Multi-model analysis of gallbladder cancer reveals the role of OxLDL-absorbing neutrophils in promoting liver invasion.

BACKGROUND: Gallbladder cancer (GBC) is the most common and lethal malignancy of the biliary tract that lacks effective therapy. In many GBC cases, infiltration into adjacent organs or distant metastasis happened long before the diagnosis, especially the direct liver invasion, which is the most common and unfavorable way of spreading. METHODS: Single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST), proteomics, and multiplexed immunohistochemistry (mIHC) were performed on GBC across multiple tumor stages to characterize the tumor microenvironment (TME), focusing specifically on the preferential enrichment of neutrophils in GBC liver invasion (GBC-LI). RESULTS: Multi-model Analysis reveals the immunosuppressive TME of GBC-LI that was characterized by the enrichment of neutrophils at the invasive front. We identified the context-dependent transcriptional states of neutrophils, with the Tumor-Modifying state being associated with oxidized low-density lipoprotein (oxLDL) metabolism. In vitro assays showed that the direct cell-cell contact between GBC cells and neutrophils led to the drastic increase in oxLDL uptake of neutrophils, which was primarily mediated by the elevated OLR1 on neutrophils. The oxLDL-absorbing neutrophils displayed a higher potential to promote tumor invasion while demonstrating lower cancer cytotoxicity. Finally, we identified a neutrophil-promoting niche at the invasive front of GBC-LI that constituted of KRT17+ GBC cells, neutrophils, and surrounding fibroblasts, which may help cultivate the oxLDL-absorbing neutrophils. CONCLUSIONS: Our study reveals the existence of a subset of pro-tumoral neutrophils with a unique ability to absorb oxLDL via OLR1, a phenomenon induced through cell-cell contact with KRT17+ GBC cells in GBC-LI.

Machine learning assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues.

Significance: Label-free multimodal imaging methods that can provide complementary structural and chemical information from the same sample are critical for comprehensive tissue analyses. These methods are specifically needed to study the complex tumor-microenvironment where fibrillar collagen's architectural changes are associated with cancer progression. To address this need, we present a multimodal computational imaging method where mid-infrared spectral imaging (MIRSI) is employed with second harmonic generation (SHG) microscopy to identify fibrillar collagen in biological tissues. Aim: To demonstrate a multimodal approach where a morphology-specific contrast mechanism guides a mid-infrared spectral imaging method to detect fibrillar collagen based on its chemical signatures. Approach: We trained a supervised machine learning (ML) model using SHG images as ground truth collagen labels to classify fibrillar collagen in biological tissues based on their mid-infrared hyperspectral images. Five human pancreatic tissue samples (sizes are in the order of millimeters) were imaged by both MIRSI and SHG microscopes. In total, 2.8 million MIRSI spectra were used to train a random forest (RF) model. The remaining 68 million spectra were used to validate the collagen images generated by the RF-MIRSI model in terms of collagen segmentation, orientation, and alignment. Results: Compared to the SHG ground truth, the generated MIRSI collagen images achieved a high average boundary F-score (0.8 at 4 pixels threshold) in the collagen distribution, high correlation (Pearson's R 0.82) in the collagen orientation, and similarly high correlation (Pearson's R 0.66) in the collagen alignment. Conclusions: We showed the potential of ML-aided label-free mid-infrared hyperspectral imaging for collagen fiber and tumor microenvironment analysis in tumor pathology samples.

Multi-omics analysis reveals key regulatory defense pathways and genes involved in salt tolerance of rose plants.

Salinity stress causes serious damage to crops worldwide, limiting plant production. However, the metabolic and molecular mechanisms underlying the response to salt stress in rose (Rosa spp.) remain poorly studied. We therefore performed a multi-omics investigation of Rosa hybrida cv. Jardin de Granville (JDG) and Rosa damascena Mill. (DMS) under salt stress to determine the mechanisms underlying rose adaptability to salinity stress. Salt treatment of both JDG and DMS led to the buildup of reactive oxygen species (H2O2). Palisade tissue was more severely damaged in DMS than in JDG, while the relative electrolyte permeability was lower and the soluble protein content was higher in JDG than in DMS. Metabolome profiling revealed significant alterations in phenolic acid, lipids, and flavonoid metabolite levels in JDG and DMS under salt stress. Proteome analysis identified enrichment of flavone and flavonol pathways in JDG under salt stress. RNA sequencing showed that salt stress influenced primary metabolism in DMS, whereas it substantially affected secondary metabolism in JDG. Integrating these datasets revealed that the phenylpropane pathway, especially the flavonoid pathway, is strongly enhanced in rose under salt stress. Consistent with this, weighted gene coexpression network analysis (WGCNA) identified the key regulatory gene chalcone synthase 1 (CHS1), which is important in the phenylpropane pathway. Moreover, luciferase assays indicated that the bHLH74 transcription factor binds to the CHS1 promoter to block its transcription. These results clarify the role of the phenylpropane pathway, especially flavonoid and flavonol metabolism, in the response to salt stress in rose.

ZNF692 promotes the migration and response to immunotherapy of clear cell renal cell carcinoma cells by targeting metabolic pathway.

Clear cell renal cell carcinoma (ccRCC), with high mortality and poor prognosis, is the most common type of renal malignancy. It is necessary to identify new biomarkers that can serve as indicators for the detection of ccRCC at its early stages. In this study, we analyzed the role of classical zinc finger protein 692 (ZNF692) in ccRCC using datasets from The Cancer Genome Atlas (TCGA) and Single Cell Portal and immunohistochemical (IHC) staining of a tissue-microarray, and analyzed the function of ZNF692 in ccRCC cells. The analyses indicated that ZNF692 was upregulated in ccRCC samples compared with normal or paracancerous control samples (P < 0.001) and that the expression of this gene was linked to poor overall survival (HR = 2.1, P < 0.0001). The knockdown of ZNF692 inhibited the proliferation and migration of ccRCC cells by target GTPase-activating protein (SH3 domain)-binding protein 2 (G3BP2), and transmembrane 9 superfamily member 2 (TM9SF2)). T, B, proximal, and collecting tubule cells are the dominant cell types in normal kidney tissue where ZNF692 is expressed. In addition, immune checkpoint blockade (ICB) therapy dramatically changed the expression patterns of ZNF692. Collectively, these data indicate that ZNF692 may serve as prognosis, and as a potential indicator of the response to ICB therapy, a possibility needs to be verified by a case‒control study.

Selpercatinib attenuates bleomycin-induced pulmonary fibrosis by inhibiting the TGF-ß1 signaling pathway.

IPF is a chronic, progressive, interstitial lung disease with high mortality. Current drugs have limited efficacy in curbing disease progression and improving quality of life. Selpercatinib, a highly selective inhibitor of receptor tyrosine kinase RET (rearranged during transfection), was approved in 2020 for the treatment of a variety of solid tumors with RET mutations. In this study, the action and mechanism of Selpercatinib in pulmonary fibrosis were evaluated in vivo and in vitro. In vivo experiments demonstrated that Selpercatinib significantly ameliorated bleomycin (BLM)-induced pulmonary fibrosis in mice. In vitro, Selpercatinib inhibited the proliferation, migration, activation and extracellular matrix deposition of fibroblasts by inhibiting TGF-ß1/Smad and TGF-ß1/non-Smad pathway, and suppressed epithelial-mesenchymal transition (EMT) like process of lung epithelial cells via inhibiting TGF-ß1/Smad pathway. The results of in vivo pharmacological tests corroborated the results obtained from the in vitro experiments. Further studies revealed that Selpercatinib inhibited abnormal phenotypes of lung fibroblasts and epithelial cells in part by regulating its target RET. In short, Selpercatinib inhibited the activation of fibroblasts and EMT-like process of lung epithelial cells by inhibiting TGF-ß1/Smad and TGF-ß1/non-Smad pathways, thus alleviating BLM-induced pulmonary fibrosis in mice.

Development of an individualized model for predicting postoperative delirium in elderly patients with hepatocellular carcinoma.

Postoperative delirium (POD) is a common complication in older patients with hepatocellular carcinoma (HCC) that adversely impacts clinical outcomes. We aimed to evaluate the risk factors for POD and to construct a predictive nomogram. Data for a total of 1481 older patients (training set: n=1109; validation set: n=372) who received liver resection for HCC were retrospectively retrieved from two prospective databases. The receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA) were used to evaluate the performance. The rate of POD was 13.3% (148/1109) in the training set and 16.4% (61/372) in the validation set. Multivariate analysis of the training set revealed that factors including age, history of cerebrovascular disease, American Society of Anesthesiologists (ASA) classification, albumin level, and surgical approach had significant effects on POD. The area under the ROC curves (AUC) for the nomogram, incorporating the aforementioned predictors, was 0.798 (95% CI 0.752-0.843) and 0.808 (95% CI 0.754-0.861) for the training and validation sets, respectively. The calibration curves of both sets showed a degree of agreement between the nomogram and the actual probability. DCA demonstrated that the newly established nomogram was highly effective for clinical decision-making. We developed and validated a nomogram with high sensitivity to assist clinicians in estimating the individual risk of POD in older patients with HCC.

Application and configuration analysis of electric muck transfer equipment in plateau railway tunnel: a case study in southwest China.

The burgeoning development of railway construction in plateau regions of southwest China necessitates innovative and environmentally sustainable approaches, particularly in the realm of tunnel construction, where the transfer of muck poses significant operational and environmental challenges. This research, pivoting around the application and configuration of electric muck transfer equipment in plateau railway tunnels, seeks to dissect the potentialities and impediments of transitioning from conventional diesel-powered machinery to electric alternatives, with a spotlight on mitigating environmental impacts and enhancing operational efficiency. Through an analytical lens, the study employs a case study methodology, leveraging data and insights from existing electric equipment models and their applications, provided by major manufacturers in China, to weave a comprehensive narrative around the practicalities, specifications, and challenges embedded in the adoption of electric machinery in plateau environments. The findings unveil a nuanced landscape, where the environmental and operational advantages of electric equipment are juxtaposed against a backdrop of technological, financial, and infrastructural hurdles, thereby crafting a complex tapestry of opportunities and challenges. The research further extrapolates policy recommendations and practical guidelines, advocating for a harmonized amalgamation of governmental policies, technological advancements, and strategic planning to navigate through the identified challenges and optimize the integration of electric equipment in tunnel construction practices. Envisaging future research pathways, the study underscores the criticality of perpetuating technological innovations, policy adaptations, and interdisciplinary research to further refine and enhance the application of electric muck transfer equipment in plateau railway tunnel projects, thereby contributing to the broader narrative of sustainable construction practices in challenging terrains.

QTL-seq analysis identified the genomic regions of plant height and days to heading in high-latitude rice.

Introduction: Rice (Oryza sativa L.) is one of the most extensive crops in the world. China's Heilongjiang Province is the northernmost rice-growing region in the world. However, rice cultivars suitable for growth in low-latitude regions may not mature normally due to their distinct climate and short frost-free period. It is necessary to precisely determine the frost-free period for each region to make the best use of the rice growth stage so as to ensure the maturity and yield of different rice cultivars in Heilongjiang Province. The time span of the heading stage is a key parameter for evaluating the adaptability of a rice cultivar to a specific rice-growing region. Given the above facts, it is of high importance to study the associated genes and sites controlling days to heading (DH) and plant height (PH) of rice in Heilongjiang Province. Bulked segregant analysis (BSA) combined with high-throughput sequencing can effectively exclude interferences from background genomic differences, making it suitable for analyzing the associated sites of complex agronomic traits in early generations. Methods: In this study, an F3 segregating population was obtained by crossing two main cultivars that are grown under different temperatures and day-light conditions in Heilongjiang. Two pools of extreme phenotypes were built for the DH and PH of the population. For SNP and InDel variants obtained from whole-genome resequencing in the pools, an association analysis was performed using the Euclidean distance (ED) algorithm and the SNP/InDel index algorithm. Results: The intersection of SNP and InDel regions associated with the phenotypes was considered to obtain the final associated sites. After excluding interferences from the cloned genes on chromosomes 2 and 7, a total length of 6.34 Mb on chromosomes 1, 3, and 10 and 3.16 Mb on chromosomes 1 and 10 were left associated with PH and DH, respectively. Then, we performed a gene annotation analysis for candidate genes in the remaining regions using multiple genome annotation databases. Our research provides basic data for subsequent gene mapping and cloning. Discussion: By mining more genetic loci associated with the days to heading and plant height of rice, we may provide abundant genetic resources for refined molecular breeding in Heilongjiang Province.

Alkaloids from Fritillaria przewalskii Bulbs and Their Anti-Alzheimer's Disease Activities.

Three undescribed isosteroidal alkaloids, przewalskines A-C (1-3), as well as seven known alkaloids (4-10) were obtained from Fritillaria przewalskii bulbs. Their structures were deduced by extensive HRESIMS, 1D NMR, and 2D NMR analyses, and their bioactivities were evaluated involving the anti-inflammatory and inhibitory potencies on AChE, BChE, and Aß aggregation. Compound 4 revealed the potent effect on inhibiting Aß aggregation activity with IC50 value of 33.1 µM, AChE activity with IC50 value of 6.9 µM, and also showed NO release inhibitory acitivity with IC50 value of 32.6 µM. These findings contribute new multi-.target anti-AD agents and embody the chemical diversity of F. przewalskii.

Base-promoted triple cleavage of CCl2Br: a direct one-pot synthesis of unsymmetrical oxalamide derivatives.

We present a novel, eco-friendly and one-pot approach for synthesizing unsymmetrical oxalamides with the aid of dichloroacetamide and amine/amides in the presence of CBr4 in a basic medium. The use of water as a potent supplement for the oxygen atom source and the detailed mechanism have been disclosed. Moreover, the protocol involves triple cleavage of CCl2Br and the formation of new C-O/C-N bonds, with the advantage of achieving selective bromination using CBr4 with good to excellent yield under mild conditions. The method also demonstrates promise for industrial use, as proven by its effective implementation in gram-scale synthesis conducted in a batch process, along with its utilization in a continuous-flow system.

Non-destructive detection of egg white and yolk morphology transformation and salt content of salted duck eggs in salting by hyperspectral imaging.

Salt content is a crucial indicator of the maturity and internal quality of salted duck eggs (SDEs) during the pickling process. However, there is currently no valid and rapid method available for accurately detecting salt content. In the present study, we utilized hyperspectral imaging to no-destructively determine the salt content in egg yolks, egg whites, and whole eggs during the curing period. Firstly, principal component analysis was applied to explain the characteristics of egg yolk and white morphology transformation of SDEs with different maturities during curing. Secondly, sensitive spectral factors representative of changes in the salt content of SDEs were extracted by three spectral transformations (Savitzky-Golay SG, continuum removal CR, and first-order derivation FD) and three approaches of selecting characteristic wavelengths (successive projection algorithm SPA, uninformative variables elimination UVE and competitive adaptive reweighting sampling algorithm CARS). The results of the PLSR model suggested that the optimal models for predicting salt content in egg yolks, whites, and whole eggs were SG-UVE-PLSR (predicted coefficient of determination Rp2=0.912, predicted standard deviation SEp=0.151, residual prediction deviation RPD = 3.371), CR-CARS-PLSR (Rp2=0.873, SEp=0.862, RPD = 2.806), and CR-UVE-PLSR (Rp2=0.877, SEp=0.680, RPD = 2.851), respectively. Eventually, the optimal prediction model for the salt content of the whole egg was employed to a pixel spectral matrix to calculate the salt content values of pixel points on the hyperspectral image of SDEs. Additionally, pseudo-color techniques were employed to visualize the spatial distribution of predicted salt content. This work will provide a theoretical foundation for rapidly detecting maturity and enabling high-throughput quality sorting of SDEs.

An Evidence Map of Clinical Practice Guideline Recommendations on Stroke Rehabilitation.

ABSTRACT: The purpose of this study was to provide an evidence map for explaining research trends and gaps. Four databases and CPGs-related websites were searched up to March 2022. Basic information, methodological quality, reporting quality of CPGs, and similar stroke recommendations were extracted. The methodological and reporting quality of stroke CPGs were evaluated using the AGREE II instrument and the RIGHT checklist. The bubble plot format of the evidence map helped visualize the overall quality. Data management and analysis were performed using Excel 2013 and SPSS 22.0 software. A total of 12 CPGs, published between 1997 and 2020 were included for in-depth analysis. The identified CPGs had a mixed quality and scored poorly in the developmental rigor and applicability domains by AGREE II. According to the RIGHT checklist, field four (clarity of expression) showed the highest (79.2%), and field three (rigor of formulation) secured the lowest (28%) reporting rates. The stroke rehabilitation recommendations primarily focused on organizational management, timing and intensity, rehabilitation and nutritional management of dysphagia, return to work, communication, speech, and language function. This would promote improvement in developing trustworthy CPGs for stroke rehabilitation.

The effect of radiotherapy on patients with pathological stage IIB breast cancer after breast-conserving surgery or mastectomy: A cohort study.

BACKGROUND: Breast cancer is one of the most common cancers in women, and treatment options include surgery, systemic therapies, and radiotherapy (RT). While postoperative RT plays an important role in reducing local recurrence rates and improving survival outcomes, its exact impact on patients with pathological stage IIB breast cancers remains unidentified. METHODS: In this retrospective cohort study, patients with newly diagnosed pathological stage IIB breast cancer who underwent surgery and postoperative RT were included. The data were collected from medical records, and survival outcomes were assessed using the Kaplan-Meier method, log-rank tests, and Cox regression models. RESULTS: In total, 350 patients participated in this study. Overall survival, locoregional recurrence-free survival, event-free survival, and distant metastasis-free survival rates did not significantly differ between those who received RT and those who did not. Multivariate analyses revealed that patients who received anthracycline or taxane chemotherapy had better survival outcomes. CONCLUSION: Our findings demonstrated that postoperative RT had no significant effect on overall survival, locoregional recurrence, event-free survival, or distant metastasis rates in patients with pathological stage IIB breast cancer. However, anthracycline- and taxane-based chemotherapies were associated with improved outcomes. These findings demonstrated the complexities of treating such patient populations with multimodal therapies. Further research is needed to ensure optimal postoperative RT in patients with pathological stage IIB breast cancer. Clinicians must consider individual patient characteristics and incorporate comprehensive treatment approaches to ensure successful outcomes in this population.

Toxoplasma gondii surface antigen 1 (SAG1) interacts in vitro with host cell receptor for activated C kinase 1 (RACK1).

Toxoplasma gondii (T. gondii) surface antigen 1 (SAG1) is crucial for tachyzoite invasion into host cells. However, the role of SAG1 in interaction with host cells remains unknown. The primary objective of this study was to analyze and validate the interaction between SAG1 and host cells. RACK1, an intracellular multifunctional protein, was identified as a SAG1 binding partner in host cells. Furthermore, the expression of RACK1 is manipulated by SAG1, and depletion of RACK1 negatively regulated host cell viability. These results imply that through interaction with RACK1, SAG1 preserves the viability of host cells to satisfy the survival needs of T. gondii. Our findings suggest a novel role for SAG1 in intracellular parasitism.

Self-assembly flexible SERS imprinted membrane based on Ag nanocubes for selective detection of microcystin-LR.

Silver nanocubes monolayer-modified polydimethylsiloxane (Ag NC/PDMS) flexible SERS substrates have been prepared by a three-phase interface self-assembly procedure. The combination of this method with membrane technology brings nanoparticles in close proximity, densely, and regularly arranged in monolayers over a large area, leading to excellent SERS properties. Considering the complexity of practical detection, molecular imprinted polymers (MIPs) were anchored on the surface of SERS substrate and applied to selective detection of microcystin-LR (MC-LR). It is worth mentioning that the SERS imprinted membranes (AP-MIMs) were still clearly detected at a concentration of 0.1 µg·L-1 of MC-LR in drinking water, and the detection limit was as low as 0.0067 µg·L-1. The substrate exhibited excellent uniformity with a relative standard deviation (RSD) of 6.1%. In the presence of interference molecules, AP-MIMs exhibited excellent selectivity for MC-LR. Furthermore, in the spiking and recovery tests of practical lake water samples, the method showed excellent recoveries ranging from 96.47 to 105.31%. It has been demonstrated that the prepared AP-MIMs can be applied to sensitive and specific detection of trace amounts of MC-LR in drinking water.

Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation.

The role of fibrillar collagen in the tissue microenvironment is critical in disease contexts ranging from cancers to chronic inflammations, as evidenced by many studies. Quantifying fibrillar collagen organization has become a powerful approach for characterizing the topology of collagen fibers and studying the role of collagen fibers in disease progression. We present a deep learning-based pipeline to quantify collagen fibers' topological properties in microscopy-based collagen images from pathological tissue samples. Our method leverages deep neural networks to extract collagen fiber centerlines and deep generative models to create synthetic training data, addressing the current shortage of large-scale annotations. As a part of this effort, we have created and annotated a collagen fiber centerline dataset, with the hope of facilitating further research in this field. Quantitative measurements such as fiber orientation, alignment, density, and length can be derived based on the centerline extraction results. Our pipeline comprises three stages. Initially, a variational autoencoder is trained to generate synthetic centerlines possessing controllable topological properties. Subsequently, a conditional generative adversarial network synthesizes realistic collagen fiber images from the synthetic centerlines, yielding a synthetic training set of image-centerline pairs. Finally, we train a collagen fiber centerline extraction network using both the original and synthetic data. Evaluation using collagen fiber images from pancreas, liver, and breast cancer samples collected via second-harmonic generation microscopy demonstrates our pipeline's superiority over several popular fiber centerline extraction tools. Incorporating synthetic data into training further enhances the network's generalizability. Our code is available at https://github.com/uw-loci/collagen-fiber-metrics.

Prevalence and determinants of food insecurity during the 2022 COVID-19 related lockdown in Shanghai.

The SARS-CoV-2 coronavirus pandemic has led to increased food insecurity levels. This cross-sectional study examines the prevalence and determinants of food insecurity during the two-month (1 April to 1 June 2022) city-wide lockdown in Shanghai. The data was collected via an online questionnaire from 3230 adult Shanghai residents during the lockdown. Food insecurity was measured using an adapted version of the Household Food Insecurity Access Scale. Nearly 70% of participants reported being exposed to food insecurity. Using multivariable logistic regressions, we examined the associations between key correlates (i.e. age, income, lockdown-related income loss, migration, employment status, social capital, preparedness, and received social support) and overall food insecurity while adjusting for ethnicity, gender, education, household size, and marital status. Results showed that compared to local Shanghai residents, migrants (i.e, permanent migrants with Hukou (OR = 2.16), permanent migrants without Hukou (OR = 2.06), temporary migrants (OR = 2.74)), and participants with less than or greather than 50% lockdown-related income loss (OR = 2.60, OR = 3.09), were associated with higher odds of overall food insecurity. Participants with greater preparedness (OR = 0.66), greater bonding social capital (OR = 0.93), and greater bridging social capital (OR = 0.94), had lower odds of overall food insecurity. Targeted interventions are needed to enhance food resilience and health equity among vulnerable populations.

Changes in carotid artery texture by ultrasound and elastin features in a murine model.

Objective: In humans, arterial grayscale ultrasound texture features independently predict adverse cardiovascular disease (CVD) events and change with medical interventions. We performed this study to examine how grayscale ultrasound texture features and elastin fibers change in plaque-free segments of the arterial wall in a murine model prone to atherosclerosis. Methods: A total of 10 Apoetm1Unc/J mice (n = 5 male, n = 5 female) were imaged at 6, 16, and 24 weeks of age. Two mice were euthanized at 6 and 16 weeks and the remaining mice at 24 weeks. Texture features were extracted from the ultrasound images of the distal 1.0 mm of the common carotid artery wall, and elastin measures were extracted from histology images. Two-way analysis of variance was used to evaluate associations between week, sex, and grayscale texture features. Texture feature and elastin number comparisons between weeks were conducted using the sex-by-week two-way interaction contrasts. Sex-specific correlations between the number of elastin fibers and grayscale texture features were analyzed by conducting non-parametric Spearman's rank correlation analyses. Results: Arterial wall homogeneity changed significantly in male mice from 6 to 24 weeks, with a mean (SD) of 0.14 (0.03) units at 6 weeks and 0.18 (0.03) units at 24 weeks (p = 0.026). Spatial gray level dependence matrices-homogeneity (SGLD-HOM) also correlated with carotid artery plaque score (rs = 0.707, p = 0.033). Elastin fibers in the region of interest decreased from 6 to 24 weeks for both male and female mice, although only significantly in male mice. The mean (SD) number of elastin fibers for male mice was 5.32 (1.50) at 6 weeks and 3.59 (0.38) at 24 weeks (p = 0.023). For female mice, the mean (SD) number of elastin fibers was 3.98 (0.38) at 6 weeks and 3.46 (0.19) at 24 weeks (p = 0.051). Conclusion: Grayscale ultrasound texture features that are associated with increased risk for CVD events in humans were used in a murine model, and the grayscale texture feature SGLD-HOM was shown to change in male mice from 6 weeks to 24 weeks. Structural alterations of the arterial wall (change in elastin fiber number) were observed during this time and may differ by sex.