cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.tpvwx7
title: Occurrence Download

description: A dataset containing 110994 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Corallorhiza trifida"
 ]
}

 The dataset includes 110994 records from 426 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043391-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bn8x72
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amaranthus hybridus",
 "Country is Bulgaria",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043478-250717081556266/datasets/export for details.
DOI: 10.15468/dl.sd9v6k
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Caspiomyzon graecus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043477-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29442768
title: Evaluation of antihypertensive effects of <i>Ophioglossum vulgatum: in silico</i> and <i>in vivo</i> evidence in spontaneously hypertensive

description: This study investigated and evaluated the antihypertensive effects and mechanisms of <i>Ophioglossum vulgatum</i>(OV) through a combination of computational simulations and <i>in vivo</i> experiments.Initially, an <i>in silico</i> analysis using network pharmacology was employed to identify target proteins, followed by molecular docking and molecular dynamics simulations. Network pharmacology data indicated that OV may influence several pathways involved in blood pressure regulation. Molecular docking revealed the effective targets of OV, showing that some of its major active compounds could potentially bind directly to the active sites of angiotensin receptors and calcium channel proteins. <i>In vivo</i> experiments demonstrated that administration of 20 mg/kg crude OV extract to spontaneously hypertensive rats (SHR) significantly reduced mean blood pressure by 31.53% within 60 min, alleviating hypertensive symptoms. Based on our <i>in silico</i> and <i>in vivo</i> evidence, the rapid antihypertensive effects of OV may be related to its action on the RAS and calcium channels, leading to vasodilation.These acute antihypertensive effects suggest that OV has the potential to be a candidate for blood pressure medication, particularly for urgent blood pressure reduction, and an effective antihypertensive agent in plant-based medicine. This study investigated and evaluated the antihypertensive effects and mechanisms of <i>Ophioglossum vulgatum</i>(OV) through a combination of computational simulations and <i>in vivo</i> experiments. Initially, an <i>in silico</i> analysis using network pharmacology was employed to identify target proteins, followed by molecular docking and molecular dynamics simulations. Network pharmacology data indicated that OV may influence several pathways involved in blood pressure regulation. Molecular docking revealed the effective targets of OV, showing that some of its major active compounds could potentially bind directly to the active sites of angiotensin receptors and calcium channel proteins. <i>In vivo</i> experiments demonstrated that administration of 20 mg/kg crude OV extract to spontaneously hypertensive rats (SHR) significantly reduced mean blood pressure by 31.53% within 60 min, alleviating hypertensive symptoms. Based on our <i>in silico</i> and <i>in vivo</i> evidence, the rapid antihypertensive effects of OV may be related to its action on the RAS and calcium channels, leading to vasodilation. These acute antihypertensive effects suggest that OV has the potential to be a candidate for blood pressure medication, particularly for urgent blood pressure reduction, and an effective antihypertensive agent in plant-based medicine.
DOI: 10.6084/m9.figshare.29442768.v1
title: Evaluation of antihypertensive effects of <i>Ophioglossum vulgatum: in silico</i> and <i>in vivo</i> evidence in spontaneously hypertensive

description: This study investigated and evaluated the antihypertensive effects and mechanisms of <i>Ophioglossum vulgatum</i>(OV) through a combination of computational simulations and <i>in vivo</i> experiments.Initially, an <i>in silico</i> analysis using network pharmacology was employed to identify target proteins, followed by molecular docking and molecular dynamics simulations. Network pharmacology data indicated that OV may influence several pathways involved in blood pressure regulation. Molecular docking revealed the effective targets of OV, showing that some of its major active compounds could potentially bind directly to the active sites of angiotensin receptors and calcium channel proteins. <i>In vivo</i> experiments demonstrated that administration of 20 mg/kg crude OV extract to spontaneously hypertensive rats (SHR) significantly reduced mean blood pressure by 31.53% within 60 min, alleviating hypertensive symptoms. Based on our <i>in silico</i> and <i>in vivo</i> evidence, the rapid antihypertensive effects of OV may be related to its action on the RAS and calcium channels, leading to vasodilation.These acute antihypertensive effects suggest that OV has the potential to be a candidate for blood pressure medication, particularly for urgent blood pressure reduction, and an effective antihypertensive agent in plant-based medicine. This study investigated and evaluated the antihypertensive effects and mechanisms of <i>Ophioglossum vulgatum</i>(OV) through a combination of computational simulations and <i>in vivo</i> experiments. Initially, an <i>in silico</i> analysis using network pharmacology was employed to identify target proteins, followed by molecular docking and molecular dynamics simulations. Network pharmacology data indicated that OV may influence several pathways involved in blood pressure regulation. Molecular docking revealed the effective targets of OV, showing that some of its major active compounds could potentially bind directly to the active sites of angiotensin receptors and calcium channel proteins. <i>In vivo</i> experiments demonstrated that administration of 20 mg/kg crude OV extract to spontaneously hypertensive rats (SHR) significantly reduced mean blood pressure by 31.53% within 60 min, alleviating hypertensive symptoms. Based on our <i>in silico</i> and <i>in vivo</i> evidence, the rapid antihypertensive effects of OV may be related to its action on the RAS and calcium channels, leading to vasodilation. These acute antihypertensive effects suggest that OV has the potential to be a candidate for blood pressure medication, particularly for urgent blood pressure reduction, and an effective antihypertensive agent in plant-based medicine.
DOI: 10.6084/m9.figshare.29125636
title: From lab-to-clinic with model informed formulation development: a case study of hydroxyzine SR tablets

description: Model Informed Formulation Development (MIFD) uses physiologically based pharmacokinetic (PBPK) modelling and other <i>in silico</i> tools to facilitate new product development. These tools help set target profiles, predict <i>in vivo</i> formulation performance, guide iterative development, define dissolution parameters, and convince the regulatory agencies about a drug’s safety and efficacy.This study involves development of a sustained release formulation for Hydroxyzine, an anti-histamine with sedation as a significant side effect. The aim was to design a formulation that releases the drug slowly, reducing the peak plasma concentration without losing on the effectiveness. A preliminary absorption model was developed using immediate release formulation data, and various hypothetical dissolution profiles were evaluated in this model. The new drug product, manufactured using Matrixeal<sup>TM</sup> technology, underwent preliminary bioequivalence (BE) studies in healthy volunteers. These results were used to refine the model and further modify the formulation, whose performance was predicted <i>via</i> virtual BE studies. Confirmatory BE studies with 70 volunteers under fasting state validated the new formulation. The model also established clinically relevant dissolution specifications and assessed the food effect on the drug product.This work showcases the application of PBPK modelling in developing new modified release drug product of Hydroxyzine. Model Informed Formulation Development (MIFD) uses physiologically based pharmacokinetic (PBPK) modelling and other <i>in silico</i> tools to facilitate new product development. These tools help set target profiles, predict <i>in vivo</i> formulation performance, guide iterative development, define dissolution parameters, and convince the regulatory agencies about a drug’s safety and efficacy. This study involves development of a sustained release formulation for Hydroxyzine, an anti-histamine with sedation as a significant side effect. The aim was to design a formulation that releases the drug slowly, reducing the peak plasma concentration without losing on the effectiveness. A preliminary absorption model was developed using immediate release formulation data, and various hypothetical dissolution profiles were evaluated in this model. The new drug product, manufactured using Matrixeal<sup>TM</sup> technology, underwent preliminary bioequivalence (BE) studies in healthy volunteers. These results were used to refine the model and further modify the formulation, whose performance was predicted <i>via</i> virtual BE studies. Confirmatory BE studies with 70 volunteers under fasting state validated the new formulation. The model also established clinically relevant dissolution specifications and assessed the food effect on the drug product. This work showcases the application of PBPK modelling in developing new modified release drug product of Hydroxyzine.
DOI: 10.6084/m9.figshare.29125636.v1
title: From lab-to-clinic with model informed formulation development: a case study of hydroxyzine SR tablets

description: Model Informed Formulation Development (MIFD) uses physiologically based pharmacokinetic (PBPK) modelling and other <i>in silico</i> tools to facilitate new product development. These tools help set target profiles, predict <i>in vivo</i> formulation performance, guide iterative development, define dissolution parameters, and convince the regulatory agencies about a drug’s safety and efficacy.This study involves development of a sustained release formulation for Hydroxyzine, an anti-histamine with sedation as a significant side effect. The aim was to design a formulation that releases the drug slowly, reducing the peak plasma concentration without losing on the effectiveness. A preliminary absorption model was developed using immediate release formulation data, and various hypothetical dissolution profiles were evaluated in this model. The new drug product, manufactured using Matrixeal<sup>TM</sup> technology, underwent preliminary bioequivalence (BE) studies in healthy volunteers. These results were used to refine the model and further modify the formulation, whose performance was predicted <i>via</i> virtual BE studies. Confirmatory BE studies with 70 volunteers under fasting state validated the new formulation. The model also established clinically relevant dissolution specifications and assessed the food effect on the drug product.This work showcases the application of PBPK modelling in developing new modified release drug product of Hydroxyzine. Model Informed Formulation Development (MIFD) uses physiologically based pharmacokinetic (PBPK) modelling and other <i>in silico</i> tools to facilitate new product development. These tools help set target profiles, predict <i>in vivo</i> formulation performance, guide iterative development, define dissolution parameters, and convince the regulatory agencies about a drug’s safety and efficacy. This study involves development of a sustained release formulation for Hydroxyzine, an anti-histamine with sedation as a significant side effect. The aim was to design a formulation that releases the drug slowly, reducing the peak plasma concentration without losing on the effectiveness. A preliminary absorption model was developed using immediate release formulation data, and various hypothetical dissolution profiles were evaluated in this model. The new drug product, manufactured using Matrixeal<sup>TM</sup> technology, underwent preliminary bioequivalence (BE) studies in healthy volunteers. These results were used to refine the model and further modify the formulation, whose performance was predicted <i>via</i> virtual BE studies. Confirmatory BE studies with 70 volunteers under fasting state validated the new formulation. The model also established clinically relevant dissolution specifications and assessed the food effect on the drug product. This work showcases the application of PBPK modelling in developing new modified release drug product of Hydroxyzine.
DOI: 10.6084/m9.figshare.29167006
title: Machine learning-driven bioavailability prediction in early-stage drug development: a KNIME-based computational workflow for digital health applications

description: Bioavailability prediction remains a significant challenge in early-stage drug development, where conventional experimental approaches are time-consuming and resource-intensive. This study explores the application of machine learning techniques to enhance the efficiency of bioavailability prediction. By leveraging computational workflows within the KNIME Analytics Platform, we aim to automate bioavailability assessment and reduce dependence on costly <i>in vitro</i> and <i>in vivo</i> studies. A dataset comprising 475 drug-like compounds characterised by key molecular descriptors was analysed using multiple machine learning models, including Random Forest, Gradient Boosting, Decision Trees, k-Nearest Neighbours, and neural networks. Model performance was assessed through 5-fold cross-validation, with ensemble models outperforming linear and neural network-based approaches. Random Forest demonstrated the highest predictive performance (<i>R</i><sup>2</sup> = 0.87, RMSE = 0.08). Feature importance analysis identified topological polar surface area and solubility as the most influential factors in bioavailability prediction. The findings underscore the potential of integrating open-source tools and machine learning methodologies in pharmaceutical research, improving workflow efficiency while adhering to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. This approach facilitates rapid and cost-effective bioavailability assessment, supporting AI-driven predictive modelling and digital health applications in drug development.
DOI: 10.6084/m9.figshare.29167006.v1
title: Machine learning-driven bioavailability prediction in early-stage drug development: a KNIME-based computational workflow for digital health applications

description: Bioavailability prediction remains a significant challenge in early-stage drug development, where conventional experimental approaches are time-consuming and resource-intensive. This study explores the application of machine learning techniques to enhance the efficiency of bioavailability prediction. By leveraging computational workflows within the KNIME Analytics Platform, we aim to automate bioavailability assessment and reduce dependence on costly <i>in vitro</i> and <i>in vivo</i> studies. A dataset comprising 475 drug-like compounds characterised by key molecular descriptors was analysed using multiple machine learning models, including Random Forest, Gradient Boosting, Decision Trees, k-Nearest Neighbours, and neural networks. Model performance was assessed through 5-fold cross-validation, with ensemble models outperforming linear and neural network-based approaches. Random Forest demonstrated the highest predictive performance (<i>R</i><sup>2</sup> = 0.87, RMSE = 0.08). Feature importance analysis identified topological polar surface area and solubility as the most influential factors in bioavailability prediction. The findings underscore the potential of integrating open-source tools and machine learning methodologies in pharmaceutical research, improving workflow efficiency while adhering to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. This approach facilitates rapid and cost-effective bioavailability assessment, supporting AI-driven predictive modelling and digital health applications in drug development.
DOI: 10.6084/m9.figshare.29396380
title: In silico analysis of nicotine’s molecular targets in Parkinson’s disease

description: We aimed to elucidate the molecular processes involved in how nicotine affects PD.Toxicogenomic, molecular mechanisms, physicochemical properties, pharmacokinetic profile, and biological activity were analysed.We found that the therapeutic potential of nicotine in PD may be attributed to its ability to modulate the expression of 38 genes, especially GAPDH, TNF, IL6, and BDNF. The molecular mechanisms underlying the protective effects of nicotine against PD involve several pathways, including the ‘Parkinson’s disease pathway’, ‘the selenium micronutrient network’, ‘the oxidative stress response’, ‘dopamine binding’, ‘Parkinsonian disorders’, and ‘Lewy body disease’. miRNAs like hsa-miRNA-203a-3p and miRNA-26b-5p and transcription factors like HNF4, MAPK3, and EVI1 explained how nicotine protects neurons from PD.An assessment was also carried out on drug candidates (polaprezinc) and miRNA sponges (hsa-miR-181a-5p, hsa-miR-124-3p, hsa-miR-1-3p) that may possess the capability to synergize the effects of nicotine. Nicotine’s physicochemical properties, pharmacokinetic profile, and biological activity are conducive to its favourable attributes in the context of PD, including high gastrointestinal absorption, ability to penetrate the blood-brain barrier, non-P-glycoprotein nature, and antiparkinsonian effects.Nicotine plays crucial roles in the pathophysiology of PD. Further work is needed to evaluate the impact of nicotine on non-motor symptoms. We aimed to elucidate the molecular processes involved in how nicotine affects PD. Toxicogenomic, molecular mechanisms, physicochemical properties, pharmacokinetic profile, and biological activity were analysed. We found that the therapeutic potential of nicotine in PD may be attributed to its ability to modulate the expression of 38 genes, especially GAPDH, TNF, IL6, and BDNF. The molecular mechanisms underlying the protective effects of nicotine against PD involve several pathways, including the ‘Parkinson’s disease pathway’, ‘the selenium micronutrient network’, ‘the oxidative stress response’, ‘dopamine binding’, ‘Parkinsonian disorders’, and ‘Lewy body disease’. miRNAs like hsa-miRNA-203a-3p and miRNA-26b-5p and transcription factors like HNF4, MAPK3, and EVI1 explained how nicotine protects neurons from PD. An assessment was also carried out on drug candidates (polaprezinc) and miRNA sponges (hsa-miR-181a-5p, hsa-miR-124-3p, hsa-miR-1-3p) that may possess the capability to synergize the effects of nicotine. Nicotine’s physicochemical properties, pharmacokinetic profile, and biological activity are conducive to its favourable attributes in the context of PD, including high gastrointestinal absorption, ability to penetrate the blood-brain barrier, non-P-glycoprotein nature, and antiparkinsonian effects. Nicotine plays crucial roles in the pathophysiology of PD. Further work is needed to evaluate the impact of nicotine on non-motor symptoms.
DOI: 10.6084/m9.figshare.29396380.v1
title: In silico analysis of nicotine’s molecular targets in Parkinson’s disease

description: We aimed to elucidate the molecular processes involved in how nicotine affects PD.Toxicogenomic, molecular mechanisms, physicochemical properties, pharmacokinetic profile, and biological activity were analysed.We found that the therapeutic potential of nicotine in PD may be attributed to its ability to modulate the expression of 38 genes, especially GAPDH, TNF, IL6, and BDNF. The molecular mechanisms underlying the protective effects of nicotine against PD involve several pathways, including the ‘Parkinson’s disease pathway’, ‘the selenium micronutrient network’, ‘the oxidative stress response’, ‘dopamine binding’, ‘Parkinsonian disorders’, and ‘Lewy body disease’. miRNAs like hsa-miRNA-203a-3p and miRNA-26b-5p and transcription factors like HNF4, MAPK3, and EVI1 explained how nicotine protects neurons from PD.An assessment was also carried out on drug candidates (polaprezinc) and miRNA sponges (hsa-miR-181a-5p, hsa-miR-124-3p, hsa-miR-1-3p) that may possess the capability to synergize the effects of nicotine. Nicotine’s physicochemical properties, pharmacokinetic profile, and biological activity are conducive to its favourable attributes in the context of PD, including high gastrointestinal absorption, ability to penetrate the blood-brain barrier, non-P-glycoprotein nature, and antiparkinsonian effects.Nicotine plays crucial roles in the pathophysiology of PD. Further work is needed to evaluate the impact of nicotine on non-motor symptoms. We aimed to elucidate the molecular processes involved in how nicotine affects PD. Toxicogenomic, molecular mechanisms, physicochemical properties, pharmacokinetic profile, and biological activity were analysed. We found that the therapeutic potential of nicotine in PD may be attributed to its ability to modulate the expression of 38 genes, especially GAPDH, TNF, IL6, and BDNF. The molecular mechanisms underlying the protective effects of nicotine against PD involve several pathways, including the ‘Parkinson’s disease pathway’, ‘the selenium micronutrient network’, ‘the oxidative stress response’, ‘dopamine binding’, ‘Parkinsonian disorders’, and ‘Lewy body disease’. miRNAs like hsa-miRNA-203a-3p and miRNA-26b-5p and transcription factors like HNF4, MAPK3, and EVI1 explained how nicotine protects neurons from PD. An assessment was also carried out on drug candidates (polaprezinc) and miRNA sponges (hsa-miR-181a-5p, hsa-miR-124-3p, hsa-miR-1-3p) that may possess the capability to synergize the effects of nicotine. Nicotine’s physicochemical properties, pharmacokinetic profile, and biological activity are conducive to its favourable attributes in the context of PD, including high gastrointestinal absorption, ability to penetrate the blood-brain barrier, non-P-glycoprotein nature, and antiparkinsonian effects. Nicotine plays crucial roles in the pathophysiology of PD. Further work is needed to evaluate the impact of nicotine on non-motor symptoms.
DOI: 10.15468/dl.qw62xn
title: Occurrence Download

description: A dataset containing 2426 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bidens frondosa",
 "Country is Portugal",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2426 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043479-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.