cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/v7luid
title: Replication Data for: Effects of Different Combinations of Hands-On and Virtual Lab Activities on Pre-Service Elementary Teachers’ Physical Science Content Knowledge and Self-Efficacy in Teaching Science

description: The dataset is for the manuscript "Effects of Different Combinations of Hands-On and Virtual Lab Activities on Pre-Service Elementary Teachers’ Physical Science Content Knowledge and Self-Efficacy in Teaching Science" submitted to Journal of College Science Teaching for publication. It consists of student responses to STEBI-B survey and Physical Science Content Knowledge (PSCK) test over three semesters.
description: The manuscript associated with the data was submitted and currently under review. I as the author am required to post their data in a suitable repository by Publicly Available data policy.
DOI: 10.15468/dl.3pjghz
title: Occurrence Download

description: A dataset containing 4148 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mnesithea Kunth"
 ]
}

 The dataset includes 4148 records from 91 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002263-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z3npbx
title: Occurrence Download

description: A dataset containing 113 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "Country is one of (United States of America, United States Minor Outlying Islands, American Samoa, Micronesia (Federated States of), Guam, Marshall Islands, Northern Mariana Islands, Puerto Rico, Palau, Virgin Islands (U.S.))",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Hesperia leonardus montana (Skinner, 1911))"
 ]
}

 The dataset includes 113 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002264-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/9smm09
title: A13_25227.jpg

description: Link to OCHRE database: &lt;a href = 'http://pi.lib.uchicago.edu/1001/org/ochre/23ff8e14-a662-4116-b91d-95970dee99ce'&gt;http://pi.lib.uchicago.edu/1001/org/ochre/23ff8e14-a662-4116-b91d-95970dee99ce
DOI: 10.7910/dvn/gqmsjh
title: Brush Mouse Data

description: Brush mouse dataset
DOI: 10.7910/dvn/gtki2i
title: PDB: 5X8M, Durvalumab in complex with Programmed death-ligand 1 (PD-L1) , random seed 3 (311.5K, 38.5°C, 500 ns): RMSD, SASA, RMSF, Rg, H-bonds

description: PDB: 5X8M, Durvalumab in complex with Programmed death-ligand 1 (PD-L1), random seed 3 (311.5K, 38.5°C, 500 ns): RMSD, SASA, RMSF, Rg, H-bonds
DOI: 10.7910/dvn/iuuejs
title: A13_24836.jpg

description: Link to OCHRE database: &lt;a href = 'http://pi.lib.uchicago.edu/1001/org/ochre/1e062028-d9c7-467c-989f-44446cf5d523'&gt;http://pi.lib.uchicago.edu/1001/org/ochre/1e062028-d9c7-467c-989f-44446cf5d523
DOI: 10.7910/dvn/8mnpoq
title: Interleukin 1-beta contributes to chronic obstructive pulmonary disease development by inducing reactive oxygen species production in neutrophils

description: The original data of our work.
DOI: 10.7910/dvn/fl5kvq
title: A89_3388.jpg

description: Link to OCHRE database: &lt;a href = 'http://pi.lib.uchicago.edu/1001/org/ochre/d91fc90d-36d7-504c-58f2-cef469a1d379'&gt;http://pi.lib.uchicago.edu/1001/org/ochre/d91fc90d-36d7-504c-58f2-cef469a1d379
DOI: 10.15468/dl.h5fdma
title: Occurrence Download

description: A dataset containing 23395 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mollugo L."
 ]
}

 The dataset includes 23395 records from 635 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002265-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m2r5ef
title: Occurrence Download

description: A dataset containing 1103549 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Belgium, Germany, Netherlands)",
 "TaxonKey is one of (Ondatra zibethicus (Linnaeus, 1766), Myocastor coypus (Molina, 1782))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1103549 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014487-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sry8pm
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-100.29561 24.64973,-100.0938 24.64973,-100.0938 24.9558,-100.29561 24.9558,-100.29561 24.64973))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Anaxyrus punctatus (Baird & Girard, 1852)"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014497-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nvqzrg
title: Occurrence Download

description: A dataset containing 85704 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Toxicodendron radicans (L.) Kuntze)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 85704 records from 259 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014496-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sxwxdm
title: Occurrence Download

description: A dataset containing 4710 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tradescantia spathacea Sw.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 4710 records from 128 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014498-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sud9t2
title: Occurrence Download

description: A dataset containing 351 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tribolium obliterum (Hemsl.) Renvoize)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 351 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014499-250525065834625/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.27679207
title: Applications of automatic speech recognition and text-to-speech technologies for hearing assessment: a scoping review

description: Exploring applications of automatic speech recognition and text-to-speech technologies in hearing assessment and evaluations of hearing aids. Review protocol was registered at the INPLASY database and was performed following the PRISMA scoping review guidelines. A search in ten databases was conducted in January 2023 and updated in June 2024. Studies that used automatic speech recognition or text-to-speech to assess measures of hearing ability (e.g. speech reception threshold), or to configure hearing aids were retrieved. Of the 2942 records found, 28 met the inclusion criteria. The results indicated that text-to-speech could effectively replace recorded stimuli in speech intelligibility tests, requiring less effort for experimenters, without negatively impacting outcomes (n = 5). Automatic speech recognition captured verbal responses accurately, allowing for reliable speech reception threshold measurements without human supervision (n = 7). Moreover, automatic speech recognition was employed to simulate participants’ hearing, with high correlations between simulated and empirical data (n = 14). Finally, automatic speech recognition was used to optimise hearing aid configurations, leading to higher speech intelligibility for wearers compared to the original configuration (n = 3). There is the potential for automatic speech recognition and text-to-speech systems to enhance accessibility of, and efficiency in, hearing assessments, offering unsupervised testing options, and facilitating hearing aid personalisation.
DOI: 10.6084/m9.figshare.27679207.v1
title: Applications of automatic speech recognition and text-to-speech technologies for hearing assessment: a scoping review

description: Exploring applications of automatic speech recognition and text-to-speech technologies in hearing assessment and evaluations of hearing aids. Review protocol was registered at the INPLASY database and was performed following the PRISMA scoping review guidelines. A search in ten databases was conducted in January 2023 and updated in June 2024. Studies that used automatic speech recognition or text-to-speech to assess measures of hearing ability (e.g. speech reception threshold), or to configure hearing aids were retrieved. Of the 2942 records found, 28 met the inclusion criteria. The results indicated that text-to-speech could effectively replace recorded stimuli in speech intelligibility tests, requiring less effort for experimenters, without negatively impacting outcomes (n = 5). Automatic speech recognition captured verbal responses accurately, allowing for reliable speech reception threshold measurements without human supervision (n = 7). Moreover, automatic speech recognition was employed to simulate participants’ hearing, with high correlations between simulated and empirical data (n = 14). Finally, automatic speech recognition was used to optimise hearing aid configurations, leading to higher speech intelligibility for wearers compared to the original configuration (n = 3). There is the potential for automatic speech recognition and text-to-speech systems to enhance accessibility of, and efficiency in, hearing assessments, offering unsupervised testing options, and facilitating hearing aid personalisation.
DOI: 10.6084/m9.figshare.28327918
title: Meta-analysis on lexical tone recognition in cochlear implant users

description: Lexical tone plays a vital role in speech communication in tonal languages. This study investigated lexical tone recognition in cochlear implant (CI) users, and identified potential factors that influence lexical tone recognition in the CI population. We conducted a systematic search across eleven major databases, evaluated the risk of bias in the included studies, and conducted five meta-analyses. Forty studies that utilised a multi-item alternative forced-choice paradigm were included to evaluate the performance of lexical tone recognition in CI users. CI users performed worse at recognising lexical tones than normal hearing (NH) controls. Furthermore, bimodal stimulation could benefit lexical tone recognition for CI users in both quiet and noisy conditions. Besides, the pooled results showed a negative correlation between tone recognition accuracy and age at implantation, as well as a positive correlation between tone recognition performance and the duration of CI experience. This study indicates that CI users could not recognise lexical tones at the same level as the NH population. The bimodal intervention does have a more positive effect than unimodal implantation regardless of the listening environment. Moreover, earlier implantation and longer experience with the CI could facilitate lexical tone recognition.
DOI: 10.6084/m9.figshare.28327918.v1
title: Meta-analysis on lexical tone recognition in cochlear implant users

description: Lexical tone plays a vital role in speech communication in tonal languages. This study investigated lexical tone recognition in cochlear implant (CI) users, and identified potential factors that influence lexical tone recognition in the CI population. We conducted a systematic search across eleven major databases, evaluated the risk of bias in the included studies, and conducted five meta-analyses. Forty studies that utilised a multi-item alternative forced-choice paradigm were included to evaluate the performance of lexical tone recognition in CI users. CI users performed worse at recognising lexical tones than normal hearing (NH) controls. Furthermore, bimodal stimulation could benefit lexical tone recognition for CI users in both quiet and noisy conditions. Besides, the pooled results showed a negative correlation between tone recognition accuracy and age at implantation, as well as a positive correlation between tone recognition performance and the duration of CI experience. This study indicates that CI users could not recognise lexical tones at the same level as the NH population. The bimodal intervention does have a more positive effect than unimodal implantation regardless of the listening environment. Moreover, earlier implantation and longer experience with the CI could facilitate lexical tone recognition.
DOI: 10.15468/dl.k4xad9
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-70.64404 20.74165,-73.90107 20.01283,-75.30894 18.32583,-70.93822 16.80334,-67.99639 18.24602,-67.57613 19.26077,-70.64404 20.74165))",
 "HasGeospatialIssue is false",
 "TaxonKey is Phylloicus Mueller, 1880"
 ]
}

 The dataset includes 17 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014500-250525065834625/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.25018123
title: Developing of SARS-CoV-2 fusion protein expressed in E. coli Shuffle T7 for enhanced ELISA detection sensitivity – an integrated experimental and bioinformatic approach

description: In the recent COVID-19 pandemic, developing effective diagnostic assays is crucial for controlling the spread of the SARS-CoV-2 virus. Multi-domain fusion proteins are a promising approach to detecting SARS-CoV-2 antibodies. In this study, we designed an antigen named CoV2-Pro, containing two RBD domains from SARS-CoV-2 Omicron and Delta variants and one CTD domain of the nucleoprotein in the order of RBD-RBD-N, linked by a super flexible glycine linker. We evaluated the suitability of E. coli Shuffle T7 and BL21 (DE3) strain for expressing CoV2-Pro. Moreover, Bioinformatic studies were conducted first to analyze the tertiary structure of CoV2-Pro. The CoV2-Pro sequences were cloned into a pET-32b (+) vector for expression in E. coli Shuffle T7 and BL21 (DE3). SDS-PAGE and western blot confirmed the protein expression and folding structure. The CoV2-Pro-TRX was purified by Ni-NTA affinity chromatography. Dot blot analysis was performed to evaluate the antigenic characterization of the CoV2-Pro. A molecular docking simulation was conducted to assess the binding affinity of CoV2-Pro with LY-COV555 (Bamlanivimab) monoclonal antibody. A molecular dynamic was performed to analyze the stability of the structure. Bioinformatic and experimental studies revealed a stable conformational 3D structure of the CoV2-Pro. The CoV2-Pro interacted with SARS-CoV-2 antibodies, confirming the correct antigenic structure. We assert with confidence that CoV2-Pro is ideal for developing an ELISA assay for precise diagnosis and rigorous vaccine evaluation during the COVID-19 prevalence.
DOI: 10.6084/m9.figshare.25018123.v1
title: Developing of SARS-CoV-2 fusion protein expressed in E. coli Shuffle T7 for enhanced ELISA detection sensitivity – an integrated experimental and bioinformatic approach

description: In the recent COVID-19 pandemic, developing effective diagnostic assays is crucial for controlling the spread of the SARS-CoV-2 virus. Multi-domain fusion proteins are a promising approach to detecting SARS-CoV-2 antibodies. In this study, we designed an antigen named CoV2-Pro, containing two RBD domains from SARS-CoV-2 Omicron and Delta variants and one CTD domain of the nucleoprotein in the order of RBD-RBD-N, linked by a super flexible glycine linker. We evaluated the suitability of E. coli Shuffle T7 and BL21 (DE3) strain for expressing CoV2-Pro. Moreover, Bioinformatic studies were conducted first to analyze the tertiary structure of CoV2-Pro. The CoV2-Pro sequences were cloned into a pET-32b (+) vector for expression in E. coli Shuffle T7 and BL21 (DE3). SDS-PAGE and western blot confirmed the protein expression and folding structure. The CoV2-Pro-TRX was purified by Ni-NTA affinity chromatography. Dot blot analysis was performed to evaluate the antigenic characterization of the CoV2-Pro. A molecular docking simulation was conducted to assess the binding affinity of CoV2-Pro with LY-COV555 (Bamlanivimab) monoclonal antibody. A molecular dynamic was performed to analyze the stability of the structure. Bioinformatic and experimental studies revealed a stable conformational 3D structure of the CoV2-Pro. The CoV2-Pro interacted with SARS-CoV-2 antibodies, confirming the correct antigenic structure. We assert with confidence that CoV2-Pro is ideal for developing an ELISA assay for precise diagnosis and rigorous vaccine evaluation during the COVID-19 prevalence.
DOI: 10.6084/m9.figshare.25018129.v1
title: NetVA: an R package for network vulnerability and influence analysis

description: In biological network analysis, identifying key molecules plays a decisive role in the development of potential diagnostic and therapeutic candidates. Among various approaches of network analysis, network vulnerability analysis is quite important, as it assesses significant associations between topological properties and the functional essentiality of a network. Similarly, some node centralities are also used to screen out key molecules. Among these node centralities, escape velocity centrality (EVC), and its extended version (EVC+) outperform others, <i>viz.</i>, Degree, Betweenness, and Clustering coefficient. Keeping this in mind, we aimed to develop a first-of-its-kind R package named NetVA, which analyzes networks to identify key molecular players (individual proteins and protein pairs/triplets) through network vulnerability and EVC+-based approaches. To demonstrate the application and relevance of our package in network analysis, previously published and publicly available protein–protein interactions (PPIs) data of human breast cancer were analyzed. This resulted in identifying some most important proteins. These included essential proteins, non-essential proteins, hubs, and bottlenecks, which play vital roles in breast cancer development. Thus, the NetVA package, available at https://github.com/kr-swapnil/NetVA with a detailed tutorial to download and use, assists in predicting potential candidates for therapeutic and diagnostic purposes by exploring various topological features of a disease-specific PPIs network.
DOI: 10.6084/m9.figshare.25018129
title: NetVA: an R package for network vulnerability and influence analysis

description: In biological network analysis, identifying key molecules plays a decisive role in the development of potential diagnostic and therapeutic candidates. Among various approaches of network analysis, network vulnerability analysis is quite important, as it assesses significant associations between topological properties and the functional essentiality of a network. Similarly, some node centralities are also used to screen out key molecules. Among these node centralities, escape velocity centrality (EVC), and its extended version (EVC+) outperform others, <i>viz.</i>, Degree, Betweenness, and Clustering coefficient. Keeping this in mind, we aimed to develop a first-of-its-kind R package named NetVA, which analyzes networks to identify key molecular players (individual proteins and protein pairs/triplets) through network vulnerability and EVC+-based approaches. To demonstrate the application and relevance of our package in network analysis, previously published and publicly available protein–protein interactions (PPIs) data of human breast cancer were analyzed. This resulted in identifying some most important proteins. These included essential proteins, non-essential proteins, hubs, and bottlenecks, which play vital roles in breast cancer development. Thus, the NetVA package, available at https://github.com/kr-swapnil/NetVA with a detailed tutorial to download and use, assists in predicting potential candidates for therapeutic and diagnostic purposes by exploring various topological features of a disease-specific PPIs network.
DOI: 10.6084/m9.figshare.25093383
title: Structural and accessibility studies highlight the differential binding of clemizole to TRPC5 and TRPC6

description: Transient Receptor Potential Canonical 5 (T RP C5) and T RP C6 channels play critical physiological roles in various cell types. Their involvement in numerous disease progression mechanisms has led to extensive searches for their inhibitors. Although several potent T RP C inhibitors have been developed and the structure of their binding sites were mapped using cryo electron microscopy, a comprehensive understanding of the molecular interactions within the inhibitor binding site of T RP Cs remains elusive. This study aimed to decipher the structural determinants and molecular mechanisms contributing to the differential binding of clemizole to T RP C5 and T RP C6, with a particular focus on the accessibility of binding site residues. This information can help better understand what molecular features allow for selective binding, which is a key characteristic of clinically effective pharmacological agents. Using computational methodologies, we conducted an in-depth molecular docking analysis of clemizole with T RP C5 and T RP C6 channels. The protein structures were retrieved from publicly accessible protein databases. Discovery Studio 2020 Client Visualizer and Chimera software facilitated our in-silico mutation experiments and enabled us to identify the critical structural elements influencing clemizole binding. Our study reveals key molecular determinants at the clemizole binding site, specifically outlining the role of residues' Accessible Surface Area (ASA) and Relative Accessible Surface Area (RASA) in differential binding. We found that lower accessibility of T RP C6 binding site residues, compared to those in T RP C5, could account for the lower affinity binding of clemizole to T RP C6. This work illuminates the pivotal role of binding site residue accessibility in determining the affinity of clemizole to T RP C5 and T RP C6. A nuanced understanding of the distinct binding properties between these homologous proteins may pave the way for the development of more selective inhibitors, promising improved therapeutic efficacy and fewer off-target effects. By demystifying the structural and molecular subtleties of T RP C inhibitors, this research could significantly accelerate the drug discovery process, offering hope to patients afflicted with T RP C-related diseases.