cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28397059
title: Design, synthesis and biological evaluation of non-glucosidal based 1,3,4-thiadiazoles as SGLT-2 inhibitors

description: Type-2 diabetes mellitus (T2DM) is a major metabolic disorder needing insulin-independent treatments; this study developed Schiff base 1,3,4-thiadiazole as Sodium Glucose Co-transporters 2 (SGLT2) inhibitors. The target compounds were synthesized followed by docking studies, in vitro and in vivo analysis. In vitro assay revealed SSS 6 and SSS 2 exhibited high SGLT2 inhibition activity i.e. 78.57% ± 2.8 and 74.60% ± 1.12 compared to dapagliflozin (93.65% ± 4.48) at same dosage in enzyme inhibition assays. In vivo results reveals that SSS 2 significantly improved excretion of urinary glucose (854 ± 46.51 mg/body weight) as compared to dapagliflozin (775 ± 32.68 mg/body weight. SSS 6 and SSS 2 significantly decreased blood glucose levels (137 ± 4.89 mg/dL and 183 ± 15.07 mg/dL) relative to dapagliflozin (158 ± 15.9 mg/dL). Compounds SSS 6 and SSS 2 emerge as a potential candidates for further investigation as SGLT2 inhibitors for treating T2DM.
DOI: 10.6084/m9.figshare.28397059.v1
title: Design, synthesis and biological evaluation of non-glucosidal based 1,3,4-thiadiazoles as SGLT-2 inhibitors

description: Type-2 diabetes mellitus (T2DM) is a major metabolic disorder needing insulin-independent treatments; this study developed Schiff base 1,3,4-thiadiazole as Sodium Glucose Co-transporters 2 (SGLT2) inhibitors. The target compounds were synthesized followed by docking studies, in vitro and in vivo analysis. In vitro assay revealed SSS 6 and SSS 2 exhibited high SGLT2 inhibition activity i.e. 78.57% ± 2.8 and 74.60% ± 1.12 compared to dapagliflozin (93.65% ± 4.48) at same dosage in enzyme inhibition assays. In vivo results reveals that SSS 2 significantly improved excretion of urinary glucose (854 ± 46.51 mg/body weight) as compared to dapagliflozin (775 ± 32.68 mg/body weight. SSS 6 and SSS 2 significantly decreased blood glucose levels (137 ± 4.89 mg/dL and 183 ± 15.07 mg/dL) relative to dapagliflozin (158 ± 15.9 mg/dL). Compounds SSS 6 and SSS 2 emerge as a potential candidates for further investigation as SGLT2 inhibitors for treating T2DM.
DOI: 10.6084/m9.figshare.28321564
title: Pioneering first-in-class HDAC-ROCK inhibitors as potential multitarget anticancer agents

description: With the aim of simultaneously modulating the epigenetic system and the protein kinase pathway, we selected the enzyme histone deacetylase (HDAC) and the Rho-associated protein kinases (ROCK) as desired targets to develop potential multitarget anticancer agents with additional antimetastatic properties. We report here the rational design, synthesis, and biological evaluation of the <i>first-in-class</i> HDAC/ROCK multitarget inhibitors in pancreatic ductal adenocarcinoma (PDAC) and triple-negative breast cancer (TNBC). A molecular docking study performed with the Gold software was used to develop HDAC/ROCK multitarget inhibitors. IC<sub>50</sub> values were determined by enzyme assays. The cytotoxicity, anti-migratory and anti-invasive properties of the inhibitors were evaluated using triple-negative breast cancer cells (MDA-MB-231 and HCC 1973) and pancreatic ductal adenocarcinoma cells (Panc-1 and MiaPaCa-2). <b>C-9</b> showed significant inhibition of HDAC6, ROCK1 and ROCK2. At the same time, this compound showed strong antiproliferative effects on MDA-MB-231, MiaPaCa-2 and Panc-1 cell lines with IC<sub>50</sub> values of 5.81 μM, 3.87 μM and 19.57 μM. In addition, it demonstrated great anti-invasive and anti-migratory effects. The findings of this study strongly suggest that the simultaneous inhibition of ROCK and HDACs holds significant potential as a promising therapeutic strategy in the advancement of cancer treatment.
DOI: 10.6084/m9.figshare.28321564.v1
title: Pioneering first-in-class HDAC-ROCK inhibitors as potential multitarget anticancer agents

description: With the aim of simultaneously modulating the epigenetic system and the protein kinase pathway, we selected the enzyme histone deacetylase (HDAC) and the Rho-associated protein kinases (ROCK) as desired targets to develop potential multitarget anticancer agents with additional antimetastatic properties. We report here the rational design, synthesis, and biological evaluation of the <i>first-in-class</i> HDAC/ROCK multitarget inhibitors in pancreatic ductal adenocarcinoma (PDAC) and triple-negative breast cancer (TNBC). A molecular docking study performed with the Gold software was used to develop HDAC/ROCK multitarget inhibitors. IC<sub>50</sub> values were determined by enzyme assays. The cytotoxicity, anti-migratory and anti-invasive properties of the inhibitors were evaluated using triple-negative breast cancer cells (MDA-MB-231 and HCC 1973) and pancreatic ductal adenocarcinoma cells (Panc-1 and MiaPaCa-2). <b>C-9</b> showed significant inhibition of HDAC6, ROCK1 and ROCK2. At the same time, this compound showed strong antiproliferative effects on MDA-MB-231, MiaPaCa-2 and Panc-1 cell lines with IC<sub>50</sub> values of 5.81 μM, 3.87 μM and 19.57 μM. In addition, it demonstrated great anti-invasive and anti-migratory effects. The findings of this study strongly suggest that the simultaneous inhibition of ROCK and HDACs holds significant potential as a promising therapeutic strategy in the advancement of cancer treatment.
DOI: 10.6084/m9.figshare.28398131
title: Advances of deep Neural Networks (DNNs) in the development of peptide drugs

description: Peptides are able to bind to difficult disease targets with high potency and specificity, providing great opportunities to meet unmet medical requirements. Nevertheless, the unique features of peptides, such as their small size, high structural flexibility, and scarce data availability, bring extra challenges to the design process. Firstly, this review sums up the application of peptide drugs in treating diseases. Then, the review probes into the advantages of Deep Neural Networks (DNNs) in predicting and designing peptide structures. DNNs have demonstrated remarkable capabilities in structural prediction, enabling accurate three-dimensional modeling of peptide drugs through models like AlphaFold and its successors. Finally, the review deliberates on the challenges and coping strategies of DNNs in the development of peptide drugs, along with future research directions. Future research directions focus on further improving the accuracy and efficiency of DNN-based peptide drug design, exploring novel applications of peptide drugs, and accelerating their clinical translation. With continuous advancements in technology and data accumulation, DNNs are poised to play an increasingly crucial role in the field of peptide drug development.
DOI: 10.6084/m9.figshare.28398131.v1
title: Advances of deep Neural Networks (DNNs) in the development of peptide drugs

description: Peptides are able to bind to difficult disease targets with high potency and specificity, providing great opportunities to meet unmet medical requirements. Nevertheless, the unique features of peptides, such as their small size, high structural flexibility, and scarce data availability, bring extra challenges to the design process. Firstly, this review sums up the application of peptide drugs in treating diseases. Then, the review probes into the advantages of Deep Neural Networks (DNNs) in predicting and designing peptide structures. DNNs have demonstrated remarkable capabilities in structural prediction, enabling accurate three-dimensional modeling of peptide drugs through models like AlphaFold and its successors. Finally, the review deliberates on the challenges and coping strategies of DNNs in the development of peptide drugs, along with future research directions. Future research directions focus on further improving the accuracy and efficiency of DNN-based peptide drug design, exploring novel applications of peptide drugs, and accelerating their clinical translation. With continuous advancements in technology and data accumulation, DNNs are poised to play an increasingly crucial role in the field of peptide drug development.
DOI: 10.15468/dl.7vxn5c
title: Occurrence Download

description: A dataset containing 60630 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "Geometry POLYGON((-79.404 -3.02111,-79.03435 -3.02111,-79.03435 -2.69007,-79.404 -2.69007,-79.404 -3.02111))",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (VU, CR, LC)"
 ]
}

 The dataset includes 60630 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003123-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17028/rd.lboro.28430153
title: Supplementary information files for "Resilience and vulnerabilities of urban food environments in the Asia‐Pacific region"

description: Supplementary files for article "Resilience and vulnerabilities of urban food environments in the Asia‐Pacific region"Rapid urbanisation in the Asia‐Pacific region is associated with complex changes to urban food environments. The impact of changing food environments on food purchasing and consumption and the diets and nutritional status of vulnerable groups, especially women and young children, is not well researched in low‐ and middle‐income country cities. This paper aimed to examine: the risks and opportunities for healthy diets for low income populations offered by modernising urban centres; the concept of food deserts in relation to urban food environments in the Asia‐Pacific region and how these could be mitigated; and measures to strengthen the resilience of food environments in the region using a case study of the impact of COVID‐19 on informal food vendors. Our findings indicate that the dynamic changes in urban food environments in the Asia‐ Pacific region need to be understood by examining not only modern retail food outlets but also wet markets and informal food outlets, including street foods. Efforts should be made to ensure both modern and traditional outlets provide complementary platforms for convenient, affordable and accessible nutritious foods for urban populations. The resilience of urban food environments to environmental, physical and socio‐economic shocks can be strengthened by shortening food supply chains and maximising food production in cities. Support mechanisms targeting urban informal food outlets and street vendors can also strengthen resilience and improve food security. Further research is needed on the impact of urbanising food environments on consumer choices, preferences, diets and health outcomes.<br><br>© The Authors, 2023
DOI: 10.17028/rd.lboro.28430153.v1
title: Supplementary information files for "Resilience and vulnerabilities of urban food environments in the Asia‐Pacific region"

description: Supplementary files for article "Resilience and vulnerabilities of urban food environments in the Asia‐Pacific region"Rapid urbanisation in the Asia‐Pacific region is associated with complex changes to urban food environments. The impact of changing food environments on food purchasing and consumption and the diets and nutritional status of vulnerable groups, especially women and young children, is not well researched in low‐ and middle‐income country cities. This paper aimed to examine: the risks and opportunities for healthy diets for low income populations offered by modernising urban centres; the concept of food deserts in relation to urban food environments in the Asia‐Pacific region and how these could be mitigated; and measures to strengthen the resilience of food environments in the region using a case study of the impact of COVID‐19 on informal food vendors. Our findings indicate that the dynamic changes in urban food environments in the Asia‐ Pacific region need to be understood by examining not only modern retail food outlets but also wet markets and informal food outlets, including street foods. Efforts should be made to ensure both modern and traditional outlets provide complementary platforms for convenient, affordable and accessible nutritious foods for urban populations. The resilience of urban food environments to environmental, physical and socio‐economic shocks can be strengthened by shortening food supply chains and maximising food production in cities. Support mechanisms targeting urban informal food outlets and street vendors can also strengthen resilience and improve food security. Further research is needed on the impact of urbanising food environments on consumer choices, preferences, diets and health outcomes.<br><br>© The Authors, 2023
DOI: 10.5281/zenodo.14883259
title: Global Hourly Seamless Aerosol Optical Depth Dataset (2022) at 0.05°×0.05° Resolution

description: This dataset was producted based on MERRA-2 AOD, MODIS MAIAC AOD, and VIIRS NOAA/SNPP DB/DT AOD products.
DOI: 10.5281/zenodo.14883260
title: Global Hourly Seamless Aerosol Optical Depth Dataset (2022) at 0.05°×0.05° Resolution

description: This dataset was producted based on MERRA-2 AOD, MODIS MAIAC AOD, and VIIRS NOAA/SNPP DB/DT AOD products.
DOI: 10.5281/zenodo.14870888
title: Dynamical Response of a Newtonian Fluid Interface to Mixed Oscillatory Deformations

description: In this work, the behavior of a slender probe floating horizontally on a water/air interface with specific interfacial properties, namely shear, dilational, and extensional viscosities, is simulated using the finite volume method. The aim is to analyze the feasibility of separating the components due to each of the mentioned deformation modes. The system consists of a small diameter cylindrical probe (typically 400 microns) placed horizontally on a water/air interface; the floating probe, submerged to its median plane by capillary effects, moves sinusoidally in the direction perpendicular to its axis.

To carry out the analysis, the interface dynamics equations were implemented in the open-source software OpenFoam. The behavior of the probe was simulated for Marangoni numbers between 1 and $10^5$, combined with ratios of the dilational rate to the shear stress $\Theta$, between 1 and $10^5$. The behavior of the probe was successfully simulated, and the forces exerted on the probe by the different deformation modes were calculated.
DOI: 10.5281/zenodo.14870889
title: Dynamical Response of a Newtonian Fluid Interface to Mixed Oscillatory Deformations

description: In this work, the behavior of a slender probe floating horizontally on a water/air interface with specific interfacial properties, namely shear, dilational, and extensional viscosities, is simulated using the finite volume method. The aim is to analyze the feasibility of separating the components due to each of the mentioned deformation modes. The system consists of a small diameter cylindrical probe (typically 400 microns) placed horizontally on a water/air interface; the floating probe, submerged to its median plane by capillary effects, moves sinusoidally in the direction perpendicular to its axis.

To carry out the analysis, the interface dynamics equations were implemented in the open-source software OpenFoam. The behavior of the probe was simulated for Marangoni numbers between 1 and $10^5$, combined with ratios of the dilational rate to the shear stress $\Theta$, between 1 and $10^5$. The behavior of the probe was successfully simulated, and the forces exerted on the probe by the different deformation modes were calculated.
DOI: 10.5281/zenodo.14882951
title: Dynamical Response of a Newtonian Fluid Interface to Mixed Oscillatory Deformations

description: In this work, the behavior of a slender probe floating horizontally on a water/air interface with specific interfacial properties, namely shear, dilational, and extensional viscosities, is simulated using the finite volume method. The aim is to analyze the feasibility of separating the components due to each of the mentioned deformation modes. The system consists of a small diameter cylindrical probe (typically 400 microns) placed horizontally on a water/air interface; the floating probe, submerged to its median plane by capillary effects, moves sinusoidally in the direction perpendicular to its axis.

To carry out the analysis, the interface dynamics equations were implemented in the open-source software OpenFoam. The behavior of the probe was simulated for Marangoni numbers between 1 and $10^5$, combined with ratios of the dilational rate to the shear stress $\Theta$, between 1 and $10^5$. The behavior of the probe was successfully simulated, and the forces exerted on the probe by the different deformation modes were calculated.
DOI: 10.5281/zenodo.14883576
title: Documentary references for Editorial submitted to Medical Research Archives of The European Society of Medicine
DOI: 10.5281/zenodo.14883577
title: Documentary references for Editorial submitted to Medical Research Archives of The European Society of Medicine
DOI: 10.5281/zenodo.14290525
title: Supplemental Data for "Deep-Time Human-Environment Interactions as Primary Legacy Drivers of Modern Coastal Ecosystems"
DOI: 10.5281/zenodo.14290526
title: Supplemental Data for "Deep-Time Human-Environment Interactions as Primary Legacy Drivers of Modern Coastal Ecosystems"
DOI: 10.34740/kaggle/dsv/10774590
title: Gladiator Combat Records and Profiles Dataset
DOI: 10.5281/zenodo.7490294
title: All-sky Hourly Land Surface Temperature of contiguous United States and Mexico (2017-2021)

description: This dataset has been published on Remote Sensing of Environment, and please cite the published paper: https://doi.org/10.1016/j.rse.2022.113105, and original ABI projection and gridded format in different resolutions can be found at http://glass.umd.edu/allsky_LST/ABI/


The data uploaded on Zenodo is the gridded output of which lat/lon spatial resolution is 0.05 degrees. The scaling factor for LST is 0.01.


By characterizing high-frequency surface thermal dynamics at a medium spatial scale, hourly land surface temperatures (LST), retrieved from geostationary satellite thermal infrared (TIR) observations, shows great potential to be used across a range of scientific applications; however, cloud cover typically leads to data gaps and degraded retrieval accuracy in TIR LST products, such as the official Advanced Baseline Imager (ABI) LST product. Studies have focused on the LST gap reconstruction; however, most interpolation-based methods only work for a short-term cloud duration and are unable to adequately compensate for cloud effects, and traditional surface energy balance (SEB)-based methods are able to handle cloud coverage while they are not feasible for use at night. Moreover, few studies have concentrated on recovering the abnormal retrievals of partial cloud pixels. In this study, an all-sky diurnal, hourly LST estimation method based on SEB theory was proposed; the proposed method involved three major steps: 1) an original spatiotemporal dynamic model of LST was constructed from ECMWF Reanalysis v.5 (ERA5); 2) clear-sky ABI LST was then assimilated to the dynamic model to generate a continuous LST series; 3) the diurnal cloud effects were superimposed on cloudy time estimated by an innovative optimization method from satellite radiation products. A 2-km, all-sky, hourly LST product was produced over the contiguous US and Mexico from July 2017 to June 2021. Validation was conducted using ground measurements at 18 sites from Surface Radiation (SURFRAD) and core AmeriFlux networks, and produced an overall root-mean-square error (RMSE) of 2.44 K, a bias of −0.19 K, and an R2 of 0.97 based on 408,300 samples. For clear-sky samples, the RMSE values were 2.37 and 2.24 K for day and nighttime, respectively, which was a notable improvement over the corresponding values of the official ABI LST product (2.73 and 2.86 K, respectively). The RMSE values on cloudy-sky were 2.78 and 2.23 K for day and nighttime, respectively. The daily mean LST by aggregating all-sky, hourly LST had an RMSE of 1.13 K and R2 of 0.99. Overall, this product showed reliability under consistent cloud durations, although it was slightly affected by surface elevation. The diurnal temperature cycle climatology of major land cover types was also characterized. The product is freely available at: http://glass.umd.edu/allsky_LST/ABI/.
DOI: 10.5281/zenodo.7490295
title: All-sky Hourly Land Surface Temperature of contiguous United States and Mexico (2017-2021)

description: This dataset has been published on Remote Sensing of Environment, and please cite the published paper: https://doi.org/10.1016/j.rse.2022.113105, and original ABI projection and gridded format in different resolutions can be found at http://glass.umd.edu/allsky_LST/ABI/


The data uploaded on Zenodo is the gridded output of which lat/lon spatial resolution is 0.05 degrees. The scaling factor for LST is 0.01.


By characterizing high-frequency surface thermal dynamics at a medium spatial scale, hourly land surface temperatures (LST), retrieved from geostationary satellite thermal infrared (TIR) observations, shows great potential to be used across a range of scientific applications; however, cloud cover typically leads to data gaps and degraded retrieval accuracy in TIR LST products, such as the official Advanced Baseline Imager (ABI) LST product. Studies have focused on the LST gap reconstruction; however, most interpolation-based methods only work for a short-term cloud duration and are unable to adequately compensate for cloud effects, and traditional surface energy balance (SEB)-based methods are able to handle cloud coverage while they are not feasible for use at night. Moreover, few studies have concentrated on recovering the abnormal retrievals of partial cloud pixels. In this study, an all-sky diurnal, hourly LST estimation method based on SEB theory was proposed; the proposed method involved three major steps: 1) an original spatiotemporal dynamic model of LST was constructed from ECMWF Reanalysis v.5 (ERA5); 2) clear-sky ABI LST was then assimilated to the dynamic model to generate a continuous LST series; 3) the diurnal cloud effects were superimposed on cloudy time estimated by an innovative optimization method from satellite radiation products. A 2-km, all-sky, hourly LST product was produced over the contiguous US and Mexico from July 2017 to June 2021. Validation was conducted using ground measurements at 18 sites from Surface Radiation (SURFRAD) and core AmeriFlux networks, and produced an overall root-mean-square error (RMSE) of 2.44 K, a bias of −0.19 K, and an R2 of 0.97 based on 408,300 samples. For clear-sky samples, the RMSE values were 2.37 and 2.24 K for day and nighttime, respectively, which was a notable improvement over the corresponding values of the official ABI LST product (2.73 and 2.86 K, respectively). The RMSE values on cloudy-sky were 2.78 and 2.23 K for day and nighttime, respectively. The daily mean LST by aggregating all-sky, hourly LST had an RMSE of 1.13 K and R2 of 0.99. Overall, this product showed reliability under consistent cloud durations, although it was slightly affected by surface elevation. The diurnal temperature cycle climatology of major land cover types was also characterized. The product is freely available at: http://glass.umd.edu/allsky_LST/ABI/.
DOI: 10.5281/zenodo.14865256
title: Dataset for iScore: A ML-Based Scoring Function for de novo Drug Discovery

description: DUD-E_prepared.zip: contains the prepared structures (pdbs and SMILES) for the DUD-E dataset user for re-evaluating the screening power of the model.

Target-fishing_prepared.zip: contains the prepared structures (pdbs and sdf) for the target fishing dataset user for evaluating the target fishing performance of the model.
DOI: 10.5281/zenodo.14865257
title: Dataset for iScore: A ML-Based Scoring Function for de novo Drug Discovery

description: DUD-E_prepared.zip: contains the prepared structures (pdbs and SMILES) for the DUD-E dataset user for re-evaluating the screening power of the model.

Target-fishing_prepared.zip: contains the prepared structures (pdbs and sdf) for the target fishing dataset user for evaluating the target fishing performance of the model.