cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccvdwlp
title: CCDC 786953: Experimental Crystal Structure Determination

description: Related Article: Jian Zhang, J.T.Bu, Shumei Chen, Tao Wu, Shoutian Zheng, Yigang Chen, R.A.Nieto, Pingyun Feng, Xianhui Bu|2010|Angew.Chem.,Int.Ed.|49|8876|doi:10.1002/anie.201003900
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/ccvdwmq
title: CCDC 786954: Experimental Crystal Structure Determination

description: Related Article: Jian Zhang, J.T.Bu, Shumei Chen, Tao Wu, Shoutian Zheng, Yigang Chen, R.A.Nieto, Pingyun Feng, Xianhui Bu|2010|Angew.Chem.,Int.Ed.|49|8876|doi:10.1002/anie.201003900
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/ccvdwnr
title: CCDC 786955: Experimental Crystal Structure Determination

description: Related Article: Jian Zhang, J.T.Bu, Shumei Chen, Tao Wu, Shoutian Zheng, Yigang Chen, R.A.Nieto, Pingyun Feng, Xianhui Bu|2010|Angew.Chem.,Int.Ed.|49|8876|doi:10.1002/anie.201003900
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/ccvdwps
title: CCDC 786956: Experimental Crystal Structure Determination

description: Related Article: Jian Zhang, J.T.Bu, Shumei Chen, Tao Wu, Shoutian Zheng, Yigang Chen, R.A.Nieto, Pingyun Feng, Xianhui Bu|2010|Angew.Chem.,Int.Ed.|49|8876|doi:10.1002/anie.201003900
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.rhfv2h
title: Occurrence Download

description: A dataset containing 14611 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Fungi)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((127.5 30,135 30,135 37.5,127.5 37.5,127.5 30))"
 ]
}

 The dataset includes 14611 records from 87 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044410-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.32kap8
title: Occurrence Download

description: A dataset containing 14766 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2016",
 "Geometry POLYGON ((-27.76146 38.54798, -27.76945 38.55832, -27.99667 38.64139, -28.28555 38.74472, -28.29778 38.7486, -28.31556 38.7486, -28.315 38.73457, -28.30139 38.72139, -28.19416 38.65028, -28.15667 38.63486, -27.84862 38.54056, -27.81084 38.53999, -27.78028 38.54193, -27.76146 38.54798))"
 ]
}

 The dataset includes 14766 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042429-250920141307145/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.25750096.v1
title: Additional file 2 of A novel non-negative Bayesian stacking modeling method for Cancer survival prediction using high-dimensional omics data

description: Supplementary Material 2.
DOI: 10.6084/m9.figshare.26715541
title: Additional file 3 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 3. Clinical characteristics for the benign, malignant, and overlapping patients between the two LC-MS/MS analysis sets in the study cohort. Study population N = 117. Total range or percentage in the parentheses. *Total pancreatectomy includes total pancreatectomy and total pancreatoduodenectomy. **Other entities include all other benign entities than Intraductal Papillary Mucinous Neoplasm (IPMN) and pancreatitis. ***No patient diagnosed with benign disease had known development of cancer in the periampullary region by the time of last follow-up. **** The nine overlapping samples between the two LC-MS/MS runs used for normalization. BMI = body mass index [50]. CA19-9 = Cancer antigen 19-9.
DOI: 10.6084/m9.figshare.26715541.v1
title: Additional file 3 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 3. Clinical characteristics for the benign, malignant, and overlapping patients between the two LC-MS/MS analysis sets in the study cohort. Study population N = 117. Total range or percentage in the parentheses. *Total pancreatectomy includes total pancreatectomy and total pancreatoduodenectomy. **Other entities include all other benign entities than Intraductal Papillary Mucinous Neoplasm (IPMN) and pancreatitis. ***No patient diagnosed with benign disease had known development of cancer in the periampullary region by the time of last follow-up. **** The nine overlapping samples between the two LC-MS/MS runs used for normalization. BMI = body mass index [50]. CA19-9 = Cancer antigen 19-9.
DOI: 10.6084/m9.figshare.26715547
title: Additional file 5 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 5. Histopathology characteristics for the patients with malignant periampullary disease. Study population N = 72. Total range or percentage in the parenthesis.
DOI: 10.6084/m9.figshare.26715547.v1
title: Additional file 5 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 5. Histopathology characteristics for the patients with malignant periampullary disease. Study population N = 72. Total range or percentage in the parenthesis.
DOI: 10.6084/m9.figshare.26715553
title: Additional file 7 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 7. Differences in metabolite profiles ascribable to neoadjuvant treatment in malignant and benign samples – FDR values. Table with metabolites and associated FDR q-values when comparing samples from patients receiving neoadjuvant chemotherapy (N = 6) and cancer patients with no chemotherapy prior to surgery (N = 66)”. Wilcoxon’s Rank Sum Test was used to calculate the p-values. The p-values were adjusted for multiple testing by the Benjamini-Hochberg method (FDR). FDR-values &lt; 0.05 are in bold. See Additional file 6. FDR = False Discovery Rate.
DOI: 10.6084/m9.figshare.26715553.v1
title: Additional file 7 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 7. Differences in metabolite profiles ascribable to neoadjuvant treatment in malignant and benign samples – FDR values. Table with metabolites and associated FDR q-values when comparing samples from patients receiving neoadjuvant chemotherapy (N = 6) and cancer patients with no chemotherapy prior to surgery (N = 66)”. Wilcoxon’s Rank Sum Test was used to calculate the p-values. The p-values were adjusted for multiple testing by the Benjamini-Hochberg method (FDR). FDR-values &lt; 0.05 are in bold. See Additional file 6. FDR = False Discovery Rate.
DOI: 10.6084/m9.figshare.26715562
title: Additional file 10 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 10. Associations between clinical variables and metabolites and overall survival – Univariable Cox regression. Univariable Cox Regression model for patients with periampullary cancer (N = 64). Patients that received neoadjuvant chemotherapy (N = 6), one patient with metastasis at the time of diagnosis and one patient with non-standard treatment regime were excluded. P-values &lt; 0.05 are in bold. CI = Confidence Interval.
DOI: 10.6084/m9.figshare.26715562.v1
title: Additional file 10 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 10. Associations between clinical variables and metabolites and overall survival – Univariable Cox regression. Univariable Cox Regression model for patients with periampullary cancer (N = 64). Patients that received neoadjuvant chemotherapy (N = 6), one patient with metastasis at the time of diagnosis and one patient with non-standard treatment regime were excluded. P-values &lt; 0.05 are in bold. CI = Confidence Interval.
DOI: 10.6084/m9.figshare.26715568
title: Additional file 12 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 12. Associations between selected clinical variables and metabolites and overall survival in patients with periampullary cancer. Multivariable Cox Regression model for patients with periampullary cancer (N = 64) prior to stepwise regression algorithm with backwards elimination. Patients that received neoadjuvant chemotherapy (N = 6), one patient with metastasis at the time of diagnosis and one patient with non-standard treatment regime were excluded. P-values &lt; 0.05 are in bold. CI = Confidence Interval.
DOI: 10.6084/m9.figshare.26715568.v1
title: Additional file 12 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 12. Associations between selected clinical variables and metabolites and overall survival in patients with periampullary cancer. Multivariable Cox Regression model for patients with periampullary cancer (N = 64) prior to stepwise regression algorithm with backwards elimination. Patients that received neoadjuvant chemotherapy (N = 6), one patient with metastasis at the time of diagnosis and one patient with non-standard treatment regime were excluded. P-values &lt; 0.05 are in bold. CI = Confidence Interval.
DOI: 10.6084/m9.figshare.26715571
title: Additional file 13 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 13. Associations between selected clinical variables and metabolites and overall survival – Multivariable Cox regression. Multivariable Cox Regression model with stepwise regression algorithm with backwards elimination for patients with periampullary cancer (N = 64). Selection of variables based on univariable Cox regression model (Additional file 10). Patients that received neoadjuvant chemotherapy (N = 6), one patient with metastasis at the time of diagnosis and one patient with non-standard treatment regime were excluded. P-values &lt; 0.05 are in bold. CI = Confidence Interval.
DOI: 10.6084/m9.figshare.26715571.v1
title: Additional file 13 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 13. Associations between selected clinical variables and metabolites and overall survival – Multivariable Cox regression. Multivariable Cox Regression model with stepwise regression algorithm with backwards elimination for patients with periampullary cancer (N = 64). Selection of variables based on univariable Cox regression model (Additional file 10). Patients that received neoadjuvant chemotherapy (N = 6), one patient with metastasis at the time of diagnosis and one patient with non-standard treatment regime were excluded. P-values &lt; 0.05 are in bold. CI = Confidence Interval.
DOI: 10.6084/m9.figshare.26715583
title: Additional file 17 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 17. Differences in metabolite profiles in patients with benign and malignant disease - FDR values. Table with metabolites and associated FDR q-values when comparing samples from patients with benign (N = 45) and malignant (N = 66) periampullary disease. Patients with neoadjuvant chemotherapy were excluded (N = 6). Wilcoxon’s Rank Sum Test was used to calculate the p-values. The p-values were adjusted for multiple testing by the Benjamini-Hochberg method (FDR). FDR-values &lt; 0.05 are in bold. See Fig. 2 and Additional file 6. FDR = False Discovery Rate.
DOI: 10.6084/m9.figshare.26715583.v1
title: Additional file 17 of Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

description: Additional file 17. Differences in metabolite profiles in patients with benign and malignant disease - FDR values. Table with metabolites and associated FDR q-values when comparing samples from patients with benign (N = 45) and malignant (N = 66) periampullary disease. Patients with neoadjuvant chemotherapy were excluded (N = 6). Wilcoxon’s Rank Sum Test was used to calculate the p-values. The p-values were adjusted for multiple testing by the Benjamini-Hochberg method (FDR). FDR-values &lt; 0.05 are in bold. See Fig. 2 and Additional file 6. FDR = False Discovery Rate.
DOI: 10.6084/m9.figshare.25750111
title: Additional file 2 of Acetylation proteomics and metabolomics analyses reveal the involvement of starch synthase undergoing acetylation modification during UV-B stress resistance in Rhododendron Chrysanthum Pall

description: Supplementary Material 2.
DOI: 10.6084/m9.figshare.25750111.v1
title: Additional file 2 of Acetylation proteomics and metabolomics analyses reveal the involvement of starch synthase undergoing acetylation modification during UV-B stress resistance in Rhododendron Chrysanthum Pall

description: Supplementary Material 2.
DOI: 10.6084/m9.figshare.26715598
title: Additional file 3 of Acetylation proteomics and metabolomics analyses reveal the involvement of starch synthase undergoing acetylation modification during UV-B stress resistance in Rhododendron Chrysanthum Pall

description: Supplementary Material 3.
DOI: 10.6084/m9.figshare.26715598.v1
title: Additional file 3 of Acetylation proteomics and metabolomics analyses reveal the involvement of starch synthase undergoing acetylation modification during UV-B stress resistance in Rhododendron Chrysanthum Pall

description: Supplementary Material 3.
DOI: 10.6084/m9.figshare.26715604
title: Additional file 4 of Acetylation proteomics and metabolomics analyses reveal the involvement of starch synthase undergoing acetylation modification during UV-B stress resistance in Rhododendron Chrysanthum Pall

description: Supplementary Material 4.
DOI: 10.6084/m9.figshare.26715604.v1
title: Additional file 4 of Acetylation proteomics and metabolomics analyses reveal the involvement of starch synthase undergoing acetylation modification during UV-B stress resistance in Rhododendron Chrysanthum Pall

description: Supplementary Material 4.
DOI: 10.6084/m9.figshare.26715607
title: Additional file 5 of Acetylation proteomics and metabolomics analyses reveal the involvement of starch synthase undergoing acetylation modification during UV-B stress resistance in Rhododendron Chrysanthum Pall

description: Supplementary Material 5.
DOI: 10.6084/m9.figshare.26715607.v1
title: Additional file 5 of Acetylation proteomics and metabolomics analyses reveal the involvement of starch synthase undergoing acetylation modification during UV-B stress resistance in Rhododendron Chrysanthum Pall

description: Supplementary Material 5.
DOI: 10.6084/m9.figshare.26715610
title: Additional file 6 of Acetylation proteomics and metabolomics analyses reveal the involvement of starch synthase undergoing acetylation modification during UV-B stress resistance in Rhododendron Chrysanthum Pall

description: Supplementary Material 6.
DOI: 10.6084/m9.figshare.26715610.v1
title: Additional file 6 of Acetylation proteomics and metabolomics analyses reveal the involvement of starch synthase undergoing acetylation modification during UV-B stress resistance in Rhododendron Chrysanthum Pall

description: Supplementary Material 6.
DOI: 10.3886/e208259v1
title: Prostitution and Induced Abortions

description: The study focuses on estimating impacts of bans on prostitution on prevalence of induced abortions.
DOI: 10.6084/m9.figshare.25750126
title: Additional file 2 of Immunologic responses to the third and fourth doses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in cell therapy recipients: a systematic review and meta-analysis

description: Additional file 2: Fig. S1. Forest plot of pooled seropositive rate difference between third and second dose in HSCT patients. Fig. S2. Forest plot of pooled seropositive rate difference between fourth and third dose in HSCT patients. Fig. S3. Forest plot of pooled seropositive rate difference between third and second dose in CAR-T cell patients. Fig. S4. Forest plot of seroconversion after the third dose in HSCT recipients by the interval between transplantation and vaccination initiation. This plot demonstrates higher seroconversion rates among patients with a median interval of more than 12 months from cell therapy to the first dose of immunization. Fig. S5. Forest plot of seroconversion after third dose in HSCT recipients by brand of the mRNA vaccine received.
DOI: 10.6084/m9.figshare.25750126.v1
title: Additional file 2 of Immunologic responses to the third and fourth doses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in cell therapy recipients: a systematic review and meta-analysis

description: Additional file 2: Fig. S1. Forest plot of pooled seropositive rate difference between third and second dose in HSCT patients. Fig. S2. Forest plot of pooled seropositive rate difference between fourth and third dose in HSCT patients. Fig. S3. Forest plot of pooled seropositive rate difference between third and second dose in CAR-T cell patients. Fig. S4. Forest plot of seroconversion after the third dose in HSCT recipients by the interval between transplantation and vaccination initiation. This plot demonstrates higher seroconversion rates among patients with a median interval of more than 12 months from cell therapy to the first dose of immunization. Fig. S5. Forest plot of seroconversion after third dose in HSCT recipients by brand of the mRNA vaccine received.
DOI: 10.6084/m9.figshare.25749891
title: Additional file 1 of Gut microbiome and resistome characterization of pigs treated with commonly used post-weaning diarrhea treatments

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.25749891.v1
title: Additional file 1 of Gut microbiome and resistome characterization of pigs treated with commonly used post-weaning diarrhea treatments

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.25750132
title: Additional file 2 of Quorum sensing in bacteria: in silico protein analysis, ecophysiology, and reconstruction of their evolutionary history

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.25750132.v1
title: Additional file 2 of Quorum sensing in bacteria: in silico protein analysis, ecophysiology, and reconstruction of their evolutionary history

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.26715802
title: Additional file 3 of Quorum sensing in bacteria: in silico protein analysis, ecophysiology, and reconstruction of their evolutionary history

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26715802.v1
title: Additional file 3 of Quorum sensing in bacteria: in silico protein analysis, ecophysiology, and reconstruction of their evolutionary history

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.26715811
title: Additional file 4 of Mortality and its predictors among human immunodeficiency virus-infected children younger than 15 years receiving antiretroviral therapy in Ethiopia: a systematic review and meta-analysis

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.26715811.v1
title: Additional file 4 of Mortality and its predictors among human immunodeficiency virus-infected children younger than 15 years receiving antiretroviral therapy in Ethiopia: a systematic review and meta-analysis

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.25749921
title: Additional file 1 of Cooperation of immune regulators Tollip and surfactant protein A inhibits influenza A virus infection in mice

description: Additional file 1. WT IAV vs WT PBS – downregulated genes. A table of genes downregulated by IAV in WT mouse macrophages, with the log2 fold change, and p-values.
DOI: 10.6084/m9.figshare.25749921.v1
title: Additional file 1 of Cooperation of immune regulators Tollip and surfactant protein A inhibits influenza A virus infection in mice

description: Additional file 1. WT IAV vs WT PBS – downregulated genes. A table of genes downregulated by IAV in WT mouse macrophages, with the log2 fold change, and p-values.
DOI: 10.6084/m9.figshare.25750137
title: Additional file 2 of Cooperation of immune regulators Tollip and surfactant protein A inhibits influenza A virus infection in mice

description: Additional file 2. WT IAV vs WT PBS – upregulated genes. A table of genes upregulated by IAV in WT mouse macrophages, with the log2 fold change, and p-values.
DOI: 10.17632/5x46832drv.1
title: Postoperative evaluation in third molar surgery performed with osteotomy in patients attended in the surgery area

description: This study analyses postoperative complications in third molar extraction surgeries, both with
and without osteotomy, categorising tooth positions using the Pell and Gregory classification.
The main hypothesis is that the osteotomy technique is associated with a higher incidence of
complications and slower recovery times due to the complexity of the tooth positions being
treated.
Clinical data were collected from patients who underwent these procedures at the Dr René Puig
Bentz Clinic. Variables recorded included type of surgery, dental classification, presence of
dental and bone fractures, soft tissue tears, and postoperative signs and symptoms (pain, swelling
and limitation of oral opening). Follow-up included the immediate and long-term evaluation of
mandibular mobility and pain progression.
Methods employed included clinical review, radiographic classification and systematic
postoperative evaluation to identify complications and differences between groups. Standardised
protocols for surgery and postoperative management were applied, enabling the study to be
replicated in other centres under similar conditions.
The results show that the Pell and Gregory Class I technique is the most common in both types
of surgery, although the osteotomy technique is used for more complex cases (Classes II and III).

The most frequent complication was dental fractures in molars 4.8 and 3.8, with bone fractures
predominating in women.