cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25549/inscriptifact-ouc1sto800948
title: InscriptiFact -- an image database of inscriptions and artifacts

description: The InscriptiFact Collection is designed to allow access via the Internet to high-resolution images of ancient inscriptions and artifacts, primarily from the Near Eastern and Mediterranean Worlds. The targeted inscriptions constitute some of the world’s earliest written records, which are mostly housed in a number of international museums and libraries, as well as field projects where inscriptions still remain in situ. Included, for example, are, selected Dead Sea Scrolls; cuneiform tablets from Mesopotamia, Persia, Canaan and Egypt; early Jewish papyri from Egypt; lapidary inscriptions, primarily from Jordan, Lebanon and Cyprus; inscriptions on a variety of hard media (e.g., ostraca, copper, semi-precious stones, jar handles) mostly written in early Canaanite, Phoenician, Hebrew, Aramaic, Ammonite and Edomite; and much more. These ancient texts are foundational documents that serve as a point of reference for Judaism, Christianity, Islam and the cultures out of which they emerged. The name "InscriptiFact" is intended to convey the concept of a scholarly archive based on "facts" about "inscriptions" and "artifacts." West Semitic Research Project (WSRP) under the auspices of the University of Southern California (USC) is broadly acknowledged as a leader in the application of photographic and digital technologies to capture and analyze data of ancient texts. The West Semitic Research image archive now contains approximately 1,500,000 images. Important! Search terms with more than one word or number need to be enclosed in quotation marks.Guide to Searching InscriptiFact
DOI: 10.25549/inscriptifact-ouc110807005
title: Mesha Inscription, KAI 181, Mesha' Inscription, Mesha'-Inschrift, Mesha Stela, Mesha' Stela

description: [Text Description:] Commemoration of military actions and building projects of Mesha, King of Moab ❧ [Text or Publication Number Note:] KAI 181 ❧ [Excavation Description:] Discovered in 1868 by a German missionary in Diban (Dhiban) ❧ [Medium:] Stone ❧ [Script Note:] Moabite ❧ [Physical Object Description:] Basalt Stone, 1.1 meters high, 60-68 cm wide (or 1.15 m x 60 cm), rounded at the top ❧ [Physical Object Note:] Present stele has been restored from fragments, and missing text reconstructed based on paper squeezes
DOI: 10.25549/inscriptifact-ouc15235060
title: Document of Wifehood

description: [Text or Publication Number Note:] TAD B3.8; Kraeling 7, 15, 18/1, 3,8,13,18,19,22,26,30 ❧ [Excavation Description:] Found by farmers in tell on island of Elephantine; acquired by Charles Edwin Wilbour in 1893 ❧ [Medium:] Papyrus ❧ [Script Note:] Aramaic ❧ [Physical Object Description:] Papyrus, BM 47.218.150+97; BM 47.218.155 frgs 1,3,8,13,18,19,22,26,30
DOI: 10.25549/inscriptifact-ouc110807001
title: Mesha Inscription, KAI 181, Mesha' Inscription, Mesha'-Inschrift, Mesha Stela, Mesha' Stela

description: [Text Description:] Commemoration of military actions and building projects of Mesha, King of Moab ❧ [Text or Publication Number Note:] KAI 181 ❧ [Excavation Description:] Discovered in 1868 by a German missionary in Diban (Dhiban) ❧ [Medium:] Stone ❧ [Script Note:] Moabite ❧ [Physical Object Description:] Basalt Stone, 1.1 meters high, 60-68 cm wide (or 1.15 m x 60 cm), rounded at the top ❧ [Physical Object Note:] Present stele has been restored from fragments, and missing text reconstructed based on paper squeezes
DOI: 10.25549/inscriptifact-ouc110805657
title: Part of painted plaster wall

description: [Text Description:] Red, blue and black decoration with lines, circles and rosettes. ❧ [Excavation Description:] Ziyaret Tepe Archaeological Project, an international collaboration led by Prof. Tim Matney of the University of Akron, Ohio ❧ [Medium:] Plaster ❧ [Script Note:] Non-Text ❧ [Physical Object Description:] Assemblage of painted wall plaster
DOI: 10.25549/inscriptifact-ouc110805651
title: Part of painted plaster wall

description: [Text Description:] Red, blue and black decoration with lines, circles and rosettes. ❧ [Excavation Description:] Ziyaret Tepe Archaeological Project, an international collaboration led by Prof. Tim Matney of the University of Akron, Ohio ❧ [Medium:] Plaster ❧ [Script Note:] Non-Text ❧ [Physical Object Description:] Assemblage of painted wall plaster
DOI: 10.25549/inscriptifact-ouc110806982
title: Mesha Inscription, KAI 181, Mesha' Inscription, Mesha'-Inschrift, Mesha Stela, Mesha' Stela

description: [Text Description:] Commemoration of military actions and building projects of Mesha, King of Moab ❧ [Text or Publication Number Note:] KAI 181 ❧ [Excavation Description:] Discovered in 1868 by a German missionary in Diban (Dhiban) ❧ [Medium:] Stone ❧ [Script Note:] Moabite ❧ [Physical Object Description:] Basalt Stone, 1.1 meters high, 60-68 cm wide (or 1.15 m x 60 cm), rounded at the top ❧ [Physical Object Note:] Present stele has been restored from fragments, and missing text reconstructed based on paper squeezes
DOI: 10.6084/m9.figshare.25195956
title: Anti-diabetic drug discovery using the bioactive compounds of <i>Momordica charantia</i> by molecular docking and molecular dynamics analysis

description: Diabetes mellitus (DM) is a multifactorial life-threatening endocrine disease characterized by abnormalities in glucose metabolism. It is a chronic metabolic disease that involves multiple enzymes such as α-amylase and α-glucosidases. Inhibition of these enzymes has been identified as a promising method for managing diabetes, and researchers are currently focusing on discovering novel α-amylase and α-glucosidase inhibitors for diabetes therapy. Hence, we have selected 12 bioactive compounds from the <i>Momordica charantia</i> (MC) plant and performed a virtual screening and molecular dynamics investigation to identify natural inhibitors of α-amylase and α-glucosidases. Our <i>in silico</i> result revealed that phytocompound Rutin showed the highest binding affinity against α-amylase (1HNY) enzymes at (−11.68 kcal/mol), followed by Karaviloside II (−9.39), Momordicoside F (−9.19), Campesterol (−9.11. While docking against α-glucosidases (4J5T), Rutin again showed the greatest binding affinity (−11.93 kcal/mol), followed by Momordicine (−9.89), and Campesterol (−8.99). Molecular dynamics (MD) simulation research is currently the gold standard for drug design and discovery. Consequently, we conducted simulations of 100 nanoseconds (ns) to assess the stability of protein-ligand complexes based on parameters like RMSD, RMSF, RG, PCA, and FEL. The significance of our findings indicates that rutin from MC might serve as an effective natural therapeutic agent for diabetes management due to its strongest binding affinities with α-amylase and α-glucosidase enzymes. Further research in animals and humans is essential to validate the efficacy of these drug molecules.
DOI: 10.6084/m9.figshare.25195956.v1
title: Anti-diabetic drug discovery using the bioactive compounds of <i>Momordica charantia</i> by molecular docking and molecular dynamics analysis

description: Diabetes mellitus (DM) is a multifactorial life-threatening endocrine disease characterized by abnormalities in glucose metabolism. It is a chronic metabolic disease that involves multiple enzymes such as α-amylase and α-glucosidases. Inhibition of these enzymes has been identified as a promising method for managing diabetes, and researchers are currently focusing on discovering novel α-amylase and α-glucosidase inhibitors for diabetes therapy. Hence, we have selected 12 bioactive compounds from the <i>Momordica charantia</i> (MC) plant and performed a virtual screening and molecular dynamics investigation to identify natural inhibitors of α-amylase and α-glucosidases. Our <i>in silico</i> result revealed that phytocompound Rutin showed the highest binding affinity against α-amylase (1HNY) enzymes at (−11.68 kcal/mol), followed by Karaviloside II (−9.39), Momordicoside F (−9.19), Campesterol (−9.11. While docking against α-glucosidases (4J5T), Rutin again showed the greatest binding affinity (−11.93 kcal/mol), followed by Momordicine (−9.89), and Campesterol (−8.99). Molecular dynamics (MD) simulation research is currently the gold standard for drug design and discovery. Consequently, we conducted simulations of 100 nanoseconds (ns) to assess the stability of protein-ligand complexes based on parameters like RMSD, RMSF, RG, PCA, and FEL. The significance of our findings indicates that rutin from MC might serve as an effective natural therapeutic agent for diabetes management due to its strongest binding affinities with α-amylase and α-glucosidase enzymes. Further research in animals and humans is essential to validate the efficacy of these drug molecules.
DOI: 10.25549/inscriptifact-ouc110806992
title: Mesha Inscription, KAI 181, Mesha' Inscription, Mesha'-Inschrift, Mesha Stela, Mesha' Stela

description: [Text Description:] Commemoration of military actions and building projects of Mesha, King of Moab ❧ [Text or Publication Number Note:] KAI 181 ❧ [Excavation Description:] Discovered in 1868 by a German missionary in Diban (Dhiban) ❧ [Medium:] Stone ❧ [Script Note:] Moabite ❧ [Physical Object Description:] Basalt Stone, 1.1 meters high, 60-68 cm wide (or 1.15 m x 60 cm), rounded at the top ❧ [Physical Object Note:] Present stele has been restored from fragments, and missing text reconstructed based on paper squeezes
DOI: 10.25549/inscriptifact-ouc110805646
title: Part of painted plaster wall

description: [Text Description:] Red, blue and black decoration with lines, circles and rosettes. ❧ [Excavation Description:] Ziyaret Tepe Archaeological Project, an international collaboration led by Prof. Tim Matney of the University of Akron, Ohio ❧ [Medium:] Plaster ❧ [Script Note:] Non-Text ❧ [Physical Object Description:] Assemblage of painted wall plaster
DOI: 10.6084/m9.figshare.28100034
title: Is it feasible to use AI-based drug design methods in the process of generating effective COVID-19 inhibitors? A validation study using molecular docking, molecular simulation, and pharmacophore methods

description: Although the COVID-19 pandemic has been brought under control to some extent globally, there is still debate in the industry about the feasibility of using artificial intelligence (AI) to generate COVID small-molecule inhibitors. In this study, we explored the feasibility of using AI to design effective inhibitors of COVID-19. By combining a generative model with reinforcement learning and molecular docking, we designed small-molecule inhibitors targeting the COVID-19 3CLpro enzyme. After screening based on molecular docking scores and physicochemical properties, we obtained five candidate inhibitors. Furthermore, theoretical calculations confirmed that these candidate inhibitors have significant binding stability with COVID-19 3CLpro, comparable to or better than existing COVID-19 inhibitors. Additionally, through ligand-based pharmacophore model screening, we validated the effectiveness of the generative model, demonstrating the potential value of AI in drug design.
DOI: 10.6084/m9.figshare.28100034.v1
title: Is it feasible to use AI-based drug design methods in the process of generating effective COVID-19 inhibitors? A validation study using molecular docking, molecular simulation, and pharmacophore methods

description: Although the COVID-19 pandemic has been brought under control to some extent globally, there is still debate in the industry about the feasibility of using artificial intelligence (AI) to generate COVID small-molecule inhibitors. In this study, we explored the feasibility of using AI to design effective inhibitors of COVID-19. By combining a generative model with reinforcement learning and molecular docking, we designed small-molecule inhibitors targeting the COVID-19 3CLpro enzyme. After screening based on molecular docking scores and physicochemical properties, we obtained five candidate inhibitors. Furthermore, theoretical calculations confirmed that these candidate inhibitors have significant binding stability with COVID-19 3CLpro, comparable to or better than existing COVID-19 inhibitors. Additionally, through ligand-based pharmacophore model screening, we validated the effectiveness of the generative model, demonstrating the potential value of AI in drug design.
DOI: 10.25549/inscriptifact-ouc110806962
title: Mesha Inscription, KAI 181, Mesha' Inscription, Mesha'-Inschrift, Mesha Stela, Mesha' Stela

description: [Text Description:] Commemoration of military actions and building projects of Mesha, King of Moab ❧ [Text or Publication Number Note:] KAI 181 ❧ [Excavation Description:] Discovered in 1868 by a German missionary in Diban (Dhiban) ❧ [Medium:] Stone ❧ [Script Note:] Moabite ❧ [Physical Object Description:] Basalt Stone, 1.1 meters high, 60-68 cm wide (or 1.15 m x 60 cm), rounded at the top ❧ [Physical Object Note:] Present stele has been restored from fragments, and missing text reconstructed based on paper squeezes
DOI: 10.6084/m9.figshare.25265849
title: Caffeic acid, a dietary polyphenol, pre-sensitizes pancreatic ductal adenocarcinoma to chemotherapeutic drug

description: Resistance to chemotherapeutics is an eminent cause that leads to search for options that help in diminution of pancreatic ductal adenocarcinoma (PDAC) by overcoming resistance issues. Caffeic acid (CFA), a polyphenol occurring in many dietary foods, is known to show antidiabetic and anticancer properties potential. To unveil the effect of CFA on PDAC, we carried out this research in PDAC cells, following which we checked the combination effect of CFA and chemotherapeutics and pre-sensitization effects of CFA. Multitudinous web-based approaches were applied for identifying CFA targets in PDAC and then getting their interconnections. Subsequently, we manifested CFA effects by <i>in-vitro</i> analysis showing IC<sub>50</sub> concentrations of 37.37 and 15.06 µM on Panc-1 and Mia-PaCa-2, respectively. The combination index of CFA with different drugs was explored which showed the antagonistic effects of combination treatment leading to further investigation of the pre-sensitizing effects. CFA pre-sensitization reduced IC<sub>50</sub> concentration of doxorubicin in both PDAC cell lines which also triggered ROS generation determined by 2′,7′-dichlorofluorescin diacetate assay. The differential gene expression analysis after CFA treatment showed discrete genes affected in both cells, i.e. N-Cad and Cas9 in Panc-1 and Pi3K/AkT/mTOR along with p53 in Mia-PaCa-2. Collectively, this study investigated the role of CFA as PDAC therapeutics and explored the mechanism in mitigating resistance of PDAC by sensitizing to chemotherapeutics.
DOI: 10.6084/m9.figshare.25265849.v1
title: Caffeic acid, a dietary polyphenol, pre-sensitizes pancreatic ductal adenocarcinoma to chemotherapeutic drug

description: Resistance to chemotherapeutics is an eminent cause that leads to search for options that help in diminution of pancreatic ductal adenocarcinoma (PDAC) by overcoming resistance issues. Caffeic acid (CFA), a polyphenol occurring in many dietary foods, is known to show antidiabetic and anticancer properties potential. To unveil the effect of CFA on PDAC, we carried out this research in PDAC cells, following which we checked the combination effect of CFA and chemotherapeutics and pre-sensitization effects of CFA. Multitudinous web-based approaches were applied for identifying CFA targets in PDAC and then getting their interconnections. Subsequently, we manifested CFA effects by <i>in-vitro</i> analysis showing IC<sub>50</sub> concentrations of 37.37 and 15.06 µM on Panc-1 and Mia-PaCa-2, respectively. The combination index of CFA with different drugs was explored which showed the antagonistic effects of combination treatment leading to further investigation of the pre-sensitizing effects. CFA pre-sensitization reduced IC<sub>50</sub> concentration of doxorubicin in both PDAC cell lines which also triggered ROS generation determined by 2′,7′-dichlorofluorescin diacetate assay. The differential gene expression analysis after CFA treatment showed discrete genes affected in both cells, i.e. N-Cad and Cas9 in Panc-1 and Pi3K/AkT/mTOR along with p53 in Mia-PaCa-2. Collectively, this study investigated the role of CFA as PDAC therapeutics and explored the mechanism in mitigating resistance of PDAC by sensitizing to chemotherapeutics.
DOI: 10.25549/inscriptifact-ouc110805642
title: Part of painted plaster wall

description: [Text Description:] Red, blue and black decoration with lines, circles and rosettes. ❧ [Excavation Description:] Ziyaret Tepe Archaeological Project, an international collaboration led by Prof. Tim Matney of the University of Akron, Ohio ❧ [Medium:] Plaster ❧ [Script Note:] Non-Text ❧ [Physical Object Description:] Assemblage of painted wall plaster
DOI: 10.6084/m9.figshare.25265828
title: Network pharmacology integrated molecular docking of fucoidan against oral cancer and <i>in vitro</i> evaluation- A study using GEO datasets

description: Oral cancer is a widespread health concern in rural India due to a lack of awareness, delayed diagnosis and limited access to affordable treatment options. The current chemotherapy has notable side effects, underscoring the need for new drug candidates with improved bioavailability and specificity. In this current research, fucoidan, a sulphated polysaccharide, was extracted from the brown algae <i>Spatoglossum asperum,</i> and shown to be cytotoxic <i>in vitro</i> against oral cancer cells (KB cell line) at an IC<sub>50</sub> of 107.76 µg/ml, suggesting its potential as a drug candidate. This study further aimed to explore the potential therapeutic implications of fucoidan in managing oral cancer using network pharmacology. PharmMapper, Comparative Toxicogenomics Database and SuperPred were initially used to identify fucoidan protein targets. The identified targets were further screened against Gene Expression Omnibus (GSE23558, GSE25099 and GSE146483), OMIM, TCGA and GeneCards datasets to identify oral cancer-specific protein targets. The interactions between the selected proteins were visualised using STRING and Cytoscape. Subsequently, <b>D</b>atabase for <b>A</b>nnotation, <b>V</b>isualization and <b>I</b>ntegrated <b>D</b>iscovery was used for gene ontology and <b>K</b>yoto <b>E</b>ncyclopedia of <b>G</b>enes and <b>G</b>enomes pathway enrichment analysis of candidate targets. The cancer-related network was assessed using CancerGeneNet, while life expectancy based on the expression of the top 10 CytoHubba ranked hub genes was evaluated using Kaplan-Meier plots. Finally, EGFR, AKT1, HSP90AA1 and SRC were selected for docking and molecular dynamics simulation with fucoidan, using Maestro and GROMACS, respectively.
DOI: 10.6084/m9.figshare.25265828.v1
title: Network pharmacology integrated molecular docking of fucoidan against oral cancer and <i>in vitro</i> evaluation- A study using GEO datasets

description: Oral cancer is a widespread health concern in rural India due to a lack of awareness, delayed diagnosis and limited access to affordable treatment options. The current chemotherapy has notable side effects, underscoring the need for new drug candidates with improved bioavailability and specificity. In this current research, fucoidan, a sulphated polysaccharide, was extracted from the brown algae <i>Spatoglossum asperum,</i> and shown to be cytotoxic <i>in vitro</i> against oral cancer cells (KB cell line) at an IC<sub>50</sub> of 107.76 µg/ml, suggesting its potential as a drug candidate. This study further aimed to explore the potential therapeutic implications of fucoidan in managing oral cancer using network pharmacology. PharmMapper, Comparative Toxicogenomics Database and SuperPred were initially used to identify fucoidan protein targets. The identified targets were further screened against Gene Expression Omnibus (GSE23558, GSE25099 and GSE146483), OMIM, TCGA and GeneCards datasets to identify oral cancer-specific protein targets. The interactions between the selected proteins were visualised using STRING and Cytoscape. Subsequently, <b>D</b>atabase for <b>A</b>nnotation, <b>V</b>isualization and <b>I</b>ntegrated <b>D</b>iscovery was used for gene ontology and <b>K</b>yoto <b>E</b>ncyclopedia of <b>G</b>enes and <b>G</b>enomes pathway enrichment analysis of candidate targets. The cancer-related network was assessed using CancerGeneNet, while life expectancy based on the expression of the top 10 CytoHubba ranked hub genes was evaluated using Kaplan-Meier plots. Finally, EGFR, AKT1, HSP90AA1 and SRC were selected for docking and molecular dynamics simulation with fucoidan, using Maestro and GROMACS, respectively.
DOI: 10.25549/inscriptifact-ouc110806958
title: Mesha Inscription, KAI 181, Mesha' Inscription, Mesha'-Inschrift, Mesha Stela, Mesha' Stela

description: [Text Description:] Commemoration of military actions and building projects of Mesha, King of Moab ❧ [Text or Publication Number Note:] KAI 181 ❧ [Excavation Description:] Discovered in 1868 by a German missionary in Diban (Dhiban) ❧ [Medium:] Stone ❧ [Script Note:] Moabite ❧ [Physical Object Description:] Basalt Stone, 1.1 meters high, 60-68 cm wide (or 1.15 m x 60 cm), rounded at the top ❧ [Physical Object Note:] Present stele has been restored from fragments, and missing text reconstructed based on paper squeezes
DOI: 10.25549/inscriptifact-ouc110805640
title: Part of painted plaster wall

description: [Text Description:] Red, blue and black decoration with lines, circles and rosettes. ❧ [Excavation Description:] Ziyaret Tepe Archaeological Project, an international collaboration led by Prof. Tim Matney of the University of Akron, Ohio ❧ [Medium:] Plaster ❧ [Script Note:] Non-Text ❧ [Physical Object Description:] Assemblage of painted wall plaster
DOI: 10.6084/m9.figshare.28072101
title: <i>In silico</i> screening of dicoumarols as potential <i>Mur B</i> enzyme inhibitors in <i>Mycobacterium tuberculosis</i>: molecular docking, ADME, QSAR and MD simulations

description: UDP-N-acetylenolpyruvoylglucosamine reductase (<i>Mur B)</i> from <i>Mycobacterium tuberculosis</i> has gathered significant pharmaceutical interest as a pivotal target because of its essential role in bacterial viability. This study employed computational methods to screen and assess the inhibitory potential of dicoumarol derivatives against the <i>Mur B</i> protein. A diverse set of dicoumarols, sourced from PubChem and Zinc database, is subjected to molecular docking, ADME studies, and MD simulations to elucidate interacting modes and stability. A QSAR model was constructed for dicoumarol derivatives based on known inhibitor MIC values against <i>Staphylococcus aureus</i> and <i>Mur B</i>. The four best dicoumarols (<b>CID142097979, CID54716867, CID91962283, CID54705236</b>) aligned well with the model. Subsequently, these dicoumarols were scrutinized <i>via</i> 200 ns MD simulations and MM-PBSA analysis to assess their complex stability with <i>Mur B</i> protein. Various MD simulation parameters such as RMSD, RMSF, Rg, H-bonds, PCA, and FEL were employed. The 200 ns MD simulation analysis outcomes indicated that the <b><i>Mur B-</i>CID54705236</b> complex exhibited the highest stability and possessed the binding energy of −59.96 kcal/mol further verifying its stability. The post-dynamic simulation analysis showed four hydrogen bond formations with Ser70, Asn71, Leu72 and Gln137 residues at the active site of <i>Mur B</i>. Overall, these results underscored dicoumarol derivatives as potential <i>Mur B</i> inhibitors and these findings can serve as a basis for further <i>in vitro</i> studies against <i>Mur B</i> protein.