Share your research data

BACKGROUND: Major noncardiac surgery is associated with high rates of postoperative myocardial injury and other complications. Remote ischemic preconditioning (RIPC) was reported to decrease these complication rates. However, such supportive evidence lacks robustness. METHODS: In a multinational, double-blind trial, we randomly assigned adult high-risk patients undergoing noncardiac surgical procedures to receive RIPC or sham RIPC after the induction of general anesthesia and before surgery. RIPC involved three 5-minute ischemic cycles, each followed by 5 minutes of reperfusion, using a blood pressure cuff inflated to 200 mm Hg. The primary end point was the rate of myocardial injury, defined by an increase in postoperative troponin levels above the highest 99th percentile of reference values. Secondary outcomes included myocardial infarction, stroke, acute kidney injury, need for intensive care unit, length of hospital stay, and 30-day all-cause mortality. RESULTS: We recruited 1213 patients in 25 hospitals and 8 countries. We randomly assigned 599 patients to RIPC and 614 to sham RIPC. The most frequent surgical procedures were abdominal or intrathoracic surgeries (406 patients [33.6%]). RIPC was applied to the upper limb in 1014 patients (84.8%) and to the lower limb in 182 patients (15.2%). Postoperative myocardial injury occurred in 215 of 566 patients (38.0%) in the RIPC group and in 223 of 596 patients (37.4%) in the sham RIPC group (relative risk, 1.02 [95% CI, 0.88–1.18; P=0.84). There were no significant differences in the rate of any secondary outcomes. We observed 11 episodes of limb petechiae (10 [1.7%] in the RIPC group versus one [0.2%] in the sham RIPC group) and 34 (6.0%) hospital readmissions in the RIPC group versus 20 (3.5%) in the sham RIPC group. CONCLUSIONS: Among adult patients undergoing noncardiac surgery, RIPC did not reduce myocardial injury or other postoperative complications. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02427867.

BACKGROUND Patients undergoing cardiac surgery often receive red-cell transfusions, along with the associated risks and costs. Early intraoperative normovolemic hemodilution (i.e., acute normovolemic hemodilution [ANH]) is a blood-conservation technique that entails autologous blood collection before initiation of cardiopulmonary bypass and reinfusion of the collected blood after bypass weaning. More data are needed on whether ANH reduces the number of patients receiving allogeneic red-cell transfusion. METHODS In a multinational, single-blind trial, we randomly assigned adults from 32 centers and 11 countries who were undergoing cardiac surgery with cardiopulmonary bypass to receive ANH (withdrawal of ≥650 ml of whole blood with crystalloids replacement if needed) or usual care. The primary outcome was the transfusion of at least one unit of allogeneic red cells during the hospital stay. Secondary outcomes were death from any cause within 30 days after surgery or during the hospitalization for surgery, bleeding complications, ischemic complications, and acute kidney injury. RESULTS A total of 2010 patients underwent randomization; 1010 were assigned to ANH and 1000 to usual care. Among patients with available data, 274 of 1005 (27.3%) in the ANH group and 291 of 997 (29.2%) in the usual-care group received at least one allogeneic red-cell transfusion (relative risk, 0.93; 95% confidence interval, 0.81 to 1.07; P = 0.34). Surgery for postoperative bleeding was performed in 38 of 1004 patients (3.8%) in the ANH group and 26 of 995 patients (2.6%) in the usual-care group. Death within 30 days or during hospitalization occurred in 14 of 1008 patients (1.4%) in the ANH group and 16 of 997 patients (1.6%) in the usual care group. Safety outcomes were similar in the two groups. CONCLUSIONS Among adults undergoing cardiac surgery, ANH did not reduce the number of patients receiving allogeneic red-cell transfusion. (Funded by the Italian Ministry of Health; ANH ClinicalTrials.gov number, NCT03913481.)

This Word document contains the comprehensive data extraction matrix, presented as a structured table of the 61 synthesized empirical studies analyzed in this review. The table systematically maps each study's operationalized terminology (dependency, addiction, problematic use), applied theoretical frameworks, identified antecedents, multi-domain consequences, and psychometric measurement scales.

This dataset contains RGB images of jujube (Ziziphus jujuba) leaves collected for research on automatic plant disease recognition, stress detection, and leaf health assessment. The images are grouped into five phenotypic classes: 1.Anthracnose 2.Healthy 3.Powdery Mildew 4.Insect Damage 5.Yellow Leaf In total, the dataset includes 1,260 images, with 300 images per class for Anthracnose, Healthy, Insect Damage, and Yellow Leaf, and 60 images for Powdery Mildew. The lower number of Powdery Mildew samples reflects its lower prevalence during the data collection period and is intentionally preserved to represent realistic field conditions. Images were acquired under natural field conditions with varying backgrounds, illumination, and leaf orientations to improve the robustness and real-world relevance of computer vision and deep learning models trained on this dataset. All images are provided in their original RGB format without synthetic augmentation; users may apply their own augmentation strategies (e.g., rotation, flipping, color jitter) and class-weighting methods to address class imbalance in downstream analyses.A key strength of this dataset is the expert verification of disease and syndrome information: The presence or absence of disease for each symptomatic class (Anthracnose, Powdery Mildew, Insect Damage, Yellow Leaf) and the Healthy class was verified and documented through a formal disease verification certificate issued by qualified experts.In addition, a separate syndrome and medicine verification certificate is provided, describing the characteristic visual syndromes (leaf symptoms) of each disease class and confirming the recommended treatment/management options (e.g., appropriate pesticides, fungicides, or other control measures) as validated by subject-matter specialists. Scanned copies of both the disease verification certificate and the syndrome and medicine verification certificate are included as supplementary files in this repository. These documents provide users with transparent evidence of diagnostic validity and treatment recommendations, enhancing the reliability of the dataset for scientific, agronomic, and decision-support applications. This dataset is intended for, but not limited to: Training and benchmarking image classification and deep learning models for jujube leaf disease detection.Research on plant stress phenotyping and early disease diagnosis. Development of mobile or edge-based decision support systems for farmers and extension workers. Educational purposes in plant pathology, precision agriculture, and agricultural informatics. Users are encouraged to cite this dataset when using it in publications and to note the presence of the attached verification certificates as part of the dataset’s quality assurance.

Experimental data from Taguchi L9 optimization and characterization of KCl-modified guava seed biochar for sulfate adsorption. Dataset includes: - Precursor screening results - Synthesis optimization parameters - Kinetic and equilibrium adsorption data - Fixed-bed column breakthrough curves with synthetic solutions - Material characterization (XRD, N2 isotherms, FTIR) Note: Raw groundwater and industrial wastewater data not included due to confidentiality restrictions on source locations and industrial data.

To address the lack of large-scale point clouds dataset for training point cloud completion models in civil engineering, we publish this dataset. This dataset comprises the synthetic and case study datasets used in the paper ‘BridgeDiff: A two-stage conditional diffusion model for bridge point cloud completion’. This dataset comprises 1,000 synthetic single-span masonry arch bridge point cloud samples for point cloud completion. Each single-span sample includes 1 ground truth point cloud and 24 partial point clouds with varying perspectives and degrees of data loss, a total of 24,000 sample pairs for training. For ease of processing, each sample is stored as a binary (.pt) file. The two case studies are a canal bridge in Birmingham, UK, and the Welland Viaduct in Harringworth, UK. Both point clouds have undergone registration, denoising and downsampling, the full scan data will be made available once the paper has been accepted.

Optical properties of chromophoric dissolved organic matter (CDOM) in Poyang Lake during winter drought (January 2015) and summer flood (July 2016)

This is the replication package for "Tax Loss Carryforwards and Firms' Risk" by Favilukis, Giammarino, Pizarro, and Simutin; accepted for publication by the Journal of Financial Economics.

MOIVE1 for AT2 ORGANOIDS "RESPIRATION"

This dataset supports the article entitled “Crosslinker-dependent effective network topology and property responses of SSBR revealed by molecular dynamics simulations”. It contains molecular models, crosslink-topology statistics, mean-squared displacement data, free-volume and density results, density-temperature data used for glass-transition-temperature determination, reverse non-equilibrium molecular dynamics results for thermal conductivity, elastic-modulus results, figure source data, and analysis scripts for neat and crosslinked solution-polymerized styrene-butadiene rubber systems. The investigated crosslinking systems include sulfur, HVA-2, TMPTMA and TAIC. The files are organized according to the corresponding analyses and figures in the associated manuscript. Please consult 00_README.txt for file descriptions, units and instructions for reuse.