Multi-tissue transcriptome-wide association study identifies novel candidate susceptibility genes for cataract.

Introduction: Cataract is the leading cause of blindness among the elderly worldwide. Twin and family studies support an important role for genetic factors in cataract susceptibility with heritability estimates up to 58%. To date, 55 loci for cataract have been identified by genome-wide association studies (GWAS), however, much work remains to identify the causal genes. Here, we conducted a transcriptome-wide association study (TWAS) of cataract to prioritize causal genes and identify novel ones, and examine the impact of their expression. Methods: We performed tissue-specific and multi-tissue TWAS analyses to assess associations between imputed gene expression from 54 tissues (including 49 from the Genotype Tissue Expression (GTEx) Project v8) with cataract using FUSION software. Meta-analyzed GWAS summary statistics from 59,944 cataract cases and 478,571 controls, all of European ancestry and from two cohorts (GERA and UK Biobank) were used. We then examined the expression of the novel genes in the lens tissue using the iSyTE database. Results: Across tissue-specific and multi-tissue analyses, we identified 99 genes for which genetically predicted gene expression was associated with cataract after correcting for multiple testing. Of these 99 genes, 20 (AC007773.1, ANKH, ASIP, ATP13A2, CAPZB, CEP95, COQ6, CREB1, CROCC, DDX5, EFEMP1, EIF2S2, ESRRB, GOSR2, HERC4, INSRR, NIPSNAP2, PICALM, SENP3, and SH3YL1) did not overlap with previously reported cataract-associated loci. Tissue-specific analysis identified 202 significant gene-tissue associations for cataract, of which 166 (82.2%), representing 9 unique genes, were attributed to the previously reported 11q13.3 locus. Tissue-enrichment analysis revealed that gastrointestinal tissues represented one of the highest proportions of the Bonferroni-significant gene-tissue associations (21.3%). Moreover, this gastrointestinal tissue type was the only anatomical category significantly enriched in our results, after correcting for the number of tissue donors and imputable genes for each reference panel. Finally, most of the novel cataract genes (e.g., Capzb) were robustly expressed in iSyTE lens data. Discussion: Our results provide evidence of the utility of imputation-based TWAS approaches to characterize known GWAS risk loci and identify novel candidate genes that may increase our understanding of cataract etiology. Our findings also highlight the fact that expression of genes associated with cataract susceptibility is not necessarily restricted to lens tissue.

Automatic soft-tissue analysis on orthodontic frontal and lateral facial photographs based on deep learning.

BACKGROUND: To establish the automatic soft-tissue analysis model based on deep learning that performs landmark detection and measurement calculations on orthodontic facial photographs to achieve a more comprehensive quantitative evaluation of soft tissues. METHODS: A total of 578 frontal photographs and 450 lateral photographs of orthodontic patients were collected to construct datasets. All images were manually annotated by two orthodontists with 43 frontal-image landmarks and 17 lateral-image landmarks. Automatic landmark detection models were established, which consisted of a high-resolution network, a feature fusion module based on depthwise separable convolution, and a prediction model based on pixel shuffle. Ten measurements for frontal images and eight measurements for lateral images were defined. Test sets were used to evaluate the model performance, respectively. The mean radial error of landmarks and measurement error were calculated and statistically analysed to evaluate their reliability. RESULTS: The mean radial error was 14.44 ± 17.20 pixels for the landmarks in the frontal images and 13.48 ± 17.12 pixels for the landmarks in the lateral images. There was no statistically significant difference between the model prediction and manual annotation measurements except for the mid facial-lower facial height index. A total of 14 measurements had a high consistency. CONCLUSION: Based on deep learning, we established automatic soft-tissue analysis models for orthodontic facial photographs that can automatically detect 43 frontal-image landmarks and 17 lateral-image landmarks while performing comprehensive soft-tissue measurements. The models can assist orthodontists in efficient and accurate quantitative soft-tissue evaluation for clinical application.

Evaluation of the soft tissue facial profile in different skeletal malocclusions in relation to age.

BACKGROUND: The aim of the study was to assess the thickness of the soft tissue facial profile (STFP) in relation to the skeletal malocclusion, age and gender. METHODS: All patients, aged 7-35 years, who were seeking orthodontic treatment at the Department of Orthodontics, Medical University of Warsaw between 2019 and 22 were included in the study. All patients had lateral head radiographs taken before the treatment. The cephalometric analysis was performed including the STFP analysis. The patients were allocated to one of six groups based on age and skeletal relations (ANB angle). The minimum number of patients in each group was 60 with equal gender distribution. The STFP analysis included ten linear measurements. RESULTS: A total of 300 patients were included in the study and allocated to five groups. Group 6 (growing patients with skeletal Class III malocclusion) was not included in the study as it failed to achieve the assumed group size. There were significant differences in the thickness of the STFP in relation to the skeletal malocclusions. Adults with skeletal Class III malocclusion had significantly thicker subnasal soft tissues compared to patients with skeletal Class I and Class II malocclusions. The thickness of the lower lip in patients with Class II skeletal malocclusion was significantly bigger compared to the other groups. Children and adolescents with Class II malocclusions had thicker lower lip in comparison to the group with Class I malocclusion. The majority of the STFP measurements were significantly smaller in children and adolescents compared to adults. The thickness of the STFP in males was significantly bigger in all age groups compared to females. CONCLUSIONS: The thickness of facial soft tissues depends on the patient's age and gender. The degree of compensation of the skeletal malocclusion in the STFP may be a decisive factor during orthodontic treatment planning regarding a surgical approach or a camouflage treatment of skeletal defects.

Improved Preservation of Mouse Intestinal Tissue Using a Formalin/Acetic Acid Fixative and Quantitative Histological Analysis Using QuPath.

The architecture and morphology of the intestinal tissue from mice or other small animals are difficult to preserve for histological and molecular analysis due to the fragile nature of this tissue. The intestinal mucosa consists of villi and crypts lined with epithelial cells. In between the epithelial folds extends the lamina propria, a loose connective tissue that contains blood and lymph vessels, fibroblasts, and immune cells. Underneath the mucosa are two layers of contractile smooth muscle and nerves. The tissue experiences significant changes during fixation, which can impair the reliability of histologic analysis. Poor-quality histologic sections are not suitable for quantitative image-based tissue analysis. This article offers a new fixative composed of neutral buffered formalin (NBF) and acetic acid, called FA. This fixative significantly improved the histology of mouse intestinal tissue compared to traditional NBF and enabled precise, reproducible histologic molecular analyses using QuPath software. Algorithmic training of QuPath allows for automated segmentation of intestinal compartments, which can be further interrogated for cellular composition and disease-related changes. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Improved preservation of mouse intestinal tissue using a formalin/acetic acid fixative Support Protocol: Quantitative tissue analysis using QuPath.

Metabolite correlation permutation after mice acute exposure to PM2.5: Holistic exploration of toxicometabolomics by network analysis.

Many environmental toxicants can cause systemic effects, such as fine particulate matter (PM2.5), which can penetrate the respiratory barrier and induce effects in multiple tissues. Although metabolomics has been used to identify biomarkers for PM2.5, its multi-tissue toxicology has not yet been explored holistically. Our objective is to explore PM2.5 induced metabolic alterations and unveil the intra-tissue responses along with inter-tissue communicational effects. In this study, following a single intratracheal instillation of multiple doses (0, 25, and 150 µg as the control, low, and high dose), non-targeted metabolomics was employed to evaluate the metabolic impact of PM2.5 across multiple tissues. PM2.5 induced tissue-specific and dose-dependent disturbances of metabolites and their pathways. The remarkable increase of both intra- and inter-tissue correlations was observed, with emphasis on the metabolism connectivity among lung, spleen, and heart; the tissues' functional specificity has marked their toxic modes. Beyond the inter-status comparison of the metabolite fold-changes, the current correlation network built on intra-status can offer additional insights into how the multiple tissues and their metabolites coordinately change in response to external stimuli such as PM2.5 exposure.

Practical considerations for pathological diagnosis and molecular profiling of cholangiocarcinoma: an expert review for best practices.

INTRODUCTION: Advances in precision medicine have expanded access to targeted therapies and demand for molecular profiling of cholangiocarcinoma (CCA) patients in routine clinical practice. However, pathologists face challenges in establishing a definitive intrahepatic CCA (iCCA) diagnosis while preserving sufficient tissue for molecular profiling. Additionally, they frequently face challenges in optimal tissue handling to preserve nucleic acid integrity. AREAS COVERED: This article first identifies the challenges in establishing a definitive diagnosis of iCCA in a lesional liver biopsy while preserving sufficient tissue for molecular profiling. Then, the authors explore the clinical value of molecular profiling, the basic principles of single gene and next-generation sequencing (NGS) techniques, and the challenges in tissue sampling for genomic testing. They also propose an algorithm for best practice in tissue management for molecular profiling of CCA. EXPERT OPINION: Several practical challenges face pathologists during tissue sampling and processing for molecular profiling. Optimized tissue processing, careful tissue handling, and selection of appropriate approaches to molecular testing are essential to ensure that the highest possible quality of diagnostic information is provided in the greatest proportion of cases.

Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy.

Breast cancer is one of the most spread and monitored pathologies in high-income countries. After breast biopsy, histological tissue is stored in paraffin, sectioned and mounted. Conventional inspection of tissue slides under benchtop light microscopes involves paraffin removal and staining, typically with H&E. Then, expert pathologists are called to judge the stained slides. However, paraffin removal and staining are operator-dependent, time and resources consuming processes that can generate ambiguities due to non-uniform staining. Here we propose a novel method that can work directly on paraffined stain-free slides. We use Fourier Ptychography as a quantitative phase-contrast microscopy method, which allows accessing a very wide field of view (i.e., mm2) in one single image while guaranteeing high lateral resolution (i.e., 0.5 µm). This imaging method is multi-scale, since it enables looking at the big picture, i.e. the complex tissue structure and connections, with the possibility to zoom-in up to the single-cell level. To handle this informative image content, we introduce elements of fractal geometry as multi-scale analysis method. We show the effectiveness of fractal features in describing and classifying fibroadenoma and breast cancer tissue slides from ten patients with very high accuracy. We reach 94.0 ± 4.2% test accuracy in classifying single images. Above all, we show that combining the decisions of the single images, each patient's slide can be classified with no error. Besides, fractal geometry returns a guide map to help pathologist to judge the different tissue portions based on the likelihood these can be associated to a breast cancer or fibroadenoma biomarker. The proposed automatic method could significantly simplify the steps of tissue analysis and make it independent from the sample preparation, the skills of the lab operator and the pathologist.

[Intraoperative stimulated Raman histology for personalized brain tumor surgery]. / Personalisierte Hirntumorchirurgie mittels intraoperativer stimulierter Raman-Histologie.

BACKGROUND: In brain tumor surgery a personalized surgical approach is crucial to achieve a maximum safe tumor resection. The extent of resection decisively depends on the histological diagnosis. Stimulated Raman histology (SRH), a fiber laser-based optical imaging method, offers the possibility for evaluation of an intraoperative diagnosis in a few minutes. OBJECTIVE: To provide an overview on the applications of SRH in neurosurgery and transference of the technique to other surgical disciplines. METHODS: Description of the technique and review of the current literature on SRH. RESULTS: The SRH technique was successfully used in multiple neuro-oncological tumor entities. Initial pilot projects showed the potential for analysis of extracranial tumors. CONCLUSION: The use of SRH provides a near real-time diagnosis with high diagnostic accuracy and provides further developmental potential to improve personalized tumor surgery.

Stoichiometry of growth under variable scenarios of nutrient limitation: Differential homeostasis of body composition among growth phenotypes of the Manila clam.

Fast- and slow-growing phenotypes from two separate breeding families of the Manila clam (Ruditapes philippinarum) were alternatively fed two monoalgal diets with high and low N content (C:N ratios of 4.9 and 13.5, respectively). After 35 days of food conditioning, clams were sacrificed, and the soft body was dissected out into five different tissue fractions to determine the corresponding ponderal ratios (tissue wt./body wt.) and a separate analysis of the elemental composition of these tissues. Previously reported C and N balances performed with the same conditioning diets were integrated and compared with tissue composition of the same phenotypes in order to assess the efficacy of mechanisms elicited to compensate for N deficit. Broad differences in dietary N content resulted in only minor changes in whole-body C:N composition which suggests a noticeable degree of homeostatic regulation of nutrient balances. This regulation was found to be stricter in fast-compared to slow-growing phenotypes and differed among the various body tissues. Using the threshold element ratio approach, physiological mechanisms were identified that partly compensate for large stoichiometric mismatches between low-N food and body tissues.

Robust detection of clinically relevant features in single-cell RNA profiles of patient-matched fresh and formalin-fixed paraffin-embedded (FFPE) lung cancer tissue.

PURPOSE: Single-cell transcriptional profiling reveals cell heterogeneity and clinically relevant traits in intra-operatively collected patient-derived tissue. So far, single-cell studies have been constrained by the requirement for prospectively collected fresh or cryopreserved tissue. This limitation might be overcome by recent technical developments enabling single-cell analysis of FFPE tissue. METHODS: We benchmark single-cell profiles from patient-matched fresh, cryopreserved and archival FFPE cancer tissue. RESULTS: We find that fresh tissue and FFPE routine blocks can be employed for the robust detection of clinically relevant traits on the single-cell level. Specifically, single-cell maps of fresh patient tissues and corresponding FFPE tissue blocks could be integrated into common low-dimensional representations, and cell subtype clusters showed highly correlated transcriptional strengths of signaling pathway, hallmark, and clinically useful signatures, although expression of single genes varied due to technological differences. FFPE tissue blocks revealed higher cell diversity compared to fresh tissue. In contrast, single-cell profiling of cryopreserved tissue was prone to artifacts in the clinical setting. CONCLUSION: Our analysis highlights the potential of single-cell profiling in the analysis of retrospectively and prospectively collected archival pathology cohorts and increases the applicability in translational research.

Forty-eight-year follow-up of a female worker exposed to highly enriched uranium via chronic and acute inhalation.

The United States Transuranium and Uranium Registries (USTUR) is a unique resource of data and materials for studying biokinetics of uranium in the human body. In this study, bioassay data and post-mortem organ activities from a female whole-body USTUR donor who was exposed to highly enriched uranium were analyzed using the IMBA Professional Plus® software to derive the best estimate of the total intake. The resulting radiation doses delivered to this individual's whole body and major target organs were calculated from estimated intake based on case-specific dose coefficients derived using the AIDE® software. Both intake and dose calculations were carried out using the biokinetic and dosimetric models recommended by the International Commission on Radiological Protection (ICRP) in its Occupational Intakes of Radionuclides publication series. Different exposure scenarios including chronic and acute inhalation intakes were tested. A combination of a chronic inhalation intake and two acute inhalation intakes appears to best describe the bioassay data. To fit this female individual's autopsy data, the transfer rate from the liver to the blood was increased by a factor of 8 and the transfer rate from the kidneys to the blood was decreased by a factor of 2.2. This resulted in the best fit to all data (p = 0.519). The total intake was estimated to be 44.1 kBq, and the committed effective dose was 211 mSv with 96.8% contributed by 234U. 96.6% of the committed effective dose was contributed by the lungs. The remaining 3.4% of the committed effective dose was contributed by all systemic tissues and organs with the highest contribution (0.40%) from the red bone marrow. It is concluded that the current ICRP models, with the adjustment for smoking status, adequately describe uranium biokinetics for this individual except retention in the liver and kidneys. However, this study was based on a single case and may not be sufficient to identify any apparent sex-specific differences in uranium biokinetics.

Long-term retention and distribution of highly enriched uranium in an occupationally exposed female.

The United States Transuranium and Uranium Registries' (USTUR) female whole body tissue donor studied here was occupationally exposed to highly enriched uranium for 17 years. One hundred and twenty-nine tissue samples were collected at the time of death, 31 years post-exposure. These samples were radiochemically analyzed for uranium. The highest uranium concentration of 16.5 ± 2.0 µg kg-1 was measured in the lungs, and the lowest concentration of 0.11 ± 0.01 µg kg-1 in the liver. The thyroid had the highest concentration of 6.3 ± 2.9 µg kg-1 among systemic tissues. Mass-weighted average concentration in the entire skeleton was estimated to be 1.60 ± 0.19 µg kg-1. In the skeleton, uranium was non-uniformly distributed among different bones. Thirty-one years after the intake, approximately 40% of occupational uranium was still retained in the skeleton, followed by the kidneys (~ 30%), and the brain and liver (~ 10%). Systemic uranium was equally distributed between the skeleton and soft tissues. Uranium content in systemic organs followed the pattern: skeleton > > brain ≈ kidneys > heart ≈ liver > thyroid ≈ spleen. Uranium distribution in this female was compared to previously published USTUR data for male tissue donors. It is concluded that no difference in uranium systemic distribution was observed between female and male individuals. It is demonstrated that dose assessment based on the current ICRP biokinetic model overestimated the dose to the brain by 20%.

Fast and low-cost method for direct and simultaneous determination of nitrogen and carbon in soybean leaves using benchtop and portable near-infrared devices.

BACKGROUND: The current techniques for determining carbon and nitrogen content to provide information about the nutritional status of plants are time-consuming and expensive. For this reason, the objective of this study was to develop an analytical method for the direct and simultaneous determination of nitrogen and carbon elemental content in soybean leaves using near-infrared spectroscopy and compare the performance of conventional (1100-2500 nm spectral range) and portable equipment (1100-1700 nm spectral range). Partial least-squares regression models were developed using 27 soybean leaf samples collected during the 2021 harvest and applied for the simultaneous determination of carbon and nitrogen in 13 samples collected during the 2022 harvest. RESULTS: The root-mean-square error of prediction values for nitrogen and carbon were low (2.42 g kg-1 and 4.37 g kg-1 respectively) for the benchtop method yielded low but higher for the portable method (3.82 g kg-1 and 10.7 g kg-1 respectively). The benchtop method did not show significant differences when compared with the reference method for determining nitrogen and carbon. In contrast, the portable methodology showed potential as a screening method for determining nitrogen levels, particularly in fieldwork. CONCLUSION: The methodologies evaluated in this study were implemented and evaluated under real crop monitoring conditions, using independent sets of calibration and prediction samples. Their utilization enables the acquisition of cost-effective, safe analytical data aligning with the principles of green analytical chemistry. © 2023 Society of Chemical Industry.

Advances in Imaging Mass Spectrometry for Biomedical and Clinical Research.

Imaging mass spectrometry (IMS) allows for the untargeted mapping of biomolecules directly from tissue sections. This technology is increasingly integrated into biomedical and clinical research environments to supplement traditional microscopy and provide molecular context for tissue imaging. IMS has widespread clinical applicability in the fields of oncology, dermatology, microbiology, and others. This review summarizes the two most widely employed IMS technologies, matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI), and covers technological advancements, including efforts to increase spatial resolution, specificity, and throughput. We also highlight recent biomedical applications of IMS, primarily focusing on disease diagnosis, classification, and subtyping.

Ratiometric luminescent sensor based on BSA-coated gold/silver nanoclusters for the selective determination and spatiotemporal imaging of gallic acid in plants.

A new fluorescence sensing strategy has been developed. Four bimetallic nanoclusters, gold/silver, gold/copper, gold/molybdenum and gold/cobalt, were prepared using bovine serum albumin (BSA) as a reducing and stabilizing agent. The fluorescence properties of four nanoclusters were explored by solid-state UV and XPS. The gold/silver nanoclusters (BSA-Au/Ag NCs) with the best ratiometric fluorescence properties for gallic acid (GA) in plants were selected to realize the sensitive detection of GA. GA affected the conformation of BSA, thereby disrupting the luminescent environment of the nanoclusters, resulting in a pronounced fluorescence quenching at 566 nm. The ratiometric fluorescence signal (I566/I453) was used for trace detection of GA in plants. It has a wide response range of 1.25-40.0 µM and a low detection limit of 45.27 nM. GA was detected at 19.49 µM in the plant extract, and the spiked recoveries ranged from 96.09 to 104.6%. In addition, due to the non-toxic and biocompatible properties of BSA, BSA-Au/Ag NCs have also been validated for fluorescence imaging of plant tissues. It realized the comparison of GA content in different parts of plants and the difference of GA content in plants after abiotic stress. Therefore, the developed strategy offers potential application for the analytical study of active substances in plants.

MATLAB-Based Algorithm and Software for Analysis of Wavy Collagen Fibers.

Knowledge of soft tissue fiber structure is necessary for accurate characterization and modeling of their mechanical response. Fiber configuration and structure informs both our understanding of healthy tissue physiology and of pathological processes resulting from diseased states. This study develops an automatic algorithm to simultaneously estimate fiber global orientation, abundance, and waviness in an investigated image. To our best knowledge, this is the first validated algorithm which can reliably separate fiber waviness from its global orientation for considerably wavy fibers. This is much needed feature for biological tissue characterization. The algorithm is based on incremental movement of local regions of interest (ROI) and analyzes two-dimensional images. Pixels belonging to the fiber are identified in the ROI, and ROI movement is determined according to local orientation of fiber within the ROI. The algorithm is validated with artificial images and ten images of porcine trachea containing wavy fibers. In each image, 80-120 fibers were tracked manually to serve as verification. The coefficient of determination R2 between curve lengths and histograms documenting the fiber waviness and global orientation were used as metrics for analysis. Verification-confirmed results were independent of image rotation and degree of fiber waviness, with curve length accuracy demonstrated to be below 1% of fiber curved length. Validation-confirmed median and interquartile range of R2, respectively, were 0.90 and 0.05 for curved length, 0.92 and 0.07 for waviness, and 0.96 and 0.04 for global orientation histograms. Software constructed from the proposed algorithm was able to track one fiber in about 1.1 s using a typical office computer. The proposed algorithm can reliably and accurately estimate fiber waviness, curve length, and global orientation simultaneously, moving beyond the limitations of prior methods.

Feeding ecology based on stable carbon and nitrogen isotopes: A comparative study on different Guiana dolphin tissues.

Different tissues are used for stable isotope analysis in cetacean investigations. However, variation in the isotopic composition of tissues with different turnover rates has been reported for cetaceans. To better understand stable carbon and nitrogen isotopes (δ13C and δ15N) in skin compared to other tissues, this study assessed the isotopic variation among the liver, muscle, and skin of Guiana dolphins (Sotalia guianensis), as well as the influence of sex on these variations. No differences were found in δ13C among male tissues, but females showed lower values in the liver compared to muscle and skin. Differences in δ15N were observed among all tissues, with different variation patterns for males and females. Four females were distinguished from males and other females by their 13C depletion in all tissues and δ15N variation pattern. We conclude that skin and muscle may be equivalent in δ13C values for Guiana dolphins. The multiple-tissue analysis brings new insights into their feeding ecology and provides background for stable isotope analysis using non-destructive sampling techniques in small cetaceans.

Clinical Proteomics for Solid Organ Tissues.

The evaluation of biopsied solid organ tissue has long relied on visual examination using a microscope. Immunohistochemistry is critical in this process, labeling and detecting cell lineage markers and therapeutic targets. However, while the practice of immunohistochemistry has reshaped diagnostic pathology and facilitated improvements in cancer treatment, it has also been subject to pervasive challenges with respect to standardization and reproducibility. Efforts are ongoing to improve immunohistochemistry, but for some applications, the benefit of such initiatives could be impeded by its reliance on monospecific antibody-protein reagents and limited multiplexing capacity. This perspective surveys the relevant challenges facing traditional immunohistochemistry and describes how mass spectrometry, particularly liquid chromatography-tandem mass spectrometry, could help alleviate problems. In particular, targeted mass spectrometry assays could facilitate measurements of individual proteins or analyte panels, using internal standards for more robust quantification and improved interlaboratory reproducibility. Meanwhile, untargeted mass spectrometry, showcased to date clinically in the form of amyloid typing, is inherently multiplexed, facilitating the detection and crude quantification of 100s to 1000s of proteins in a single analysis. Further, data-independent acquisition has yet to be applied in clinical practice, but offers particular strengths that could appeal to clinical users. Finally, we discuss the guidance that is needed to facilitate broader utilization in clinical environments and achieve standardization.

Breast tissue analysis using a clinically compatible combined time-resolved fluorescence and diffuse reflectance (TRF-DR) system.

OBJECTIVE: This work aims to develop a clinically compatible system that can perform breast tissue analysis in a more time efficient process than conventional histopathological assessment. The potential for such a system to be used in vivo in the operating room or surgical suite to improve patient outcome is investigated. METHOD: In this work, 80 matched pairs of invasive ductal carcinoma and adjacent normal breast tissue were measured in a combined time-resolved fluorescence and diffuse reflectance (DA) system. Following measurement, the fluorescence intensity of collagen and flavin adenine dinucleotide (FAD); the fluorescence lifetime of collagen, nicotinamide adenine dinucleotide (NADH), and FAD; the DA; absorption coefficient; and reduced scattering coefficient were extracted. Samples then underwent histological processing and H&E staining to classify composition as tumor, fibroglandular, and/or adipose tissue. RESULTS: Statistically significant differences in the collagen and FAD fluorescence intensity, collagen and FAD fluorescence lifetime, DA, and scattering coefficient were found between each tissue group. The NADH fluorescence lifetime and absorption coefficient were statistically different between the tumor and fibroglandular groups, and the tumor and adipose groups. While many breast tissue analysis studies label fibroglandular and adipose together as "normal" breast tissue, this work indicates that some differences between tumor and fibroglandular tissue are not the same as differences between tumor and adipose tissue. Observations of the reduced scatter coefficient may also indicate further classification to include fibro-adipose may be necessary. Future work would benefit from the additional tissue classification. CONCLUSION: With observable differences in optical parameters between the three tissue types, this system shows promise as a breast analysis tool in a clinical setting. With further work involving samples of mixed composition, this combined system could potentially be used intraoperatively for rapid margin assessment.

A Comparative Study of Ultrasmall Calcium Carbonate Nanoparticles for Targeting and Imaging Atherosclerotic Plaque.

Atherosclerosis is a complex disease that can lead to life-threatening events, such as myocardial infarction and ischemic stroke. Despite the severity of this disease, diagnosing plaque vulnerability remains challenging due to the lack of effective diagnostic tools. Conventional diagnostic protocols lack specificity and fail to predict the type of atherosclerotic lesion and the risk of plaque rupture. To address this issue, technologies are emerging, such as noninvasive medical imaging of atherosclerotic plaque with customized nanotechnological solutions. Modulating the biological interactions and contrast of nanoparticles in various imaging techniques, including magnetic resonance imaging, is possible through the careful design of their physicochemical properties. However, few examples of comparative studies between nanoparticles targeting different hallmarks of atherosclerosis exist to provide information about the plaque development stage. Our work demonstrates that Gd (III)-doped amorphous calcium carbonate nanoparticles are an effective tool for these comparative studies due to their high magnetic resonance contrast and physicochemical properties. In an animal model of atherosclerosis, we compare the imaging performance of three types of nanoparticles: bare amorphous calcium carbonate and those functionalized with the ligands alendronate (for microcalcification targeting) and trimannose (for inflammation targeting). Our study provides useful insights into ligand-mediated targeted imaging of atherosclerosis through a combination of in vivo imaging, ex vivo tissue analysis, and in vitro targeting experiments.