cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25442/hku.29986843.v1
title: Supporting data for High-Accuracy Dataset Generation and Machine Learning Enhancement of Density Functional Theory

description: Computational chemistry combines theoretical chemistry with computer simulations to simulate and calculate molecular properties and chemical reactions. Due to their complex structures, organic molecules are relatively difficult to handle in computational chemistry. As an efficient quantum mechanical method for solving the Schrödinger equation, density functional theory (DFT) describes the system through electron density, avoiding complex multi-electron wave functions, and thus has advantages in computational efficiency and application scope. However, the core challenge of DFT theory lies in the uncertainty of the exchange-correlation (XC) functional, meaning that the exact XC potential and its corresponding energy are not yet fully determined. The widely used B3LYP and CCSD methods for finding the XC functional also have their own limitations and drawbacks.To address these issues, this work presents a comprehensive investigation of machine learning-enhanced density functional theory through systematic construction of a large-scale quantum chemical dataset and neural network based correction methods. Inspired by the Holographic Electron Density Theorem, a comprehensive dataset was constructed encompassing 593 diverse molecular systems from established benchmarks (G2, W4-11, GMTKN55), systematically expanded through geometric perturbations including bond stretching, angular bending, and conformational sampling. The dataset employed rigorous computational protocols using PySCF with cc-pVDZ and cc-pVTZ basis sets, calculating electronic structures across multiple theory levels.Local electronic environments were standardized as 9×9×9 density cubes centered at atomic positions, with principal axis alignment ensuring rotational invariance and systematic re-gridding producing uniform 5×5×5 representations. Three machine learning approaches were developed and tested: anMLP Mixer for exchange-correlation potential prediction, a fully connected network for energy corrections, and an ML-PBE method for systematic error reduction. Results demonstrate exceptional performance improvements with accuracy enhancements spanning multiple orders of magnitude compared to conventional functionals. This approach advances accurate calculation of exchange-correlation potentials from electron density distributions, enhancing DFT development through systematic dataset construction and machine learning enhancement.<br>
DOI: 10.25442/hku.29986843
title: Supporting data for High-Accuracy Dataset Generation and Machine Learning Enhancement of Density Functional Theory

description: Computational chemistry combines theoretical chemistry with computer simulations to simulate and calculate molecular properties and chemical reactions. Due to their complex structures, organic molecules are relatively difficult to handle in computational chemistry. As an efficient quantum mechanical method for solving the Schrödinger equation, density functional theory (DFT) describes the system through electron density, avoiding complex multi-electron wave functions, and thus has advantages in computational efficiency and application scope. However, the core challenge of DFT theory lies in the uncertainty of the exchange-correlation (XC) functional, meaning that the exact XC potential and its corresponding energy are not yet fully determined. The widely used B3LYP and CCSD methods for finding the XC functional also have their own limitations and drawbacks.To address these issues, this work presents a comprehensive investigation of machine learning-enhanced density functional theory through systematic construction of a large-scale quantum chemical dataset and neural network based correction methods. Inspired by the Holographic Electron Density Theorem, a comprehensive dataset was constructed encompassing 593 diverse molecular systems from established benchmarks (G2, W4-11, GMTKN55), systematically expanded through geometric perturbations including bond stretching, angular bending, and conformational sampling. The dataset employed rigorous computational protocols using PySCF with cc-pVDZ and cc-pVTZ basis sets, calculating electronic structures across multiple theory levels.Local electronic environments were standardized as 9×9×9 density cubes centered at atomic positions, with principal axis alignment ensuring rotational invariance and systematic re-gridding producing uniform 5×5×5 representations. Three machine learning approaches were developed and tested: anMLP Mixer for exchange-correlation potential prediction, a fully connected network for energy corrections, and an ML-PBE method for systematic error reduction. Results demonstrate exceptional performance improvements with accuracy enhancements spanning multiple orders of magnitude compared to conventional functionals. This approach advances accurate calculation of exchange-correlation potentials from electron density distributions, enhancing DFT development through systematic dataset construction and machine learning enhancement.<br>
DOI: 10.25442/hku.29987365
title: Supporting data for "Development of the peptide antagonist targeting FGF23 for the treatment of hypophosphataemia"

description: FGF23 is an endocrine hormone that plays a critical role in phosphate and vitamin D metabolism. Its biological activity requires binding to the FGFR-α-Klotho receptor complex for signal transduction. Excessive FGF23 leads to hypophosphatemia and related disorders. Currently, there are limited FGF23-targeting drugs available on the market, and they have some side effects. Therefore, we designed FGF23-antagonizing peptides through virtual screening and introduced lipid modifications to enhance their plasma half-life. This peptide demonstrated FGF23-inhibitory activity in vitro and exhibited a 6.5-hour extension in plasma half-life in vivo. In vivo studies demonstrated its ability to counteract the physiological alterations induced by acute FGF23 injection. Finally, in hypophosphatemic mouse models, we found that both acute and short-term administration of this peptide elevated serum phosphate levels. Long-term administration of this peptide increased serum phosphate levels, enhanced bone formation, and restored both cardiac function and body weight.
DOI: 10.25442/hku.29987365.v1
title: Supporting data for "Development of the peptide antagonist targeting FGF23 for the treatment of hypophosphataemia"

description: FGF23 is an endocrine hormone that plays a critical role in phosphate and vitamin D metabolism. Its biological activity requires binding to the FGFR-α-Klotho receptor complex for signal transduction. Excessive FGF23 leads to hypophosphatemia and related disorders. Currently, there are limited FGF23-targeting drugs available on the market, and they have some side effects. Therefore, we designed FGF23-antagonizing peptides through virtual screening and introduced lipid modifications to enhance their plasma half-life. This peptide demonstrated FGF23-inhibitory activity in vitro and exhibited a 6.5-hour extension in plasma half-life in vivo. In vivo studies demonstrated its ability to counteract the physiological alterations induced by acute FGF23 injection. Finally, in hypophosphatemic mouse models, we found that both acute and short-term administration of this peptide elevated serum phosphate levels. Long-term administration of this peptide increased serum phosphate levels, enhanced bone formation, and restored both cardiac function and body weight.
DOI: 10.25442/hku.29984548
title: Supporting data for “Inheriting and Continuing Master Sheng Yen’s Legacy – A Study of Dharma Drum Mountain as a Centre of Buddhist Learning and Practice”

description: This is a study of Dharma Drum Mountain (DDM), an international Buddhist order founded by Master Sheng Yen (1931-2009), investigating the mechanisms through which DDM inherits and continues the legacy of its late founder. It unfolds a case of institutional succession in modern Chinese Chán. By employing textual analysis and ethnographic fieldwork experience in Taiwan, Hong Kong, the United States and London, this study contributes latest empirical data and insights to examine how a large-scale Buddhist organisation addresses the challenges of leadership and legacy continuity following the founders' passing, amid evolving needs of the modern world.
DOI: 10.25442/hku.29984548.v1
title: Supporting data for “Inheriting and Continuing Master Sheng Yen’s Legacy – A Study of Dharma Drum Mountain as a Centre of Buddhist Learning and Practice”

description: This is a study of Dharma Drum Mountain (DDM), an international Buddhist order founded by Master Sheng Yen (1931-2009), investigating the mechanisms through which DDM inherits and continues the legacy of its late founder. It unfolds a case of institutional succession in modern Chinese Chán. By employing textual analysis and ethnographic fieldwork experience in Taiwan, Hong Kong, the United States and London, this study contributes latest empirical data and insights to examine how a large-scale Buddhist organisation addresses the challenges of leadership and legacy continuity following the founders' passing, amid evolving needs of the modern world.
DOI: 10.25442/hku.29977666
title: Supporting data for "antimicrobial resistance and pathogen transmission in clinical and food samples in Hong Kong"

description: This study comprehensively investigates antimicrobial resistance (AMR) in Hong Kong across clinical, food, animal, and environmental reservoirs using a One Health approach. The data files were used to determine the current situation of the resistome profile in Gram-negative bacteria isolated from food and clinical isolates in Hong Kong. Genome analyses were conducted together with genome data downloaded from the NCBI database. The two Excel files were processed data, providing summaries of the genome analysis by sample types, and the zip file contained the raw data used in the analysis. Downloaded sequences were not included in the zip file.
DOI: 10.25442/hku.29977666.v1
title: Supporting data for "antimicrobial resistance and pathogen transmission in clinical and food samples in Hong Kong"

description: This study comprehensively investigates antimicrobial resistance (AMR) in Hong Kong across clinical, food, animal, and environmental reservoirs using a One Health approach. The data files were used to determine the current situation of the resistome profile in Gram-negative bacteria isolated from food and clinical isolates in Hong Kong. Genome analyses were conducted together with genome data downloaded from the NCBI database. The two Excel files were processed data, providing summaries of the genome analysis by sample types, and the zip file contained the raw data used in the analysis. Downloaded sequences were not included in the zip file.
DOI: 10.15468/dl.65atd9
title: Occurrence Download

description: A dataset containing 78265 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Thymus serpyllum"
 ]
}

 The dataset includes 78265 records from 666 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044018-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25442/hku.29992651
title: Supporting data for ''Eliciting Broadly Neutralizing Antibodies against HIV-1 by Vaccinations Using Immunogens Derived from a Chinese Patient''

description: My research projects involve construction of HIV-1 vaccines based on the envelope glycoproteins of HIV-1 as the immunogens, investigation of humoral antibody responses of those vaccines on animals, and discovery of antibodies from the immunized animals. Specifically, 16 vaccines were constructed, with a total of 109 animals utilized for investigating the immune responses. The datasets are categorized by chapters of my thesis. Files that utilized for constructing each figures were put into one file with the name of that figure. Chapter 3 of my thesis described the construction and characterization of vaccines, and thereby all the files in Dataset (Chapter 3) are related to the blue-native PAGE, western blotting analysis, DNA gel electrophoresis, ELISA for relative antigenicity, size exclusion chromatography, and immunofluorescence assays results. Chapter 4 of my thesis describe the immune responses of the animal immunization studies, and thereby all the files in Dataset (Chapter 4) are related to ELISA for endpoint titer measurement and pseudoviruses neutralization assay. Chapter 5 of my thesis describe the antibody isolation from immunized animals, and thereby all the files in Dataset (Chapter 5) are related to primer design, DNA gel electrophoresis for antibody recovery, FACS sorting data, sanger sequencing of recovered antibody, and profiling. All the raw data and analyzed data (if required) are included
DOI: 10.25442/hku.29992651.v1
title: Supporting data for ''Eliciting Broadly Neutralizing Antibodies against HIV-1 by Vaccinations Using Immunogens Derived from a Chinese Patient''

description: My research projects involve construction of HIV-1 vaccines based on the envelope glycoproteins of HIV-1 as the immunogens, investigation of humoral antibody responses of those vaccines on animals, and discovery of antibodies from the immunized animals. Specifically, 16 vaccines were constructed, with a total of 109 animals utilized for investigating the immune responses. The datasets are categorized by chapters of my thesis. Files that utilized for constructing each figures were put into one file with the name of that figure. Chapter 3 of my thesis described the construction and characterization of vaccines, and thereby all the files in Dataset (Chapter 3) are related to the blue-native PAGE, western blotting analysis, DNA gel electrophoresis, ELISA for relative antigenicity, size exclusion chromatography, and immunofluorescence assays results. Chapter 4 of my thesis describe the immune responses of the animal immunization studies, and thereby all the files in Dataset (Chapter 4) are related to ELISA for endpoint titer measurement and pseudoviruses neutralization assay. Chapter 5 of my thesis describe the antibody isolation from immunized animals, and thereby all the files in Dataset (Chapter 5) are related to primer design, DNA gel electrophoresis for antibody recovery, FACS sorting data, sanger sequencing of recovered antibody, and profiling. All the raw data and analyzed data (if required) are included
DOI: 10.15468/dl.f3p2kv
title: Occurrence Download

description: A dataset containing 289 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euphorbia heterophylla",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 289 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044100-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d9nzf4
title: Occurrence Download

description: A dataset containing 153 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euphorbia heterophylla",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 153 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044097-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25442/hku.29993734
title: Supporting data for "Different diagnostic methods for evaluating antibiotics resistance in Clostridioides difficile"

description: This study aimed to evaluate the performance of the gradient strip method with the agar dilution method for determining the minimum inhibitory concentrations (MICs) of MTZ and VAN against C. difficile, assess the reproducibility of the gradient strip method, and explore the correlation between genotypic characteristics and phenotypic AMR patterns.This retrospective cohort study examined 150 deduplicated clinical C. difficile isolates collected from Queen Elizabeth Hospital, Kwong Wah Hospital and Queen Mary Hospital in Hong Kong between 2023 and 2024. The MIC values for MTZ and VAN were determined for each isolate using both the agar dilution (reference method) and gradient strip methods, with their essential (EA) and categorical (CA) agreement calculated according to the US Food and DrugAdministration’s (FDA) criteria. The reproducibility was assessed using technical replicates and represented by Bland-Altman plots. Lastly, phenotypic MICs of the isolates were compared with their corresponding genetic AMR profiles determined by whole genome sequencing.
DOI: 10.25442/hku.29993734.v1
title: Supporting data for "Different diagnostic methods for evaluating antibiotics resistance in Clostridioides difficile"

description: This study aimed to evaluate the performance of the gradient strip method with the agar dilution method for determining the minimum inhibitory concentrations (MICs) of MTZ and VAN against C. difficile, assess the reproducibility of the gradient strip method, and explore the correlation between genotypic characteristics and phenotypic AMR patterns.This retrospective cohort study examined 150 deduplicated clinical C. difficile isolates collected from Queen Elizabeth Hospital, Kwong Wah Hospital and Queen Mary Hospital in Hong Kong between 2023 and 2024. The MIC values for MTZ and VAN were determined for each isolate using both the agar dilution (reference method) and gradient strip methods, with their essential (EA) and categorical (CA) agreement calculated according to the US Food and DrugAdministration’s (FDA) criteria. The reproducibility was assessed using technical replicates and represented by Bland-Altman plots. Lastly, phenotypic MICs of the isolates were compared with their corresponding genetic AMR profiles determined by whole genome sequencing.
DOI: 10.15468/dl.aw5w6u
title: Occurrence Download

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

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044101-250827131500795/datasets/export for details.
DOI: 10.7910/dvn/wegqsb
title: Acanthaceae

description: Conjunto de dados sobre a família botânica Acanthaceae, coletados a partir de diferentes projetos e parcerias em expedições botânicas na Amazônia brasileira, que auxilam a identificação da biodiversidade da flora amazônica.
DOI: 10.25442/hku.29755940
title: Supporting data for "Electrochemical Aptamer Biosensors for Point-of-Care Diagnostics"

description: This dataset contains the 4 projects in the thesis titled "Electrochemical Aptamer Biosensors for Point-of-Care Diagnostics".The saliva COVID nucleocapsid (N) protein detection project describes the adaptation of 4 different N protein aptamers into electrochemical biosensing for COVID diagnosis using saliva samples.The Liquid-Liquid phase separation (LLPS) electrochemical aptamer biosensing project investigates COVID spike protein enrichment and improved electrochemical sensitivity in synthetic and serum biofluids.The methylene-blue (MB)-modified aptamer electrochemical sensing is a novel non-natural aptamer with intrinsic redox activity for CA19-9 pancreatic cancer diagnosis.The aptamer-OECT is the integration of organic electrochemical transistor into traditional electrochemical aptamer biosensing for enhanced analytical sensitivity against cortisol, insulin and spike protein.Each project folder includes the raw data files, excel logbook for analysis and Origin files for figures. Raw data files are allocated into separated subfolders according to the subtitles in each thesis chapter. Excel files record the data summary for all experiments described in the thesis. The Origin files summarize the data from each experiment to plot the figures presented in the thesis.<br>
DOI: 10.25442/hku.29755940.v1
title: Supporting data for "Electrochemical Aptamer Biosensors for Point-of-Care Diagnostics"

description: This dataset contains the 4 projects in the thesis titled "Electrochemical Aptamer Biosensors for Point-of-Care Diagnostics".The saliva COVID nucleocapsid (N) protein detection project describes the adaptation of 4 different N protein aptamers into electrochemical biosensing for COVID diagnosis using saliva samples.The Liquid-Liquid phase separation (LLPS) electrochemical aptamer biosensing project investigates COVID spike protein enrichment and improved electrochemical sensitivity in synthetic and serum biofluids.The methylene-blue (MB)-modified aptamer electrochemical sensing is a novel non-natural aptamer with intrinsic redox activity for CA19-9 pancreatic cancer diagnosis.The aptamer-OECT is the integration of organic electrochemical transistor into traditional electrochemical aptamer biosensing for enhanced analytical sensitivity against cortisol, insulin and spike protein.Each project folder includes the raw data files, excel logbook for analysis and Origin files for figures. Raw data files are allocated into separated subfolders according to the subtitles in each thesis chapter. Excel files record the data summary for all experiments described in the thesis. The Origin files summarize the data from each experiment to plot the figures presented in the thesis.<br>
DOI: 10.15468/dl.92wuhg
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dicrossus warzeli)",
 "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 18 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044098-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17082275
title: THE ROLE OF TOBACCO IN THE HUMAN BODY, ITS MECHANISMS OF ACTION AND PREVENTION.
DOI: 10.5281/zenodo.17082276
title: THE ROLE OF TOBACCO IN THE HUMAN BODY, ITS MECHANISMS OF ACTION AND PREVENTION.
DOI: 10.15468/dl.sae4wq
title: Occurrence Download

description: A dataset containing 6469 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pityopsis graminifolia"
 ]
}

 The dataset includes 6469 records from 180 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044099-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25442/hku.30000457
title: Supporting data for "Aptamers for Exosome Enrichment and Their Multifunctional Applications in Biomolecular Sensing"

description: This thesis focuses on the development of DNA aptamers for exosome enrichment and biosensor establishment. The research includes the isolation of exosomes, selection of DNA aptamers with high affinity, and the application of these aptamers for enhanced exosome enrichment and detection. In addition, the aptamers are integrated with optical fiber technology to construct an aptamer–optical fiber biosensor, enabling the sensitive detection of exosomes and viral proteins. All experimental data generated throughout the study have been compiled into the accompanying dataset. This dataset contains raw data collected from various experiments, including gel electrophoresis, ELONA, western blot, and transmission electron microscopy (TEM), as well as processed data and analysis files, primarily generated using GraphPad Prism. All files are named and numbered according to the corresponding figures and experiments presented in the thesis. For access to specific data documents, please refer to the instructions provided in the README file.