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opencc-by-4.0May 2023View details →

Assessment of non-communicable diseases screening practices among university lecturers in Ghana – a cross sectional single centre study

This section highlights the various methods used for this study. It covered study setting, study design, study approach, study population, sampling techniques, sample size calculation, inclusion and exclusion criteria, ethical consideration, data collection, data management and data analysis.   Study Setting The study was carried out at Kwame Nkrumah University of Science and Technology (KNUST), Kumasi between February to August, 2022.  The study covered all the six (6) Colleges in the University.   Study Design This was a cross sectional study to ascertain health check practices among university lecturers.   Study Approach The study employed quantitative approach in which data was collected using questionnaires with both closed- and open-ended questions. Study Population The study population involved 838 Lecturers across the six Colleges at Kwame Nkrumah University of Science and Technology (KNUST), Kumasi. A study of the lecturer population per college revealed that Colleges of Health Sciences (highest) and Agric /Natural resources (lowest) were the outliers (Quality Assurance and Planning Office, 2020).   Sampling Technique   Simple probability technique was used to select the name of a college and the day/date to visit. Two sets of papers were folded with names of colleges (set 1) and day/date of visit (set 2). A picker picked one folded paper from each set and the name of the college and the day/date to visit was matched. In this case, the ordering of date and visit gave 1st College of Humanities & Social Sciences, 2nd College of Agric and Natural Resources, 3rd College of Art & Built Environment, 4th College of Engineering, 5th College of Science and 6th College of Health Sciences. We then used the ‘walk in’’ system to select the study participants. Within the days to visit a college, any lecturer we meet in his/ her office was a potential study participant.       Sample Size Calculation The sample size was obtained using Yamane, 1967 formulae as shown below:     Where n= is the population of Lecturers in at KNUST E= is the level of precision Therefore:             n= 838                                       1+838 (0.0025) n =    838 1+ 2.098   838 3.095                                                                                                                 n=270                                                                       However, due to logistical constrains, 205 participants were contacted across the 6 Colleges at Kwame Nkrumah University of Science and Technology. We then applied simple proportions to get the number of lecturers to be consulted in each college.   Inclusion and Exclusions Criteria Inclusion criteria was made up of all Lecturers on KNUST campus who are in active service and consented to participate. All other staff not within this category were excluded from this research.   Ethical Considerations Ethical approval was sought from the CHRPE, KNUST with approval reference no: CHRPE/AP/581/21. The aim of the research was explained to participants. Those who consented to participate in the research were given consent forms to sign and date. Again, participants were assured of confidentiality. Participants were told that, they were free to withdraw from the study in the cause of time. In other words, study participants were not coerced into the study.   Data Collection Tool Data was collected using structured questionnaires. The questionnaires covered dietary intake, alcohol intake, issues on physical inactivity and tobacco use. Aside these four main risk factors of NCDs, the questionnaire also captured frequency of blood pressure checks, blood pressure outcome anytime it is checked (systolic and diastolic), frequency of general body check-up, frequency of anthropometric measurement checks (weight and height), an assessment of impressions about the outcome of weight and height checks, an assessment of intended measures to be taken depending on the outcomes of weight and health checked. Again, the general observation of the nature of job as a lecturer and health status especially the outcome of blood pressure monitoring were also assessed. The questionnaire also captured the socio-demographic status of Lecturers,   Data Management Only the Research Team had access to data. Data was kept confidential. The researchers had planned of disposing data from the storage 5 years after the publication of this research. Collected data was entered and cleaned using Microsoft Excel spread sheet, and then imported into STATA version 14.0 (Stata Corp LP, College Station, Texas, USA) for statistical analysis and results.   Data Analysis Descriptive statistics were used to summarize the characteristics of the study population by employing frequencies and percentages for categorical data. In addition, the degree of relatedness (association) was evaluated using Chi-square (χ2) or Fisher’s exact tests where appropriate with a p ≤0.05 assumed to be statistically significant. Both bivariate and multivariate logistic regression analyses were performed and adjusted for colleges effect to identify associations among the variables of interest. Variables having significant association in the logistic regression models were set at p≤0.05 with 95% confidence interval (95% CI) for both unadjusted and adjusted odds ratios (OR, AOR).   Variables BP was selected as the dependent variable, and in turn define as Normal: ≤ 120/80 mmHg; Elevated: Systolic between 120-129 and diastolic ≤ 80; Hypertension: Systolic ≥ 130 or diastolic ≥ 80. Then dichotomized into Normal blood pressure: ≤ 120/80 mmHg and high blood pressure (Hypertension): ≥ 130/90 mmHg for logistic regression analyses. Independent variables were socio-demographics; gender, age, marital status, staff rank and lecturer’s colleges (categorized into binary variable; COHS /COS/COE and CABE/CANR/COHSS), family history of NCDs and health check status. In this study, the variable “very often” denotes (doing the activity in question more than 4 times a month), “often” denotes (doing the activity in question at least twice a month), and “not often” denotes (doing the activity in question once a month).

opencc-by-4.0May 2023View details →

Assessment of non-communicable diseases screening practices among university lecturers in Ghana – a cross sectional single centre study

Data Collection Tool Data were collected using structured questionnaires. The questionnaires covered dietary intake, alcohol intake, issues with physical inactivity, and tobacco use. Aside from these four main risk factors of NCDs, the questionnaire also captured the frequency of blood pressure checks, blood pressure outcome anytime it is checked (systolic and diastolic), frequency of general body check-ups, frequency of anthropometric measurement checks (weight and height), an assessment of impressions about the outcome of weight and height checks, an assessment of intended measures to be taken depending on the outcomes of weight and health checked. Again, the general observation of the nature of the job as a lecturer and health status especially the outcome of blood pressure monitoring were also assessed. The questionnaire also captured the socio-demographic status of Lecturers,   Data Management Only the Research Team had access to data. Data was kept confidential. The researchers had planned of disposing data from the storage 5 years after the publication of this research. Collected data was entered and cleaned using Microsoft Excel spread sheet, and then imported into STATA version 14.0 (Stata Corp LP, College Station, Texas, USA) for statistical analysis and results.   Data Analysis Descriptive statistics were used to summarize the characteristics of the study population by employing frequencies and percentages for categorical data. In addition, the degree of relatedness (association) was evaluated using Chi-square (χ2) or Fisher’s exact tests where appropriate with a p ≤0.05 assumed to be statistically significant. Both bivariate and multivariate logistic regression analyses were performed and adjusted for colleges' effect to identify associations among the variables of interest. Variables having significant association in the logistic regression models were set at p≤0.05 with 95% confidence interval (95% CI) for both unadjusted and adjusted odds ratios (OR, AOR).   Variables BP was selected as the dependent variable, and in turn define as Normal: ≤ 120/80 mmHg; Elevated: Systolic between 120-129 and diastolic ≤ 80; Hypertension: Systolic ≥ 130 or diastolic ≥ 80. Then dichotomized into Normal blood pressure: ≤ 120/80 mmHg and high blood pressure (Hypertension): ≥ 130/90 mmHg for logistic regression analyses. Independent variables were socio-demographics; gender, age, marital status, staff rank, and lecturer’s colleges (categorized into binary variables; Colleges, family history of NCDs, and health check status. In this study, the variable “very often” denotes (doing the activity in question more than 4 times a month), “often” denotes (doing the activity in question at least twice a month), and “not often” denotes (doing the activity in question once a month).

opencc-by-4.0Jun 2023View details →

Project "Public services management system to improve the quality and accessibility of services" (01.2.2-LMT-K-718-03-0019) literature review screening results

The results of the keyword query in Scopus search with the abstracts were screened using abstractr platform at <a href="http://abstrackr.cebm.brown.edu">http://abstrackr.cebm.brown.edu</a>. Four reviewers reviewed intersecting subsets of the overall list of publications in separate reviews, therefore duplicate records in the file are possible. The results from four reviews were combined into one file using functionality of abstractr platform. The reviews were finalized in February, 2022. Majority of the publications from the Scopus query results were automatically assigned low relevance scores thanks to the active learning algorithm used by abstractr and therefore were not reviewed manually.Notes on the columns of the dataset:<ul><li>(internal) id  - internal id added by abstractr.</li><li>(source) id  - Scopus document id followed by underscore and '1' (if publication has DOI)  or 'n' (if publication has no DOI).</li><li>keywords - authors' keywords and Scopus keywords concatenated from the Scopus query results.</li><li>abstract - an abstract of a publication from the Scopus query results.</li><li>title - title of a publication from the Scopus query results.</li><li>journal - journal of a publication from the Scopus query results.</li><li>authors - authors of a publlication from the Scopus query results.</li><li>consensus - for publications reviewed by multiple reviewers the consensus decision is signified by '1', no consensus - by 'x' and unable to asses consensus by 'o'. These codes are generated by abstrackr.</li><li>eg - the first reviewer id. Code '1' means the publication was selected based on title and abstract, '0' - unsure, '-1' rejected.</li><li>dj - the second reviewer id. Code '1' means the publication was selected based on title and abstract, '0' - unsure, '-1' rejected.</li><li>rp - the third reviewer id. Code '1' means the publication was selected based on title and abstract, '0' - unsure, '-1' rejected.</li><li>mp - the fourth reviewer id. Code '1' means the publication was selected based on title and abstract, '0' - unsure, '-1' rejected.</li><li>count (+1) - integer, the number of reviewers selecting the publication for fulltext reading. Calculated from 'eg ','dj ','rp' and 'mp' columns.</li><li>count (0) - integer, the number of reviewers not sure of selecting the publication for fulltext reading. Calculated from 'eg ','dj ','rp' and 'mp' columns.</li><li>count (-1)  - integer, the number of reviewers not selecting the publication for fulltext reading. Calculated from 'eg ','dj ','rp' and 'mp' columns.</li><li>at leat once selected - binary integer, representing the final decision rule to select publications for fulltext reading and further analysis.</li></ul>The data were collected as a part of the project "Public services management system to improve the quality and accessibility of services" ("Viešųjų paslaugų vadybos sistema paslaugų kokybei ir prieinamumui gerinti"), grant no. 01.2.2-LMT-K-718-03-0019, funded by the Lithuanian research council.

opencc-by-4.0Aug 2013View details →

Genome-Wide Mutational Signatures of Aristolochic Acid and Its Application as a Screening Tool

The .zip files contain the fastq files for the cell line data published in DOI: 10.1126/scitranslmed.3006086 plus results of analyzing these data. HK2_AA and HK2b-8d2 were exposed to AA (aristolochic acid I), and HK2_ctrl was an unexposed control. The .tsv files are VCF-like files with the mutations found in the exposed cells. spectrum_counts.txt are what are now called "SBS96" spectra -- counts of single base substitutions in the contexts of preceding and following bases. The PDF file has plots of these.  (The HUC1 cells that were exposed did not show AA-related mutations.)

opencc-by-4.0Aug 2023View details →

Raw data for the article: High-throughput computational solvent screening for lignocellulosic biomass processing

This data set contains the raw data for the article "High-throughput computational solvent screening for lignocellulosic biomass processing" published in Chemical Engineering Journal, DOI: <a href="https://doi.org/10.1016/j.cej.2022.139476">https://doi.org/10.1016/j.cej.2022.139476</a>

opencc-by-4.0Dec 2023View details →

CRISPR/dCas9-mediated DNA demethylation screen identifies driver epigenetic determinants of colorectal cancer (Processed data)

Background: Promoter hypermethylation of tumour suppressor genes is frequently observed during the malignant transformation of colorectal cancer (CRC). However, whether this epigenetic mechanism is an actual driver of cancer or is a mere consequence of the carcinogenic process remains to be elucidated. Results: In this work we performed an integrative multi -omic approach to identify gene candidates with strong correlations between DNA methylation and gene expression in human CRC samples and a set of 8 colon cancer cell lines. As a proof of concept, we combined recent CRISPR-Cas9 epigenome editing tools (dCas9-TET1, dCas9-TET-IM) with a custom arrayed gRNA library to modulate the DNA methylation status of 56 promoters previously linked with strong epigenetic repression in CRC, and we monitored the potential functional consequences of such DNA methylation loss by means of a high-content cell proliferation screen. Overall, the epigenetic modulation of most of these DNA methylated regions had a mild impact in the reactivation of gene expression and in the viability of cancer cells. Interestingly, we found that epigenetic reactivation of RSPO2 in the tumour context was associated with a significant impairment in cell proliferation in p53-/- cancer cell lines and further validation with human samples demonstrated that the epigenetic silencing of RSPO2 is a mid-late event in the adenoma to carcinoma sequence. Conclusions: These results highlight the potential role of DNA methylation as a driver mechanism of CRC and open up the venue for the identification of novel therapeutic windows based on the epigenetic reactivation of certain tumour suppressor genes.

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Data from: DNA metabarcoding for biodiversity monitoring in a national park: screening for invasive and pest species

<ol> <li>DNA metabarcoding was utilized for a large-scale, multi-year assessment of biodiversity in Malaise trap collections from the Bavarian Forest National Park (Germany, Bavaria). </li> <li>Principal Component Analysis of read count-based biodiversities revealed clustering in concordance with whether collection sites were located inside or outside of the National Park.</li> <li>Jaccard distance matrices of the presences of BINs at collection sites in the two survey years (2016 and 2018) were significantly correlated.</li> <li>Overall similar patterns in the presence of total arthropod BINs, as well as BINs belonging to four major arthropod orders across the study area, were observed in both survey years, and are also comparable with results of a previous study based on DNA barcoding of Sanger-sequenced specimens.</li> <li>A custom reference sequence library was assembled from publicly available data to screen for pest or invasive arthropods among the specimens or from the preservative ethanol.</li> <li> A single 98.6% match to the invasive bark beetle Ips duplicatus was detected in an ethanol sample. This species has not previously been detected in the National Park. </li> </ol>

opencc-zeroJul 2020View details →

Figshare40/100

Screen captures illustrating molecular 3D model sharing through Sketchfab, Google Poly and NIH Print Exchange

Sharing 3D models illustrated by 6 screen captures.    1: cardboard stereo view with Sketchfab of example 1 (ACE-spike coronavirus complex)   2: tuning of VR/AR settings on the Sketchfab platform (example 1)   3: Sketchfab web view of example 1   4: Sketchfab 3D Model inspector applied to example 1 model   4: Google Poly web view of example 1

opencc-by-4.0Dec 2019View details →

opencc-by-4.0Aug 2020View details →

Non-target screening of organic compounds in offshore produced water by GC×GC-MS (associated data)

Associated data for the manuscript titled "Non-target screening of organic compounds in offshore produced water by GC×GC-MS" Preprint doi://10.26434/chemrxiv.13317938

opencc-by-4.0Oct 2019View details →

Using Blender EEVEE for the Generation of Real Time Background Plate in Green Screen Movie Shots

This talk will introduce you to the use of blender EEVEE for green screen shots for a short movie. Green (and blue) screen shots are notoriously difficult to get the lighting condition right, since the image from the camera is dominated by the bright green background. It is very helpful on the set to see in real time the final composition of the scene with the proper background to make adjustments of the camera and the lighting position and the lighting intensity and color. For the shots a large volume mocap solution (Optitrack) was used to track the movie camera (Arri Alexa) and the transformation data was sent to Blender to animate the virtual camera. The previously laser scanned background was rendered in real time in EEVEE. To combine the camera image and the rendered image a dedicated live-keying hardware was used. The described set-up was used in connection with the research project Virtually Real – Aesthetics and Perception of Virtual Spaces in Film by the Zurich University of the Arts and the University of Bern, funded by the Swiss National Science Foundation.

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Screen captures illustrating and depicting EM densities of the ACE2 (PDB ID 6CS2) model

Depicting of cryo-EM density maps using the provided python script option of the first example of our paper (see links). The lack of sufficient density for a few of the outer loops is quite obvious from these images.

opencc-by-4.0Dec 2020View details →

opencc-by-4.0Dec 2020View details →

Raw data for "Host-interactor screens of Phytophthora infestans RXLR proteins reveal vesicle trafficking as a major effector-targeted process"

This dataset contains raw and original images, phylogenetic tree files, sequence alignment files used for phylogenetic tree construction and unprocessed data for figures presented in the manuscript titled "Host-interactor screens of Phytophthora infestans RXLR proteins reveal vesicle trafficking as a major effector-targeted process". Each zip file contains raw data for each figure in the manuscript. A version of the manuscript is available on bioRxiv with doi.org/10.1101/2020.09.24.308585.

opencc-by-4.0Feb 2021View details →

Data for "An optimized genome-wide virus-free CRISPR screen for mammalian cells"

This is the raw data from the article "An optimized genome-wide virus-free CRISPR screen for mammalian cells " and scripts for analyzing it.

opencc-zeroMar 2016View details →

Screening for Atrial Fibrillation using Oscillometry

Data set supporting publication regarding the use of pulse rate variability as measured by an oscillometric blood pressure device to identify atrial fibrillation.

PanDDA analysis of BRD1 screened against 3D-Fragment-Consortium Fragment Library (HTML Summary)

Interactive summary page for "PanDDA analysis of BRD1 screened against 3D-Fragment-Consortium Fragment Library". Please click on "0_index.html" in the "Files" section to open the interactive summary. All datasets are also available as combined zip files from https://zenodo.org/record/48769 .

PanDDA analysis of JMJD2D screened against Zenobia Fragment Library (HTML Summary)

Interactive summary page for "PanDDA analysis of JMJD2D screened against Zenobia Fragment Library". Please click on "0_index.html" in the "Files" section to open the interactive summary. All datasets are also available as combined zip files from https://zenodo.org/record/48770 .

PanDDA analysis of SP100 screened against selection of Maybridge Fragment Library (HTML Summary)

Interactive summary page for "PanDDA analysis of SP100 screened against selection of Maybridge Fragment Library". Please click on "0_index.html" in the "Files" section to open the interactive summary. All datasets are also available as combined zip files from https://zenodo.org/record/48771 .

PanDDA analysis of BAZ2B screened against Zenobia Fragment Library (HTML Summary)

Interactive summary page for "PanDDA analysis of BAZ2B screened against Zenobia Fragment Library". Please click on "0_index.html" in the "Files" section to open the interactive summary. All datasets are also available as combined zip files from https://zenodo.org/record/48768 .

opencc-by-4.0Jul 2017View details →

Neural Touch-Screen Ensemble Performance 2017-07-03

A studio performance of an RNN-controlled Touch Screen Ensemble from 2017-07-03 at the University of Oslo. In this performance, a touch-screen musician improvises with a computer-controlled ensemble of three artificial performers. A recurrent neural network tracks the touch gestures of the human performer and predicts musically appropriate gestural responses for the three artificial musicians. The performances on the three 'AI' iPads are then constructed from matching snippets of previous human recordings. A plot of the whole ensemble's touch gestures are shown on the projected screen. This performance uses Metatone Classifier (https://doi.org/10.5281/zenodo.51712) to track touch gestures and Gesture-RNN (https://github.com/cpmpercussion/gesture-rnn) to predict gestural states for the ensemble. The touch-screen app used in this performance was PhaseRings (https://doi.org/10.5281/zenodo.50860).