1,724,765 research outputs found
Astronomische Nachrichten, 11" 3529-3544
No full textR. Astronomische Nachrichten, 11" 3529-3544. In: Bulletin astronomique, tome 17, 1900. pp. 152-160
Block Card 3529 Helene Court
No full textThis image was produced by the Auditor's Office in Lucas County, Ohio for tax assessment purposes. Associated dates are approximate. Descriptive terms related to this photograph include: Ranch Style | 3529 Helene Court (Toledo, Ohio) | Dwelling | Wajer-Brooks Addition | Trilby Are
Block Card 3529 Watson Avenue
No full textThis image was produced by the Auditor's Office in Lucas County, Ohio for tax assessment purposes. Associated dates are approximate. Descriptive terms related to this photograph include: dwelling | 3529 Watson Avenue (Toledo, Ohio) | Folk House Style | Craftsman Style | Almeda Heights Second Addition (Toledo, Ohio) | Willys Park area (Toledo, Ohio) | West Toledo (Toledo, Ohio
Block Card 3529 Burton Avenue
No full textThis image was produced by the Auditor's Office in Lucas County, Ohio for tax assessment purposes. Associated dates are approximate. Descriptive terms related to this photograph include: dwelling | 3529 Burton Avenue (Toledo, Ohio) | Cape Cod Style | Almeda Heights Second Addition (Toledo, Ohio) | Willys Park area (Toledo, Ohio) | West Toledo (Toledo, Ohio
Block Card 3529 Almeda Drive
No full textThis image was produced by the Auditor's Office in Lucas County, Ohio for tax assessment purposes. Associated dates are approximate. Descriptive terms related to this photograph include: dwelling | 3529 Almeda Drive (Toledo, Ohio) | Bungalow Style | Craftsman Style | Almeda Heights (Toledo, Ohio) | Willys Park area (Toledo, Ohio) | West Toledo (Toledo, Ohio
Delivery of miR‐3529‐3p using MnO2‐SiO2‐APTES nanoparticles combined with phototherapy suppresses lung adenocarcinoma progression by targeting HIGD1A
No full textAbstract Background The present study aimed to investigate the function of miR‐3529‐3p in lung adenocarcinoma and MnO2‐SiO2‐APTES (MSA) as a promising multifunctional delivery agent for lung adenocarcinoma therapy. Methods Expression levels of miR‐3529‐3p were evaluated in lung carcinoma cells and tissues by qRT‐PCR. The effects of miR‐3529‐3p on apoptosis, proliferation, metastasis and neovascularization were assessed by CCK‐8, FACS, transwell and wound healing assays, tube formation and xenografts experiments. Luciferase reporter assays, western blot, qRT‐PCR and mitochondrial complex assay were used to determine the targeting relationship between miR‐3529‐3p and hypoxia‐inducible gene domain family member 1A (HIGD1A). MSA was fabricated using MnO2 nanoflowers, and its heating curves, temperature curves, IC50, and delivery efficiency were examined. The hypoxia and reactive oxygen species (ROS) production was investigated by nitro reductase probing, DCFH‐DA staining and FACS. Results MiR‐3529‐3p expression was reduced in lung carcinoma tissues and cells. Transfection of miR‐3529‐3p could promote apoptosis and suppress cell proliferation, migration and angiogenesis. As a target of miR‐3529‐3p, HIGD1A expression was downregulated, through which miR‐3529‐3p could disrupt the activities of complexes III and IV of the respiratory chain. The multifunctional nanoparticle MSA could not only efficiently deliver miR‐3529‐3p into cells, but also enhance the antitumor function of miR‐3529‐3p. The underlying mechanism may be that MSA alleviates hypoxia and has synergistic effects in cellular ROS promotion with miR‐3529‐3p. Conclusions Our results establish the antioncogenic role of miR‐3529‐3p, and demonstrate that miR‐3529‐3p delivered by MSA has enhanced tumor suppressive effects, probably through elevating ROS production and thermogenesis
Henderson Plumbing Company - Henderson, Kentucky (SC 3529)
Full text linkFinding aid and scan (Click on Additional Files below) for Manuscripts Small Collection 3529. Undated letter of the Henderson Plumbing Company, Henderson, Kentucky promoting its services. The letterhead includes images of products used and a standard repair kit carried by servicemen. Attached to the letter is a sample of a fabric-reinforced washer for faucets
Recommended from our members
Abstract 3529: Leveraging deep learning for fully automated analysis of pre-clinical mouse positron emission tomography
No full textAbstract Turning early-cancer diagnosis into actionable treatment often relies on highly accurate and sensitive imaging techniques to guide surgical intervention or to monitor therapeutic efficacy. Earli is developing a highly sensitive, orthogonal approach that uses genetic constructs to usurp dysregulated cancer pathways to force the tumor to produce a PET reporter gene, enabling the use of radiotracers amenable to positron emission tomography/computed tomography (PET/CT) to guide precision imaging. However, analysis of PET/CT images using standard manual and semi-automated methods is challenging resulting in reduced experimental throughput and user variability, highlighting the need for a fully automated PET/CT analysis pipeline using Deep Learning (DL). To increase pre-clinical throughput and reduce inter-user variability, we developed an automated DL processing pipeline in Python to perform three major tasks: separation of multi-mouse bed data for PET uptake quantification by mouse, segmentation of tumors and background organs, and quantification of PET signal for PK/PD analysis. Preclinical PET/CT data was acquired using a 4 animal, multi-mouse bed and separated into individual mice by co-registering the reconstructed CT image against a multi-mouse bed reference mask using a rigid 3D Euler transformation algorithm and cropping at fixed indices. Following mouse separation, a 3D nnUNet architecture is used to perform semantic segmentation of regions of interest (ROI) on CT for bi-hemispheric subcutaneous tumors, lungs, liver, kidneys, spleen, and the bladder. nnUNet was trained on PET/CT of 311 mice consisting of a mixture of naïve and tumor-bearing animals subcutaneously implanted with H1299 cells using a five-fold cross-validation strategy with 1000 epochs per fold. Model performance was evaluated by comparing the network prediction to the reference manually annotated masks using the Dice coefficient. PET uptake is reported as percent injected dose per milliliter (%ID/mL) or standardized uptake value (SUV). Segmentation performance results for the hold-out set identified mean Dice scores greater than 0.80 for all ROIs, reflecting the similarity between model predictions and human annotations. The automated pipeline reduced the analysis time from 5.5-6 hours per mouse when using traditional manual/semi-automatic approaches to approximately 15 minutes. In summary, we developed a fully automated DL-based PET/CT quantification pipeline for pre-clinical mouse studies that provides accurate ROI segmentation and PET uptake quantification, significantly increasing experimental throughput and reducing inter-user variability. Further improvements to model inference include loss functions weighted for poor performing ROIs and addition of lung nodule segmentation for eventual translation to humans as an accompaniment to Earli’s theranostic programs. Citation Format: Hung-Yu Henry Lee, Mohammed Goryawala, Tim Sproul, Maggie Louie, David Suhy. Leveraging deep learning for fully automated analysis of pre-clinical mouse positron emission tomography [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3529
- …
