Dataset Search

The oleaginous, carotenogenic yeast Rhodotorula toruloides has been increasingly explored as a platform organism for the production of terpenoids and fatty acid derivatives. Fatty alcohols, a fatty acid derivative widely used in the production of detergents and surfactants, can be produced microbially with the expression of a heterologous fatty acyl-CoA reductase. Due to its high lipid production, R. toruloides has high potential for fatty alcohol production, and in this study several metabolic engineering approaches were investigated to improve the titer of this product. Fatty acyl-CoA reductase from Marinobacter aqueolei was co-expressed with SpCas9 in R. toruloides IFO0880 and a panel of gene overexpressions and Cas9-mediated gene deletions were explored to increase the fatty alcohol production. Two overexpression targets (ACL1 and ACC1, improving cytosolic acetyl-CoA and malonyl-CoA production, respectively) and two deletion targets (the acyltransferases DGA1 and LRO1) resulted in significant (1.8 to 4.4-fold) increases to the fatty alcohol titer in culture tubes. Combinatorial exploration of these modifications in bioreactor fermentation culminated in a 3.7 g/L fatty alcohol titer in the LRO1Δ mutant. As LRO1 deletion was not found to be beneficial for fatty alcohol production in other yeasts, a lipidomic comparison of the DGA1 and LRO1 knockout mutants was performed, finding that DGA1 is the primary acyltransferase responsible for triacylglyceride production in R. toruloides, while LRO1 disruption simultaneously improved fatty alcohol production, increased diacylglyceride and triacylglyceride production, and increased glucose consumption. The fatty alcohol titer of fatty acyl-CoA reductase-expressing R. toruloides was significantly improved through the deletion of LRO1, or the deletion of DGA1 combined with overexpression of ACC1 and ACL1. Disruption of LRO1 surprisingly increased both lipid and fatty alcohol production, creating a possible avenue for future study of the lipid metabolism of this yeast.

This archive contains all the alignments and trees used in the HIPPI paper [1]. The pfam.tar archive contains the PFAM families used to build the HMMs and BLAST databases. The file structure is: ./X/Y/initial.fasttree ./X/Y/initial.fasta where X is a Pfam family, Y is the cross-fold set (0, 1, 2, or 3). Inside the folder are two files, initial.fasta which is the Pfam reference alignment with 1/4 of the seed alignment removed and initial.fasttree, the FastTree-2 ML tree estimated on the initial.fasta. The query.tar archive contains the query sequences for each cross-fold set. The associated query sequences for a cross-fold Y is labeled as query.Y.Z.fas, where Z is the fragment length (1, 0.5, or 0.25). The query files are found in the splits directory. [1] Nguyen, Nam-Phuong D, Mike Nute, Siavash Mirarab, and Tandy Warnow. (2016) HIPPI: Highly Accurate Protein Family Classification with Ensembles of HMMs. To appear in BMC Genomics.

To generate the bibliographic and survey data to support a data reuse study conducted by several Library faculty and accepted for publication in the Journal of Academic Librarianship, the project team utilized a series of web-based online scripts that employed several different endpoints from the Scopus API. The related dataset: "Data for: An Examination of Data Reuse Practices within Highly Cited Articles of Faculty at a Research University" contains survey design and results. <br /> 1) <b>getScopus_API_process_dmp_IDB.asp</b>: used the search API query the Scopus database API for papers by UIUC authors published in 2015 -- limited to one of 9 pre-defined Scopus subject areas -- and retrieve metadata results sorted highest to lowest by the number of times the retrieved articles were cited. The URL for the basic searches took the following form: https://api.elsevier.com/content/search/scopus?query=(AFFIL%28(urbana%20OR%20champaign) AND univ*%29) OR (AF-ID(60000745) OR AF-ID(60005290))&apikey=xxxxxx&start=" & nstart & "&count=25&date=2015&view=COMPLETE&sort=citedby-count&subj=PHYS<br /> Here, the variable nstart was incremented by 25 each iteration and 25 records were retrieved in each pass. The subject area was renamed (e.g. from PHYS to COMP for computer science) in each of the 9 runs. This script does not use the Scopus API cursor but downloads 25 records at a time for up to 28 times -- or 675 maximum bibliographic records. The project team felt that looking at the most 675 cited articles from UIUC faculty in each of the 9 subject areas was sufficient to gather a robust, representative sample of articles from 2015. These downloaded records were stored in a temporary table that was renamed for each of the 9 subject areas. <br /> 2) <b>get_citing_from_surveys_IDB.asp</b>: takes a Scopus article ID (eid) from the 49 UIUC author returned surveys and retrieves short citing article references, 200 at a time, into a temporary composite table. These citing records contain only one author, no author affiliations, and no author email addresses. This script uses the Scopus API cursor=* feature and is able to download all the citing references of an article 200 records at a time. <br /> 3) <b>put_in_all_authors_affil_IDB.asp</b>: adds important data to the short citing records. The script adds all co-authors and their affiliations, the corresponding author, and author email addresses. <br /> 4) <b>process_for_final_IDB.asp</b>: creates a relational database table with author, title, and source journal information for each of the citing articles that can be copied as an Excel file for processing by the Qualtrics survey software. This was initially 4,626 citing articles over the 49 UIUC authored articles, but was reduced to 2,041 entries after checking for available email addresses and eliminating duplicates.

Example scripts and configuration files needed to perform select simulations described in the manuscript "Percolation transition prescribes protein size-specific barrier to passive transport through the nuclear pore complex."

The dataset includes bee community data from a study conducted down in southern Illinois across three forested public land sites. Bee diversity and abundance data, as well as environmental variables, are included for each plot. Each plot was visited a total of four times.

Census data collected at Trelease Woods in 1936 with information on tree species, stem count, diameter at breast height (DBH), and basal area. The plot boundaries from the 1936 census were georeferenced to subset 2018 census data for a direct comparison between the two census years.

This study presents a cost-effective strategy for producing organic acids from glucose and xylose using the acid-tolerant yeast, Issatchenkia orientalis. I. orientalis was engineered to produce lactic acid from xylose, and the resulting strain, SD108XL, successfully converted sorghum hydrolysates into lactic acid. In order to enable low-pH fermentation, a self-buffering strategy, where the lactic acid generated by the SD108XL strain during fermentation served as a buffer, was developed. As a result, the SD108 strain produced 67 g/L of lactic acid from 73 g/L of glucose and 40 g/L of xylose, simulating a sugar composition of sorghum biomass hydrolysates. Moreover, techno-economic analysis underscored the efficiency of the self-buffering strategy in streamlining the downstream process, thereby reducing production costs. These results demonstrate the potential of I. orientalis as a platform strain for the cost-effective production of organic acids from cellulosic hydrolysates.

These datasets provide the basis of our analysis in the paper - The Potential Impact of a Clean Energy Society On Air Quality. All datasets here are from the model output (CAM4-chem). All the simulations were run to steady-state and only the outputs used in the analysis are archived here.

This dataset contains all the raw data, figures, and Prism files corresponding to each experiment performed for the paper “Hippocampal ensembles regulate circuit-induced relapse of extinguished fear.”

This document contains the Supplemental Materials for Chapter 4: Climate Change Impacts on Agriculture from the report "An Assessment of the Impacts of Climate Change in Illinois" published in 2021.

Drainage network analysis is fundamental to understanding the characteristics of surface hydrology. Based on elevation data, drainage network analysis is often used to extract key hydrological features like drainage networks and streamlines. Limited by raster-based data models, conventional drainage network algorithms typically allow water to flow in 4 or 8 directions (surrounding grids) from a raster grid. To resolve this limitation, this paper describes a new vector-based method for drainage network analysis that allows water to flow in any direction around each location. The method is enabled by rapid advances in Light Detection and Ranging (LiDAR) remote sensing and high-performance computing. The drainage network analysis is conducted using a high-density point cloud instead of Digital Elevation Models (DEMs) at coarse resolutions. Our computational experiments show that the vector-based method can better capture water flows without limiting the number of directions due to imprecise DEMs. Our case study applies the method to Rowan County watershed, North Carolina in the US. After comparing the drainage networks and streamlines detected with corresponding reference data from US Geological Survey generated from the Geonet software, we find that the new method performs well in capturing the characteristics of water flows on landscape surfaces in order to form an accurate drainage network. This dataset contains all the code, notebooks, datasets used in the study conducted for the research publication titled " A Vector-Based Method for Drainage Network Analysis Based on LiDAR Data ". ## What's Inside A quick explanation of the components * `A Vector Approach to Drainage Network Analysis Based on LiDAR Data.ipynb` is a notebook for finding the drainage network based on LiDAR data *`Picture1.png` is a picture representing the pseudocode of our new algorithm * HPC` folder contains codes for running the algorithm with sbatch in HPC ** `execute.sh` is a bash script file that use sbatch to conduct large scale analysis for the algorithm ** `run.sh` is a bash script file that calls the script file `execute.sh` for large scale calculation for the algorithm ** `run.py` includes the codes implemented for the algorithm * `Rowan Creek Data` includes data that are used in the study ** `3_1.las` and `3_2.las ` are the LiDAR data files that is used in our analysis presented in the paper. Users may use this data file to reproduce our results and may replace it with their own LiDAR file to run this method over different areas ** `reference` folder includes reference data from USGS *** `reference_3_1.tif` and `reference_3_2.tif` are reference data for the drainage system analysis retrieved from USGS.

Bigheaded carp were collected from the Illinois and Des Plaines Rivers, parts of the Illinois Waterway, from May to November 2018. A total of 93 fish were collected during sampling for a study comprised of 40 females, 41 males, and 12 unsexed fish. GC/MS metabolite profiling analysis detected 180 compounds. Livers from carp at the leading edge had differences in energy use and metabolism, and suppression of protective mechanisms relative to downstream fish; differences were consistent across time. This body of work provides evidence that water quality is linked to carp movement in the Illinois River. As water quality in this region continues to improve, consideration of this impact on carp spread is essential to protect the Great Lakes.

This dataset helps to investigate the Spatial Accessibility to HIV Testing, Treatment, and Prevention Services in Illinois and Chicago, USA. The main components are: population data, healthcare data, GTFS feeds, and road network data. The core components are: 1) `GTFS` which contains GTFS (<a href="https://gtfs.org/">General Transit Feed Specification</a>) data which is provided by Chicago Transit Authority (CTA) from <a href="https://developers.google.com/transit/gtfs">Google's GTFS feeds</a>. Documentation defines the format and structure of the files that comprise a GTFS dataset: <a href="https://developers.google.com/transit/gtfs/reference?csw=1">https://developers.google.com/transit/gtfs/reference?csw=1</a>. 2) `HealthCare` contains shapefiles describing HIV healthcare providers in Chicago and Illinois respectively. The services come from <a href="https://locator.hiv.gov/">Locator.HIV.gov</a>. 3) `PopData` contains population data for Chicago and Illinois respectively. Data come from The American Community Survey and <a href="https://map.aidsvu.org/map">AIDSVu</a>. AIDSVu (https://map.aidsvu.org/map) provides data on PLWH in Chicago at the census tract level for the year 2017 and in the State of Illinois at the county level for the year 2016. The American Community Survey (ACS) provided the number of people aged 15 to 64 at the census tract level for the year 2017 and at the county level for the year 2016. The ACS provides annually updated information on demographic and socio economic characteristics of people and housing in the U.S. 4) `RoadNetwork` contains the road networks for Chicago and Illinois respectively from <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> using the Python <a href="https://osmnx.readthedocs.io/en/stable/">osmnx</a> package. <b>The abstract for our paper is:</b> Accomplishing the goals outlined in “Ending the HIV (Human Immunodeficiency Virus) Epidemic: A Plan for America Initiative” will require properly estimating and increasing access to HIV testing, treatment, and prevention services. In this research, a computational spatial method for estimating access was applied to measure distance to services from all points of a city or state while considering the size of the population in need for services as well as both driving and public transportation. Specifically, this study employed the enhanced two-step floating catchment area (E2SFCA) method to measure spatial accessibility to HIV testing, treatment (i.e., Ryan White HIV/AIDS program), and prevention (i.e., Pre-Exposure Prophylaxis [PrEP]) services. The method considered the spatial location of MSM (Men Who have Sex with Men), PLWH (People Living with HIV), and the general adult population 15-64 depending on what HIV services the U.S. Centers for Disease Control (CDC) recommends for each group. The study delineated service- and population-specific accessibility maps, demonstrating the method’s utility by analyzing data corresponding to the city of Chicago and the state of Illinois. Findings indicated health disparities in the south and the northwest of Chicago and particular areas in Illinois, as well as unique health disparities for public transportation compared to driving. The methodology details and computer code are shared for use in research and public policy.

This dataset contains R codes used to produce the figures submitted in the manuscript titled "Understanding the multifaceted geospatial software ecosystem: a survey approach". The raw survey data used to populate these charts cannot be shared due to the survey consent agreement.

For economic and sustainable biomanufacturing, the oleaginous yeast Rhodotorula toruloides has emerged as a promising platform for producing biofuels, pharmaceuticals, and other valuable chemicals. However, genetic manipulation of R. toruloides has been limited by its high GC content and the lack of a replicating plasmid, necessitating gene integration into the genome of the yeast. To address these challenges, we developed the RT-EZ (R. toruloides Efficient Zipper) toolkit, a versatile tool based on Golden Gate assembly, designed to streamline R. toruloides engineering with improved efficiency and flexibility. The RT-EZ toolkit simplifies vector construction by incorporating new features such as bidirectional promoters and 2A peptides, color-based screening using RFP, and sequences optimized for both Agrobacterium tumefaciens-mediated transformation (ATMT) and easy linearization, enabling straightforward selection and transformation. Notably, the RT-EZ kit can be used to construct an expression cassette with four different genes in one assembly reaction, significantly improving vector construction speed and efficiency. The utility of the RT-EZ toolkit was demonstrated through the successful synthesis of arachidonic acid in R. toruloides by coexpressing fatty acid elongases and desaturases. This result underscores the potential of the RT-EZ toolkit to advance synthetic biology in R. toruloides, providing a streamlined method for addressing genetic engineering challenges in the yeast.

This dataset includes data on soil properties, soil N pools, and soil N fluxes presented in the manuscript, "Effects of an invasive perennial forb on gross soil nitrogen cycling and nitrous oxide fluxes," submitted to Ecology for peer-reviewed publication. Please refer to that publication for details about methodologies used to generate these data and for the experimental design.

This dataset contains EEG and Temperature data acquired from inside the bore of an MRI scanner during scanning with two different types of fMRI sequences: single-band and and multi-band. The EEG data were acquired from the heads of adult humans undergoing scanning, and can be used to assess differences in EEG data quality due to sequence type. The temperature data were acquired from a watermelon phantom and can be used to assess heating differences due to sequence type.

This data set explores the effect of the cyanobacterial gene ictB on photosynthesis in sorghum, under both normal greenhouse growing temperatures (32 C / 25 C) and during and after an 8 day chilling stress (10 C / 5 C). IctB is a cyanobacterial gene of unknown function, which was initially thought to be involved in inorganic carbon transport into cells. While ictB is known now not to be an independently active carbon transporter in its own right, it may play a role in passive diffusion of metabolites. This transgene was introduced into sorghum by the lab of Thomas Clemente, through Agrobacterium mediated transformation, alone and in combination with the tomato sedoheptulose-1,7-bisphosphatase (SBPase) gene. Eleven events (six double construct and five single construct ictB) were involved in this study. SBPase was included because some previous experiments in C3 species and some previous modeling work, as well as its position at a metabolic branch point, indicates it plays a role as a control point for photosynthesis. A chilling treatment was included because chilling is one of the most serious ecological factors limiting the range of C4 species. Data includes gene expression, metabolomics (at normal growing temperature), SBPase enzyme activity, biomass and photosynthetic traits at both warm temperature and during and after chilling stress. ----------------- EXPLANATORY NOTES FOR ICTB/SBPASE SORGHUM MANUSCRIPT Data are organized into 10 worksheets, representing an expected 10 tables that will serve a supplementary role in the final publication. These include data on gene expression, metabolomics (at normal growing temperature), SBPase enzyme activity, biomass and photosynthetic traits at both warm temperature and during and after chilling stress. <i><b>Tables are as follows:</i></b> 1. Event_Code: for Table S1. Event codes for events and constructs. Two constructs were generated for this study, and numerous transgenic “events” (i.e. independent transformations) were carried out for each construct. A construct represents the actual vector which was introduced into the plants (complete with promoter, gene of interest, marker gene, etc.) while an event represents a single successful introduction of the transgene. Events are uniquely labeled with letter and number strings but also with a four-digit number for ease of reference, this table explains which event corresponds to each four-digit number. 2. Photosynthetic_Data: for Table S2. Photosynthetic data at greenhouse growing temperature, for ictB single construct, ictB/SBPase double construct, and wild type lines. Five ictB and six ictB/SBPase events were included. Greenhouse growing temperature was approximately 32 °C and 25 °C night. Photosynthetic parameters were measured using a Licor 6400-XT, and included parameters related to carbon dioxide uptake, water loss, and chlorophyll fluorescence. 3. Chilling_Treatment: for Table S3. Photosynthetic response to chilling treatment, for ictB single construct, and wild type lines. Four ictB events were included. Chilling treatment lasted approximately 8 days and began either 3.5 or 5.5 weeks after transplanting the plants (chilling was done in two batches). Chilling treatment involved temperatures of 10 °C day / 7 °C night in growth chambers. Photosynthetic parameters were measured at several time points during and after the chilling treatment, were measured using a Licor 6400-XT, and included parameters related to carbon dioxide uptake, water loss, and chlorophyll fluorescence. 4. SBPase_Activity: for Table S4. SBPase activity in double construct plants. These data measure in vitro substrate-saturated activity of SBPase in desalted extracts from leaf tissues, at 25 °C. Units are micromoles of SBP processed per second per m2 of leaf tissue. Five ictB/SBPase events were included. 5. 2014_gene_exp: for Table S5. Gene expression in 2014 experiment (units of cycle times). These data measure cycle times to threshold, relative to reference genes, for expression of ictB and SBPase. Six ictB single construct events and five ictB/SBPase double construct events were included. Cycle times to threshold relative to reference genes (ΔCT) are inversely related to number of transcripts relative to reference genes, as follows: ΔCT = -log2([NictB]/[Nreference])/[1 + log2b] where b = efficiency of replication. 6. 2016_gene_exp: for Table S5. Gene expression in 2016 experiment (units of cycle times). These data measure cycle times to threshold, relative to reference genes, for expression of ictB and SBPase. Six ictB single construct events and five ictB/SBPase double construct events were included. Cycle times to threshold relative to reference genes (ΔCT) are inversely related to number of transcripts relative to reference genes, as follows: ΔCT = -log2([NictB]/[Nreference])/[1 + log2b] where b = efficiency of replication. 7. Metabolites: for Table S7. Levels of 267 metabolites in leaf tissue. Four ictB single construct events and four ictB/SBPase double construct events were included in these analyses. Metabolites were measured in methanol-extracted samples, either by liquid chromatography / mass spectrometry or by gas chromatography / mass spectrometry, and were compared between events on a relative basis. As quantification was relative to wild type rather than on an absolute basis, no units are included. 8. Metabolite_F_values: for Table S8. F values for effects of ictB, SBPase (in cases where the model was better with a SBPase effect) and event. These analyses are done for each metabolite included in Table S7, and show effects of the explanatory variables ictB, SBPase, and individual event. 9. Biomass_2020: for Table S9. Biomass and grain yield at harvest, for ictB, ictB/SBPase and wild type sorghum plants in spring 2020. Four ictb/SBPase double construct and four ictB single construct events were included. 10. Biomass_2017: for Table S10. Biomass and grain yield at harvest, in chilled and non-chilled sorghum plants containing the ictB transgene (along with wild type controls) in fall 2017. Four ictB single construct events were included. Chilling treatment involved temperatures of 10 °C day / 7 °C night in growth chambers. <i><b>All the variables in the file are explained as below:</i></b> o Type (IctB-SBPase and IctB). This refers to whether a plant is wild type, single construct (contains only the ictB transgene) or double construct (contains both the ictB and SBPase transgenes). o Code: these codes are shorter labels to refer to each transgene event for the sake of convenience. o Alternate_Code: these codes are shorter labels to refer to each transgene event for the sake of convenience. o Event Number: these are unique labels for each transgenic events. o Construct Number: these are labels for each transgenic construct (either the ictB single construct or the ictB/SBPase double construct). o year (i): this refers to the year in which the study was conducted (2014, 2016, 2017, or 2020) o transgene or Transgenic: whether the transgene was present o construct or Type : whether the ictB or the ictB/SBPase construct was present (double, single, wildtype): o temp: leaf temperature during the measurement o A: carbon assimilation rate, in μmol m-2 s-1 o gs: stomatal conductance, in mol m-2 s-1 o CI: intercellular carbon dioxide concentration, in parts per million or μL L-1 o fvfm:FV’/FM’ (maximal potential photosystem II quantum yield under light adapted conditions), dimensionless ratio o phipsill: ΦPSII (maximal potential photosystem II quantum yield under light adapted conditions), dimensionless ratio o qP: photochemical quenching, i.e. ratio of ΦPSII to FV’/FM’ , dimensionless ratio o iwue: intrinsic water use efficiency, i.e. ratio of carbon assimilation rate to stomatal conductance, in units of μmol mol-1 o event: individual transgenic / transformation event o Vmax: substrate-saturated in vitro activity of the SBPase enzyme, in μmol m-2 s-1 o ID: identification number of sample o ΔCT1: difference in cycle times to threshold during gene expression (quantitative PCR) assay, between ictB and the reference gene GAPDH, in units of cycles o ΔCT2: cycle times to threshold during gene expression (quantitative PCR) assay, between SBPase and the reference gene GAPDH, in units of cycles o GAPDH: cycle times to threshold for the reference gene GAPDH (glyceraldehyde phosphate dehydrogenase) o IctB: cycle times to threshold for the gene of interest ictB o SBPase: cycle times to threshold for the gene of interest SBPase o v1 to v267 represent individual metabolite (see the heading immediately above the labels v1, v2, etc.). Variables v268-v272 refer to total (summed) metabolite levels for particular pathways of interest. o leaf: Leaf and stem dry biomass (in grams) o seed: Seedhead dry biomass (in grams) o biomass: Total (leaf, stem + seed head) dry biomass (in grams) o harvind: ratio of seed head dry biomass to total dry biomass o treatment (chilled and nonchilled): “Chilled” plants were grown under warm greenhouse conditions (32 °C day / 25 °C night) for 6 or 8 weeks, then switched to chilling temperatures under growth chamber conditions (10 °C / 7 °C night) for 8 days, and were then returned to greenhouse growing conditions. -----------------

Related to the raw entity mentions (https://doi.org/10.13012/B2IDB-4163883_V1), this dataset represents the effects of the data cleaning process and collates all of the entity mentions which were too ambiguous to successfully link to the ChEBI ontology.

This dataset contains the pregnancy status of wild, white-tailed deer (Odocoileus virginianus) from northern Illinois culled as part of the Illinois Department of Natural Resources' chronic wasting disease (CWD) surveillance program. Fiscal years 2005 through 2024 are included. A fiscal year is the time between July 1st of one calendar year and June 30th of the next. Variables in this dataset include the pregnancy status, CWD infection status, age, weight, and day of mortality for each female deer, as well as the deer land cover utility (LCU) score for the TRS, township, or county from which the deer was culled. The deer population density of the county is also included. Data have been anonymized for landowner privacy reasons so that the location and year are not identifiable, but will give the same modeling results by maintaining how the data are grouped. The R code used to conduct the regression modeling is also included.

This dataset consists of the time-of-flight secondary ion mass spectrometry (TOF-SIMS) depth profiling data that was collected with a PHI nanoTOF II Parallel Imaging MS/MS instrument from a 70 micron by 70 micron region on a recombinant HEK cell labeled with a stain that accumulates in the endoplasmic reticulum (ER-Tracker Blue White DPX, Invitrogen).

File Name: Inclusion_Criteria_Annotation.csv Data Preparation: Xiaoru Dong Date of Preparation: 2019-04-04 Data Contributions: Jingyi Xie, Xiaoru Dong, Linh Hoang Data Source: Cochrane systematic reviews published up to January 3, 2018 by 52 different Cochrane groups in 8 Cochrane group networks. Associated Manuscript authors: Xiaoru Dong, Jingyi Xie, Linh Hoang, and Jodi Schneider. Associated Manuscript, Working title: Machine classification of inclusion criteria from Cochrane systematic reviews. Description: The file contains lists of inclusion criteria of Cochrane Systematic Reviews and the manual annotation results. 5420 inclusion criteria were annotated, out of 7158 inclusion criteria available. Annotations are either "Only RCTs" or "Others". There are 2 columns in the file: - "Inclusion Criteria": Content of inclusion criteria of Cochrane Systematic Reviews. - "Only RCTs": Manual Annotation results. In which, "x" means the inclusion criteria is classified as "Only RCTs". Blank means that the inclusion criteria is classified as "Others". Notes: 1. "RCT" stands for Randomized Controlled Trial, which, in definition, is "a work that reports on a clinical trial that involves at least one test treatment and one control treatment, concurrent enrollment and follow-up of the test- and control-treated groups, and in which the treatments to be administered are selected by a random process, such as the use of a random-numbers table." [Randomized Controlled Trial publication type definition from https://www.nlm.nih.gov/mesh/pubtypes.html]. 2. In order to reproduce the relevant data to this, please get the code of the project published on GitHub at: https://github.com/XiaoruDong/InclusionCriteria and run the code following the instruction provided. 3. This datafile (V2) is a updated version of the datafile published at https://doi.org/10.13012/B2IDB-5958960_V1 with some minor spelling mistakes in the data fixed.

An online knowledge, attitudes, and practices survey on ticks and tick-borne diseases was distributed to veterinary professionals in Southern and Central Illinois during summer and fall 2020. These are the raw data associated with that survey and the survey questions used. * NOTE: "age" and "gender" variables were removed from the data to protect participants.

This dataset includes the source data for Figures 1-4 and supplementary figures 1-10 for the manuscript "Kinetic and structural mechanism for DNA unwinding by a non-hexameric helicase".

This dataset contains: field study design parameters, plant performance metrics, and nitrogen cycling rates associated with a field experiment that compared nitrification rates between maize lines with and without nitrification inhibition loci nitrogen fixation rates with with and without a nitrogen fixing inoculant product. The overarching goal was to evaluate nitrogen fixation by a diazotroph inoculant and retention of nitrogen in the rhizosphere via a novel nitrification inhibition phenotype of maize.