cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2khw54
title: CCDC 2368746: Experimental Crystal Structure Determination

description: Related Article: Shuai Liang, Shi-Kun Yan, Yu-Xuan Wen, Yan-Rui Zhao, Jin Zhang, Ji-Xiang Hu|2024|J.Mater.Chem.C|13|672|doi:10.1039/D4TC04169K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2l56bb
title: CCDC 2388281: Experimental Crystal Structure Determination

description: Related Article: Krishna Pandey, Samsul Arafin, Grayson Venus, Eli Jones, Yachu Du, Mina Dumre Pandey, Tahir Awais, Lichang Wang, Kyle N. Plunkett|2025|J.Mater.Chem.C|13|842|doi:10.1039/D4TC04251D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2l56cc
title: CCDC 2388282: Experimental Crystal Structure Determination

description: Related Article: Krishna Pandey, Samsul Arafin, Grayson Venus, Eli Jones, Yachu Du, Mina Dumre Pandey, Tahir Awais, Lichang Wang, Kyle N. Plunkett|2025|J.Mater.Chem.C|13|842|doi:10.1039/D4TC04251D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2l24rl
title: CCDC 2385349: Experimental Crystal Structure Determination

description: Related Article: Shuai Liang, Shi-Kun Yan, Yu-Xuan Wen, Yan-Rui Zhao, Jin Zhang, Ji-Xiang Hu|2024|J.Mater.Chem.C|13|672|doi:10.1039/D4TC04169K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2l56dd
title: CCDC 2388283: Experimental Crystal Structure Determination

description: Related Article: Krishna Pandey, Samsul Arafin, Grayson Venus, Eli Jones, Yachu Du, Mina Dumre Pandey, Tahir Awais, Lichang Wang, Kyle N. Plunkett|2025|J.Mater.Chem.C|13|842|doi:10.1039/D4TC04251D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.734hec
title: Occurrence Download

description: A dataset containing 36438 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capra hircus Linnaeus, 1758",
 "Country is Australia",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 36438 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055959-241126133413365/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.28131524
title: Dataset of Risks Analysis and Internet Perception Among Spanish University Students (EU-JER Journal)

description: Dataset used to analysis
DOI: 10.6084/m9.figshare.28131524.v1
title: Dataset of Risks Analysis and Internet Perception Among Spanish University Students (EU-JER Journal)

description: Dataset used to analysis
DOI: 10.15468/dl.fvcjt2
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Achatina fulica Bowdich, 1822"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055962-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nmrrb7
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Cuba",
 "TaxonKey is Eugenia uniflora L."
 ]
}

 The dataset includes 17 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055963-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uapeuz
title: Occurrence Download

description: A dataset containing 2423 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is SANT-Bryo"
 ]
}

 The dataset includes 2423 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055964-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c50000c1x
title: MassIVE MSV000096771 - Metabolic consequences of erastin-induced ferroptosis in human ovarian cancer cells
title: Ovarian cancer has been difficult to cure due to acquired or intrinsic resistance Q10 and therefore, newer or more effective drugs/approaches are needed for a successful treatment in the clinic. Erastin (ER), a ferroptosis inducer, kills tumor cells by generating and accumulating reactive oxygen species (ROS) within the cell, resulting in an iron-dependent oxidative damage-mediated ferroptotic cell death. We have utilized human ovarian cancer cell lines, OVCAR- 8 and its adriamycin-selected, multi-drug resistance protein (MDR1)-expressing NCI/ADR-RES, both equally sensitive to ER, to identify metabolic biomarkers of ferroptosis. Our studies showed that ER treatment rapidly depleted cellular glutathione and cysteine and enhanced formation of ophthalamate (OPH) in both cells. Opthalalmate has been proposed to be a biomarker of oxidative stress in cells. Our study also found significant decreases in cellular taurine, a natural antioxidant in cells. Additionally, we found that ER treatment decreased cellular levels of NAD+/NADP+, carnitines and glutamine/glutamate in both cells, suggesting significant oxidative stress, decrease in energy production, and cellular and mitochondrial disfunctions, leading to cell death. Our studies identified several potential biomarkers of ER-induced ferroptosis including OPH, taurine, NAD+, NADP+ and glutamate in ovarian cancer cells. Identifying specific metabolic biomarkers that are predictive of whether a cancer is susceptible to ferroptosis will help us devise more successful treatment modalities.
DOI: 10.6084/m9.figshare.28099772
title: <b>Cross-Cultural Validation of the Sexual Experiences Survey: Sexual Violence in Costa Rica - Datasets and Materials</b>

description: Cross-cultural validation of research measures is a necessary and often overlooked step when conducting research within new study populations. This study focuses on the translation and adaptation of the Sexual Experiences Survey - Short Form Victimization (SES; Koss et al., 2007) for its use in Costa Rica. A total of 182 women participated in two studies testing the original, translated SES and later the adapted Costa Rican Sexual Experiences Survey (CRSES). Adaptation of the instrument followed guidelines from local experts in gender-based violence, feedback from study participants, and translation support from a local philologist. Results show an increase in reporting rates with the CRSES, excellent internal reliability when using both instruments, as well as reliable construct validity when testing the association between the CRSES and post-traumatic stress disorder, a variable commonly associated with sexual violence victimization. Sexual violence rates in this study were high, urging future research on the subject in Costa Rica.
DOI: 10.6084/m9.figshare.28099772.v1
title: <b>Cross-Cultural Validation of the Sexual Experiences Survey: Sexual Violence in Costa Rica - Datasets</b>

description: Cross-cultural validation of research measures is a necessary and often overlooked step when conducting research within new study populations. This study focuses on the adaptation and translation of the Sexual Experiences Survey (SES; Koss et al., 2007) for its use in Costa Rica. A total of 182 women participated in two studies testing the original translated SES and later the adapted Costa Rican Sexual Experiences Survey (CRSES). Results show an increase in reporting rates with the CRSES, as well as reliable construct validity when testing the association between sexual violence and PTSD. Sexual violence rates in this study were high, urging future research on the subject in Costa Rica.
DOI: 10.6084/m9.figshare.28131647
title: Dataset of "¿Predice el miedo a sentirse excluido (FOMO) el uso problemático de internet? Análisis en universitarios/as españoles/as"

description: Dataset to analysis
DOI: 10.6084/m9.figshare.28131647.v1
title: Dataset of "¿Predice el miedo a sentirse excluido (FOMO) el uso problemático de internet? Análisis en universitarios/as españoles/as"

description: Dataset to analysis
DOI: 10.6084/m9.figshare.27702576
title: Simulation-Based, Finite-Sample Inference for Privatized Data

description: Privacy protection methods, such as differentially private mechanisms, introduce noise into resulting statistics which often produces complex and intractable sampling distributions. In this article, we propose a simulation-based “repro sample” approach to produce statistically valid confidence intervals and hypothesis tests, which builds on the work of Xie and Wang. We show that this methodology is applicable to a wide variety of private inference problems, appropriately accounts for biases introduced by privacy mechanisms (such as by clamping), and improves over other state-of-the-art inference methods such as the parametric bootstrap in terms of the coverage and Type I error of the private inference. We also develop significant improvements and extensions for the repro sample methodology for general models (not necessarily related to privacy), including (a) modifying the procedure to ensure guaranteed coverage and Type I errors, even accounting for Monte Carlo error, and (b) proposing efficient numerical algorithms to implement the confidence intervals and <i>p</i>-values. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.27702576.v2
title: Simulation-Based, Finite-Sample Inference for Privatized Data

description: Privacy protection methods, such as differentially private mechanisms, introduce noise into resulting statistics which often produces complex and intractable sampling distributions. In this article, we propose a simulation-based “repro sample” approach to produce statistically valid confidence intervals and hypothesis tests, which builds on the work of Xie and Wang. We show that this methodology is applicable to a wide variety of private inference problems, appropriately accounts for biases introduced by privacy mechanisms (such as by clamping), and improves over other state-of-the-art inference methods such as the parametric bootstrap in terms of the coverage and Type I error of the private inference. We also develop significant improvements and extensions for the repro sample methodology for general models (not necessarily related to privacy), including (a) modifying the procedure to ensure guaranteed coverage and Type I errors, even accounting for Monte Carlo error, and (b) proposing efficient numerical algorithms to implement the confidence intervals and <i>p</i>-values. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.27702576.v1
title: Simulation-based, Finite-sample Inference for Privatized Data

description: Privacy protection methods, such as differentially private mechanisms, introduce noise into resulting statistics which often produces complex and intractable sampling distributions. In this paper, we propose a simulation-based “repro sample” approach to produce statistically valid confidence intervals and hypothesis tests, which builds on the work of Xie and Wang (2022). We show that this methodology is applicable to a wide variety of private inference problems, appropriately accounts for biases introduced by privacy mechanisms (such as by clamping), and improves over other state-of-the-art inference methods such as the parametric bootstrap in terms of the coverage and type I error of the private inference. We also develop significant improvements and extensions for the repro sample methodology for general models (not necessarily related to privacy), including 1) modifying the procedure to ensure guaranteed coverage and type I errors, even accounting for Monte Carlo error, and 2) proposing efficient numerical algorithms to implement the confidence intervals and <i>p</i>-values.
DOI: 10.6084/m9.figshare.27702574
title: Unlocking Retrospective Prevalent Information in EHRs—A Revisit to the Pairwise Pseudolikelihood

description: Electronic health records offer abundant data on various diseases and health conditions, enabling researchers to explore the relationship between disease onset age and underlying risk factors. Unlike mortality data, the event of interest is nonterminal, hence, individuals can retrospectively report their disease-onset-age upon recruitment to the study. These individuals, diagnosed with the disease before entering the study, are termed “prevalent.” The ascertainment imposes a left truncation condition, also known as a “delayed entry,” because individuals had to survive a certain period before being eligible for enrollment. The standard method to accommodate delayed entry conditions on the entire history up to recruitment, hence, the retrospective prevalent failure times are conditioned upon and cannot participate in estimating the disease-onset-age distribution. Other methods that condition on less information and allow the incorporation of the prevalent observations either bring about numerical and computational difficulties or require statistical assumptions that are violated by most biobanks. This work presents a novel estimator of the coefficients in a regression model for the age-at-onset, successfully using the prevalent data. Asymptotic results are provided, and simulations are conducted to showcase the substantial efficiency gain. In particular, the method is highly useful in leveraging large-scale repositories for replication analysis of genetic variants. Indeed, analysis of urinary bladder cancer data reveals that the proposed approach yields about twice as many replicated discoveries compared to the popular approach. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.27702574.v2
title: Unlocking Retrospective Prevalent Information in EHRs—A Revisit to the Pairwise Pseudolikelihood

description: Electronic health records offer abundant data on various diseases and health conditions, enabling researchers to explore the relationship between disease onset age and underlying risk factors. Unlike mortality data, the event of interest is nonterminal, hence, individuals can retrospectively report their disease-onset-age upon recruitment to the study. These individuals, diagnosed with the disease before entering the study, are termed “prevalent.” The ascertainment imposes a left truncation condition, also known as a “delayed entry,” because individuals had to survive a certain period before being eligible for enrollment. The standard method to accommodate delayed entry conditions on the entire history up to recruitment, hence, the retrospective prevalent failure times are conditioned upon and cannot participate in estimating the disease-onset-age distribution. Other methods that condition on less information and allow the incorporation of the prevalent observations either bring about numerical and computational difficulties or require statistical assumptions that are violated by most biobanks. This work presents a novel estimator of the coefficients in a regression model for the age-at-onset, successfully using the prevalent data. Asymptotic results are provided, and simulations are conducted to showcase the substantial efficiency gain. In particular, the method is highly useful in leveraging large-scale repositories for replication analysis of genetic variants. Indeed, analysis of urinary bladder cancer data reveals that the proposed approach yields about twice as many replicated discoveries compared to the popular approach. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.27702574.v1
title: Unlocking Retrospective Prevalent Information in EHRs - a Revisit to the Pairwise Pseudolikelihood

description: Electronic health records offer abundant data on various diseases and health conditions, enabling researchers to explore the relationship between disease onset age and underlying risk factors. Unlike mortality data, the event of interest is non-terminal, hence individuals can retrospectively report their disease-onset-age upon recruitment to the study. These individuals, diagnosed with the disease before entering the study, are termed “prevalent”. The ascertainment imposes a left truncation condition, also known as a “delayed entry”, because individuals had to survive a certain period before being eligible for enrollment. The standard method to accommodate delayed entry conditions on the entire history up to recruitment, hence the retrospective prevalent failure times are conditioned upon and cannot participate in estimating the disease-onset-age distribution. Other methods that condition on less information and allow the incorporation of the prevalent observations either bring about numerical and computational difficulties or require statistical assumptions that are violated by most biobanks. This work presents a novel estimator of the coefficients in a regression model for the age-at-onset, successfully utilizing the prevalent data. Asymptotic results are provided, and simulations are conducted to showcase the substantial efficiency gain. In particular, the method is highly useful in leveraging large-scale repositories for replication analysis of genetic variants. Indeed, analysis of urinary bladder cancer data reveals that the proposed approach yields about twice as many replicated discoveries compared to the popular approach.
DOI: 10.6084/m9.figshare.28131658
title: Robust Bayesian Modeling of Counts with Zero Inflation and Outliers: Theoretical Robustness and Efficient Computation

description: Count data with zero inflation and large outliers are ubiquitous in many scientific applications. However, posterior analysis under a standard statistical model, such as Poisson or negative binomial distribution, is sensitive to such contamination. This study introduces a novel framework for Bayesian modeling of counts that is robust to both zero inflation and large outliers. In doing so, we introduce rescaled beta distribution and adopt it to absorb undesirable effects from zero and outlying counts. The proposed approach has two appealing features: the efficiency of the posterior computation via a custom Gibbs sampling algorithm and a theoretically guaranteed posterior robustness, where extreme outliers are automatically removed from the posterior distribution. We demonstrate the usefulness of the proposed method by applying it to trend filtering and spatial modeling using predictive Gaussian processes.
DOI: 10.6084/m9.figshare.28131658.v1
title: Robust Bayesian Modeling of Counts with Zero Inflation and Outliers: Theoretical Robustness and Efficient Computation

description: Count data with zero inflation and large outliers are ubiquitous in many scientific applications. However, posterior analysis under a standard statistical model, such as Poisson or negative binomial distribution, is sensitive to such contamination. This study introduces a novel framework for Bayesian modeling of counts that is robust to both zero inflation and large outliers. In doing so, we introduce rescaled beta distribution and adopt it to absorb undesirable effects from zero and outlying counts. The proposed approach has two appealing features: the efficiency of the posterior computation via a custom Gibbs sampling algorithm and a theoretically guaranteed posterior robustness, where extreme outliers are automatically removed from the posterior distribution. We demonstrate the usefulness of the proposed method by applying it to trend filtering and spatial modeling using predictive Gaussian processes.
DOI: 10.6084/m9.figshare.28131662
title: Supplementary Material for: Incidence and clinical features of inguinal metastases of testicular germ cell tumors

description: Introduction
Half of all patients with testicular germ cell tumours (GCTs) present with metastases to retroperitoneal lymph nodes or visceral organs. Inguinal metastases (I/M) are very rare. We aimed to evaluate the relative frequency and clinical features of I/M and to look for predisposing factors.
Methods
A cohort of 740 GCT patients treated between 2010-2022 was analyzed. The frequency of I/M and their clinical features were statistically compared among the subgroups. 
Results
Eight patients had I/M, with a median age of 55 years, all of whom had primary seminoma, six had previous groin surgery. The relative frequency of I/M is 1.1% and 8.3% in the GCT patient cohort and the metastasized seminoma subgroup, respectively. All patients were cured, six underwent surgery and additional chemotherapy, and two received cisplatin-based chemotherapy alone. 
Discussion
Inguinal metastases occur in approximately 1% of GCT patients. Prior groin surgery, bulky retroperitoneal metastases and possibly histology of seminoma represent risk factors for I/M. The presence of I/M does not adversely affect prognosis, and all cases can be cured with standard therapeutic measures. Lymph node excision may be required to establish the diagnosis. In patients with risk factors, follow-up examinations should include the groins.
DOI: 10.15468/dl.4ajdhs
title: Occurrence Download

description: A dataset listing the 355 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Données STOC-EPS"
 ]
}

 The dataset's 355 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055961-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pjc42v
title: Occurrence Download

description: A dataset containing 3214 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Chordeiles acutipennis (Hermann, 1783)"
 ]
}

 The dataset includes 3214 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055966-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.