Second Harmonic Generation Imaging Research Articles

Combined flat-field and frequency filter approach to correcting artifacts of multichannel two-photon microscopy.

Multiphoton microscopy (MPM) is a useful biomedical imaging tool for its ability to probe labeled and unlabeled depth-resolved tissue biomarkers at high resolution. Automated MPM tile scanning allows for whole-slide image acquisition but can suffer from tile-stitching artifacts that prevent accurate quantitative data analysis. We have investigated postprocessing artifact correction methods using ImageJ macros and custom Python code. Quantitative and qualitative comparisons of these methods were made using whole-slide MPM autofluorescence and second-harmonic generation images of human duodenal tissue. Image quality after artifact removal is assessed by evaluating the processed image and its unprocessed counterpart using the root mean square error, structural similarity index, and image histogram measurements. Consideration of both quantitative and qualitative results suggest that a combination of a custom flat-field-based correction and frequency filtering processing step provide improved artifact correction when compared with each method used independently to correct for tiling artifacts of tile-scan MPM images. While some image artifacts remain with these methods, further optimization of these processing steps may result in computational-efficient methods for removing these artifacts that are ubiquitous in large-scale MPM imaging. Removal of these artifacts with retention of the original image information would facilitate the use of this imaging modality in both research and clinical settings, where it is highly useful in collecting detailed morphologic and optical properties of tissue.

Functional Assessment of Human Articular Cartilage Using Second Harmonic Generation (SHG) Imaging: A Feasibility Study.

Many arthroscopic tools developed for knee joint assessment are contact-based, which is challenging for in vivo application in narrow joint spaces. Second harmonic generation (SHG) laser imaging is a non-invasive and non-contact method, thus presenting an attractive alternative. However, the association between SHG-based measures and cartilage quality has not been established systematically. Here, we investigated the feasibility of using image-based measures derived from SHG microscopy for objective evaluation of cartilage quality as assessed by mechanical testing. Human tibial plateaus harvested from nine patients were used. Cartilage mechanical properties were determined using indentation stiffness (Einst) and streaming potential-based quantitative parameters (QP). The correspondence of the cartilage electromechanical properties (Einst and QP) and the image-based measures derived from SHG imaging, tissue thickness and cell viability were evaluated using correlation and logistic regression analyses. The SHG-related parameters included the newly developed volumetric fraction of organised collagenous network (Φcol) and the coefficient of variation of the SHG intensity (CVSHG). We found that Φcol correlated strongly with Einst and QP (ρ = 0.97 and - 0.89, respectively). CVSHG also correlated, albeit weakly, with QP and Einst, (|ρ| = 0.52-0.58). Einst and Φcol were the most sensitive predictors of cartilage quality whereas CVSHG only showed moderate sensitivity. Cell viability and tissue thickness, often used as measures of cartilage health, predicted the cartilage quality poorly. We present a simple, objective, yet effective image-based approach for assessment of cartilage quality. Φcol correlated strongly with electromechanical properties of cartilage and could fuel the continuous development of SHG-based arthroscopy.

Label-free assessment of pathological changes in pancreatic intraepithelial neoplasia by biomedical multiphoton microscopy.

Pancreatic intraepithelial neoplasia (PanIN) is the most common precursor lesion that has the potential to progress to invasive pancreatic cancer, and early and rapid detection may offer patients a chance for treatment before the development of invasive carcinoma. Therefore, the identification of PanIN holds significant clinical importance. In this study, we first used multiphoton microscopy (MPM) combining two-photon excitation fluorescence and second-harmonic generation imaging to label-free detect PanIN and attempted to differentiate between normal pancreatic ducts and different grades of PanIN. Then, we also developed an automatic image processing strategy to extract eight morphological features of collagen fibers from MPM images to quantify the changes in collagen fibers surrounding the ducts. Experimental results demonstrate that the combination of MPM and quantitative information can accurately identify normal pancreatic ducts and different grades of PanIN. This study may contribute to the rapid diagnosis of pancreatic diseases and may lay the foundation for further clinical application of MPM.

In vivo label-free tissue histology through a microstructured imaging window.

Tissue histopathology, based on hematoxylin and eosin (H&E) staining of thin tissue slices, is the gold standard for the evaluation of the immune reaction to the implant of a biomaterial. It is based on lengthy and costly procedures that do not allow longitudinal studies. The use of non-linear excitation microscopy in vivo, largely label-free, has the potential to overcome these limitations. With this purpose, we develop and validate an implantable microstructured device for the non-linear excitation microscopy assessment of the immune reaction to an implanted biomaterial label-free. The microstructured device, shaped as a matrix of regular 3D lattices, is obtained by two-photon laser polymerization. It is subsequently implanted in the chorioallantoic membrane (CAM) of embryonated chicken eggs for 7 days to act as an intrinsic 3D reference frame for cell counting and identification. The histological analysis based on H&E images of the tissue sections sampled around the implanted microstructures is compared to non-linear excitation and confocal images to build a cell atlas that correlates the histological observations to the label-free images. In this way, we can quantify the number of cells recruited in the tissue reconstituted in the microstructures and identify granulocytes on label-free images within and outside the microstructures. Collagen and microvessels are also identified by means of second-harmonic generation and autofluorescence imaging. The analysis indicates that the tissue reaction to implanted microstructures is like the one typical of CAM healing after injury, without a massive foreign body reaction. This opens the path to the use of similar microstructures coupled to a biomaterial, to image in vivo the regenerating interface between a tissue and a biomaterial with label-free non-linear excitation microscopy. This promises to be a transformative approach, alternative to conventional histopathology, for the bioengineering and the validation of biomaterials in in vivo longitudinal studies.

Automated quantitative assay of fibrosis characteristics in tuberculosis granulomas.

Granulomas, the pathological hallmark of Mycobacterium tuberculosis (Mtb) infection, are formed by different cell populations. Across various stages of tuberculosis conditions, most granulomas are classical caseous granulomas. They are composed of a necrotic center surrounded by multilayers of histocytes, with the outermost layer encircled by fibrosis. Although fibrosis characterizes the architecture of granulomas, little is known about the detailed parameters of fibrosis during this process. In this study, samples were collected from patients with tuberculosis (spanning 16 organ types), and Mtb-infected marmosets and fibrotic collagen were characterized by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy using a stain-free, fully automated analysis program. Histopathological examination revealed that most granulomas share common features, including necrosis, solitary and compact structure, and especially the presence of multinuclear giant cells. Masson's trichrome staining showed that different granuloma types have varying degrees of fibrosis. SHG imaging uncovered a higher proportion (4%~13%) of aggregated collagens than of disseminated type collagens (2%~5%) in granulomas from matched tissues. Furthermore, most of the aggregated collagen presented as short and thick clusters (200~620 µm), unlike the long and thick (200~300 µm) disseminated collagens within the matched tissues. Matrix metalloproteinase-9, which is involved in fibrosis and granuloma formation, was strongly expressed in the granulomas in different tissues. Our data illustrated that different tuberculosis granulomas have some degree of fibrosis in which collagen strings are short and thick. Moreover, this study revealed that the SHG imaging program could contribute to uncovering the fibrosis characteristics of tuberculosis granulomas.

Monitoring the response of a model protocell to dye and surfactant molecules through second harmonic generation and fluorescence imaging.

Probing the interaction between molecules and protocells is crucial for understanding the passive transport of functional molecules in and out of artificial and real cells. Second-harmonic generation (SHG) has been proven to be a powerful method for analyzing the adsorption and cross-membrane transport of molecules on lipid bilayers. In this study, we used SHG and two-photon fluorescence (TPF) imaging to study the interaction of charged dye molecules (D289) with a lipid vesicle. Unexpectedly, it was observed that the transport of D289 at a relatively high concentration is not as efficient as that at a lower dye concentration. Periodic shrinking of the model protocell and discharging of D289 out from the vesicle were revealed by combined analyses of SHG and TPF images. The response of the vesicle to a surfactant was also analyzed with D289 as a probe. This work demonstrates that the combined SHG and TPF imaging method is a unique approach that can provide detailed information on the interaction of molecules and lipids (both morphology and molecular kinetics). Determining these subtle interfacial kinetics in molecules is important for understanding the mechanism of many biophysical processes occurring on lipids.

Cervical Collagen Network Porosity Assessed by SHG Endomicroscopy Distinguishes Preterm and Normal Pregnancy - a Pilot Study.

Preterm birth (PTB) remains a pressing global health concern associated with premature cervical ripening and weakened cervical mechanical strength. Second harmonic generation (SHG) microscopy has proved instrumental in tracking progressive changes in cervical collagen morphology during pregnancy. To translate this imaging modality into clinical practice, we have developed a flexible SHG endomicroscope for label-free visualization of cervical collagen architecture. This study aims to assess the feasibility of our SHG endomicroscope for non-invasive differentiation of normal and PTB mouse models, with the ultimate goal of enabling early diagnosis and risk assessment of PTB in vivo. in this pilot investigation, we conducted endomicroscopic SHG imaging on frozen cervical tissue sections and intact cervices resected from both normal pregnant mice and mifepristone-induced PTB mouse models, and then analyzed the acquired images to identify collagen morphology characteristics associated with abnormal cervical collagen remodeling. quantitative image analysis revealed significantly altered collage spatial distribution, larger collagen fiber diameter and pore size, along with reduced pore numbers in SHG endomicroscopy images from PTB mouse models compared to normal pregnant mice. Similar trends were consistent across SHG endomicroscopy images of subepithelial collagen fibers acquired directly from intact cervices. overall, the experiment results underscore the potential of SHG endomicroscopy, coupled with quantitative image analysis, for clinically evaluating cervical collagen remodeling and PTB risk.

Anisotropic charge transport study of highly oriented P4T2F-HD thin film fabricated at air–liquid interface through second harmonic generation (SHG) analysis

Carrier transport anisotropy in highly oriented P4T2F-HD thin films prepared by the UFTM technique was directly visualized using the sophisticated SHG imaging method.

Effect of out of plane orientation on polarization second harmonic generation of single collagen fibrils.

Second harmonic generation (SHG) microscopy has emerged as a powerful technique for visualizing collagen organization within tissues. Amongst the many advantages of SHG is its sensitivity to collagen nanoscale organization, and its presumed sensitivity to the relative out of plane polarity of fibrils. Recent results have shown that circular dichroism SHG (CD-SHG), a technique that has been commonly assumed to reveal the relative out of plane polarity of collagen fibrils, is actually insensitive to changes in fibril polarity. However, results from another research group seem to contradict this conclusion. Both previous results have been based on SHG imaging of collagen fibrils within tissues, therefore, to gain a definitive understanding of the sensitivity of SHG to relative out of plane polarity, the results from individual fibrils are desirable. Here we present polarization resolved SHG microscopy (PSHG) data from individual collagen fibrils oriented out of the image plane by buckling on an elastic substrate. We show through correlation with atomic force microscopy measurements that SHG intensity can be used to estimate the out of plane angle of individual fibrils. We then compare the sensitivity of two PSHG techniques, CD-SHG and polarization-in, polarization-out SHG (PIPO-SHG), to the relative out of plane polarity of individual fibrils. We find that for single fibrils CD-SHG is insensitive to relative out of polarity and we also demonstrate the first direct experimental confirmation that PIPO-SHG reveals the relative out of plane polarity of individual collagen fibrils.

Categorization of collagen type I and II blend hydrogel using multipolarization SHG imaging with ResNet regression

Previously, the discrimination of collagen types I and II was successfully achieved using peptide pitch angle and anisotropic parameter methods. However, these methods require fitting polarization second harmonic generation (SHG) pixel-wise information into generic mathematical models, revealing inconsistencies in categorizing collagen type I and II blend hydrogels. In this study, a ResNet approach based on multipolarization SHG imaging is proposed for the categorization and regression of collagen type I and II blend hydrogels at 0%, 25%, 50%, 75%, and 100% type II, without the need for prior time-consuming model fitting. A ResNet model, pretrained on 18 progressive polarization SHG images at 10° intervals for each percentage, categorizes the five blended collagen hydrogels with a mean absolute error (MAE) of 0.021, while the model pretrained on nonpolarization images exhibited 0.083 MAE. Moreover, the pretrained models can also generally regress the blend hydrogels at 20%, 40%, 60%, and 80% type II. In conclusion, the multipolarization SHG image-based ResNet analysis demonstrates the potential for an automated approach using deep learning to extract valuable information from the collagen matrix.

Mask R-CNN provides efficient and accurate measurement of chondrocyte viability in the label-free assessment of articular cartilage

ObjectiveChondrocyte viability (CV) can be measured with the label-free method using second harmonic generation (SHG) and two-photon excitation autofluorescence (TPAF) imaging. To automate the image processing for the label-free CV measurement, we previously demonstrated a two-step deep-learning method: Step 1 used a U-Net to segment the lacuna area on SHG images; Step 2 used dual CNN networks to count live cells and the total number of cells in extracted cell clusters from TPAF images. This study aims to develop one-step deep learning methods to improve the efficiency of CV measurement. MethodTPAF/SHG images were acquired simultaneously on cartilage samples from rats and pigs using two-photon microscopes and were merged to form RGB color images with red, green, and blue channels assigned to emission bands of oxidized flavoproteins, reduced forms of nicotinamide adenine dinucleotide, and SHG signals, respectively. Based on the Mask R-CNN, we designed a deep learning network and its denoising version using Wiener deconvolution for CV measurement. ResultsUsing training and test datasets from rat and porcine cartilage, we have demonstrated that Mask R-CNN-based networks can segment and classify individual cells with a single-step processing flow. The absolute error (difference between the measured and the ground-truth CV) of the CV measurement using the Mask R-CNN with or without Wiener deconvolution denoising reaches 0.01 or 0.08, respectively; the error of the previous CV networks is 0.18, significantly larger than that of the Mask R-CNN methods. ConclusionsMask R-CNN-based deep-learning networks improve efficiency and accuracy of the label-free CV measurement.

Non-invasive assessment of hair regeneration in androgenetic alopecia mice in vivo using two-photon and second harmonic generation imaging.

The identification of crucial targets for hair regrowth in androgenetic alopecia (AGA) involves determining important characteristics and different stages during the process of hair follicle regeneration. Traditional methods for assessing key features and different stages of hair follicle primarily involve taking skin tissue samples and determining them through various staining or other methods. However, non-invasive assessment methods have been long sought. Therefore, in this study, endogenous fluorescence signals from skin keratin and second harmonic signals from skin collagen fibers were utilized as probes, two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) imaging techniques were employed to non-invasively assess hair shafts and collagen fibers in AGA mice in vivo. The TPEF imaging technique revealed that the alternation of new and old hair shafts and the different stages of the growth period in AGA mice were delayed. In addition, SHG imaging found testosterone reduced hair follicle area and miniaturized hair follicles. The non-invasive TPEF and SHG imaging techniques provided important methodologies for determining significant characteristics and different stages of the growth cycle in AGA mice, which will facilitate future non-invasive assessments on human scalps in vivo and reduce the use of animal testing.

Multimodal imaging of metabolic activities for distinguishing subtypes of breast cancer.

Triple negative breast cancer (TNBC) is a highly aggressive form of cancer. Detecting TNBC early is crucial for improving disease prognosis and optimizing treatment. Unfortunately, conventional imaging techniques fall short in providing a comprehensive differentiation of TNBC subtypes due to their limited sensitivity and inability to capture subcellular details. In this study, we present a multimodal imaging platform that integrates heavy water (D2O)-probed stimulated Raman scattering (DO-SRS), two-photon fluorescence (TPF), and second harmonic generation (SHG) imaging. This platform allows us to directly visualize and quantify the metabolic activities of TNBC subtypes at a subcellular level. By utilizing DO-SRS imaging, we were able to identify distinct levels of de novo lipogenesis, protein synthesis, cytochrome c metabolic heterogeneity, and lipid unsaturation rates in various TNBC subtype tissues. Simultaneously, TPF imaging provided spatial distribution mapping of NAD[P]H and flavin signals in TNBC tissues, revealing a high redox ratio and significant lipid turnover rate in TNBC BL2 (HCC1806) samples. Furthermore, SHG imaging enabled us to observe diverse orientations of collagen fibers in TNBC tissues, with higher anisotropy at the tissue boundary compared to the center. Our multimodal imaging platform offers a highly sensitive and subcellular approach to characterizing not only TNBC, but also other tissue subtypes and cancers.

Regional biomechanical characterization of human ascending aortic aneurysms: Microstructure and biaxial mechanical response.

The ascending thoracic aortic aneurysm (ATAA) is a permanent dilatation of the vessel with a high risk of adverse events, and shows heterogeneous properties. To investigate regional differences in the biomechanical properties of ATAAs, tissue samples were collected from 10 patients with tricuspid aortic valve phenotype and specimens from minor, anterior, major, and posterior regions were subjected to multi-ratio planar biaxial extension tests and second-harmonic generation (SHG) imaging. Using the data, parameters of a microstructure-motivated constitutive model were obtained considering fiber dispersion. SHG imaging showed disruptions in the organization of the layers. Structural and material parameters did not differ significantly between regions. The non-symmetric fiber dispersion model proposed by Holzapfel etal. [25] was used to fit the data. The mean angle of collagen fibers was negatively correlated between minor and anterior regions, and the parameter associated with collagen fiber stiffness was positively correlated between minor and major regions. Furthermore, correlations were found between the stiffness of the ground matrix and the mean fiber angle, and between the parameter associated with the collagen fiber stiffness and the out-of-plane dispersion parameter in the posterior and minor regions, respectively. The experimental data collected in this study contribute to the biomechanical data available in the literature on human ATAAs. Region-specific parameters for the constitutive models are fundamental to improve the current risk stratification strategies, which are mainly based on aortic size. Such investigations can facilitate the development of more advanced finite element models capable of capturing the regional heterogeneity of pathological tissues. STATEMENT OF SIGNIFICANCE: Tissue samples of human ascending thoracic aortic aneurysms (ATAA) were collected. Samples from four regions underwent multi-ratio planar biaxial extension tests and second-harmonic generation imaging. Region-specific parameters of a microstructure-motivated model considering fiber dispersion were obtained. Structural and material parameters did not differ significantly between regions, however, the mean fiber angle was negatively correlated between minor and anterior regions, and the parameter associated with collagen fiber stiffness was positively correlated between minor and major regions. Furthermore, correlations were found between the stiffness of the ground matrix and the mean fiber angle, and between the parameter associated with the collagen fiber stiffness and the out-of-plane dispersion parameter in the posterior and minor regions, respectively. This study provides a unique set of mechanical and structural data, supporting the microstructural influence on the tissue response. It may facilitate the development of better finite element models capable of capturing the regional tissue heterogeneity.

Aberration free synthetic aperture second harmonic generation holography.

Second harmonic generation (SHG) microscopy is a valuable tool for optical microscopy. SHG microscopy is normally performed as a point scanning imaging method, which lacks phase information and is limited in spatial resolution by the spatial frequency support of the illumination optics. In addition, aberrations in the illumination are difficult to remove. We propose and demonstrate SHG holographic synthetic aperture holographic imaging in both the forward (transmission) and backward (epi) imaging geometries. By taking a set of holograms with varying incident angle plane wave illumination, the spatial frequency support is increased and the input and output pupil phase aberrations are estimated and corrected - producing diffraction limited SHG imaging that combines the spatial frequency support of the input and output optics. The phase correction algorithm is computationally efficient and robust and can be applied to any set of measured field imaging data.

Single bacteria identification with second-harmonic generation in MoS2

Transition-metal dichalcogenides exhibit extraordinary optical nonlinearities, making them promising candidates for advanced photonic applications. Here, we present the microbial control over second-harmonic generation (SHG) in monolayer MoS2 and the identification of single-cell bacteria. Bacteria deposited on monolayer MoS2 induce a change in the SHG signal, in the form of anisotropic polarization responses that depend on the relative orientation of the bacteria with respect to the MoS2 crystallographic direction. The anisotropic enhancement is consistent with the presence of a tensile stress along the lateral direction of bacteria axis; SHG imaging is highly effective in monitoring biomaterial strain as low as 0.1%. We also investigate the ultraviolet-induced removal of single bacteria, through the SHG imaging of MoS2. By monitoring the transient SHG signals, we determine the rupture times for bacteria, which varies noticeably for each species. This allows us to distinguish specific bacteria that share habitats; SHG imaging is useful for label free identification of pathogens at the single cell levels such as E. coli and L. casei. This label-free detection and identification of pathogens at the single-cell level can have a profound impact on the development of diagnostic tools for various applications.

Optical Setup for Investigating the Hyperpolarizability of Organic Nanostructure Materials in Solutions Using Electric Field Induced Second Harmonic Generation

Abstract: In this paper, an optical setup for electric field-induced second-harmonic generation (EFISH) at 1.9 μm experiment was arranged and used to investigate and determine the hyperpolarizability of some nanostructure organic components in two different solutions. First, a laser beam at 1.9 μm was generated by pumping a hydrogen Raman cell pressurized to 55 bar with 10 Hz Q-switched Nd: YAG nanosecond laser operating at λ = 1.064 μm. Next, the generated laser beam was aligned with all optical components within the assembly. The final step was to optimize the beam’s power and polarization at the center of the EFSH cell. Different nanostructure organic samples in solutions were prepared with nearly the same standard concentration of about 5 mmol/L to be investigated under the optimized system. Two solvents were used in this work, dichloromethane, or DCM (CH2Cl2), and chloroform, or trichloromethane (CHCl3). First, the harmonic order hyperpolarizability of five organic molecules in solutions with different chemical components such as quinolinium groups and organic boron complexes (supplied by the Chemistry Department at Catania University, Italy) were experimentally investigated experimentally. Only component (2-(2-[5′-(N,N-dimethylamino)-(2,2′-bithiophen)-5-yl]vinyl)-1-methyquinolin-1-ium iodide) in chloroform showed a significant difference in Maker fringes amplitude of the applied electrical field in comparison with fringes of its pure solvent. The value ofμfor this component has been calculated as 1320 x 10-48 esu. This value indicates that the component is a suitable candidate for use in second-harmonic generation imaging for biological applications. Keywords: Electric field-induced second-harmonic generation (EFISH), Harmonic light, Organic materials, hyperpolarizability. PACS: Nonlinear optics, 42.65.-k, Electric fields, instrumentation for measurement, 07.50.-e, Organic-inorganic hybrid nanostructures, 81.07.Pr, Organic materials optical materials, 42.70.Jk

Super-Resolution Second-Harmonic Generation Imaging with Multifocal Structured Illumination Microscopy.

Second-harmonic generation (SHG) is a noninvasive imaging technique that enables the exploration of physiological structures without the use of an exogenous label. However, traditional SHG imaging is limited by optical diffraction, which restricts the spatial resolution. To break this limitation, we developed a novel approach called multifocal structured illumination microscopy-SHG (MSIM-SHG). By combination of SHG with MSIM, SHG-based super-resolution imaging of material molecules can be achieved, and this SHG super-resolution imaging has a wide range of applications for biological tissues and cells. MSIM-SHG achieved a lateral full width at half-maximum (fwhm) of 147 ± 13 nm and an axial fwhm of 493 ± 47 nm by imaging zinc oxide (ZnO) particles. Furthermore, MSIM-SHG was utilized to quantify collagen fiber alignment in various tissues such as the ovary, muscle, heart, kidney, and cartilage, demonstrating its feasibility for identifying collagen characteristics. MSIM-SHG has potential as a powerful tool for clinical diagnosis and biological research.

Morpho-mechanical mapping of human dura mater microstructure

The human dura mater is known to impact vastly traumatic brain injury mechanopathology. In spite of this involvement, dura mater is typically neglected in computational and physical human head models. The lack of location-dependent microstructural and related mechanical data of dura mater may be considered a rationale behind this simplification. The anisotropic nature of dura mater under various loading conditions so far remains unelucidated. Furthermore, principal collagen fiber orientation is yet to be quantified for a morpho-mechanically-informed material model on the dura mater. This study aims to assess how location-dependent mechanical anisotropy is linked to principal collagen fiber orientation. Uniaxial extension tests were performed in a heated tissue bath for 60 samples from six individuals and correlated to the three-dimensional collagen structure in four individuals using second-harmonic generation (SHG) imaging. Failure stress and stretch at failure, elastic modulus, and a microstructurally motivated material model were integrated to examine local differences in dura mater morpho-mechanics. The quantitative observation of collagen fiber orientation and dispersion confirmed that collagen is highly aligned in the human dura mater and that both fiber orientation and dispersion differ depending on the location investigated. This observation provides a possible explanation for the previously observed isotropic mechanical behavior, as the main collagen fiber direction is not oriented along the anterior-posterior or medial-lateral direction at most of the mapped locations. Additionally, these site-dependent structural properties have implications for the mechanical load response and therefore potentially for the regional functions dura mater has to fulfill. The here chosen non-symmetrical fiber dispersion material model fits the data well and provides a comprehensive parameter base for further studies and future finite element models. Statement of significanceThe human dura mater greatly affects traumatic brain injury mechanisms, but it is often ignored in computational and physical head models. This is because there is a lack of detailed microstructural and mechanical data specific to the dura mater. Its anisotropic nature and collagen fiber orientation have not been fully understood, hindering the development of an accurate material model. Hence, this study combines morphological data on collagen fiber orientation and dispersion at multiple locations of human cranial dura mater, and links microstructure to location-specific load-displacement behavior. It provides microstructurally informed mechanical information towards realistic head models for predicting location-dependent tissue behavior and failure for assessing brain injury and graft material development.

RepE: unsupervised representation learning for image enhancement in nonlinear optical microscopy.

We present an unsupervised learning denoising method, RepE (representation and enhancement), designed for nonlinear optical microscopy images, such as second harmonic generation (SHG) and two-photon fluorescence (TPEF). Addressing the challenge of effectively denoising images with various noise types, RepE employs an encoder network to learn noise-free representations and a reconstruction network to generate denoised images. It offers several key advantages, including its ability to (i) operate without restrictive statistic assumptions, (ii) eliminate the need for clean-noisy pairs, and (iii) requires only a few training images. Comparative evaluations on real-world SHG and TPEF images from esophageal cancer tissue slides (ESCC) demonstrate that our method outperforms existing techniques in image quality metrics. The proposed method provides a practical, robust solution for denoising nonlinear optical microscopy images, and it has the potential to be extended to other nonlinear optical microscopy modalities.