100 research outputs found

    CLIP goes 3D: Leveraging Prompt Tuning for Language Grounded 3D Recognition

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    Vision-Language models like CLIP have been widely adopted for various tasks due to their impressive zero-shot capabilities. However, CLIP is not suitable for extracting 3D geometric features as it was trained on only images and text by natural language supervision. We work on addressing this limitation and propose a new framework termed CG3D (CLIP Goes 3D) where a 3D encoder is learned to exhibit zero-shot capabilities. CG3D is trained using triplets of pointclouds, corresponding rendered 2D images, and texts using natural language supervision. To align the features in a multimodal embedding space, we utilize contrastive loss on 3D features obtained from the 3D encoder, as well as visual and text features extracted from CLIP. We note that the natural images used to train CLIP and the rendered 2D images in CG3D have a distribution shift. Attempting to train the visual and text encoder to account for this shift results in catastrophic forgetting and a notable decrease in performance. To solve this, we employ prompt tuning and introduce trainable parameters in the input space to shift CLIP towards the 3D pre-training dataset utilized in CG3D. We extensively test our pre-trained CG3D framework and demonstrate its impressive capabilities in zero-shot, open scene understanding, and retrieval tasks. Further, it also serves as strong starting weights for fine-tuning in downstream 3D recognition tasks.Comment: Website: https://jeya-maria-jose.github.io/cg3d-web

    Ethyl gallate isolated from phenol-enriched fraction of Caesalpinia mimosoides Lam. Promotes cutaneous wound healing: a scientific validation through bioassay-guided fractionation

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    The tender shoots of Caesalpinia mimosoides Lam. are used ethnomedically by the traditional healers of Uttara Kannada district, Karnataka (India) for the treatment of wounds. The current study was aimed at exploring phenol-enriched fraction (PEF) of crude ethanol extract of tender shoots to isolate and characterize the most active bio-constituent through bioassay-guided fractionation procedure. The successive fractionation and sub-fractionation of PEF, followed by in vitro scratch wound, antimicrobial, and antioxidant activities, yielded a highly active natural antioxidant compound ethyl gallate (EG). In vitro wound healing potentiality of EG was evidenced by a significantly higher percentage of cell migration in L929 fibroblast cells (97.98 ± 0.46% at 3.81 μg/ml concentration) compared to a positive control group (98.44 ± 0.36%) at the 48th hour of incubation. A significantly higher rate of wound contraction (98.72 ± 0.41%), an elevated tensile strength of the incised wound (1,154.60 ± 1.42 g/mm2), and increased quantity of connective tissue elements were observed in the granulation tissues of the 1% EG ointment treated animal group on the 15th post-wounding day. The accelerated wound healing activity of 1% EG was also exhibited by histopathological examinations through Hematoxylin and Eosin, Masson’s trichome, and Toluidine blue-stained sections. Significant up-regulation of enzymatic and non-enzymatic antioxidant contents (reduced glutathione, superoxide dismutase, and catalase) and down-regulation of oxidative stress marker (lipid peroxidation) clearly indicates the effective granular antioxidant activity of 1% EG in preventing oxidative damage to the skin tissues. Further, in vitro antimicrobial and antioxidant activities of EG supports the positive correlation with its enhanced wound-healing activity. Moreover, molecular docking and dynamics for 100 ns revealed the stable binding of EG with cyclooxygenase-2 (−6.2 kcal/mol) and matrix metalloproteinase-9 (−4.6 kcal/mol) and unstable binding with tumor necrosis factor-α (−7.2 kcal/mol), suggesting the potential applicability of EG in inflammation and wound treatment

    Elucidating type 2 diabetes mellitus risk factor by promoting lipid metabolism with gymnemagenin: An in vitro and in silico approach

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    Introduction: Adipose tissue functions as a key endocrine organ which releases multiple bioactive substances and regulate obesity-linked complications. Dysregulation of adipocyte differentiation, triglyceride metabolism, adipokines production and lipid transport contributes to impaired lipid metabolism resulting in obesity, insulin resistance and type 2 diabetes. Gymnema sylvestre plant is frequently used in Ayurveda for treatment of diabetes and obesity. Gymnemagenin is a major bioactive compound of Gymnema sylvestre. The present study was undertaken to elucidate the role of gymnemagenin in lipid metabolism by in vitro and computational approaches.Methods: A panel of twelve genes viz., Fasn, Lipe, Lpl, Pparg, Plin2, Cidea, Scd1, Adipoq, Lep, Ccl2, Fabp4, and Slc2a4, essential in lipid metabolism were selected and gene expression pattern and triglyceride content were checked in adipocytes (3T3L1 cells) with/without treatment of gymnemagenin by Real time PCR and colorimetric estimation, respectively. Mode of action of gymnemagenin on Pparg and Fabp4 was accomplished by computational studies. Gene set enrichment and network pharmacology were performed by STRING and Cytoscape. Molecular docking was performed by AutoDock vina by POAP pipeline. Molecular dynamics, MM-PBSA were done by Gromacs tool.Results:In vitro study showed that gymnemagenin improved triglyceride metabolism by up regulating the expression of lipase genes viz., Lipe and Lpl which hydrolyse triglyceride. Gymnemagenin also up regulated the expression of anti-inflammatory gene Adipoq. Importantly, gymnemagenin treatment up regulated the expression of Pparg gene and the downstream target genes (Plin2, Cidea, and Scd1) which are associated with adipogenesis. However, gymnemagenin has no effect on expression of Fabp4, codes for a lipid transport protein. In silico study revealed that gymnemagenin targeted 12 genes were modulating 6 molecular pathways involved in diabetes and obesity. Molecular docking and dynamics revealed that gymnemagenin stably bind to active site residue of Pparg and failed to bind to Fabp4 active site compared to its standard molecules throughout 100 ns MD production run. Gymnemagenin scored binding free energy of −177.94 and −25.406 kJ/mol with Pparg and Fabp4, respectively.Conclusion: Gymnemagenin improved lipid metabolism by increasing triglyceride hydrolysis (lipolysis), up regulating the crucial gene of adipogenesis and increasing the expression of anti-inflammatory adipokine proving its therapeutic importance as anti-obesity and anti-diabetic phytocompound

    Comparison of two fluorescent probes in preclinical non-invasive imaging and image-guided debridement surgery of Staphylococcal biofilm implant infections

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    Abstract Implant-associated infections are challenging to diagnose and treat. Fluorescent probes have been heralded as a technologic advancement that can improve our ability to non-invasively identify infecting organisms, as well as guide the inexact procedure of surgical debridement. This study’s purpose was to compare two fluorescent probes for their ability to localize Staphylococcus aureus biofilm infections on spinal implants utilizing noninvasive optical imaging, then assessing the broader applicability of the more successful probe in other infection animal models. This was followed by real-time, fluorescence image-guided surgery to facilitate debridement of infected tissue. The two probe candidates, a labelled antibiotic that targets peptidoglycan (Vanco-800CW), and the other, a labelled antibody targeting the immunodominant Staphylococcal antigen A (1D9-680), were injected into mice with spine implant infections. Mice were then imaged noninvasively with near infrared fluorescent imaging at wavelengths corresponding to the two probe candidates. Both probes localized to the infection, with the 1D9-680 probe showing greater fidelity over time. The 1D9-680 probe was then tested in mouse models of shoulder implant and allograft infection, demonstrating its broader applicability. Finally, an image-guided surgery system which superimposes fluorescent signals over analog, real-time, tissue images was employed to facilitate debridement of fluorescent-labelled bacteria

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH -Mutant Molecular Profiles

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    Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahepatic CCA cases and propose a molecular classification scheme. We identified an IDH mutant-enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance
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