80 Works

Additional file 29 of Proteogenomic insights into the biology and treatment of pancreatic ductal adenocarcinoma

Yexin Tong, Mingjun Sun, Lingli Chen, Yunzhi Wang, Yan Li, Lingling Li, Xuan Zhang, Yumeng Cai, Jingbo Qie, Yanrui Pang, Ziyan Xu, Jiangyan Zhao, Xiaolei Zhang, Yang Liu, Sha Tian, Zhaoyu Qin, Jinwen Feng, Fan Zhang, Jiajun Zhu, Yifan Xu, Wenhui Lou, Yuan Ji, Jianyuan Zhao, Fuchu He, Yingyong Hou … & Chen Ding
Additional file 29: Table S7. Characterization of Immune Infiltration in PDAC. Table S7A Matrix of xCell signatures significantly altered in 5 immune subgroups. Table S7B Matrix describing the expression of proteins in 5 immune subgroups. Table S7C Matrix of GSVA scores of pathways significantly altered in 5 immune subgroups, transcriptome level. Table S7D Matrix of amplification/deletion events of genes in 5 immune subgroups. Table S7E Matrix describing the expression of proteins involved in TCA cycle.

Additional file 30 of Proteogenomic insights into the biology and treatment of pancreatic ductal adenocarcinoma

Yexin Tong, Mingjun Sun, Lingli Chen, Yunzhi Wang, Yan Li, Lingling Li, Xuan Zhang, Yumeng Cai, Jingbo Qie, Yanrui Pang, Ziyan Xu, Jiangyan Zhao, Xiaolei Zhang, Yang Liu, Sha Tian, Zhaoyu Qin, Jinwen Feng, Fan Zhang, Jiajun Zhu, Yifan Xu, Wenhui Lou, Yuan Ji, Jianyuan Zhao, Fuchu He, Yingyong Hou … & Chen Ding
Additional file 30: Table S8. HOGA1 inactivation promotes pancreatic cancer growth through activating LARP7-CDK1 pathway. Table S8A Quantified western blot results of 12 pairs of samples. Table S8B Proliferation of PANC-1 and BxPC-3 cells associated with HOGA1 knocked down. Table S8C Proliferation of PANC-1 and BxPC-3 cells associated with HOGA1 overexpressed. Table S8D Proliferation of PANC-1 and BxPC-3 cells associated with metabolic enzyme treatment. Table S8E A list of 773 different proteins detected in PANC-1...

sj-xlsx-3-tva-10.1177_15248380221134294 – Supplemental material for Exploring the Activities and Target Audiences of School-Based Violence Prevention Programs: Systematic Review and Intervention Component Analysis

Andrew J. Rizzo, Noreen Orr, Naomi Shaw, Caroline Farmer, Annah Chollet, Honor Young, Vashti Berry, Emma Rigby, Ann Hagell, Chris Bonell & G. J. Melendez-Torres
Supplemental material, sj-xlsx-3-tva-10.1177_15248380221134294 for Exploring the Activities and Target Audiences of School-Based Violence Prevention Programs: Systematic Review and Intervention Component Analysis by Andrew J. Rizzo, Noreen Orr, Naomi Shaw, Caroline Farmer, Annah Chollet, Honor Young, Vashti Berry, Emma Rigby, Ann Hagell, Chris Bonell and G. J. Melendez-Torres in Trauma, Violence, & Abuse

Influenza clinical risk groups 2017 version - Chronic renal disease diagnoses

Sara Thomas
Read v2 codes for a diagnosis of long-term kidney disease as an indication for influenza vaccination, including CKD stages 3-5, a history of renal transplant, dialysis or arteriovenous fistula, or nephrotic syndrome. Read v2 codes for CKD stages 1-2 and "resolved" CKD are also included, with an indicator flag. For this project, individuals were considered to have long-term kidney disease if: they had any code in this list AND the latest code before the index...

Codelists for: \"Acute cardiovascular events after SARS-CoV-2 infection in England in 2020: a self-controlled case series study\"

Jennifer Davidson, Ami Banerjee, Liam Smeeth & Charlotte Warren-Gash

Samvad Project Datasets

Emma Beaumont

Data for: “Adoption of C-reactive protein rapid tests in primary care in the Netherlands and England: a comparative health systems analysis”

Juan Emmanuel Dewez & Shunmay Yeung
This qualitative dataset was produced as part of a study to understand the factors that contribute to high versus low availability of C-reactive protein point-of-care tests (CRP POCTs) in two countries with different levels of availability (the Netherlands and England), and to explore whether the tests are used on children. The dataset contains extracts from stakeholder interviews and document analysis performed in relation to these two countries.

Codelists for: \"Effect of cardiovascular risk profile on severe outcomes of COVID-19 in England in 2020: a population-based cohort study\"

Jennifer Davidson, Helen Mcdonald, Helen Strongman, Sharon Cadogan, Ami Banerjee, Liam Smeeth & Charlotte Warren-Gash

From Black Box to Shining Spotlight: Using Random Forest Prediction Intervals to Illuminate the Impact of Assumptions in Linear Regression

Andrew J. Sage, Yang Liu & Joe Sato
We introduce a pair of Shiny web applications that allow users to visualize random forest prediction intervals alongside those produced by linear regression models. The apps are designed to help undergraduate students deepen their understanding of the role that assumptions play in statistical modeling by comparing and contrasting intervals produced by regression models with those produced by more flexible algorithmic techniques. We describe the mechanics of each approach, illustrate the features of the apps, provide...

AHHA Malawi Trial Dataset - Version 2

Edward Joy, Joanna Sturgess & Elizabeth Allen
The Alleviating Hidden Hunger with Agronomy (AHHA) Malawi trial sought to test the efficacy of alleviating selenium deficiency through consumption of maize flour enriched with fertilizers in a Malawi-based context. The anonymised dataset contains outcome results of the investigation. This dataset is an update to the version published at 10.17037/DATA.00001993, containing 12 additional measurements.

Data for: \"Availability and use of rapid diagnostic tests for the management of acute childhood infections in Europe\"

Manuel Dewez & Shunmay Yeung
A set of datasets obtained through a cross sectional survey of European paediatricians for the purpose of estimating the availability and use of rapid point-of-care diagnostic tests for the management of acute childhood infections and identify the main determinants. The dataset contains anonymised responses from 1154 primary care paediatricians from 19 countries, and 1188 hospital paediatricians from 504 unique hospitals from 29 countries and data dictionaries.

Additional file 24 of Proteogenomic insights into the biology and treatment of pancreatic ductal adenocarcinoma

Yexin Tong, Mingjun Sun, Lingli Chen, Yunzhi Wang, Yan Li, Lingling Li, Xuan Zhang, Yumeng Cai, Jingbo Qie, Yanrui Pang, Ziyan Xu, Jiangyan Zhao, Xiaolei Zhang, Yang Liu, Sha Tian, Zhaoyu Qin, Jinwen Feng, Fan Zhang, Jiajun Zhu, Yifan Xu, Wenhui Lou, Yuan Ji, Jianyuan Zhao, Fuchu He, Yingyong Hou … & Chen Ding
Additional file 24: Table S2. The Impacts of Somatic Copy Number Alterations in PDAC Cohort. Table S2A Matrix of amplification peaks, followed by the genes contained in them, 95% confidence level. Table S2B Matrix of deletion peaks, followed by the genes contained in them, 95% confidence level. Table S2C Matrix of the top 10 mutated genes in PDAC of Fudan cohort. Table S2D Matrix of the 10 mutated genes used in Figure 1C of ICGC,...

Additional file 27 of Proteogenomic insights into the biology and treatment of pancreatic ductal adenocarcinoma

Yexin Tong, Mingjun Sun, Lingli Chen, Yunzhi Wang, Yan Li, Lingling Li, Xuan Zhang, Yumeng Cai, Jingbo Qie, Yanrui Pang, Ziyan Xu, Jiangyan Zhao, Xiaolei Zhang, Yang Liu, Sha Tian, Zhaoyu Qin, Jinwen Feng, Fan Zhang, Jiajun Zhu, Yifan Xu, Wenhui Lou, Yuan Ji, Jianyuan Zhao, Fuchu He, Yingyong Hou … & Chen Ding
Additional file 27: Table S5. 8p11.22 Amplification Associated with PDAC Metastasis. Table S5A The matrix describing mutations in PDAC metastatic patients and non-metastatic patients. Table S5B Matrix of GSVA scores of pathways significantly altered in PDAC metastatic patients and non-metastatic patients, proteome level. Table S5C Matrix of xCell signatures significantly altered in PDAC metastatic patients and non-metastatic patients, transcriptome level. Table S5D Matrix describing the cis-effects of genes located on chromosome 8p11.22. Table S5E Matrix...

Additional file 27 of Proteogenomic insights into the biology and treatment of pancreatic ductal adenocarcinoma

Yexin Tong, Mingjun Sun, Lingli Chen, Yunzhi Wang, Yan Li, Lingling Li, Xuan Zhang, Yumeng Cai, Jingbo Qie, Yanrui Pang, Ziyan Xu, Jiangyan Zhao, Xiaolei Zhang, Yang Liu, Sha Tian, Zhaoyu Qin, Jinwen Feng, Fan Zhang, Jiajun Zhu, Yifan Xu, Wenhui Lou, Yuan Ji, Jianyuan Zhao, Fuchu He, Yingyong Hou … & Chen Ding
Additional file 27: Table S5. 8p11.22 Amplification Associated with PDAC Metastasis. Table S5A The matrix describing mutations in PDAC metastatic patients and non-metastatic patients. Table S5B Matrix of GSVA scores of pathways significantly altered in PDAC metastatic patients and non-metastatic patients, proteome level. Table S5C Matrix of xCell signatures significantly altered in PDAC metastatic patients and non-metastatic patients, transcriptome level. Table S5D Matrix describing the cis-effects of genes located on chromosome 8p11.22. Table S5E Matrix...

IMPROVING EXPLOSIVE BODY CAPACITY IN FEMALE SHORT TRACK SPEED SKATERS

Jianjun Li, Xinchao Ge & Yang Liu
ABSTRACT Introduction The peculiar characteristics of short track speed skating should be integrated into the psychology of competitions; it is considered that elite athletes engaged in this particular sport should have a healthy psychic condition. Objective Investigate the explosive power of female speed skaters in short track speed skating. Methods 10 key athletes from the national short track speed skating team were selected, and explosive power was tested by T-test, hexagonal test, and pro sensitivity...

Additional file 4 of Strengthening vaccination delivery system resilience in the context of protracted humanitarian crisis: a realist-informed systematic review

Sharif A. Ismail, Sze Tung Lam, Sadie Bell, Fouad M. Fouad, Karl Blanchet & Josephine Borghi
Additional file 4: Appendix 4. Summary table of included studies.

Additional file 1 of Inequalities in the impact of COVID-19-associated disruptions on tuberculosis diagnosis by age and sex in 45 high TB burden countries

C. Finn McQuaid, Marc Y. R. Henrion, Rachael M. Burke, Peter MacPherson, Rebecca Nzawa-Soko & Katherine C. Horton
Additional file 1: Model code and additional tables and Figs. Table S1. Country-specific tuberculosis notifications for 2013-2020 by age and sex. Table S2. Country-specific linear models for expected notifications. Fig. S1. Country-specific linear models for expected notifications. Table S3. Country-specific numbers of missed or delayed diagnoses. Table S4. Country-specific risk-ratios for disruption to tuberculosis notifications due to the pandemic for men compared to women (both aged ≥ 15 years). Table S5. Country-specific risk-ratios for disruption...

Supporting data for: Risk factors common to leading eye health conditions and major non-communicable diseases: A rapid review and commentary

Lisa Keay, Kerrie Ren, Helen Nguyen, Claire Vajdic, Michael Odutola, Rajendra Gyawali, Melinda Toomey, Ruth Peters, Nicole Ee, Lisa Dillon, Maree Hackett, Brandon Ah Tong, Fabrizio D'Esposito, David Faulmann, Matthew Burton, Jacqueline Ramke & Isabelle Jalbert
Background: To gain an understanding of the intersection of risk factors between the most prevalent eye health conditions that are associated with vision impairment and non-communicable diseases (NCDs). Methods: A series of rapid reviews of reviews reporting on non-modifiable risk factors, age and sex, and modifiable risk factors, including social determinants, were conducted for five common eye health conditions that are the leading causes of vision impairment globally (refractive error including uncorrected refractive error, cataract,...

Additional file 29 of Proteogenomic insights into the biology and treatment of pancreatic ductal adenocarcinoma

Yexin Tong, Mingjun Sun, Lingli Chen, Yunzhi Wang, Yan Li, Lingling Li, Xuan Zhang, Yumeng Cai, Jingbo Qie, Yanrui Pang, Ziyan Xu, Jiangyan Zhao, Xiaolei Zhang, Yang Liu, Sha Tian, Zhaoyu Qin, Jinwen Feng, Fan Zhang, Jiajun Zhu, Yifan Xu, Wenhui Lou, Yuan Ji, Jianyuan Zhao, Fuchu He, Yingyong Hou … & Chen Ding
Additional file 29: Table S7. Characterization of Immune Infiltration in PDAC. Table S7A Matrix of xCell signatures significantly altered in 5 immune subgroups. Table S7B Matrix describing the expression of proteins in 5 immune subgroups. Table S7C Matrix of GSVA scores of pathways significantly altered in 5 immune subgroups, transcriptome level. Table S7D Matrix of amplification/deletion events of genes in 5 immune subgroups. Table S7E Matrix describing the expression of proteins involved in TCA cycle.

Influenza clinical risk groups 2017 version - Chronic cardiac conditions

Sara Thomas
Read v2 codes for diagnoses of chronic cardiac conditions as an indication for influenza vaccination, including congenital heart disease, hypertension with cardiac complications, chronic heart failure, history of myocardial infarction, and other cardiac conditions likely to require regular medication and/or follow-up. Definition designed to follow national guidance in indications for influenza vaccination https://www.gov.uk/government/publications/influenza-the-green-book-chapter-19

The importance of fine-scale predictors of wild boar habitat use in an isolated population

Sonny Bacigalupo, Yu-Mei Ruby Chang, Linda Dixon, Simon Gubbins, Adam Kucharski & Julian Drewe
Predicting the likelihood of wildlife presence at potential wildlife-livestock interfaces is challenging. These interfaces are usually relatively small geographical areas where landscapes show large variation over small distances. Models of wildlife distribution based on coarse data over wide geographical ranges may not be representative of these interfaces. High-resolution data can help identify fine scale predictors of wildlife habitat use at a local scale and provide more accurate predictions of species habitat use. These data may...

From Black Box to Shining Spotlight

Andrew J. Sage, Yang Liu & Joe Sato
We introduce a pair of Shiny web applications that allow users to visualize random forest prediction intervals alongside those produced by linear regression models. The apps are designed to help undergraduate students deepen their understanding of the role that assumptions play in statistical modeling by comparing and contrasting intervals produced by regression models with those produced by more flexible algorithmic techniques. We describe the mechanics of each approach, illustrate the features of the apps, provide...

From Black Box to Shining Spotlight: Using Random Forest Prediction Intervals to Illuminate the Impact of Assumptions in Linear Regression

Andrew J. Sage, Yang Liu & Joe Sato
We introduce a pair of Shiny web applications that allow users to visualize random forest prediction intervals alongside those produced by linear regression models. The apps are designed to help undergraduate students deepen their understanding of the role that assumptions play in statistical modeling by comparing and contrasting intervals produced by regression models with those produced by more flexible algorithmic techniques. We describe the mechanics of each approach, illustrate the features of the apps, provide...

Decision Modelling for Health Economic Evaluation - Exercises

Andrew Briggs

Additional file 1 of Inequalities in the impact of COVID-19-associated disruptions on tuberculosis diagnosis by age and sex in 45 high TB burden countries

C. Finn McQuaid, Marc Y. R. Henrion, Rachael M. Burke, Peter MacPherson, Rebecca Nzawa-Soko & Katherine C. Horton
Additional file 1: Model code and additional tables and Figs. Table S1. Country-specific tuberculosis notifications for 2013-2020 by age and sex. Table S2. Country-specific linear models for expected notifications. Fig. S1. Country-specific linear models for expected notifications. Table S3. Country-specific numbers of missed or delayed diagnoses. Table S4. Country-specific risk-ratios for disruption to tuberculosis notifications due to the pandemic for men compared to women (both aged ≥ 15 years). Table S5. Country-specific risk-ratios for disruption...

Registration Year

  • 2022
    80

Resource Types

  • Dataset
    80

Affiliations

  • London School of Hygiene & Tropical Medicine
    80
  • Chinese Academy of Tropical Agricultural Sciences
    34
  • Sun Yat-sen University
    34
  • Zhejiang University
    34
  • Central South University
    34
  • Fudan University Shanghai Cancer Center
    34
  • Fairy Lake Botanical Garden
    34
  • Tangshan Gongren Hospital
    34
  • Shanghai University of Traditional Chinese Medicine
    34
  • Lund University
    34