmed microstructural integrity impairment of rCC to be significantly associated with both gait and cognitive deficits in patients with PD. Early detection of microstructural changes in rCC and targeted treatment can help improve behavioral disorders. In the future, we intend to further integrate multimodal data with assessments of patient behavior both prior to and following intervention. We will validate our findings within an independent cohort to monitor disease progression and evaluate the efficacy of therapeutic interventions.

Accurate and fast segmentation of filaments and membranes in micrographs and tomograms with TARDIS.

It is now possible to generate large volumes of high-quality images of biomolecules at near-atomic resolution and in near-native states using cryogenic electron microscopy/electron tomography (Cryo-EM/ET). However, the precise annotation of structures like filaments and membranes remains a major barrier towards applying these methods in high-throughput. To address this, we present TARDIS (Transformer-based Rapid Dimensionless Instance Segmentation), a machine-learning framework for fast and accurate annotation of micrographs and tomograms. TARDIS combines deep learning for semantic segmentation with a novel geometric model for precise instance segmentation of various macromolecules. We develop pre-trained models within TARDIS for segmenting microtubules and membranes, demonstrating high accuracy across multiple modalities and resolutions, enabling segmentation of over 13,000 tomograms from the CZI Cryo-Electron Tomography data portal. As a modular framework, TARDIS can be extended to new structures and imaging modalities with minimal modification. TARDIS is open-source and freely available at https://github.com/SMLC-NYSBC/TARDIS, and accelerates analysis of high-resolution biomolecular structural imaging data.

Non-Invasive Photoacoustic Cerebrovascular Monitoring of Early-Stage Ischemic Strokes In Vivo.

Early-stage stroke monitoring enables timely intervention that is crucial to minimizing neuronal damage and increasing the extent of recovery. By monitoring collateral circulation and neovascularization after ischemic stroke, the natural recovery process can be better understood, optimize further treatment strategies, and improve the prognosis. Photoacoustic computed tomography (PACT), a non-invasive imaging modality that captures multiparametric high-resolution images of vessel structures, is well suited for evaluating cerebrovascular structures and their function. Here 3D multiparametric transcranial PACT is implemented to monitor the early stage of a photothrombotic (PT)-stroke model in living rats. New vessels in the PT-induced region are successfully observed using PACT, and these observations are confirmed by histology. Then, using multiparametric PACT, it is found that the SO2 in the ischemic area decreases while the SO2 in newly formed vessels increases, and the SO2 in the PT region also recovers. These findings demonstrate PACT's remarkable ability to image and monitor cerebrovascular morphologic and physiological changes. They highlight the usefulness of whole-brain PACT as a potentially powerful tool for early diagnosis and therapeutic decision-making in treating ischemic stroke.

Application of Source Independent Full Waveform Inversion to Land Seismic Data: A Case Study of Donggi Field, Indonesia

Abstract Full-waveform inversion (FWI) is a data-fitting process based on seismic full-wavefield modeling that provides high-resolution images of subsurface geological structures from observed field data. However, its applicability to real-world scenarios, particularly in land data, is limited due to several factors. These factors include the lack of modeling of strong surface waves, converted waves, phase dispersion, near-surface weathering layer distortion, and wave phenomena such as attenuation energy and distortion because of complex geology. Additionally, the source wavelet information is often missing for land surveys, and recorded waveforms can vary significantly due to spatially variant shot characteristics such as source charge size, shot depth, and hole pattern, as well as the distortion caused by the near-surface weathering layer. In this study, we address the main challenges of seismic data with a low signal-to-noise ratio and an unknown correct source wavelet. To solve for the unknown source wavelet, we use a source-independent objective function and perform several preprocessing techniques on the seismic input to improve the signal-to-noise ratio without significantly changing the amplitude. We use velocity analysis data as a prior model to reduce the non-linear problem. We demonstrate the effectiveness of our technique by applying it to land seismic data from the Donggi Basin in Indonesia, and our results show that the velocity model improves and has a better correlation with well-log data.

Exploring scanning electrochemical probe microscopy in single-entity analysis in biology: Past, present, and future.

Scanning Electrochemical Probe Microscopy (SEPM) shows significant potential promise for analyzing localized electrochemical activity at biological interfaces of single entities. Utilizing various SEPM probe manipulations allows real-time monitoring of the morphology and physiological activities of single biological entities, offering vital electrochemical insights into biological processes. This review focuses on the application of five SEPM techniques in imaging single biological entities, highlighting their unique advantages in the observation and quantitative evaluation of biological morphology. Specifically, these techniques not only enable high-resolution imaging of single biological structures but also allow for quantitative analysis of their response behavior. Additionally, the integration of Artificial Intelligence (AI) is discussed to improve data processing and image analysis, potentially advancing SEPM technology towards automation. Although still in an early stage, AI integration opens new avenues for deeper single-entity analysis. This review aims to offer an interdisciplinary perspective and encourage advancements in SEPM-based imaging and analytical techniques, contributing to the bioanalytical field.

Optimizing Ultrasound Probe Disinfection for Healthcare-Associated Infection Control: A Comparative Analysis of Disinfectant Efficacy.

Background/Aims: Ultrasound is a key diagnostic tool in modern medicine due to its ability to provide real-time, high-resolution images of the internal structures of the human body. Despite its undeniable advantages, there are challenges related to the contamination of ultrasound probes, with the risk of healthcare-associated infections. The aim of this review was to identify the most effective disinfectants for disinfecting ultrasound probes to prevent the transmission of pathogens between patients. Methods: A narrative review was conducted using the PubMed, CINAHL, Embase, and Cochrane Library databases, resulting in the inclusion of 16 studies from an initial 1202 records. Results: Hydrogen peroxide (H2O2) was the most effective disinfectant, especially in automated systems, achieving a >5-log10 reduction in viral load, including that of resistant pathogens like Human Papillomavirus. Chlorhexidine gluconate (4%) demonstrated strong antibacterial efficacy, eliminating 84.62% of bacterial contamination, but was less effective against viral pathogens. Glutaraldehyde was effective in some cases, though its use carried a higher risk of probe damage. The use of sodium hypochlorite varied across guidelines; some endorsed it for COVID-19 prevention, while others cautioned against its application due to potential probe damage. Conclusions: This study highlights the importance of advanced disinfection technologies and strict adherence to protocols in improving infection control. Automated systems utilizing H2O2 strike an ideal balance between antimicrobial efficacy and equipment preservation. Future research should focus on developing disinfection methods that prioritize safety, cost-effectiveness, and environmental sustainability in various clinical environments.

GLS2 links glutamine metabolism and atherosclerosis by remodeling artery walls.

Metabolic dysregulation, including perturbed glutamine-glutamate homeostasis, is common among patients with cardiovascular diseases, but the underlying mechanisms remain largely unknown. Using the human MESA cohort, here we show that plasma glutamine-glutamate ratio is an independent risk factor for carotid plaque progression. Mice deficient in glutaminase-2 (Gls2), the enzyme that mediates hepatic glutaminolysis, developed accelerated atherosclerosis and susceptibility to catastrophic cardiac events, while Gls2 overexpression partially protected from disease progression. High-throughput transcriptional profiling and high-resolution structural biology imaging of aortas showed that Gls2 deficiency perturbed extracellular matrix composition and increased vessel stiffness. This results from an imbalance of glutamine- and glutamate-dependent cross-linked proteins within atherosclerotic lesions and cellular remodeling of plaques. Thus, hepatic glutaminolysis functions as a potent regulator of glutamine homeostasis, which affects the aortic wall structure during atherosclerotic plaque progression.

Changes in choroidal thickness quantified by Optical Coherence Tomography across cognitive impairment: data from the NORFACE cohort

BackgroundOptical coherence tomography (OCT) enables high-resolution imaging of ocular structures in health and disease. Choroid thickness (CT) is a key vascular retinal parameter that can be assessed by OCT and might be relevant in the evaluation of the vascular component of cognitive decline. We aimed to investigate CT changes in a large cohort of individuals cognitive unimpaired (CU), with mild cognitive impairment due to Alzheimer's (MCI-AD), mild cognitive impairment due to cerebrovascular disease (MCI-Va), Alzheimer’s disease dementia (ADD), and vascular dementia (VaD).MethodsClinical, demographical, ophthalmological and OCT data from the Neuro-ophthalmological Research at Fundació ACE (NORFACE) project were analyzed. CT was assessed in the macula across nine Early Treatment Diabetic Retinopathy Study (ETDRS) quadrants, average thickness, total volume, and subfoveal choroidal thickness. Differences of CT among the five diagnostic groups were assessed in a multivariate regression model, adjusting for demographic and cardiovascular risk factors and OCT image quality. A comparison between manual and automatic CT measurements in a subset of participants was also performed.ResultsThe study cohort comprised 1,280 participants: 301 CU, 196 MCI-AD, 112 MCI-Va, 578 ADD, and 93 VaD. CT was significantly increased in individuals with cognitive impairment compared to those CU, particularly in the VaD and MCI-Va groups and in the peripheral ETDRS regions. No significant differences were found in inner superior, center and subfoveal choroidal thickness. The interaction of sex and diagnosis had no effect in differentiating CT. Mini-Mental State Examination (MMSE) scores were not correlated to CT. Manual and automated CT measurements showed good reliability.DiscussionOur findings indicated that peripheral choroidal thickening, especially in patients with cerebrovascular disease, may serve as a potential choroidal biomarker for cognitive decline and suggest different pathogenic pathways in AD and VaD. Further research is required to explore CT as a reliable ocular biomarker for cognitive impairment.

Alterations of gray matter asymmetry in internet gaming disorder

Structural asymmetry is a subtle but pervasive property of the human brain, which has been found altered in various psychiatric and neurocognitive disorders. However, little is known regarding potential alterations of structural asymmetry underlying internet gaming disorder (IGD). Therefore, this study aimed to investigate the structural features of gray matter asymmetry in IGD. High-resolution structural magnetic resonance imaging data were collected from 104 individuals with IGD and 104 recreational game users (RGUs). We applied a whole-brain voxel-based asymmetry (VBA) approach to determine the asymmetrical aberrations of gray matter in relation to IGD. Furthermore, the local abnormalities of structural asymmetry were employed as features to examine the effect of classification using a support vector machine (SVM). The results indicated that individuals with IGD as compared to RGUs showed asymmetrical alterations of gray matter in the medial prefrontal cortex (mPFC), orbitofrontal cortex, precuneus, middle temporal gyrus, superior parietal lobule and inferior temporal gyrus, regions implicated in hedonic motivation, self-reflection, information integration and visuospatial attention processing. Moreover, these atypical asymmetrical features can distinguish IGD subjects from RGUs with high accuracy. These results suggested that disrupted structural asymmetry of motivational reward, visuospatial and default mode circuits might be potential biomarkers for identifying pathological gaming dependence. These findings extended our understanding of structural underpinnings of IGD and provided new insights for developing effective interventions to alleviate compulsive gaming usage.

High-Resolution Total Internal Reflection-Based Structural Coloration by Electrohydrodynamic Jet Printing of Transparent Polyethylene Glycol Microdomes.

Total internal reflection (TIR)-based structural coloration is a brilliant strategy to overcome the need for periodic nanostructures and complex fabrication processes. Light entering the microdome structure undergoes TIR, and owing to varying reflection paths, it exhibits a color that changes with the microdome size. Although solution-based printing techniques have been proposed to achieve this effect, they fall short of full-color realization owing to resolution limitations. Herein, we achieved 3628 dpi of full-color and high-resolution structural color images by printing transparent microdome structures with 1.2-9.9 μm diameter using electrohydrodynamic (EHD) jet printing. Additionally, high-resolution EHD jet-printed structural color images display complex encoded information, enhancing the anticounterfeiting effectiveness through their fabrication simplicity and precise control over the microdome size. Because of these advantages, this TIR-based structural coloration technique with EHD jet printing is highly suitable for anticounterfeiting applications.

Deep Learning-Based Pediatric Brain Region Segmentation and Volumetric Analysis for General Growth Pattern in Healthy Children.

To establish a quantitative reference for brain structural changes in children with neurological disorders, we employed deep learning technique to brain region segmentation and volumetric analysis within a cohort of healthy children. In this study, we recruited 312 participants aged 1.5 to 14.5years (210 boys and 102 girls), dividing them into five age groups. High-resolution structural T1-weighted images were obtained, and an established toolkit utilizing deep learning algorithms was employed for brain region segmentation. For each age group, the volumes of gray matter and white matter, along with the thickness and surface area of the cortex, were calculated and compared between boys and girls. The results indicated that the volumes of gray matter and white matter in both bilateral cerebral hemispheres, as well as the total brain volume, increased with age. Furthermore, the volumes of the left and right hippocampus, amygdala, and thalamus also demonstrated an increase as age progressed. Conversely, cortical thickness and surface area decreased with age. Our findings provide a quantitative reference for understanding brain structural changes in children with neurological disorders.

Analytical solutions of ray-tracing equations in generalized elliptical anisotropy

Ray-tracing in anisotropic media is pivotal for interpreting observed seismic data and creating high-resolution images of subsurface structures, which are crucial in exploration geophysics. Elliptical anisotropy, a simplified model that approximates a transversely isotropic medium, is particularly relevant for geologic settings such as shale formations or stressed sedimentary layers where directional dependencies of seismic velocities are pronounced. We develop an analytical solution of the ray-tracing equations for a 2D inhomogeneous and anisotropic medium, where velocities depend elliptically on direction and increase linearly with depth — a scenario frequently encountered in stratified geologic formations. Unlike previous studies that assume constant ellipticity throughout the medium, our approach allows for variations in ellipticity, providing a more flexible and realistic representation of subsurface anisotropy. The phase velocities along the x- and z-axes are not necessarily multiples of each other at every point, offering a generalized version of the elliptical anisotropy. This enhancement may enable more accurate predictions and interpretations of observed seismic data, particularly in complex exploration scenarios. The analytical solution yields expressions for the ray paths and the wavefront normals. By setting the normals of the wavefront at the seismic source point and the location of the seismic source as the initial conditions in phase space, we explore the evolution of these wavefront normal curves across different types of the elliptical anisotropy. Our innovative approach includes plotting the evolution of wavefront normal curves on the generalized momentum coordinate plane of the phase space — that commonly overlooked in traditional models focused only on position coordinates.

Expanding Insights: Harnessing Expansion Microscopy for Super-Resolution Analysis of HIV-1–Cell Interactions

Expansion microscopy has recently emerged as an alternative technique for achieving high-resolution imaging of biological structures. Improvements in resolution are achieved by physically expanding samples through embedding in a swellable hydrogel before microscopy. However, expansion microscopy has been rarely used in the field of virology. Here, we evaluate and characterize the ultrastructure expansion microscopy (U-ExM) protocol, which facilitates approximately four-fold sample expansion, enabling the visualization of different post-entry stages of the HIV-1 life cycle, focusing on nuclear events. Our findings demonstrate that U-ExM provides robust sample expansion and preservation across different cell types, including cell-culture-adapted and primary CD4+ T-cells as well as monocyte-derived macrophages, which are known HIV-1 reservoirs. Notably, cellular targets such as nuclear bodies and the chromatin landscape remain well preserved after expansion, allowing for detailed investigation of HIV-1–cell interactions at high resolution. Our data indicate that morphologically distinct HIV-1 capsid assemblies can be differentiated within the nuclei of infected cells and that U-ExM enables detection of targets that are masked in commonly used immunofluorescence protocols. In conclusion, we advocate for U-ExM as a valuable new tool for studying virus–host interactions with enhanced spatial resolution.

Innovative sample preparation using alcohol dehydration and high refractive index medium enables acquisition of two-channel super-resolution 3D STED image of an entire oocyte.

Super-resolution (SR) microscopy is a cutting-edge method that can provide detailed structural information with high resolution. However, the thickness of the specimen has been a major limitation for SR methods, and large biological structures have posed a challenge. To overcome this, the key step is to optimise sample preparation to ensure optical homogeneity and clarity, which can enhance the capabilities of SR methods for the acquisition of thicker structures. Oocytes are the largest cells in the mammalian body and are crucial objects in reproductive biology. They are especially useful for studying membrane proteins. However, oocytes are extremely fragile and sensitive to mechanical manipulation and osmotic shocks, making sample preparation a critical and challenging step. We present an innovative, simple and sensitive approach to oocyte sample preparation for 3D STED acquisition. This involves alcohol dehydration and mounting into a high refractive index medium. This extended preparation procedure allowed us to successfully obtain a unique two-channel 3D STED SR image of an entire mouse oocyte. By optimising sample preparation, it is possible to overcome current limitations of SR methods and obtain high-resolution images of large biological structures, such as oocytes, in order to study fundamental biological processes. Lay Abstract: Super-resolution (SR) microscopy is a cutting-edge tool that allows scientists to view incredibly fine details in biological samples. However, it struggles with larger, thicker specimens, as they need to be optically clear and uniform for the best imaging results. In this study, we refined the sample preparation process to make it more suitable for SR microscopy. Our method includes carefully dehydrating biological samples with alcohol and then transferring them into a mounting medium that enhances optical clarity. This improved protocol enables high-resolution imaging of thick biological structures, which was previously challenging. By optimizing this preparation method, we hope to expand the use of SR microscopy for studying large biological samples, helping scientists better understand complex biological structures.

Design and Verification of a Versatile and Lightweight Radar Platform for High-Resolution Imaging of Glacial Subsurface Structures

Design and Verification of a Versatile and Lightweight Radar Platform for High-Resolution Imaging of Glacial Subsurface Structures

Beyond IQ: executive function deficits and their relation to functional, clinical, and neuroimaging outcomes in 3q29 deletion syndrome.

3q29 deletion syndrome (3q29del) is a rare (~1:30 000) genomic disorder associated with a wide array of neurodevelopmental and psychiatric phenotypes. Prior work by our team identified clinically significant executive function (EF) deficits in 47% of individuals with 3q29del; however, the nuances of EF in this population have not been described. We used the Behavior Rating Inventory of Executive Function (BRIEF) to perform the first in-depth assessment of real-world EF in a cohort of 32 individuals with 3q29del (62.5% male, mean age = 14.5 ± 8.3 years). All participants were also evaluated with gold-standard neuropsychiatric and cognitive assessments. High-resolution structural magnetic resonance imaging was performed on a subset of participants (n = 24). We found global deficits in EF; individuals with 3q29del scored higher than the population mean on the BRIEF global executive composite (GEC) and all subscales. In total, 81.3% of study subjects (n = 26) scored in the clinical range on at least one BRIEF subscale. BRIEF GEC T scores were higher among 3q29del participants with a diagnosis of attention deficit/hyperactivity disorder (ADHD), and BRIEF GEC T scores were associated with schizophrenia spectrum symptoms as measured by the Structured Interview for Psychosis-Risk Syndromes. BRIEF GEC T scores were not associated with cognitive ability. The BRIEF-2 ADHD form accurately (sensitivity = 86.7%) classified individuals with 3q29del based on ADHD diagnosis status. BRIEF GEC T scores were correlated with cerebellar white matter and subregional cerebellar cortex volumes. Together, these data expand our understanding of the phenotypic spectrum of 3q29del and identify EF as a core feature linked to both psychiatric and neuroanatomical features of the syndrome.

Recent advances in label-free imaging techniques based on nonlinear optical microscopy to reveal the heterogeneity of the tumor microenvironment.

The tumor microenvironment (TME) is a complex and dynamic network that significantly influences cancer progression. Understanding its intricate components, including the extracellular matrix (ECM), stromal cells, immune cells, and vascular endothelial cells, is crucial for developing effective cancer therapies. Conventional diagnostic methods, while essential, have limitations in sensitivity, specificity, and invasiveness. Label-free multimodal nonlinear optical (MNLO) microscopy offers a promising alternative, enabling detailed imaging without external labels. Techniques such as second harmonic generation (SHG), third harmonic generation (THG), coherent anti-Stokes Raman scattering (CARS), and two-photon fluorescence (TPF) provide complementary insights into the TME. SHG is particularly effective for imaging collagen fibers, while CARS highlights lipid-rich structures, and THG and TPF offer high-resolution imaging of cellular and subcellular structures. These modalities reveal crucial information about tumor progression, including changes in collagen organization and lipid metabolism, and allow for the study of cellular interactions and ECM remodeling. Multimodal setups, combining SHG, CARS, THG, and TPF, enable comprehensive analysis of the TME, facilitating the identification of early-stage cancerous changes and tracking of tumor progression. Despite the advantages of MNLO microscopy, such as reduced photodamage and the ability to image live tissues, challenges remain, including the complexity and cost of the setups. Addressing these challenges through technological advancements and optimization can enhance the applicability of MNLO microscopy in clinical diagnostics and cancer research, ultimately contributing to improved cancer diagnosis, prognosis, and treatment strategies.

Optimized expansion microscopy reveals species-specific spindle microtubule organization in Xenopus egg extracts.

The spindle is a key structure in cell division as it orchestrates the accurate segregation of genetic material. While its assembly and function are well-studied, the mechanisms regulating spindle architecture remain elusive. In this study, we investigate the differences in spindle organization between Xenopus laevis and Xenopus tropicalis, leveraging expansion microscopy (ExM) to overcome the limitations of conventional imaging techniques. We optimized an ExM protocol tailored for Xenopus egg extract spindles, improving upon fixation, denaturation and gelation methods to achieve higher resolution imaging of spindles. Our protocol preserves spindle integrity and allows effective pre-expansion immunofluorescence. This method enabled detailed analysis of the differences in microtubule organization between the two species. X. laevis spindles overall exhibited a broader range of bundle sizes, while X. tropicalis spindles contained mostly smaller bundles. Moreover, while both species exhibited larger bundle sizes near and at the spindle center, X. tropicalis spindles otherwise consisted of very small bundles, and X. laevis spindles medium-sized bundles. By enhancing resolution and minimizing distortions and fixation artifacts, our optimized ExM approach offers new insights into spindle morphology and provides a robust tool for studying the structural intricacies of these large cellular assemblies. This work advances our understanding of spindle architecture and opens up new avenues for exploring underlying mechanisms.